Handbook of Product and Service Development in Communication and Information Technology

HANDBOOK OF PRODUCT AND SERVICE DEVELOPMENT IN COMMUNICATION AND INFORMATION TECHNOLOGY

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Handbook of Product and Service Development in Communication and Information Technology Edited by

Timo O. Korhonen Helsinki University of Technology, Finland and

Antti Ainamo Helsinki University of Technology, Finland

KLUWER ACADEMIC PUBLISHERS NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW

eBook ISBN: Print ISBN:

0-306-48712-8 1-4020-7595-2

©2004 Springer Science + Business Media, Inc. Print ©2003 Kluwer Academic Publishers Dordrecht All rights reserved No part of this eBook may be reproduced or transmitted in any form or by any means, electronic, mechanical, recording, or otherwise, without written consent from the Publisher Created in the United States of America

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TABLE OF CONTENTS

1

CHAPTER 1: OVERVIEW CHAPTER 2: SYSTEMATIC IDEA PRODUCTION, AND CULTIVATION IN HIGH TECH-PRODUCT DEVELOPMENT 2.1. INTRODUCTION 2.2. PROCESS OF CREATIVITY 2.3. STRUCTURED CREATIVITY TECHNIQUES 2.4. SUMMARY

9 11 15 24 41

CHAPTER 3: USER CENTERED DESIGN OF TELECOMMUNICATIONS SERVICES 3.1. INTRODUCTION 3.2. VIEWPOINTS ON USER EXPERIENCE 3.3. BRINGING THE USER’S VOICE INTO THE DESIGN PROCESS 3.4. IMPOSSIBLE? No, BUT YOU HAVE TO MANAGE IT!

45 45 46 57 71

CHAPTER 4: PRODUCT DEVELOPMENT GENERATIONS: SOME LESSONS FROM PERSONAL DIGITAL ASSISTANTS AND PALMTOP COMPUTERS 4.1. INTRODUCTION 4.2. PRODUCT DEVELOPMENT IN RAPIDLY EMERGING MARKETS 4.3. METHODS 4.4. PDAS, PALMTOPS, AND 2G PHONES 4.5. CONCLUSION

79 79 80 86 86 92

CHAPTER 5: PROJECT PORTFOLIO MANAGEMENT IN TELECOMMUNICATIONS R&D 5.1. INTRODUCTION 5.2. MANAGING BUSINESS-ORIENTED R&D PROJECT PORTFOLIO MANAGEMENT 5.3. 5.4. METHODS FOR PROJECT PORTFOLIO MANAGEMENT APPLYING PORTFOLIO MANAGEMENT IN THE DIFFERENT STAGES OF R&D 5.5. 5.6. DISCUSSION

99 100 101 113 119 128 136

CHAPTER 6: QUALITY IN HIGH-TECH PRODUCT DEVELOPMENT 6.1. WHAT IS QUALITY? 6.2. WHAT IS HIGH-TECH? HOW TO DEAL WITH THE INHERENT UNCERTAINTY OF HIGH-TECH 6.3. 6.4. THE EMERGENCE OF QM FOR THE MODERN HIGH-TECH ENVIRONMENT 6.5. SEQUENTIAL AND REPETITIVE PROCESSES THE PRACTICE OF QM IN THE MODERN HIGH-TECH ENVIRONMENT 6.6.

149 149 152 152 155 158 164

v

vi 6.7.

FINAL WORDS

166

CHAPTER 7: INNOVATIONS IN THE INTERNET AND MOBILE ERA: THE REAL DOT.COM REVOLUTION WEB 171 171 7.1. INTRODUCTION 173 NEW POSSIBILITIES TO MASS-CUSTOMIZE EXISTING PRODUCTS 7.2. 177 NEW TECHNOLOGIES MAKE COMPANIES DISINTEGRATE 7.3. 179 WHO IS GOING TO PROFIT FROM THE INNOVATIONS? 7.4. THE GENERIC STRATEGIES POSSIBLE FOR INNOVATORS AND ASSET OWNERS 182 7.5. 188 7.6. CONCLUSIONS AND NEW TRENDS CHAPTER 8: PATENTING AND INTELLECTUAL PROPERTY RIGHTS IN ACADEMIC - INDUSTRIAL VENTURES 8.1. INTRODUCTION DEFINING PATENTING 8.2. 8.2. 196 8.3. APPLYING FOR A PATENT - FORMAL PROCEDURES IN EUROPEAN COUNTRIES COMPARING PATENTING IN EUROPE AND IN THE US 8.4. 8.5. PATENTING ABROAD – SOME PRACTICAL ADVISES 8.6. PATENTING IN NEW MARKET AREAS 8.6. 203 8.7. UNIVERSITY BASED RESEARCH AND PATENTING COVERING PATENTING COSTS 8.8. 8.9. LICENSING: ALTERNATIVE FOR SMALL START-UP COMPANIES 8.10. VALUATING PATENTS ON THE BALANCE SHEET 8.11. CONCLUSIONS

193 193 194 196 198 200 202 203 204 205 207 208

CHAPTER 9: FINANCE AND VENTURE CAPITAL MARKETS 9.1. INTRODUCTION 9.2. A FIVE STAGE MODEL SOURCES OF EXTERNAL FINANCE 9.3. 9.4. DEMONSTRATING PERSONAL COMMITMENT: SWEAT EQUITY 9.5. FUND RAISING CLIMATE 9.6. INVESTMENT FOCUS 9.7. VENTURE CAPITAL AND THE COMMUNICATIONS SECTOR 9.8. INITIAL PUBLIC OFFERINGS (IPOS) 9.9. GOING PUBLIC: SOME CONSIDERATIONS 9.10. PUBLIC EQUITY MARKET OVERVIEW 9.11. CONCLUDING REMARKS

211 211 211 217 218 223 224 225 229 230 231 233

CHAPTER 10: ROLE OF UNIVERSITIES IN THE PRODUCT DEVELOPMENT PROCESS: STRATEGIC CONSIDERATIONS FOR THE TELECOMMUNICATIONS INDUSTRY 10.1. EXECUTIVE SUMMARY 10.2. INTRODUCTION 10.3. TECHNOLOGY AND NEW PRODUCT DEVELOPMENT PROCESS 10.4. UNIVERSITY-INDUSTRY RELATIONSHIP

235 235 236 239 240

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10.5. 10.6. 10.7. INDEX

ROLES OF UNIVERSITIES AND THE NATURE OF SCIENTIFIC RESEARCH SOME STRATEGIC CONSIDERATIONS CONCLUSIONS

243 244 250 255

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Foreword Writing and editing of this book has been an enjoyable challenge. It is based on S-72.124, Product Development of Telecommunication Systems – a course that has been lectured on a yearly basis in Helsinki University of Technology (HUT), Finland. In this book, we have set the focus on inspecting the distinctive factors typical to the implementation of telecommunications product and service development in high-tech enterprises and especially in Finnish high-tech telecommunications companies and research enterprises. An important case we frequently refer to is the Nokia’s way to work. Fortunately enough, this book has been written in HUT, only a kilometer away from Nokia’s headquarters, and actually much, much nearer in a research cooperational sense. All of us contributing to this book know a lot about Nokia’s way of working and we believe that also you are interested in sharing our thoughts. When a company works in a high-tech field, it is not dealing with hightech services or products only, but high-tech extends to all of its infrastructures and operational levels manifested in high-systems, high-services, highdesign etc processes. In this book, our goal has been to give you a fair, general picture of the most important practicalities that should be realized in high-tech enterprises. We do this by following a top-down, multidisciplinary approach by starting from the basic ideation, usability, product conception and management issues and by proceeding to quality, financing, and patenting, emphasizing general telecommunications and e-business considerations. We are sure that this text provides useful perspectives, irrespective of your own operational level in high-tech, whether you are a telecommunications or other e-commerce beginner or professional, system designer or a manager. This book would have not been possible without all the dedication and know-how of the contributing colleagues. There have been several persons that have read the manuscript in its various stages: In this, I would like to express special thanks to Michael Hall, Ruth Vilmi, Diane Pilkinton-Pihko, and Laura Takkinen who has made a major contribution in the overall layout design. We wish you fruitful moments with this book!

Helsinki, June 2003, Editors

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Chapter 1 OVERVIEW

Timo O. Korhonen, Helsinki University of Technology, Antti Ainamo, Helsinki School of Economics, and the University of Art and Design Helsinki

High-tech product development is a challenging area to work with. It involves multiple disciplines, an endless series of tradeoffs, dilemmas, and as a rule, also dead-ends. Yet, it also involves captivating moments of insight, joy, and sheer excitement in juggling technological challenges at the same time with psychological, social, organizational, financial, and legal ones. This book covers a full array of high-tech product development concepts from the very basics of ideation, usability, strategic and project management, and quality control to Internet marketing, patenting, and financial considerations. We believe you will find our book to be a very useful tool to understand the modern high-tech processes, regardless if you are a top management strategist, an experienced product developer, a student in an engineering or business school, an Information/Communications Technology (ICT) - business entrepreneur, or an academic or industrial expert. High-tech product development is a form of highest-level knowledge management. Product development teams strive to realize company’s strategy and to deal with the challenges of tying them into the routines of project management and marketing (from top to bottom) and on the other hand, to revision and update company’s current strategy (from bottom to top). Novelty and research and knowledge intensity characterizes high-tech products and services. It’s not surprising that R&D costs are almost without exception the largest part of the end product’s price. Also, high-tech product development happens under constant, high-speed upgrades, and is intimately engaged with extremely rapidly evolving markets and changes in customer’s taste and fashion. In high-tech, today’s customer experienced excellence is tomorrows’ update potential. 1

T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 1-7. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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Handbook of Product and Service Development in Communication and Information Technology

Finland – A prototype of a high-tech society A great part of this book is based on Finnish evidence. Why Finland? It’s a country, which is both a historical and contemporary pioneer in developing telecommunications applications and services. Finland was among the first countries in the world (only three years after the United States, and one year after Sweden) to build a telephone network in the century. In the 1960s, Finnish authorities and companies began to develop a mobile telecommunications network called ARP (1971). In the 1970s, the same cluster of authorities and companies began developing the world’s first modern cellular mobile telecommunications network called the Nordic Mobile Telecommunications (NMT) in l982. In 1991, Finland opened the Global System of Mobile Telephony (GSM) network, the next cellular network generation after the NMT. GSM was the world’s first digital cellular telephone network. The GSM network is also the key development platform of the Universal Mobile Telephones System (UMTS), that is a generation cellular network whose field tests (after some aggressive licensing battles) started in Europe and Japan in 2002. The GSM system has become a touchstone for such emerging mobile services and technologies as the popular Short Message Services (SMS), Multimedia Messaging Services (MMS), Wireless Application Protocol (WAP), and General Packet Radio System (GPRS). Of these, the SMS has already proved to be a gold mine for network operators. Information and Communications Technology (ICT) is a scene of global hyper-competition. Sony, the Japanese consumer electronics corporations, and Ericsson, a Swedish telecommunications runner-up, joined hands in 2002 to form SonyEricsson, a joint venture, to gather strength in the global markets. SonyEricsson also operates in Finland. American companies such as HewlettPackard, Tellabs, and IBM as well as several other multinational ICTcompanies have established their activities in Finland. Thus, the world’s leading companies operate in Finland to benefit from the country’s highly developed information and communications technology clusters and other features of this extremely business friendly society. Within this context, Nokia, a Finnish corporation, is the world’s leading producer of mobile phones in terms of sales, profits, and stock-market performance, despite the ICT regression at the beginning of the millennium. For the largest part, Nokia’s R&D remains based in Finland, even though its financing and know-how potentials would enable it to relocate freely where ever in the world it would choose. As hinted earlier, reasons for this can be tracked both in Finnish economical, educational and social structures. For us, Finland’s high-tech clusters form a laboratory-like setting in which to analyze high-tech R&D techniques, service and product profiling as well as market

Chapter 1 Overview

3

mechanisms. It seems obvious that Finland is a country in an eagle-eye position to inspect the ICT.

The information society As we stated earlier, ICT is characterized by great challenges in terms of finding commercially applicable key ideas and drivers by which to steer the product development and marketing processes. Working in this field means being able to juggle multiple projects, as well as to manage complex arrays of technological and legal issues and relating financial risks. In ICT, end-users, service providers, terminal equipment providers, core network operators, and access network operators strive to develop a networked Information Society; that is, a world where people have seamless, global, mobile access to a communication environment that is intimately customized to their personal and work life. The new and emerging ICT enabling the Information Society is already beginning to be commercially available as for instance, in the form of sophisticated, Internet enabled Personal Digital Assistant (PDA) devices. Especially generation cellular network development is evolving very fast, e.g. creating an all-IP connected network of networks, which means combining Radio Local Area Networks (RLANs) to other access networks based on GSM, ISDN, ADSL or cable modems/satellite Internet access. Hence, we claim that the G is in great deal here even before the G has even properly started.

An integrated view of high-tech product development Fig. 1.1. summarizes our high-tech innovation and production framework. The framework codifies a high-tech company’s strategy and body of knowledge in terms of instructions and specifications that are manifested for customers in design deliverables. Company’s operational body is formed by this framework of substance and social learning in terms of in-house and outhouse knowledge flows that is guided by company’s mission and vision. It is a process of fundamental and applied research as well as industrial manufacturing facing the challenges of communication with loyal partners and intimate competitors, researchers focusing on details of the substance (not necessarily so much on commercial considerations), idealistic designers, savvy marketers, entrepreneurial financiers, administrators and legal staff. Due to the extensive, interactive nature of the high-tech, R&D teams take part in accessing, learning from, making sense of, and distributing the many different combinations of the diverse high-tech knowledge. This knowledge is accessed, processed and distributed by highly specialized team members, who

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need to be talented not only in their substance know-how, but especially in their communications skills. In addition, teams should consist of highly motivated individuals forming flexible and cooperative groups, with a great amount of intent and personal integrity.

Because of the high costs and uncertainty of high-tech product development, there are exceptionally high requirements for innovations and designs, products and services. Firstly, they must be technically up-to-date, this means that everybody in the work groups must take care of their substance knowhow. They must be cost-effective, ergonomic and fashionable, where the last one is usually the most difficult to meet. They must follow company’s manufacturing and marketing vision and mission that is manifested in branding. High-tech products and services must be characterized by well-defined quality and solid market potential in the immediate or in the very near future.

Chapter 1 Overview

5

The Structure of This Book Inspection of the elements of high-tech framework of Fig. 1.1 underlines that the ways to work in high-tech product development are undoubtedly overlapping. This means that in order to act efficiently and at the right moment we need to strive to comprehend “The Big Picture”. In this book, our goal is to outline the practices, models, and strategies that characterize stateof-the-art Finnish ICT service and product development. Sometimes this is implicit, often our discussion is based on cases, interviews and other practical studies. Our multidisciplinary approach enables you to inspect ICT from different points of view that makes it more comprehensible and applicable. This enables you to identify new perspectives in general, and makes it possible to recognize new ways to understand, cluster and interact also in your own ICT framework. We hope you an enjoyable reading experience!

Our book is divided into the following ten chapters: After this first introductory chapter, the second Chapter (Systematic Idea Production, and Cultivation in High- tech Product Development) starts by inspecting a general model of human mind and creativity proceeding then to inspect how to free creativity resources from their typical obstacles. Systematic creativity cultivation methods are divided into Brainstorming and Programmable Strategies whose applicability targets and methods are outlined. This chapter includes extensive look to modern, creativity tools, and covers an outlook how Web can enable or even hinder creative product development in modern high-tech. The third Chapter (User Centered Design of Telecommunications Services) focuses on inspecting usability development and application in telecommunications services. In addition to strictly ergonomic considerations, the standards of state-of-the-art user-centered design and usability testing require inspection of all the relevant factors in terms of the effectiveness, efficiency, and satisfaction that the services should achieve in its specified context of application. The fourth Chapter (Product Development Generations: Some Lessons from Personal Digital Assistants and Palmtop Computers) uses some case examples of Personal Digital Assistants (PDAs) to develop a theoretical lens on the general flow of high-tech product development in any product category. This is then used to predict products, market, and strategies for the forthcoming development in mobile telephony. On the basis of these predictions, the chapter provides words of guidance to service providers and terminal manufacturers.

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As a rule, high-tech projects consist of a group of interactive projects. Portfolio management (Project Portfolio Management in Telecommunications R&D) in Chapter five, discusses the relationships of these projects. Portfolio management is seen as an excellent tool to reassure the overall project quality, for instance by helping to prioritize different projects based on their strategic importance and profitability to the company, as well as on their influence on the balance of the portfolio. The advantages of portfolio management are also demonstrated. For example, portfolio management can be used to reassure the overall quality of a project in terms of helping to make the right choices about which technologies and products are critical to in-house decisions, and which technologies ought to be subcontracted or bought as specified by market standards. The sixth Chapter (Quality in High-tech Product Development) focuses on identifying quality management philosophies and their applicability in high-tech product development. In addition to the traditional requirement to reassure quality through the direct control of work and end-products, quality management methods now often also make an emphasis on quality techniques based on networking. The network of organizations, groups, and individuals serve to reduce unnecessary risks, to improve the signal-to-noise ratio in information exchange, and to enhance user experienced quality in applications and services. The Web and mobile communications are fundamentally changing the way we live and do business. However, whether network cooperation is based on remote telecommunication links or in local workgroup meetings it is only worth as much as the quality of linking and interaction between their content and languages allows. This topic is taken up in Chapter Seven (Innovations in the Internet and Mobile Era: The Real dot.com Revolution Web), which considers how companies can survive the continuous and turbulent evolvement of ICT-business. This chapter emphasizes that companies should understand what their core assets are and how the new technologies challenge and enhance their profit generating capability. Especially addressed key -elements in these survival strategies are the implementation of modularity, vertical integration, and networking. The eighth Chapter (Finance and Venture Capital Markets) considers the possibilities and demands of venture capital financing in high-tech based organizations. The chapter presents a five-stage financing model and then connects this model to the sources of financing, such as commercial banks, business angels, and venture capital funds. Understanding and protecting Intellectual Property Rights (IPR) in hightech academic-industry are made all the more important by the worldwide networking of high-tech ventures. The ninth Chapter (Patenting and Intellectual Property Rights in Academic – Industrial Ventures) presents an overview

Chapter 1 Overview

7

of patenting and licensing in Europe and in the US, and underlines the related general requirements, procedures and benefits. It presents and compares commonalties and differences between conventional patenting and IPR and strives to understand reasonable and adequate protection level. Finally, the tenth Chapter (Role of Universities in the Product Development Process - Strategic Considerations for the Telecommunications Industry) inspects how to interact in industry-university relationships in ICTframework. It points out that university-industry collaboration can provide access not only to leading edge technologies, but also to highly trained students, professors and university facilities. Also, working with universities provides the associated companies a level of flexibility in pursuing different technological trajectories either sequentially or in parallel. This is especially important in dynamic technical environment. The chapter is greatly based on extensive interviews both in Finland and abroad.

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Chapter 2 SYSTEMATIC IDEA PRODUCTION, AND CULTIVATION IN HIGH TECHPRODUCT DEVELOPMENT Timo O. Korhonen, Helsinki University of Technology, Antti Ainamo, Helsinki School of Economics, and the University of Art and Design Helsinki

How to skim this chapter This chapter discusses structured ways to innovate and make decisions. We call this solving the problem-framework. The basic workflow of our approach can be summarized as follows: 1. Selecting the Strategy: Firstly, you should note that solving a problem-framework can be done by following the Brainstorming or the Programmable Strategies. If your problem-framework is wide, and it is difficult to program in a computer, then your problem is probably of the Brainstorming -type. Typical to such cases are finding a vision or a strategy for a company, improving inventions generally, and organizational and personnelrelated challenges. If this is the case, you may skip to #3. However, in order to justify this decision further, it is recommended that you also read the following paragraph that describes the Programmable Strategy. 2. Solving Programmable Problems: If your problem-framework is more structured or it is well-defined, it can be programmed, and there are often publicly available computer programs to analyze it to produce applicable solution candidates. Typical problems of this kind are story writing (Axon 2002® and Dramatica® - programs), making a musical composition (Band in the Box® - program), transforming a photograph into a painting (PhotoShop® - program), making a structured summary from a long text or a website (Copernic Summarizer®) or writing a limerick (Axon 2002®). If you have a computer program to solve your problem you may now skip to #4. If 9

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you don’t, you may follow to #3 to develop a program by yourself to solve your problem. (If you have a Programmable Problem, but you don’t have time to develop a program for its solution, or you cannot apply your own talents here, a way out can be to consult an expert just for advice, or even to delegate a part of the problem.) 3. Solving problems by Brainstorming: To start to apply Brainstorming, you can download the Electric Mind® (www.rkwest.com) to scan and solve your framework. It has also an extensive help to guide you in this technique. Then, map your problem into Mind maps (available in Axon 2002) by using The Six Thinking Hats and Lateral Thinking strategies as explain in Section 2.3.3. 4. Pruning and verifying solutions for both strategies: At last, rank and possibly update/upgrade solution candidates by using the Question Methods by following the guidelines of Section 2.3.3.

Note that in order to get high quality outputs and work efficiently, it is recommended that you not work alone. Instead, work with a multidisciplinary team that owns a high-level of communication skills. Nor should you rely on efficiency of web access to reassure substance know-how. It cannot replace vision and expertise of skilful experts you have carefully selected by yourself for your team.

Chapter 2 Introduction

2.1.

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Introduction

In many senses, the history of humankind is the history of innovations because technological and organizational development is based on innovations. Innovations are novel products, services, and concepts, as well as ways to see things in general as for instance, nowadays, they are required to cope with globalization and environmental threats. Considering the East and the West, an important aspect is the base of an invention. In the West, an invention is associated to realized, clearly defined problems and related agony, and it is a major step of technology or thinking to solve the problem (following the thinking of Aristotle, Plato and Socrates). In the East, however, innovations are made essentially to improve existing structures or apparatuses - this is a major difference in the eastern and western way to invent [de Bono, 2002]. A future challenge for the entire inventive world is to melt these ways to innovate and invent. The objective of this chapter is to give a personal and practical view of creativity, a sample of available tools, and how they can be used to boost creativity for product development and decision-making. We will first have a look at creativity in general, where it comes from, how it can be boosted or suppressed. This is done by modeling creativity based on the three basic modules of human thinking: the Idea Generator that produces the raw material, the Filter that selects a set of potentially applicable inventive ideas and the Concept Extraction Unit that combines the ideas into practical concepts and applications. Each one of these modules follows its own operational principles that we will inspect. Depending on the problem-framework, there are two basic strategies for its processing, namely Brainstorming and Programmable Strategy. Both can be managed by several techniques and tools whose usage result in the systematic decision making / innovative process that we underline for better quality and efficiency. We will also comment on computer-aided creativity boosting and the usage of The Internet as a creativity resource.

2.1.1.

Human mind and creativity

As a rule, human problems are created and solved by human interactions with the world and with other humans - and the tool for this is the brain, which works in cultural interaction. Problems can be sensed but not solved without identification. An unfortunate fact is that we understand only a little of how the human thinking works, still there are naturally many ways to model it. For instance, it is commonly known that the brain has a right and left

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hand side and that the left hand side seems to be more rational, logical, or verbal, and the right hand side is more emotional, divergent or visual. The brain can also be modeled by dividing it into historical layers as the reptile brain, the mammal brain and the outer cortex brain (The thinking cap - brain model [Herman, 1988].) However, these physiological models offer only limited ways to inspect human creativity, for instance, it has been shown in 3D Positron Emission Tomography (PET) brain activity maps that during creative processes the whole brain is usually active. However, the PET pictures have revealed also another interesting feature of human thinking: The difference in actually doing something and just imagining it is very small - this illustrates the power of imagination in human thinking. And indeed, human imagination is an essential basis for creativity. However, imagination in itself it is not enough: specific tools must be used to get a more cultivated, structured and matured creativity output in a limited, practical timeframe.

The associative three-stage thinking model For our purposes of inspecting creativity, we note that the brain is an associative parallel-processing based apparatus with an extensive amount of feedback. Memory and perception seems to be based, to a great extent, on various ways to do pattern recognition or nonlinear filtering, which means detecting and utilizing correlation. For instance, visual sense can be analyzed in its simplest signal processing bases to consist of concatenated filters tuned to detect certain patterns in visual stimulus, as for instance horizontal or vertical lines or colors [Kaiser, 2002]. In the brain, there are also more sophisticated filters that enable us to enjoy complex visual or audible patterns as facial expressions or music 1 . In addition, memory and any concept creation are associative: therefore remembering something involves always remembering something else. It is hardly exaggeration to say that the secret of our success on this planet earth is ultimately in our brain’s capability to filter reality into “human:concepts” that form for each one of us our own and personal human world. In this sense we never see the world, we see it only in our own conceptual reality. This is manifested in any kind of sensing that basically shows, and simultaneously (and automatically) analyzes the world for us. It is the infinite problem setting - solution process of human - society interactions reflecting in the thousands of names for God as presented by Arthur C. Clarke in one of his novels [Clarke, 1953].

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Modeling creativity In order to understand and model creativity, let us now inspect the model of human thinking depicted in Fig. 2.1. In this model the human creativity process is divided into the following operational sections: The Idea Generator, the Filter Bank and the Concept Extraction Unit. This model resembles closely the id-ego-superego-model of human psyche introduced by Sigmund Freud [Freud, 1923, 1931] that is interpreted here for our purposes2. The source of creativity is the Idea Generator: It is the place where all raw material for creative process is associatively stored. It is amazing how vast this storage is. This idea is illustrated in one of A. R. Lurija’s books [Lurija, 1988], by a description of a man (called as the Mnemonist) who is capable of memorizing with a high precision an amazing number of apparently random series of numbers, words and events, even after several years. The memory testing was arranged in sessions that were described by the researcher as follows: But these sessions only further complicated my position as experimenter, for it appeared that there was no limit either to the capacity of S’s [This is the pseudonym of the subject] memory or to the durability of the [memory] traces he retained. Experiments indicated that he had no difficulty reproducing any lengthy series of words whatever, even though these had originally been presented to him a week, a month, or even many years earlier. In fact, some of

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these experiments designed to test his retention were performed fifteen or sixteen years after the session in which he had originally recalled the words. How then, the Mnemonist could remember the thing the way he did? Reading the book further reveals that the answer was in associations: he concisely used associations to remember the lists though this was also boosted by his exceptional capabilities. In fact, it appears that in the brain, everything that is sensed or experienced is stored and processed by using associations - and making associations means always creating and using patterns. The following is an excerption from the help-file of the program Electric Mind® (www.rkwest.com), that is a versatile creativity software tool addressing especially the Idea Generator: The human brain is highly skilled at pattern recognition. It will find patterns even where they don’t really exist. That is why conspiracy theories are so popular. It’s why we can look at the sky and recognize images in the clouds. It’s why we love so much to sort and classify things. Our ability to find and create patterns is a wonderful survival skill, and it’s also a great aid to creativity. However, at times it can also interfere with creativity, if we find ourselves looking for, and depending on, familiar patterns and categories, rather than spotting new ones. Coming back to our model in Fig. 2.1, we pay attention to the apparent feedback in the process that leads us to consider it as a fractal-like information processing scheme: New concepts (from society, genotype and Filter) change both the way of seeing the world, e.g. they reshape the Filter, as well as complement the contents of the Idea Generator. Due to the fact that the Filter is changed, we will have new ways of seeing, acting and analyzing the World, that reshapes the Filter and Idea Generator and so forth. Putting it into other words, one may say that this associativity and feedback leads to the observation that considering, inspecting and especially understanding any piece of data or information leads apparently into a never-ending number of associations with some other piece of information stored in the Idea Generator that in turn enables new states of awareness via the Filter modifications. It is sometimes claimed that creativity is a talent that is typical for painters, architects, inventors and scientists and that the “ordinary people” have a little or no creativity. However, based on this model, creativity can be seen as a basic process of adapting any information and therefore all sensing and problem solving is built in creativity. Therefore, there should be no reason to be afraid that the process of human creativity could ever be emptied. However, it is important to remember that all of us are different and that our talents to express, produce and cultivate creativity vary greatly in number and in

Chapter 2 Process of Creativity

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shape. Still, I would like to argue that by studying structured methods of creativity cultivation, everybody can apply a higher quality of problem solving and decision-making in work and in life in general.

2.2.

Process of Creativity

In problem solving it is easy to be satisfied with traditional strategies if there is no need to use any better. For instance, this happens with some of the every-day problems that seem to follow regular patterns with the given or otherwise familiar solutions, such as what to wear, eat or who to meet. Here the required “amount of creativity” to solve the problem is small. However, in the modern working life one is frequently facing problem-frameworks that are more elaborate and hence harder to solve, such as: How to create a lasting mission and vision for our company? How to use modern ICT technology efficiently, or what is efficient ICT technology anyhow? Do we really need the gadgets that are potentially available? Do they really make us more efficient or add more Quality in life and work? (Should these be any of the goals?) Or, how to cope with globalization, international commerce and multi-cultural interactions? Additionally, organizing your team and your own work is a challenge: Often this means getting higher quality in lesser time. Solving more advanced problems requires more advanced thinking. Let us now consider a general model of the creativity cultivation process depicted in Fig. 2.2. A starting point in this process can be a known question or a realized status where only the problem framework (appearing as a syndrome of a problem) is sensed. In the figure this represents the phase of fuzziness and ambiguity. Due to the fact that only a little of the problem and all the associated external and internal factors are realized in this stage, our acts are guided by sensing and feeling: this is the area of arts and subconscious processing, and the area of passion and fear. In this stage it is important that your backgrounds are in-order both individually and socially. This means that you and your team needs to know and manage the substance, and there needs to be build-in talents and learned strategies in the area of the problem. Interactions between team members must also be well established, meaning that the applied languages and concepts should be recognizable or already familiar to the team. For successful creativity cultivation, the importance of multidisciplinary teams can hardly be underestimated because it gives diversity in interactions and enables building fruitful novel associations. Note that the fundamental teams of human life reside both in working life and in private life, and for optimum output they both must be fully functional.

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The more information we gather on the problem setting, the more aware we become of the problem framework. Often this involves finding the right questions among the many questions that may open up the path to an applicable solution. In this early stage of brainstorming these questions must be broad and they should not be guided by the idea of the potential answers because this restricts associations. However, all the questions are not useful. For instance: If your problem is that you are apparently loosing time in your work to daily routines a non-fruitful question would be: How can I get my children to bed early enough so that I can keep on working all night long. A better question could be: How do I spend my working hours to get such a low efficiency? What do I want to achieve in my work, or what really makes me so tired? When the cycle of creativity is successful, we form new concepts and find answers, but also, at the same time, realize new problems (due to the unavoidable and inherent Filter updates) that are now revealed from the new perspectives. Then, the wheel turns back with the updated vision and information in the Idea Generator, and the cycle is ready to start again. Usually this involves re-evaluation of your goals and re-motivating of your team. In Fig. 2.3 we have summarized how this process of creativity incorporates various society-associated interactions.

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Nowadays, decision making in high-tech industry is especially difficult due to the large number of relevant factors, monitored quality requirements, and tight schedules that are required to develop competitive inventions. The Cycle of Creativity does not make this decision making easier. In order to inspect the cycle at the best phase, you should be able to decide when the required level of expertise has been achieved and an applicable, high quality solution is available. Finding this out all by yourself is very difficult and you often cannot be sure that you have reached the goals or even if you have set them appropriately. Therefore, a group and all kinds of community support and networking is required in the related aspects of the creativity process to keep you informed of the relevant references and what is actually happening in your field. In practice, this means consultation and cooperation both with ordinary customers as well as with the multidisciplinary experts inside and outside of your team. This also means continuously recognizing and studying relevant references in your area of expertise, and learning skills of group interactions as well as studying applications and development of creativity techniques.

2.2.1.

Obstacles of creativity

Obstacles in manifestation of creativity relate to your personal attitudes and surrounding society, especially to working life, friends and family, and to the lack of mastering substance, as well as to the application of creativity techniques. Creativity involves always a build-in revolutionary feature - it is, by definition, going across boundaries, widening Filters - it is the art of seeing things in different ways and creating new worlds within the world. However, it is also a practical process of condensing and pruning this material into solid, practical ideas, tools and devices. In society, human communications is enabled by common concepts, the most obvious of these being the language. Generally, in order to participate to society, persons must agree, at least to a certain extent, to its rules and regulations. However, these rules can never be optimum for a certain person, particularly because all the persons are different!3 The rules have been formed in an averaged process of social interactions as for instance in the processes of language formation or legislation. If these rules can be made more transparent or understood in a wider sense, unrealized parts of the vast Idea Generator can become accessible and interactive. This is especially essential in the Information Society, where concept creation should be an elementary tool to enable the available raw data (for instance from Internet, TV and radio) to be transformed into condensed, applicable concepts that are useful for you and your workgroup.

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Creativity, however, is not a linear process. This means that due to the extensive feedback we discussed earlier (see Fig. 2.1), the ways we see the world is continuously updated by the created and absorbed new concepts. Therefore, a creative team or a person must be willing to tolerate the related insecurity. Creativity also demands much from a variety in groups” or individuals” talents. Fig. 2.4 extracts one cycle of the thinking process of Fig. 2.2. The start-up phase requires an artistic approach: there should be divergent and innovative attitudes. The end-phase, or the Concept Creation, requires scientific thinking that is convergent and logical. Only seldom can a single individual

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master all the required abilities. Therefore, group work has been proved to be an indispensable resource in the application of creativity. However, laws of group interaction may also suppress creativity, and therefore group and personal creativity must be suitably combined by a flexible, common group culture in order to get high quality, applicable results.

Let us now summarize and comment on some of the practical obstacles of creativity: Lack of concentration: This is a very important problem in the Information Society. There seems to be something more interesting to do or to see that can suppress and deviate our power to act, observe and focus. Lack of concentration is often associated to the lack of motivation. Especially in the Information Society, one may think that everything is done already: You say. “ I can’t invent anything original.” Note that an Eastern way to define an invention is to say: It is a copy that is just in some sense better than the original one. You may also say that you are so busy that there is no time to concentrate, because there are so many things to do and so little time. However, you should admit that without concentration nothing very cultivated can be done. Therefore, practice concentration. Do not watch too much TV. Reserve time for your creativity, accept that for your team and for yourself your own contribution is essential. You must be the processing unit: You need to form your own opinions and ways to act. If you learn to concentrate, you will note that you do not loose time, but you start mastering it. Too modest or ambitious goals: Be careful when setting your objectives. Set timetables. Even a badly planned timetable is better than no-timetable:

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you can update it later. Investigate your resources: try to understand what is the sufficient level of expertise that should be established by your creativity project. Discuss the objectives and ways of realizations with your team, such that a realistic, common plan can be sketched. Avoid doing any goal setting of your own only - try to learn your substance and utilize cooperation with high quality teams and references. Comfort with habits and routines: If you are used to doing the things in a certain ways, it can be difficult to find any motivation to change your strategies of working. Often you don’t even recognize them. One way to learn to understand and update your way of working is to vary or change environments, e.g. you should frequently find yourself in different projects, a different job, even a different life style, or you may even move to live in a different country. Also here, by discussing with skilful persons in different fields of arts and science, or different nationalities, you can create some scope. Use creativity techniques (such as those we will soon discuss) to find novel ways of thinking. If you can update and change your ways of doing things, you will note that a great deal of new energy and perspectives can be revealed. Fear of making mistakes: This is a very important obstacle. Creativity means unavoidably making mistakes. Try to remember that making mistakes does not necessarily matter so much because in creativity cultivation your objective is to find new solutions. Failing can be understood as a way to crack the solid surface of everyday logic and plant new flowers of creativity. Often, a mistake might not be ultimately a mistake; this happens if you see it in some alternative way. This might be possible only after a period. Note that great inventions have often been born by mistake. Making mistakes in your work or social teams is an unavoidable touchstone of substance know-how, motivation, courage, and learning. Rigid beliefs: Our world is full of magic without consciously making it a magical place. All the applicable human knowledge has been found and verified by making extensive testing about its applicability. Try to make a difference between your beliefs and reality. What are the true limitations of your thinking and acts? What would happen if you would dare to think in some other ways? What would you win or lose? Think about future requirements: Note that much of the future can be predicted based on today’s probabilities and knowing, shaping and using these probabilities is an efficient way of shaping the future. Upbringing: Growing up means often criticizing or even abandoning your parents’ way of thinking. However, the effect of upbringing usually remains unconsciously strong even for grownups. Upbringing has usually both positive and negative effects. Try to see what is behind your attitudes, and whether they serve your present environment and challenges. Try to find strong colleagues, teams and topics to challenge your way of thinking. Strong

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challenges may help you to recognize, utilize and cope with your upbringing better. Fear of change, consequences and the weight of previous solutions: We live in a causal world meaning that for each act there exists a consequence. Don’t be afraid to change the world. Without change there is no creativity manifestation. Your previous solution might have been a working one, but you must not tie yourself to it while searching for new ones when situations require a change or launching a new concept. Absolute truths, certainty and boredom: Think why you should believe in absolute truths. For creativity it is more useful to think that objects, things and thoughts have a myriad of different properties that are interesting and more than often, can also turn out to be applicable. Challenging the conventional solutions is essential when you search for novel solutions. Certainty and creativity can only seldom be combined. If you have a tendency to boredom, you may relieve it by knowing that you never see the whole reality, only the part you are observing right now based on your present status and your history. The truth is always much more imaginable than you can ever know. Obeying principles and unwillingness to play games: To work creatively, try to understand what are the principles of objects and processes. What are your own principles of thinking? Try to learn what are the laws of nature and the nature of laws. Study the behavior of your society and how the things are thought in other societies. By recognizing principles at several levels you get more freedom for creativity because only by knowing the rules can you play and playing is an essence of creativity. However, nobody knows all the rules and sometimes we all need rule updates. Self-doubt, self-criticism, negative or too rational thought, and fear of appearing childish: Don’t doubt yourself when generating new ideas – this blocks too much information. If you wish to cultivate yourself to be a more applicable creative person, then take part in teamwork and take new challenges that reveal your properties better than just by concentrating on them by yourself. Don’t be afraid to appear childish: The only stupid question is the question that has not been asked. Don’t be afraid to combine your thoughts in irrational ways. We all do this, especially in our dreams. Irrationality is an important source of creativity. Language: Human thinking is strongly language associated: Different languages and concepts that interpret and describe the reality for us via our senses, as it appears for individuals, establish Information. Therefore, the concepts connect and separate us from the world - this refers to the Filters we have addressed earlier. Creativity means application of the present, updated and novel languages to describe, separate and process information. Learn to love and understand different languages for your pleasure of creativity!

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2.2.2.

Boosting creativity

New material fed to the Idea Generator is concisely and unconsciously absorbed from various sources of the ICT society as from papers, TV, radio and The Internet. This forms an important new raw material for the Idea Generator. Often a boost for creativity comes from external challenges - this can be some change in your life. In working life, participation to a new team might stimulate creativity because there are new persons and new problems to face. Creativity is like swimming or riding a bicycle - you must learn it by doing it. Creativity can indeed be enhanced. Here are some practical hints: Remember that all great inventions are connected to other inventions. Sir Isaac Newton summarized this as follows: “If I have seen farther, it’s by standing on the shoulders of giants.” Creativity means finding novel ideas – You may say, something a man can patent or use to establish an enterprise. An everyday illusion is that things that are invented own a significant amount of originality brought about by the inventor. Usually this is not the case. Usually originality originates from other persons’ work and that originates from other persons’ work etc. Often, chance has a great input in the process as can be seen in the history of many great inventions as penicillin, transistor, or Fox Talbot’s invention of the first photographs (calotypes) taken in 1840 [pbs, 2000; Fox, 2001]. Often creativity means active coping that is not intended for rapid profit. It is studying the inner structures of processes - it can also be reversed engineering. If the inner structure is understood, it can refine the Idea Generator and create new associations to inspect the earlier absorbed material in a new way. In the world of arts it is sometimes said that “a genuine, handmade copy” is a solid bases to establish a new style of your own! This might be a reason why the studying of paintings by copying great masters has been an elementary part of art education for ages. The same also applies to technology studies that are in very great deal investigation of earlier inventions. This idea extends even to society development. A great number of examples of the blessing of copying is seen in the rise of Japanese technology into the quality and creativity flagship of the ‘90-‘00 from the copycat of the ‘50-‘80. Take care of your substance and out-of substance know-how. This means that you should dedicate yourself to new facts and activities that you are not familiar with. If you are a technical person, try to do something artistic; if you are an artistic person, try to do some technical stuff. Strive to concisely change your paradigms - thus more vision, liberty and power can be injected to your creativity. Note that nowadays many disciplines combine science and art for successful business cases! Read magazines

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and newspapers; follow chat groups and discussion forums. Go out and listen to presentations on topics of current interest and also on out-of main streams. In order to master your substance know-how: Study the Laws of Nature and the Nature of Laws. Take notes: Write down your observations and ideas. You may first just list them but arrange them soon into Mind maps to include associations. Learn different creativity techniques and try them in practice! Be perceptive. Follow TV only for special programs of interest, a documentary or a great movie. Generally, strive to limit your TV watching and prefer interactive media. Use games for interactions and not to escape from reality. Emphasize your own thinking, meetings and discussions with your colleagues and friends. Remember to relax! Try to be without thinking the problem. As we have suggested, streams of creativity can be dammed by your conventional way of thinking. It might even happen that when you try very hard, the more difficult it comes to find any applicable solutions. Then, a solution might be in canceling out the thinking altogether! If you test this technique you find out how difficult it is to be without thinking even for one minute - to start with. However, you note that in the state of non-thinking, the Filter structure we discussed earlier, is suddenly greatly relaxed and when your consciousness returns, new material has suddenly emerged from the Idea Generator to your consciousness that might give the missing link or piece of data to continue with your process. Non-thinking resembles in great deal the relaxing and refreshing effect of dreaming. Be persistent and withstand criticism, errors are an essential part of creativity, discoveries and learning. The creative attitude was summarized a long time ago by Leonardo da Vinci as follows: Study the science of art, study the art of science, develop your senses - especially learn how to see, realize that everything connects to everything else.

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2.3.

2.3.1.

Handbook of Product and Service Development in Communication and Information Technology

Structured Creativity Techniques

Brainstorming and programmable creativity

We will now discuss the two basic structured creativity cultivation strategies as depicted in Fig. 2.5. Brainstorming [Gordon, 1961] is applicable to a wide range of innovation work, such as “What should be the Vision and Strategy of our company?” or “How to maintain our Customer Relations Management system?” It relies on boosting creativity first by opening-up obstacles of creativity and then by using different techniques of critical thinking to filter out the applicable solutions. In Brainstorming, the following general steps can be identified:

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1. Think about the concepts and facts that relate to the problem-framework (eg define the innovative objects) and list them. Thus, the topmost objects of Fig. 2.5 can be recognized.

2. Recognize and connect the listed elements by associations and/or operational links. In the figure, these are the colored, smaller parts in the objects. In practice this phase can be realized by Mind mapping (Fig. 2.10.)

3. Categorize and rank the elements by using the connections/associations of #2 above and by using your / team’s substance expertise. 4. Select and analyze the most applicable solutions by critical inspection in cooperation with your team. Care must be taken in selection of the applicable solutions because this is a dominant quality factor of the process. Here the methods of the Six Thinking Hats or Lateral Thinking [de Bono, 1990] (Section 2.3.4) provide often some help. A very simple guide to Brainstorming is build-in to the Brainstormer - program [JBL, 2002].

Techniques for effective brainstorming While starting Brainstorming, one should be as open-minded as possible and try to neglect all the criticism, because this means blocking of potentially useful raw material. In group brainstorming the free flow of ideas can be boosted by taking open-minded group members from different disciplines that are not afraid to make stupid questions. In individual Brainstorming one uses free associations that yield, at first, quite irrational outputs that later associate into more recognizable concepts. This can be assisted by The Filter Modification tools (Fig. 2.8.). Usually, more ideas appear in group Brainstorming, but group culture may hinder revealing truly revolutionary ideas. Individual Brainstorming pop-ups more original ideas but a problem is to get jammed into a certain, individually typical way of thinking. Therefore, it is recommended to apply individual and group Brainstorming interlaced. Brainstorming can be greatly enhanced by appointing supervising persons to guide the session: Session leader: This person should guide and facilitate the session, but should not interfere with his own opinions such that other opinions are persuaded or suspended. He should track time and allow everybody to express his or her minds. He should encourage the participants individually and at the group level. He should have - if possible - good general knowledge.

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Secretary: This person should document the process and assist the session leader to track the session flow. Tool-assistant: This person should be aware of creativity tools that can be used to assist the session. Note that these tools include both various computer programs as well as independent methods. Customer representative: This person should take into account the practical perspectives of the brainstorming objectives. He should interfere with the brainstorming process significantly only after substantial amount of ideas has been mapped and there seems to be not many new ideas appearing anymore. This person is responsible for bringing in the customer’s ideas and objectives as the initial opinion of company’s executives, practical constrains as money, time and personnel resources. Social facilitator: This person works in close co-operation with the persons listed above. He has had preliminary discussions with them and has formed himself a framework of the Brainstorming themes. However, he should not decide what the solution is, or even, what the problem is. Instead, he should be aware of the laws of group dynamics and human personalities and be well prepared to boost group creativity based on this framework. Technical facilitator: This person is required to assist in the realization technology related matters e.g. product development tools and production technology and general commercial aspects. Group members: These open-minded persons should be able to express their ideas and to communicate with each other. They should be able to visualize their ideas easily to different disciplines and to have fluent oral presentation. They should represent a wide range of disciplines and cultures.

2.3.2.

Programmable creativity

Let us now inspect the Programmable Creativity (Fig. 2.5). The Programmable Creativity - techniques apply to relatively tightly defined problems, such as “How to transform a photograph into a picture to look like a water color painting?” or “How to convert a set of photographs into a 3D sculpture of the object?” These call clearly a programmable solution as demonstrated in [Ulead, 1999; Photoshop, 2002]. (Note that the design of the programs itself is, of course, a Brainstorming – type problem.) ‘Replacement

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Matching’ is a general-purpose method of Programmable Creativity in which the following steps can be identified (Fig. 2.6):

1. Define the relevant trait T for a given product P. 2. List the symbols S that completely and unquestionably invoke T. 3. Construct the P-space consisting of the objects that are strongly correlated with P. 4. Substitute an aspect A of one of the objects in place of the corresponding aspect of S. 5. Repeat the stages above to produce more ideas.

It was then applied to find slogans for commercials. For example, the following slogans were produced [Goldberg, 2000]: An Apple Computer terminal offering flowers (for advertising of Apple Computers friendliness). Temple Mountain Mosque with Tennis ball texture (for advertising World Cup Tennis Tournament in Jerusalem). A cuckoo in the shape of a plane emerging from the cuckoo clock (for advertising the time accuracy of an airline company). Two Jeeps communicating in sign language (for silent car engine). A bullet-shaped car (for fast car).

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In this example, we note that the original innovation objects (the Brainstorming raw material from the Idea Generator) is first partitioned into more tangible basic elements, presenting the essential properties. Thereafter these elements are re-combined at random, but in a structured way, by following the problem setting topology. Thus, the following generalized steps of Programmable Creativity can be identified (Fig.2.5.): 1. Find out the innovation objects and the associative links. Note that you can use Brainstorming for this. 2. Separate the “headers” and “tails” of the concepts. In the example above the product’s trait and its listed symbols formed the header and the tail parts. 3. Create new lists of the correlated objects with their distinctive header and tail parts. 4. Link associatively the old and the new objects by their similar headers or tails. 5. Repeat steps 1 -4 to generate more ideas.

In Programmable Creativity, a template (a set of rules) is created that is used to channel the resources of Idea Generator. This channeling resembles greatly the Filtering we discussed earlier (Fig. 2.1). In Replace Matching, the template was a set of rules to produce the themes for commercials. Programmable Creativity templates are nowadays produced for many disciplines of Art and Science that were earlier thought to be dedicated for human creativity only, as for innovating music, paintings and drama [Photoshop, 2002; Bbox, 2002; Dramatica, 2002]. However, for many innovative problems, such templates are not readily available and producing them by yourself is usually out of the question. In addition, often you don’t need a programmable solution, because you need to solve the problem seldom or maybe only once. In this case, you may apply Brainstorming or consult experts to illustrate your problem framework.

2.3.3.

Creativity tools and the three-stage thinking model

In this chapter we investigate the systematic innovation cultivation methods by inspecting assisting computer programs (Fig. 2.8 and 2.9) by following the Three-Stage Thinking model (Fig. 2.1). As we noticed earlier, all the raw material of creativity is associatively stored in the Idea Generator. The Filters then further process this material. The target substance, workgroup,

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society and your own inherent properties determine them. Part of the Filters can be concisely modified by various methods that influence to our ways of thinking. Modification of Filters can greatly expand the range/applicability of the produced solutions. A set of creativity programs to assist you with the each stage of the model is collected to Fig. 2.9. Tools for the idea generator There are many methods and tools for Idea Generation. They apply for instance the following methods: Programmable random sentences from given words: Generating of random-word -sentences may help you to recognize unidentified thinking patterns. For obvious reason, one has the basic assumption that the solutions should be logical and therefore all problems search first for logical answers. Well, usually solutions are logical, but we don’t realize the whole logic behind them - and this is ultimately the problem whose identification requires creativity. Logical structures are constructed based on some basic assumptions that may or may not be conscious. If you can drop out your conventional way of thinking and your logic for a while, e.g. relax from your basic assumptions, new solutions are easier to find. This can be assisted by using free associative chains. For instance, if your problem were to find a better car because your old car has become too expensive to repair you might try to solve the problem with free associations by establishing the following associative chain: car, wheel, move, go, man, move, feet, town, job, money, train, airplane, bus ... and then you suddenly realize that you don’t actually need a car because you live in a city area where public transportation is cheap and its routes are extensive! A program to assist with associative thinking is the Electric Mind, that contains also an extensive help [ Rkwest, 2000]. Programmable word association: Give a word, and the program finds the respective associative words. This is realized for instance in Open Office® Thesaurus-feature. The resulting associations may reveal novel association chains that were previously unrecognized. Other programs include Idea Fisher® and Serious Creativity® [Idea, 2002; Serious, 2002] that also have a plentitude of extra creativity tools. Use of Doodles: One may agitate the Idea Generator by Doodles (Fig. 2.7). These are reinforcible pictures, starting from some simple patterns of lines or other shapes. They can be used to guide and enhance creativity, for instance, to help you to get started in a Brainstorming session. One

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interesting application of doodles is in the design of logos that is often considered to be a challenging form of art. For further information, see [JBL, 2002].

Synetics: The Idea Generator can be aggregated by applying a series of “Triggering Questions” or the “Synetics Questions” [Gordon, 1961]. This also strives to modify and identify the problem framework: Substitute/Simplify (What would you do in my place?) Combine (Think about a software being capable of evolving and reproducing?) Adapt (Think what would happen if you would have wings?) Modify/Distort (What if cars would be used sometimes upsidedown?) Put to other purposes (Think your mailbox as a kite!) Eliminate (What would you end up by removing the batteries?) Rearrange/Reverse/Scale (Reverse the order of sequence?) Let us take a practical example of Scaling: Sometimes changing the scale of the problem might change its form. For instance, if your problem is that you are too worried about your health, think about a certain probability that a car may run over you in the first sidewalk you use tomorrow morning, or the building where you are just now can collapse and kill you, or you might accidentally fall over in your chair just now and break your neck. If you exaggerate enough you might realize a true perspective for your problem. Applicable

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programs include the Brainstorming Toolbox®, and the Axon 2002 [BR, 2002; Axon 2002, 2002].

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Filter Modifications The objective of the Filter Modifications (Fig. 2.8) is to further process the material available in the Idea Generator by intentionally introducing different perspectives. Thus, new associations and structures can be generated and the focus can be sharpen (de Bono’s refers to this stage as “separating ego

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from performance”). This is based on the idea that we can concisely change the way we think. Let us now consider some methods suggested by de Bono:

The Six Thinking Hats This is a method that applies role-play to understand the problem framework. As we have noted earlier without the problem asker, there is no observed problem4. Hence, the role of the person who sets the question is an elementary one. The method of the Six Thinking Hats, is based on changing a person’s point of view to the problem, e.g. here your hat determines your role with respect of the problem5. De Bono suggests the usage of the following hats: The White Hat of Rationality: This observes the logically obvious and measurable things. Here the bases are in logic and in reasoning. The Yellow Hat of Positive-Logic: This hat underlines the things that work well. This hat also strives to find reasons why they work so well. The Yellow Hat works in close co-operation with the White Hat. The Yellow Hat can be seen to be in opposition to the Black Hat. The Black Hat of Judgment: This hat observes drawbacks, underlines potential threats and sorts things into favorable and less favorable classes. The Red Hat of Emotions: This hat is artistic and emotional presenting predominantly the traditional thinking of the right hand side of the brain. The Green Hat of Creativity: This hat gives alternatives, takes easily novel logical paths and provokes to realize alternative paths that are not easily recognized by other hats. The Blue Hat that Controls the Hats: This hat strives to see the whole problem framework and all team members. It strives to combine the worlds lying underneath the other hats. The Blue Hat associates to a metaconsciousness. How do you then apply the Hats in creative thinking? The basic idea is to swap the Hats: In individual Brainstorming you may generate different Mind maps for each hat by taking a different hat for yourself. In group Brainstorming hats should be changed between group members. Dr. de Bono also sells a computer program, Serious Creativity®, to assist you in applying the Hats. This software consists of the three modules: (a) Creativity Courseware®, IdeaPro® and Creativity Reference®. The program covers an amazing number of techniques of creative thinking. In addition, there are over 7 hours of

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lectures about creativity given by de Bono. In my opinion, there is really a lot of interesting stuff here. However, the program is quite expensive. In order to get started even without the program, the idea of The Hats can well be tested in any Brainstorming session and one can be sure to discover many useful connections and ideas.

Lateral Thinking Lateral Thinking means using logic and intuition in an unconventional way. The Six Thinking Hats is one flavor of Lateral Thinking. One may say that Lateral Thinking is a conscious way to find unconventional solutions hence it is a form of art and requires some inspiration and practical exercises to be applied successfully. This method is especially valuable when one has a tendency to end up to problems that seem to be unsolvable by their nature. It can also be used as an integrated part in Mind mapping. The following characteristics can be identified in Lateral Thinking: Strive to consider your problem framework globally enabling you to extract its significant features. Often this means making an extensive comparison to other comparable problems. Generate different points of views to your problem: Consider it by using different frameworks. An example is The Thinking Hats -approach. You may try to identify what the simple logic in your problem is and try to manage without it. Being illogical may reveal new features in your problem and its potential solution! Try to think in human ways: appreciate humor, culture and personality. We take an example: Mommy gets worried about her son’s cigarette smoking and complains about it frequently but nothing happens. Happy enough, smoking happens always outdoors and everybody can still enjoy clean indoor air apart from occasional bad breathing. One day the son comes home and finds his mommy smoking so heavily that it is practically intolerable to be indoors. This swaps roles of the mom and son and opens up a new perspective, and a potential new base for discussions. This is Lateral Thinking – the problem is set to a new framework that enables new ways for its analysis.

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Associative Mapping By following Fig. 2.8 we now address some tools of The Associative Mapping. A typical example is the Mind map shown in Fig. 2.10. In addition to supplying information for idea cultivation, Mind mapping can also be used as a general-purpose notepad, recording not only the data but also the related associations. This can improve your learning curve, for instance, while making notes in a lecture. One interesting application of the Mind mapping is to find out how well people have understood lessons in a course. At the beginning of the course their Mind maps have only a few disorganized branches and in the end their Mind maps should be large and full of branches. Dedicated computer programs are an elaborated way for doing the Mind mapping. Their benefits include easy editing of the clustered maps, vivid possibilities to illustrate ideas, ability to produce associative objects as documents, adding videos and other multimedia elements, and possibility to include sub-Mind maps. Hence, they enable one to present complicated maps easily and distribute them by email within your team. For instance, Mind Manager by Mindjet Inc. is an entry-level tool that allows easy creation and edit of the branches and their labels, associations and illustrative icons. Also sub-Mind maps are supported. For a still more demanding user one can apply Axon Idea Processor (an integrated part of Axon 2002®) that incorporates a

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build-in interactive programming language, Prolog, to further arrange ideas, for instance, to Fish-Bone or Lotus Blossom Diagrams where the first one is illustrated in the Fig. 2.11. A popular way to map problem framework is to arrange it into SWOT (Strength, Weaknesses, Opportunities, Threats) fields. One mapping technique that is often forgotten is the Venn diagram that illustrates your problem by settings overlaying theme areas to show-up a novel illustration of your problem framework. For details see the Axon 2002 help files / section “Templates”.

Concept Testing / Decision Making The last stage of the creativity cultivation methodology in Fig. 2.8 strives to validate and rank various potentially applicable alternative solutions, and to reveal the most applicable solutions. In order to realize this efficiently and with high quality, it is extremely important that you have substance knowhow in your group. In addition, a set of structured Decision Making/Concept Testing techniques should be mastered. We now briefly give a sample of those:

FFA- and PMI-analysis FFA (Force Field Analysis) and PMI (Pius/Minus/Indifferent) strive to validate different forces for and against the solution. They can also be used to make solution justifications by adjusting the discovered factors and forces. The FFA can be realized simply by giving scores to the forces against and in favor of each of the potential solutions and by scoring them in some, fixed, predefined scale. Scoring of FFA can sometimes be difficult or unreliable, because it may require finesse of expertise, or future foresight that is unreachable, for instance due to the limited time. In this case you may consider the PMI-method, in which you assign only plusses, minuses or nulls to the different alternatives and sum them up. Both methods are simple, but surprisingly efficient when applied to validating and tuning your problem-solution framework.

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Question methods In order to find the most applicable solutions you should invite somebody in your problem framework target group to visit your innovative team to make civilized and less-civilized questions about discovered connections, solutions and new inventions. This is often a very interesting and fruitful test of applicability, and surprising bottlenecks and drawbacks can be revealed that shall challenge your inventions. The Question methods can be realized by using some ready-made question-sets. An example is the “Wishful Thinking Technique” that is based on imagining a perfect solution and then making a comparison that shows how much your solution deviates from the ideal one6. One can also use the “Analogy Technique”, which applies analogy or metaphor to the solution in order to discover how similar problems have been solved in other fields. One can also apply the Why-why diagram that processes the problem by revealing some of the underlying logic by re-mapping as depicted in Fig. 2.12 [Axon 2002, 2002, Serious 2002].

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Summarizing By summarizing creativity process outcome, elementary factors can often be revealed and validated. Let us suppose that you are working as a group leader and collecting preliminary problem solutions from the group members into a report. Among other things, this means that you should find out the key concepts of each of the texts, and check that the facts are explained correctly. Your task would then to be to make decision about truly relevant factors required to solve the problem, and then to decide on a strategy for proceeding. This task can be assisted by making a summary of all the reports. When you read all the reports you may collect the key-points into a Microsoft PowerPoint® presentation, which will help you to make the important facts distinct. Drawing the concepts further into figures may reveal more about the underlying structures. Often you do the summarizing by hand, but it can also be programmed by using the Copernic Summarizer® [Copernic, 2002]. This program can summarize text from various sources as for instance from Word

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documents and from Internet pages. It can also work in real-time in web surfing.

Case studies In order to validate your solutions, Case Studies are frequently applied. This means that you or your team imagines a practical situation where your invention or process is used or tested. Case Study can be realized by verbal story telling, or you may draw a cartoon. If your team can invite a potential user of your invention a more realistic Case Study might be sketched. (Note that a Question Method also used visiting users to justify and refine solution’s validity.) Structured Case Studies can also be realized by using the Pentadmethod [Burge, 1945] which sets a certain group of questions to guide a Story-Telling plot: What is the action? (What is happening?) Who is the actor? (Who is doing the action?) What is the means? (How is the actor doing the action?) What is the purpose? (Why is the action being done?) What is the scene? (Where and when is the action occurring?) A PROLOG-version of Story-Telling is available in Axon 2002 tutorials under the help-file title “Organizing Ideas” in “Writing Demo”.

2.3.4.

Web and creativity

The Internet has become a splendid tool for getting material for creativity cultivation. One reason for The Web’s popularity is probably its apparent easiness of search and retrieval. There is also plenty of material available. However, this powerful tool has a number of important weaknesses that you should be aware of. In web searching, the first thing that one notes is that a search results usually mass of references to the documents relating way or another to your search words. How well these links then address you problem framwork? Well, sometimes they do, but often you must go through many documents before you find the things you are actually searching for. This happens due to the language gap between you and the search engine: It is often difficult to describe the problem framework in such a way that its answers can be pinpointed accurately from The Web. If we could develop a search engine that

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could map The Web’s information the same way that our brain stores information (meaning amazing finesse of associations), the chances of getting more accurate (and intelligent!) answers would be greater. But still, it would be very difficult for this machine to know the question what you really want to know, e.g. your true problem-framework.

As we have stated earlier, knowing the right question is an essential part of the applicable answer. Search engines rely on assumption that all the documents having your search words give a potential answer for your question. However, this need not be the case. Indeed, your answer can be embedded in several documents whose information should be creatively combined to realize the question and the answer. It is also possible that your intended target is in none of these documents. For instance, it is not included to the data base in a recognizable format, or it has not been invented, or your search words simply carry a different meaning due to the different perspectives (or paradigms) of the target documents. Some important properties of The Web as a creativity tool are summarized in Table 2.1. As you note, most of the weaknesses relate to the fact that you should know what to search e.g. to be aware of your own perspectives.

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Therefore, in order to target the Big Picture and to reassure the focus, search first for quality books (read readers comments on bookstores’ websites and other critics) and tutorial-type journal articles. Nowadays, libraries have extensive Websites with a large collection of online journals. After you have found and browsed through your key-publications, you may continue (as required) to work with other, more detailed references. For target’s validity, pay attention to authors, workgroups, and institutions. Publication date is important, old references carry different status than the new ones. After you have collected a number of references from The Web you need to stop and reorganize the information for your purposes. While doing this, your objectives are likely updated. For summarizing website contents you may apply Copernic Summarizer® although it has currently some drawbacks, e.g. distinction of the elements of your concern is not guaranteed and often you must go through the source material also by hand. This is one of the problems with the Web in general - there is simply too much material and you have too little time! This is precisely the reason that you have to focus on key references from the very early stages of your creative process. Moreover, surfing as it is, is a problem - it easily deviates your concentration. In summary, the Web is a magnificent and powerful tool and resource, but we need to be skilful and aware to get the best creativity push out of it.

2.4.

Summary

We have considered in this chapter a way to model human thinking and shown how creativity can be inspected and cultivated in a structured way. All the methods require practice to be mastered, therefore test and study these methods in practice. Still, it may take some time to get used to apply Systematic Creativity, your efforts will be rewarded by better-managed timetables and generally improved quality. Discuss creativity techniques and share problem-frameworks with your team and other colleagues. This is a challenge that is worth while taking seriously: the resulting discoveries make your work and life both more efficient and more enjoyable.

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NOTES 1.

This links perception into personality manifested by reasoning and emotions. Therefore one may regard using the concept of Filter a rough oversimplification. However, for our purposes, this simplification owns no major obstacles because we are interested only in developing a general model to inspect in a common, applicable framework of human thinking.

2.

An outline of our interpretation is also suggested by a Finnish brain researcher Matti Bergström [Bergström, 1979,1984]

3.

We may say that all the problems between humans are basically language problems because we don’t have a common consciousness.

4.

One may speculate if there is any problem if it is not observed.

5.

Note that it is interesting to see the resembles of this approach to everyday life where we carry several roles at home and in work. Thus this is an enjoyable role playing game.

6.

For more details see http://www.brainstorming.co.uk/tutorials/ wishfulthinkingtutorial.html

REFERENCES [Axon 2002, 2002]

Axon 2002 manual, available at http://web.singnet.com.sg/ ~axon2000/index.htm

[Bbox, 2002]

Band-in-a-Box® program by PG Music Inc.

[Bergström, 1979]

Bergström, M., Aivojen fysiologiasta ja psyykestä, 1979.

[Bergström, 1984]

Bergström, M., Vihreä teoria, 1984.

[BR, 2002]

www.brainstorming.co.uk:

[Burge, 1945]

Burge, K., A Grammar Of Motives Dealing With The Intrinsic Nature Of A Work Focusing On Dramatism And The Pentad, 1945, see also http://bradley.bradley.edu/~ell/burke.html.

[Clarke, 1953]

Clarke, A.C., Nine Billion Names of God, 1953.

[Copernic, 2002]

The Copernic Summarizer® program, www.copernic.com

[deBono, 1990]

de Bono, E., Lateral Thinking - Creativity Step-by-Step, 1990.

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[de Bono, 2002]

de Bono, E., Creativity and Quality, 2002, available at http://www.debono.com/quality.htm.

[Dramatica, 2002]

The Dramatica® program, www.dramatica.com

[Fox, 2002]

http://www.rleggat.com/photohistory/history/talbot.htm

[Freud, 1923]

Freud, S., The Ego and the Id, 1923.

[Freud, 1931]

Freud, S., The DisSection of the Psychical Personality, 1931.

[Goldberg, 1990]

Goldenberg, J., Mazursky, D. and Solomon, S., “Creative Sparks”, Science, vol. 285, 1990, available also at http://pluto.huji.ac.il.

[Gordon, 1961]

Gordon, W.J.J., Synetics: The development of creative capacity, 1961.

[Herman, 1988]

Hermann, N., The Creative Brain, 1988.

[Idea, 2002]

The Idea Fisher® program, www.ideafisher.com

[JBL, 2002]

http://www.jpb.com/ creative/doodles/ artdoodles.html#artdoodles.

[Keiser, 2002]

Keiser, P.K., The Joy of Visual Perception, 2002, available at http://www.yorku.ca/eye/thejoy.htm.

[Lurija, 1988]

Lurija, A.R., The Mind of a Mnemonist, 1988.

[Photoshop, 2002]

The Photoshop® program, www.adobe.com

[pbs, 2002]

http://www.pbs.org/ transistor/ background1/ events/miraclemo.html

[Rkwest,2000]

The Electric Mind® program, www.rkwest.com

[Serious, 2002]

The Serious Creativity® program, www.sixhats.com

[Ulead, 1999]

The Face Factory® program, Ulead Systems Inc, , www.ulead.com

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Chapter 3 USER CENTERED DESIGN OF TELECOMMUNICATIONS SERVICES Sanna Belitz*, Merja Ranta-aho**, Raila Äijö*, *Helsinki University of Technology, **Elisa Communications Ltd

3.1.

Introduction

Close your eyes and imagine that you are a technical expert in the great product development team of a telecom service provider. You have brought in a great innovation that will change the way people communicate using their mobile phones. On the basis of that, you develop a great messaging service. You go to the technology manager. She prompts you to explain how this product would be realized with the current network system infrastructure, how it would be connected to the billing system and customer care system, and so on. Lots of technological challenges are there to be solved, but finally you have the solutions. Then comes the marketing manager. He asks who will actually buy the service. Who is the target group, and what is the market potential of the service? Are there competing services? How would this service stand out among its competitors? Luckily, your team also has the answers to those questions. You produce and launch the service. Despite a great marketing effort and flawless technology, the service does not sell very well. You do get users trying your service out - ten points for marketing - but your usage statistics show that almost no-one uses the service twice. Hence, you fail to create sufficient sales volume to pay for the development and running costs of the service you have created. What went wrong, you wonder over and over again. It’s not the price even during promotional offers where users could use it for free, usage does not increase. Technically, the service functions perfectly, with any operator 45

T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 45-78. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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and every mobile phone model. Market research shows that awareness of the service is good. But then you start asking those who tried it out. There are many possible explanations that your users might give: a service too hard to learn to use, a service too cumbersome to use, a service that almost serves your needs, but not fully enough. All of them lead to one conclusion: technological perfection and great marketing are not enough. The time has come for high-tech telecom services to reach the point where a third factor, user experience plays a great role in differentiating among products. This chapter first introduces the concept of user experience and discusses why it is especially important in current and future telecommunications services. The second part of the chapter introduces user-centered design – an approach and collection of methods that can be used during product design to enhance user experience. The third part discusses the relationship of usercentered design to the product design process and managing user-centered design activities as part of the product design project.

3.2.

Viewpoints on user experience

“User experience” is the buzzword of the day in the design business. But what exactly does an experience mean? It is a vague concept which can be described as the chain of conscious events constantly going on in our mind in relation to what happens to us in an environment [Carlson, 1997]. It can also be described as a singular reaction to something we perceive, a reaction that has a beginning and an end and which always changes us in some way [Dewey, 1963]. In experiences the cognitive, the emotional, and the cultural world are closely intertwined. “Acceptability” [Nielsen, 1993] is a concept that sums up together all, or at least some, of the factors that affect the take-up and acceptance of a product or service. It consists of very diverse factors, some of which have to do with the technical aspects of the product itself, such as reliability and interoperability with other products. Others depend more on marketing aspects, e.g. cost and social acceptability. A third group of factors relates to how the user experiences the product while using it, for example usefulness and ease of use.

3.2.1.

The evolution of usability

Usability in the everyday context is often understood only as the ease of learning or ease of use of a system. But there are also other factors [Nielsen, 1993]. Good usability means that, for instance, the memorability of the sys-

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tem is good and making errors is hard or impossible. Usable products enhance the effectiveness and efficiency of work and are satisfying to the user [ISO 9241-11]. Usability is thus considered a product quality factor. In producing a usable product the users and their goals, as well as the context of use, must be specified. Besides usability, the system’s usefulness also has to be taken into account. Usefulness in this context depends on how relevant the specified goals are for a certain user in a certain situation. If the users are not able to reach their goals with the product, the product is useless, no matter how usable it is. Views about the importance of usability in product design the actual meaning of the term, and its relationship to utility have changed during the decades the concept has been in use. Rosson and Carroll (2001) describe how the term usability was first used in software design in the context of the usability of program code. In the ‘70s, the usability of software was measured mainly in terms of the efficiency and error-free usage of a system. In the latest interpretation, usability and usefulness are closely inter-related. The usability viewpoint in itself is quite rational, assuming a goaloriented user wanting to achieve something. This is quite natural, as usability is a concept developed chiefly on the basis of human-computer interaction research. According to Preece et al. (1994), the main goal in studying humancomputer interaction (HCI) is to understand and describe how information flows between the man and the machine. The theoretical foundation of HCI lies firmly in cognitive psychology, which studies information processing activities such as thinking, reasoning, and memory in the goal-oriented behavior of man. This approach might have been appropriate for developing systems for work, but, especially for the development of consumer products, other factors might be even more important for the acceptance and success of products. Since the development of graphic user interfaces, little has happened in the fields of HCI and usability research. Today, however, small mobile communication devices, as well as applications for collaborative work and distance education, are posing a new challenge to interface and interaction design. In the search for new innovations research methods have also changed, from laboratory research to ethnographic research. 3.2.2.

The meaning of emotions in product design

“The shop assistant threw the biscuit at my feet. I bent down and subserviently began to pick up the crumbs. After some fiddling, I managed to get my change out of his clenched fist.” [Overbeeke, 1999].

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If you were treated like this in a shop, you would be very offended. But, as Overbeeke et al. point out, this is how the vending machine treats you when you are buying your daily snack. Are there different standards in people’s minds for the quality of human-machine interaction and human-human interaction, then? The research indicates that there are not. Although designers and engineers have not really placed much emphasis on the importance of respecting their users, research shows that they should. People relate to computers and other media as if they were social agents [Reeves, 1996], Because of that they subconsciously expect the machines and their contents to act according to the same social conventions as the users do. With their “behavior” the machines can make people happy or irritated. This, of course, affects what the users think of the product and its manufacturers. Understanding of what makes people feel good or bad when interacting with other agents thus provides valuable information for designers. As mentioned before, the theoretical foundation of HCI lays in cognitive psychology. However, the current scientific knowledge of human psychology shows that emotions are as important as determiners of action in goal-oriented behavior as is cognition [Goleman, 1995]. Studies indicate that only a few milliseconds after perceiving something we already have a first subconscious idea of whether we like what we have experienced. This again defines further action. When we are making decisions, what we feel leads us in the right direction to where the logical thought can then be applied [Damasio, 1994]. Our emotional experiences are stored in the brain and impact on the way we form our attitudes and how we act in the future. Emotions are linked to the anticipating of events, learning, and orientating to the future. According to Fredrickson (2000), they predispose us to the course of action that currently seems to be most appropriate; for example, negative emotions often lead to avoiding or attacking behaviors. Positive emotions, however, do not have action tendencies as restricted as do negative emotions. Additionally, they do not seem to trigger as much physical action as negative emotions; rather, they seem to give rise to intellectual activities. That way they foster learning and creativity, an overall good mood, and positive attitudes. Products have emotion-related meanings for people which they may or may not recognize consciously. Holman (1986) identifies five emotional roles that a product can have. The user’s involvement with the product is lowest in the first category (background products) but intensifies category by category. Background products (e.g. furniture) are part of the environments in which people interact with others. Even though there is not necessarily any reaction to these products, their absence would be considered awkward. The emotional content of these products comes about as a result of their ability to create or destroy the scene in which the action takes place.

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Products can mediate interaction. The mediators are not only necessary to build up a channel that makes interaction possible, but they are also important in the situation in which the interaction takes place. For example postcards, telephones, and flowers, which can be used in communicating over long distances, are mediators. On the other hand, different games, which can be played by many people and have participants either as players or spectators, are also mediators. Mediators of emotional content can also be things on display (museums), things that can easily be talked about (pets and collections), and things that by reconstructing certain events facilitate the sharing of them with others (souvenirs). Products can enhance social interaction. These kinds of products make it easier for the owner to play the role he or she has adopted. For example, by serving food the importance of the relationship can be emphasized. Social interaction can also be enhanced by products which make their user more attractive (e.g. make-up) and products by which other people’s mood can be manipulated (e.g. background music). When products relate to their users’ identity they become very personal. Products can be used as symbols of one’s own identity. In that case the use of the product should be perceivable to other people. Some people need to have the means to own it before others. These products should also be personifiable. Good examples of products which relate to their users’ identity are clothes, cars, and self-made things. Sometimes products can themselves become the objects of emotions (the so-called “aficionado effect”). This often happens with collectors or “gadget freaks”, who consider the technology inside a product more important than the product itself and what it is used for. In product design, when we think of user needs, we often consider only the needs related to the user’s tasks [Jones, 2000]. This might be logical if we think of technical objects used only as a tool for some practical purpose. However, even if a product is only used as a tool, it does not necessarily follow that there are no emotional or social meanings attached to it. Further, not all products have a clearly defined purpose of use. For example, when developing WWW services the designers do not necessarily know exactly what kind of content will be used and how it will be used. Understanding the user’s life and behavior as a whole helps in these situations. But then we cannot forget the user’s needs as related to his or her social and emotional self. For example, Maslow (1943) speaks of needs related to security, love, recognition, and self-achievement. Allardt (1976), for his part, refers to the need to be part of a community in which the members care, help, and have feelings for each other, as well as needs for self-realization and status. People need to feel that they are unique and cannot be replaced and they want to take part in purposeful activity.

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Positive emotions help us achieve things by motivating us and better the quality of life [Csikszentmihalyi, 1990]. A fulfilling life which is rich in experiences results from activities that create the feeling of flow. Flow, or optimal experience, emerges from activities that are playful and require concentration. In a state of flow people feel they are in control, with their skills matching task requirements. Positive emotions facilitate learning and thinking of new choices of action. For example, it is easier for adults to learn to use a computer if the atmosphere in the learning situation is playful and experimental [Webster, 1992], Also, anxiety and negative preconceptions towards computers are notably reduced. Social and emotional needs are strong motivators of action. If designers understand how their product can support or enhance social interaction and allow the communicating of emotions, they are increasing the product’s chances of being successful. Products will elicit emotions and emotional meanings in users and convey the emotions of the designers anyway [Gaver, 1999]. To create products that elicit positive user experiences, the designers should try to control that process.

3.2.3.

Usage in context

Not only human emotions but also the contexts of use and the effect of culture have largely been overlooked in traditional HCI and usability, as criticized by many sociologically-oriented researchers (see for example [Nardi, 1996; Bannon, 1991; Suchman, 1987]). Constructing and negotiating meanings, the forming of self-identity and self-agency, and acquiring symbolic skills all become possible because of our interaction with the cultural world around us [Bruner, 1996]. Mental activity too is firmly situated in culture, since it is shaped and made possible by cultural settings and resources. Without culture phenomena such as learning, remembering, talking, and imagining become impossible. Also, our knowledge of work is partly represented in the objects used, e.g. an ax is shaped in a way that we immediately know what one can do with it. According to Bannon (1991), there are several limitations to the traditional cognitive psychology approach that result from the failure to consider contextual factors. Firstly, in the traditional view human beings are seen as passive elements in a system instead of autonomous agents who are capable of regulating their own behavior according to the demands of the environment as well as the inner world. Secondly, product design requirements are based on single individuals who use the product alone. Communication, cooperation, and coordination should also be considered when aiming for suc-

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cessful interactive products. Thirdly‚ the ecological validity of laboratory tests is questionable. Finally‚ the actual use of a system is a long-term process which demands the long-term observation of product use instead of studying only the first steps of usage. Activity theory can be helpful in outlining “the big picture”. Based on the ideas of a group of Russian psychologists‚ the theory of activity provides a framework for studies of computer use in its social‚ organizational‚ and authorial context. It also considers the goals‚ plans‚ and values of the user and the context of the historical development of the artifacts used [Engeström‚ 1987]. Activity theory’s main ideas are that the individual mind emerges‚ exists‚ and can only be understood within the context of human interaction with the world‚ and that this interaction (called activity) is socially and culturally determined [Kaptelinin‚ 1999]. For the ease of designing laboratory experiments‚ many psychological theories use human action as the unit of analysis [Kuutti‚ 1996]. This approach‚ however‚ is not very useful when stepping outside the laboratory into the real world. To solve the problem of actions always being situated in a context‚ activity theory has taken “activity” as a basic unit of analysis. Activity always also includes a minimal meaningful context [Kuutti‚ 1996]. Participating in an activity means performing conscious actions with defined goals. The process can be visualized by a triangular model comprising a subject‚ a tool‚ and an object (Fig.3.1). On the individual level a subject (individual or subgroup) undertakes an activity to reach an object. Activity is mediated by the usage of tools and the purpose of the activity is‚ hence‚ transforming the object into an outcome with the help of different kinds of tools [Engeström‚ 1987]. Objects can be both material or immaterial (ideas). The basic structure described above is too simplified to be able sufficiently to depict the complex interactions of individuals and their environment in an activity. More relationships must be introduced: subject-community and community-object [Engeström‚ 1987]. The relationship between subject and community is mediated by rules and the relationship between community and object is mediated by the division of labor. Activities are conducted through actions‚ which mean‚ for example‚ general principles and hypotheses. Actions may have their own goals and the same actions may be used in multiple activities. Activity‚ however‚ gives a reason and a motive to actions. Activity can‚ for example‚ be the visions the user has of future user experiences with a product. Actions‚ in turn‚ can be divided into a series of operations‚ the concrete physical or social conditions for carrying out the action [Petersen‚ 2002]. Kuutti (1996) states three possible contributions from activity theory in the design of computer systems: multilevelness‚ interaction in the social con-

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text‚ and in teraction in the context of history and development. Multilevelness is the possibility of seeing a phenomenon as having facets on different levels‚ for example both the social and the individual level. Social context conveys meanings to actors‚ and the focus on history and development tells us about the changing use of artifacts.

Activity theory does not provide solutions that can instantly be used in the solving of design problems‚ however. Instead‚ it can help researchers to ask meaningful questions that can help them to solve the problems they come across during the design process [Kaptelinin‚ 1999]‚ Petersen et al. (2002) used activity theory as a framework for analyzing the long-term use of an integrated television and video recorder. Their analysis revealed how the motives that caused people to buy a product in the first place can be forgotten or changed to something else during long-term use. For example‚ people do not always have the energy to learn the system functions they first thought made buying the product worthwhile. Also‚ while learning how to use the product‚ it may turn out that‚ after all‚ the user does not like the features she once appreciated. This leads to the importance of the product’s capability to provide new purposes of use. The study also indicated the importance of showing the user the available features and how they are used. Otherwise‚ users can quickly lose interest and stop using the product. Making users aware of existing features and functionalities‚ as well as meeting user

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expectations‚ is something which it is important to consider when designing marketing and product manuals. 3.2.4.

Inclusive design

Inclusiveness or “design for all” (or accessibility) is an important viewpoint in the development of telecommunications services. These services are often aimed at large populations of users‚ regardless of differences in their individual‚ sociological‚ or economic capabilities. The development towards “The Information Society” requires that certain people will not be deprived of access to information and services. This means that electronic services are designed independently of the factors that diminish some users’ chances to use them. Designers easily think of a “normal person” when designing a product (e.g. average height‚ normal motor and cognitive skills‚ normal vision and hearing‚ normal ability to move). Assuming this will leave an ever-increasing number of potential users out of reach of the product; for instance‚ in Europe‚ Eurostats estimates that 10-12% of the population has currently one or more disabilities that may hinder product usage This number will increase during the coming years with the increase in the number of elderly people‚ as old age normally brings along changes in perceptual‚ cognitive‚ and motor abilities. In the United States Section 508 of the Rehabilitation Act requires that Federal agencies’ electronic and information technology services are accessible to people with disabilities. On the basis of the accessibility initiative of the World Wide Web Consortium‚ the EU too is currently making moves towards legislation regarding the accessibility of services. Many individual countries already have demands for the equality of their citizens that can be applied to the design of public services. As a big buyer the public sector can make a difference to product design in private companies and slowly change the view of “designing to the average user”. Inclusive design is an approach to product development that aims to serve as broad a user group as possible. Inclusiveness is defined as “part of the quality of mass market products and services‚ which makes them usable for a wider market” [Hyppönen‚ 1999]‚ The means for this are user-centered design‚ modularity in design‚ and inclusive design guidelines. By paying attention to standards a higher level of compatibility and device independence‚ the cornerstones of accessibility‚ can be reached.

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3.2.5.

Handbook of Product and Service Development in Communication and Information Technology

User experience and market life cycle

There certainly are products in which user experience does not seem to be a great success factor. A seemingly obvious group is the systems used mainly by other systems or system administrators. Indeed‚ the user interface of these systems‚ if there is any‚ will probably not have to be easy to learn‚ as the users‚ if there are any human ones‚ are professionals and might be willing to spend time learning the system. But learnability is only one factor in usability and user experience. Efficiency demands for system administration are probably big‚ as are the prevention of errors in some cases. Thus‚ the nature of the user experience to be aimed for is different‚ but the demand still exists. A more complicated group of demands for user experience comes from the fact that each system that has no human end users itself is part of a larger system. Somewhere at the end of the chain‚ there will be a human end user. Figuring out how each component of the system affects the final user experience is challenging‚ especially when the components might be designed well before there really is a clear idea of how the final product for the end user should work. The greatest variation in the importance of user experience comes‚ according to several researchers‚ from the stage of the product life cycle where the product currently is. According to Norman (1998)‚ a completely new technology cannot reach a stage where it meets all the needs of the potential market at the time it is launched. It depends on the early adopters if a market is opened for the product at all. Early adopters focus on how interesting or useful the technology is to their mind. However‚ when reaching for a bigger and more relevant market share‚ the product has to appeal to late adopters also. Late adopters‚ who form the consumer market‚ appreciate user experience: things like efficiency‚ reliability‚ low cost‚ convenience‚ and aesthetics. Moreover‚ marketing becomes more important as the product matures.

3.2.6.

The special case of telecom services

Telecommunications services are a special case in relation to user experience for two reasons. Due to the nature of the services‚ it is difficult to achieve good user experience‚ but due to the business models used for telecom services‚ for most services there is at least one provider in the provider chain for whom it is essential to get users to use the service regularly‚ not only once. The difficulty of achieving good user experience in telecom services results from several factors. One reason stems from the nature of the industry. Telecommunications services are built on a large infrastructure‚ currently defined and built mostly before actual end user products are designed. This is

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quite contrary to the “traditional” product development approach (e.g. [Ulrich‚ 2000])‚ where the actual production is designed after the product. The industry relies heavily on standards‚ which are also agreed upon earlier than would be beneficial for optimal freedom of product design. Also‚ the “product” as the user perceives it is the sum of the interoperation of a chain of products‚ produced by a range of different players: terminal device vendors‚ telecom operators‚ software developers‚ and content providers. It is not always clear where responsibility for the total lies and if the total is‚ indeed‚ manageable at all. Service convergence brings an additional challenge to product design. Services that were initially based on very different technologies offering different possibilities are‚ in the era of converging services‚ expected to operate together seamlessly. Marketing displayed the WAP as “The Internet in Your Pocket” which it clearly is not; you are promised that you will get your e-mail on your cell phone but what you actually get is a series of 160-character messages. The people who make up the mass markets do not care about the technical difficulties resulting from convergence; their expectations concerning the quality and convenience of use remain the same whatever the application is. With mobile technology‚ the continually changing context of use and usage situations also has to be taken into account. Nobody uses their mobile phone in just one place. This‚ combined with the small size of the devices used as user interfaces for complicated telecom services‚ provides a great deal of difficulty for design. The user’s experience of changes in network performance‚ in Quality of Service (QoS; ITU T-Rec. E.800‚ 1994)‚ is critical to the success of a networked multimedia service (Table 3.1). Therefore‚ it is important for the service provider to understand the impact of changes in network performance on the users’ opinion of that service; it is clearly to the advantage of the service provider that users perceive their product to be acceptable. In order to determine acceptability it is essential to be able to identify how users respond to the overall network behavior and different types of errors present in a network. The quality of service‚ as the user sees it‚ does not only consist of the technological aspects. The user also evaluates the quality of service in the conclusion of the sale and support services such as installation and maintenance‚ billing and customer care. Any deviations from what is promised can result in the deterioration of the company’s image. It is important for service providers to understand that the customer wants to have an integrated‚ universal telecommunication environment. We have to stop seeing individual technologies as bases for individual products‚ and instead envision the product from the viewpoint of the end user first‚ then using

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the technologies to realize the product in integration. The complexity should be handled by the product designers‚ not by the user.

3.2.7.

A solution: user-centered design

The problem of how to create a product that is acceptable‚ intriguing‚ and perhaps even desirable to the user is many-faceted. It is not enough that the designers make up product concepts‚ specifications‚ and interaction designs based on how they themselves would like the product to be‚ or based on some stereotypes they might have of the user group. To be able to match the user’s needs with the overall structure and functionality of the completed system‚ user-centered design strives to involve the actual users in every phase of the product’s design. After finding out who the users are‚ the users‚ their goals‚ and their environments are studied by means of various methods. The first user studies take place at a very early stage of design (concept development) and later on users participate by testing and evaluating prototypes throughout the process. The potential users and their lives are a source of innovation for the designers. By familiarizing themselves with the users’ everyday lives the designers are able to form a context of design which leans on the users’ actual world. In this way the possibility of creating new product concepts and design solutions that are relevant to the users is increased.

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3.3.

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Bringing the user’ s voice into the design process

The classic design model used in software engineering is the waterfall model of design. It is quite linear‚ consisting of separate successive stages in the design process: requirements gathering‚ system and software design‚ implementation and unit testing and‚ finally‚ integration and system testing [Somerville‚ 1992]. However‚ it is recognized that this model is especially over simplistic in high-tech product development and in practice development stages overlap and feed information to each other‚ so that software design processes always become iterative (See also Chapter V). The main difference between waterfall models of design and usercentered models are that user-centered design strongly emphasizes user involvement in the design process as early on‚ and as often‚ as is possible. What is also typical of user-centered design is the use of multidisciplinary design teams which consist of both technical people and human and social scientists as was emphasized in Chapter II. Iterative design process (Fig. 3.2.) is openly acknowledged as crucial for user-centered design. Iterativeness brings flexibility‚ which means that the opinions of users and different experts can be heard when needed. Iterativeness involves the extensive use of prototypes as a way to get closer to the final product. Rapid prototyping (the using of throwaway prototypes) is a typical method used to collect information on requirements and on the adequacy of design choices. The User Centered Design (UCD) process consists of different stages‚ which‚ according to the ISO 13407 [ISO 13407‚ 1999] standard‚ are: 1) defining and understanding the context of use; 2) defining the requirements of the user and the organization; 3) providing design solutions‚ and 4) comparing the design solutions with the requirements. Sometimes process models‚ as defined in ISO 13407‚ do not work at all. For example‚ in the case of Nokia’s mobile phone development‚ many products or models of products are developed at the same time‚ the product life cycles are short‚ and there are many individual development teams at multiple sites all over the world. In these situations concurrent process models involving shared usability research have been found to work better [Ketola‚ 2000]. The rest of Section 3.3 describes methods and activities in different phases of the usability design process. Whatever the product‚ service‚ or software design process is‚ these activities should be present. They do not‚ however‚ form a sufficient model for product design on their own‚ but only complement it. Section 3.3.1 describes user-centered methods of getting to understand user needs and requirements. Section 3.3.2 discusses the product concept and the transformation of user needs to product definitions with the help

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of user involvement. Section 3.3.3 addresses user interface design issues. Section 3.3.4 presents usability evaluation methods.

3.3.1.

Inspired by the user

Service design As designers of new services we need to spend time with the actual users in their daily environment in order to understand life and its opportunities and challenges from their perspective. It is essential to know the user group in question and how they differ from each other and other user groups. Capturing the broader context of use (i.e. the cultural and organizational context; [Beyer‚ 1998]) is also important. The design of a successful service requires information about both the users’ and the company’s goals [Hackos‚ 1998]. According to Kotler (1997)‚ a market consists of all the potential customers who share a particular need or want and are willing and able to satisfy this need or want by exchange. The segments in the consumer market can be described in terms of different variables‚ for example [Kotler‚ 1997]:

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Geographic Demographic (e.g. age‚ family size‚ family life cycle‚ income‚ occupation or education) Psychographic (lifestyle‚ personality) Behavioral (e.g. benefits expected‚ usage rate‚ attitude towards product) For business markets‚ variables may include Demographic (industry‚ company size‚ location) Operating variables: (applied technologies‚ usage status‚ customer capabilities) Purchasing approaches Situational factors Personal characteristics In high-tech‚ finding out what people need and want is usually not easy. People are often preoccupied with their daily routines that they do not even realize that they could perform some activities in an easier or more effective or satisfying way than they do now. They do not usually realize the possibilities of new technology until they have actually seen it embedded in an existing product. Thus‚ the potential needs often remain latent‚ undiscovered‚ and unverbalized‚ waiting for the designer to find them. People’s experiences of products and usage situations are interesting for designers‚ but how they can be investigated is another question. Many of those experiences are mediated as stories‚ which people use as vehicles for condensing‚ remembering‚ and sharing experiences with others [Schank‚ 1990]. Interviews can provide a rich picture of the user: how she talks‚ what kind of stories she tells‚ what she regards as worth mentioning etc. Besides what the users say‚ what they do is also important and interesting. What kind of things do they have to do? What kind of activities do they participate in because they enjoy them? To find out what exactly happens during these activities an applicable research method is observation‚ which means that the designers go to the actual place of activity and see for themselves what is going on. In certain situations‚ observation is a better method than interviews‚ because people’s stories are typically abstractions that do not describe every detail of their activities. Details may‚ however‚ be very interesting and important for the designer.

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When designing for the workplace designers need to understand how real users carry out their daily tasks and how these processes could be supported or transformed by new services. In these situations methods such as interviews and observation sometimes provide data being too limited or too narrowly focused for the design. More informative methods can be used during the task analysis‚ depending on the target group and the context‚ as presented in Table 3.3. In order to be truly able to design with users in mind‚ designers have to be able to step into the shoes of whoever the users are. Designers have to find a way to empathize with the user and understand even those things which people are not able easily to talk about or show in their behavior (such as dreams‚ hopes‚ and fears). These emotional experiences are not usually accessible through traditional methods of “need finding” such as interviews and focus groups. Sanders and Dandavate (1999)‚ for example‚ present “emotional toolkits”‚ which contain different kinds of artifacts created by the design team in order to elicit emotional reactions. The emotional toolkit might contain things like press cuttings so that the user can form a picture collage‚ or diaries to fill with stories. Unconventional methods for need finding have been used‚ e.g. in an EUfunded project‚ Presence. Presence aimed to find novel interaction techniques in order to increase elderly people’s opportunities for involvement in their

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communities in three European countries [Gaver‚ 1997]. The designers were searching for inspiration that would able them to find opportunities for discovering “new pleasures‚ new forms of sociability‚ and new cultural forms” in these communities. To achieve this‚ the designers handed tools they called cultural probes to the participants. The probes consisted of maps‚ postcards‚ cameras‚ photo albums‚ and media use diaries‚ through which the participants were asked to communicate different things to the designers. The designers found the use of probes helpful in understanding the cultural differences in research areas‚ as well as understanding the rich texture of each individual culture. According to the researchers‚ the strength of the probes was that being designed particularly for this project they opened a personal communication channel between the elderly and the designers.

3.3.2.

From user needs to product definitions

The steps in product development that transform all user requirements to actual product definitions can be described as a small magic. The challenge is to derive the most relevant needs‚ prioritize them‚ to create a product concept based on that‚ and to communicate these ideas as product specifications to those performing the technical design of the product. When product design teams consist of people with varying backgrounds and goals (such as developer‚ marketing‚ and usability designers)‚ sharing all the knowledge the different team members have may prove to be difficult. The team has to be able to reach an agreement on which requirements are the most relevant and necessary and which can be left out when reaching for a successful product. For this to happen‚ user needs‚ along with the input from marketing and engineering‚ have to be captured and structured in a clear and systematic way. This information has to be available to the designers throughout the development cycle. Depending on the traditions of the technical developers‚ there are several iterative steps in reaching the final product specifications. To ensure user satisfaction‚ usability and relevance of the product‚ each iteration should include user involvement for feedback. Table 3.4 shows the user involvement steps that should be included in the design activities from the product concept to product definitions‚ along with typical methods used at each stage. In building bridges from user needs to product specifications‚ the three different viewpoints should be kept separate: User needs are expressed by the user or otherwise collected from them. The needs exist independently of any technical solution. They are the firm ground on which alternative solutions can be created. The existence of a

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user need is not a question of negotiation – one can only decide on how important it is to respond to each need with the product. Product requirements are derived from user needs. Sometimes‚ a user need can be directly transferred to a requirement‚ while sometimes the requirement is expressed in a more precise‚ measurable form. The major difference is that while we should not deny any of the user needs‚ we must select and prioritize among product requirements. One could say that product requirements reflect in a measurable form those user needs that the development team has chosen to meet with the product. There are also other sources for product requirements than user needs: data security‚ cost‚ manufacturing etc. Product properties are the selected way of implementing the product requirements. Any requirement can probably be fulfilled with different alternative technical solutions‚ and any property of the product can be a solution to one or more user needs or user requirements. At the product concept level some central properties should definitely be part of the concept; in later phases the properties would probably be called specifications. The different viewpoints of needs‚ requirements‚ and specifications can be illustrated with an example dealing with different mobile payment services (Table 3.5). The early stage for product specification is the product concept. The product concept is an abstract idea of what the product will be. For instance‚ a product based on software can be realized in a variety of ways‚ some better than others‚ but all still fulfilling the demands of the concept. User satisfaction also depends on the detailed implementation of the product. In its final stage‚ the product concept should include enough details for the marketing team to provide final product cost estimate. These are the bases of user decision whether buying the product for the offered price. The creation of a product concept is iterative. It can start from a onesentence definition such as “a Communication Tool for Teenage Girls” and end up in a rich description that resembles‚ in some ways‚ the product definition. Adding user and usage context information to the actual product description is an advantage for the later design phases‚ as the information can be used. Concepts are generated on the basis of user data in interdisciplinary sessions which aim for creative ideation with different methods (e.g. brainstorming‚ see also Chapter II). To communicate user research findings to other people in the design team‚ user profiles are often used [Hackos‚ 1998]. User profiles are fictional characterizations of potential users whose features are taken from the actual users studied. It is advantageous to represent the fic-

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tional users to the design team as visually as possible since illustrations help in the adoption of emotional stance towards the characters.

Concepts have to be evaluated by the potential users. In this phase the designers do not yet have to know how the design is going to be implemented. They are just communicating and validating their ideas. On the other hand‚ concept testing can be used to compare implementations of the broader concept with different technologies that have different detail outcomes for the user. For example‚ designing a mobile payment system could be realized with different authentication technologies and different sources for the payment (credit card‚ phone bill‚ separate bank account)‚ among which users might have very different preferences.

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Concept testing requires finding ways to communicate concepts to users so that they‚ in turn‚ can understand the concepts and their purposes and relate to the usage situations of the new concepts. Concepts can be presented to the users through stories in which imaginary users (user profiles) are pictured in a variety of usage situations (use scenarios). To help the evaluators to empa-

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thize and identify with the imaginary users‚ the stories are again often presented both visually and in writing (storyboards). In the VIRIKE project [Mantere‚ 2002]‚ scenarios were used when presenting concepts for interactive web services for members of the target group‚ elderly people (Fig. 3.3). The stories of fictional elderly people using different services were simply visualized with the help of a PowerPoint show. The presentation was a success as the participants easily understood the technological services and the usage situations. Many participants also reported how they could feel exactly what the people in the scenarios were going through.

Fulton-Suri and Marsh (2000) find scenarios useful in stimulating usercentered ideation‚ as an illustration of different kinds of issues related to concepts‚ to get the concepts evaluated and to show product’s role in a larger context. However‚ they also warn of several pitfalls. Scenarios should not be too easy or simple but should picture the complexity of the real world. The user characters should be believable and realistic rather than stereotypes. Only one scenario is not enough; the power of scenarios lies in their flexibility in producing alternatives and enabling comparisons. In creating scenarios it is also easy to lose focus and dramatize things too much in order to keep the stories interesting. Since fictional stories are easy to change the designers may be tempted to change secondary things in order to make their ideas work. However‚ scenarios are used to test‚ challenge‚ and improve product ideas‚ not to force acceptance of weak design ideas.

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One systematic approach for keeping the requirements that come from different directions coherent is a model called FURPS — functionality‚ usability‚ reliability‚ performance‚ and supportability - a set of software quality factors developed by Hewlett Packard [Grady‚ 1992]. Usability is assessed by considering the human factors‚ overall aesthetics‚ consistency‚ and documentation. Requirements coming from the users of the system can be mapped to any of the FURPS classes – most typically to functional and usability requirements.

The requirements have to be prioritized to indicate which are the most important requirements for the finished system. Design tradeoffs cannot be made if all requirements are thought of as having equal importance. In software design in particular‚ a method called “Use Cases” [Jacobson‚ 1994] has been created to describe the actions the system takes to deliver to the user what he needs. All the use cases of the system describe all the ways of using the system. According to the Use Case - approach‚ all development projects should start by finding out the use cases‚ then design and test according to those use cases. The Use Case - model lists all the possible actors

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and all the possible use cases and their variants (odd cases‚ error flows) a system can have. In using the Use Case - approach one should be quite clear as to what the use case is describing; as in Table 3.5‚ user needs are different from user/ product requirements‚ which again are different from specifications. Use cases are mostly used in describing product specifications and sometimes used in describing requirements (e.g. describing the selected process that the product should allow for from the viewpoint of the user)‚ but rarely in describing genuine user needs. Use Cases represent model-based thinking [Beyer‚ 1998] and differs from use scenarios in that they are intended to help with the design of the system architecture and are already more simplified than use scenarios. This is necessary in order to be able to define concrete specifications and solutions connected with the system structure. Scenarios represent story-based thinking and are meant to clarify the concepts and the purposes of use even to people without any technical know-how. The stories show particular instances of the system being used‚ while the models show how the system can support those stories [Beyer‚ 1998]. To further ensure that the design is starting to develop according to user needs‚ prototyping is highly recommended. At the product definition stage paper prototypes or sketches can be used to reach a more concrete understanding of the concepts and to explore different kinds of possibilities. At this point‚ there can be several diverging and competing designs which can be shown to the users and design team for evaluative comments. Little by little‚ the designs become more elaborate. When building prototypes‚ several different approaches can be taken [Preece‚ 1994]. Full prototypes already incorporate all the necessary features‚ but at a lower level of performance than the final system. Horizontal prototypes have a user interface‚ but no functionality behind it. Vertical prototypes contain all the highand low-level functionality of a restricted part of a system. High fidelity prototypes mean that the final interface is demonstrated as closely as possible through a medium such as video. The selection of prototyping methods depends‚ of course‚ on the phase of the design cycle. At the beginning it is desirable to use cheap prototyping methods and produce several different designs. The closer one gets to the end of the project‚ the more important it is to commit to only one design and try to represent it in as close a manner to the final product as possible. If one chooses evolutionary prototyping the prototypes actually evolve to a ready product. The downside is that often designers settle for one design solution too early.

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Handbook of Product and Service Development in Communication and Information Technology

User interface design issues

User-centered design is often thought of only as dealing with user interface design and usability as reached by the visual designer through clear visualization of system functionality. As‚ hopefully‚ it has become clear‚ the foundations for good usability and meeting user needs are laid with task analysis and user involvement is beneficial even during the early phases of design. While the earlier phases require information from the intended users of the particular product‚ user interface designers can utilize more general knowledge of human behavior and design guidelines. When reaching the point in product design at which the user interface and its interaction methods are to be designed‚ information as to how people think and how they learn is needed. Both general models (e.g. the action cycle proposed by Norman‚ 1988) and guidelines (e.g usability heuristics‚ originally reported in Nielsen and Molich‚ 1990‚ and revised by Nielsen‚ 1993)‚ as well as device-specific information about typical user behavior (e.g. research on WWW user behavior by Spool‚ 1998)‚ can be found. The human user is sometimes presented as being machine-like‚ scanning the environment for signals and responding to them appropriately. This model of the user is not always useful and can lead to the designer wondering why the user did not notice some button or text‚ or why the user did not understand the obvious‚ or why the user just was not able to figure out how to operate a product. A more elaborated user models reminds us that in every interaction the user carries with her previous experiences‚ expectations‚ and knowledge of other interactions. All of these affect what the user expects to perceive‚ what she actually perceives‚ and how she interprets meanings. Thus‚ being aware of the particular user group’s well-known conventions‚ the symbols used‚ and competing products’ user interface conventions helps to build a product that meets the expectations of the user. Learning to use a technical device involves either rote learning of action sequences or slowly increasing the understanding of the system – how the tasks map on the functions. The larger the system is‚ the easier the latter should be. Rote learning of elaborated‚ hard-to-rationalize - sequences should not be expected from a regular user. Norman (1988) states in his model of the action cycle that the user has basically two main problems to solve when using a device. First‚ he must decide which device functions match the task he wants to accomplish. Second‚ he must interpret the response of the system in order to decide whether the outcome was desired. Both of these problems require the usage of some kind of mapping of hierarchical tasks to device functions and knowledge about expected outcomes. To help the user to form a model of how the system functions Norman (1988) proposes visibility and the provision of a good concep-

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tual model. This means that in the user interface the system is presented in a consistent way‚ enabling the user easily to form a coherent user’s model of the system. Norman’s tools for achieving this are affordances‚ restrictions‚ and natural mappings. Affordances are the (visual) properties of an object that tell‚ relying on cultural conventions‚ how the object is used and for what. Restrictions are‚ for example‚ logical or physical means of preventing erroneous actions‚ thus allowing the user safely to explore the system. Natural mappings can be‚ for example‚ spatial‚ linguistic‚ or process-like. An object or action in the user interface should refer to an object or action in the real world‚ or user task‚ in an obvious way. It should be presented in the user interface in such terms and with such a visual appearance and spatial location that this reference can easily be recognized by the user. A similar guideline from Nielsen (1993) is the need to match between system and the real world. “Visibility”‚ as described by Norman (1988)‚ refers to designing the user interface in a way that reveals the system status and makes apparent available functionality. Essentially the same is stated in Nielsen’s heuristic visibility of system status. Other design guidelines support this guideline by providing the means for achieving visibility from two different perspectives – minimalism and clarity of information. Norman’s very general design guidelines‚ as well as the usability heuristics‚ serve as a broad checklist. Of actual standards‚ the ISO 9241 - Ergonomic Requirements for Office Work with Visual Display Terminals standard contains a series of general guideline sets for user interface design. The designer should also check the availability of more precise guidelines and user interface standards‚ which can exist for the service platform or device type (www‚ mobile phone)‚ manufacturer (e.g. Microsoft or Apple Macintosh user interface guidelines)‚ user interface type (speech‚ text‚ GUI)‚ or even user groups (e.g. inclusive design guidelines for visually impaired users). Standards and other user interface guidelines are useful in many ways. Standards can ensure a common terminology‚ maintainability and extendibility‚ reduction in training costs‚ and the promotion of health and safety. Device and operating system independence is also made possible through following standards.

3.3.4.

Evaluating usability

When forming the system requirements‚ appropriate usability specifications are set as well. This means that the designers decide which criteria concerning usability should be met to make the product’s level of usability acceptable at the time of launch. At this point‚ it is also decided how to measure

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these attributes set in the specification. The measures can be‚ for example‚ the number of errors in a task‚ the time needed to complete a task‚ learning rate etc [Preece‚ 1994]‚ ISO/IEC 9126-4 suggests measurements for effectiveness‚ productivity‚ satisfaction‚ and safety that can be used for this purpose. Usability can and should be evaluated in different design phases for different purposes. At the beginning of the design process‚ existing products can be evaluated so as to gain an understanding of problems that should be remedied in the new design‚ or for getting baseline information for setting usability goals. Benchmark tests for competing products serve similar purposes. During design‚ formative evaluation helps designers to make design decisions. Summative evaluation before the release of the product serves as a check for reaching usability goals. Usability testing is a usability evaluation methodology‚ where observation of system usage‚ thinking-aloud methods‚ and protocol analysis are combined. The user is performing quasi-real tasks with the system‚ set by the experimenter who observes the usage situation. Usability testing has the purpose of determining the quality of user interface design with regard to ease and effectiveness of usage and user satisfaction. The reliability of usability tests (as compared to actual usage) relies mainly on three factors: the selection of representative users‚ the selection of meaningful tasks‚ and the interaction during the test situation. Testing the product with real users gives the designers information as to how this particular user group relates to the technology being tested‚ how it fits into their tasks‚ and what the exact problems are. However‚ user testing contains methodological pitfalls‚ as described in detail in Nielsen (1993). Because of the great individual variety among users the reliability of the tests can be a problem. The validity of the tests should also be considered carefully. It is always questionable whether tests with simplified tasks in the laboratory or other kinds of artificial situations measure anything that is relevant in realworld use. Therefore‚ designing the test to be as close as possible to real usage‚ with tasks which are actually meaningful for the test user at the moment of testing‚ is crucial for reliable results. Expert evaluations‚ another group of usability evaluation methods‚ are made by persons working in the field of usability and/or design. Usually these methods consist of careful and systematic inspection of the system by comparing overall functions and structure to preset usability guidelines and heuristics‚ or by simulating user behavior according to a specific procedure. For example‚ Nielsen’s heuristic evaluation consists of ten rules that should be taken into account in the design. The downside of the inspection methods is that only about 35% of usability problems are usually found this way. The result is better when many inspectors are used‚ as well as when inspectors are trained in the field of usability. Additionally‚ the fact that usability inspectors

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do not necessarily have any knowledge of the actual users’ work tasks hinders the efficient finding of flaws in relation to specific work tasks. The final usability test before the product launch should always be performed with actual users. This test tells the designers how well they have reached the goals set in the usability specification and what still has to be improved in later versions. After the final tests it is often not possible to make any great changes any more‚ for example in the structure of the system‚ so the final tests should by no means be the only usability tests that are carried out during the product design life cycle. The relationship between usability testing and other product testing deserves some attention. As great deal of the other testing is performed with the ready product to check if the product meets specifications‚ why should not this be the case for usability testing too? Usability evaluations have an important overall quality indicating meaning: on their part‚ they reassure also some of the technical specifications‚ for instance in the user experience of a user interface. The design process is not over once the first user interaction with the service has been completed. Continuous observation of use and collection of feedback from users is required after the launch. In an ideal situation modifications to existing services should be made on the basis of the received feedback‚ but in any case feedback is valuable and should be used when designing service updates or entirely new services.

3.4.

Impossible? No‚ but you have to manage it!

Modern user-centered design of high-tech products and services can be seen as a remedy to the increasing problems designers are faced in attempting to meet user needs with a complicated set of technical features. Still‚ the adoption of related new work practices in organizations is not easy. For example‚ in Nokia Telecommunications‚ it took eight years for the UCD team to reach the respect where they were invited to all major product design phases [Korhonen‚ 2000]. Success in user-centered design does not rely only on individual skill. It is essentially an organizational discipline. There are several different usability maturity or capability assessment models [Jokela‚ 2001]‚ which evaluate an organization’s attitudes‚ resources‚ processes‚ and routines that deal with usercentered design. The bottom line is that the models evaluate the organization’s capacity to constantly achieve highly usable products. Usability capability models evaluate the presence and execution of user-centered design activities‚ project management‚ and organization-wide training and guidance.

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Some problems seem to occur regularly during attempts to take on usercentered design. Many of them have to do with project or process management‚ the timing of activities‚ and conceptual mix-ups.

3.4.1.

Timing of activities‚ management of requirements: there is only one design process

A typical beginner’s error seems to be great enthusiasm for usability testing‚ which is applied to the finished product two weeks before launch‚ as a kind of stamp of approval. The result is usually a list of usability problems‚ often including more than 10 serious problems that should be fixed before release. Given that there is no time for fixes (they should be postponed to the next release‚ they say)‚ the end result is that the money spent on the tests is wasted and the members of the design team are frustrated. This is not a good way to get things going and might even lead to user-centered design gaining a bad reputation. To conduct usability tests very late might seem very natural‚ as other product testing is also done at the end. But usability testing should not be seen as part of testing the product but as testing the specifications. This means that UI design can never be a separate activity from the whole product design. There is only one design process‚ and there is only one set of requirements‚ which should be managed as a whole. Starting user involvement too late will lead to frustration and the wasting of money‚ but‚ unfortunately‚ it is easier to sell usability test results to management than it is proactive user involvement. Some experiences indicate‚ though‚ that from end-project testing it is possible to “creep” forward in successive projects‚ as every successful instance of usability testing provides a reason for starting the process earlier next time. There is a grave danger that involvement which is badly communicated and managed‚ and executed practically too late‚ will give usability experts a “usability police” role‚ without any significant constructive role If the start has been the typical late usability test‚ the best thing to do is really to keep the usability test results as a basis for the next version. New requirements stemming from these results can then be managed like other requirements. Requirements management is crucially important with user involvement. Keeping track of all user feedback‚ discarded design solutions‚ and changing requirements may be hard‚ but it will save time and effort. Also‚ setting clear deadlines for any proposals for changes and making a prioritization of all requirements together ultimately benefits usability too. All usability evaluations should therefore be timed so that the results are available before such deadlines.

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As there will always be a hurry‚ the temptation to skip user testing will be strong‚ as it will produce a delay. It is wisdom on the part of management to understand that even though a product may be released faster without user testing‚ a successful and usable product probably comes out fastest with doing the tests. When the organization achieves routine in user involvement‚ it also learns to shorten the delay by preparing for the test in advance‚ parallel to other design activities.

3.4.2.

Conceptual confusion with user data: What‚ and what for?

When usability is introduced‚ the other half of user-centered design – relevance‚ utility – is sometimes forgotten. But no fantastic UI design can make the product a success if the concept just does not appeal. In the enthusiasm generated by what it seems to make possible‚ an idea may seem very appealing‚ but actual users do not buy the idea. Some small detail of realism may be forgotten – characteristics of the usage context‚ already-existing better products‚ or‚ simply‚ the slowness with which people change their habits. User involvement in the concept design and requirements elicitation phase is rarer than in the UI testing phase. (Here‚ asking user representatives for wish lists does not count as real user involvement.) One reason for this might be that it seems there already is user involvement – market research. Indeed‚ the line between market research and user research is hard to draw. Still‚ even intensive focus group discussions might not give interaction designers the necessary information about task steps and decisions or possible usage situations and needs related to them. Also‚ communicating rich user data should be done in a way that saves at least some of the detail. Diminishing scenario-like usage descriptions to feature lists is one problem. Sometimes‚ too‚ task analysis (that should attempt to describe the task process in detail) is mixed up with asking for a feature list. Yet another possible source of confusion is in the relationship of Data vs. Creativity. User data is a rich source and‚ if it exists‚ it should be used. But this does not mean that the designer is not allowed to be creative (Chapter II). Users can and should be used as a source of inspiration – really great innovations only seldom come from user requirements‚ as they are so novel that no user would have been able to demand them. But great innovations too can be user tested and improved upon both in the product concept phase as well as in the UI prototype phase. Realizing this is possibly one of the basic clues to successful product design.

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Allardt E.‚ Hyvinvoinnin ulottuvuuksia, Söderström‚ Porvoo‚ 1976.

[Bannon‚ 1991]

Bannon L.‚ “From human factors to human actors: the role of psychology and human-computer interaction studies in system design”‚ in Design at Work: Cooperative Design of Computer Systems, Greenbaum J. and Kyng M. eds.‚ Lawrence Erlbaum Associates‚ New Jersey‚ 1991.

[Beyer‚ 1998]

Beyer H. and Holtzblat K.‚ Contextual Design: Defining Customer-Centered Systems, Morgan Kaufmann Publishers Inc‚ 1998.

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Bruner J.‚ Culture of education, Cambridge‚ MA‚ 1996.

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Csikszentmihalyi M.‚ Flow:The psychology of optimal experience, Harper & Row Publisher Inc‚ NY‚ 1990.

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Fredrickson B.L.‚ “Cultivating positive emotions to optimize health and well-being”‚ Prevention & Treatment‚ vol. 3‚ article 0001a‚ American Psychological Association‚ 2000 Available from http://journals.apa.org/prevention/ volume3/ pre0030001a.html [16 Nov 200l]

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Goleman D.‚ Emotional intelligence. Bantam Books‚ NY‚ 1995.

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Grady R.‚ Practical Software Metrics for Project Management and Process Improvement, Prentice-Hall‚ 1992.

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Holman R.H.‚ “Advertising and emotionality”‚ in Peterson R.A.‚ Hoyer W.D. and Wilson W.R.‚ eds‚ The role of affect in consumer behavior: emerging theories and applications, Lexington Books‚ MA‚ 1986.

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Hyppönen H.‚ Kemppainen E‚ Gill J.‚ Slater J.‚ Poulson D. and Ekberg J.‚ Handbook on Inclusive Design of Telematics Applications, 1999 (http://www.stakes.fi/include/handbook.htm)

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ISO 13407. Human-centred design processes for interactive system, International Organization for Standardization‚ 1999.

[ISO 9241-1‚1997]

ISO 9241-1‚ Ergonomic requirements for office work with visual display terminals, International Organization for Standardization‚ 1997.

[ISO 9241-11‚ 1998]

ISO 9241-11‚ Guidance on Usability, International Organization for Standardization‚ 1998.

[ISO/IEC DTR 9126-4‚ 2001] ISO/IEC DTR 9126-4‚ Software Engineering - Product quality Part 4: Quality in use metrics, International Organization for Standardization‚ 2001. [ITU-T Rec. E.800‚ 1994]

ITU-T Rec. E.800‚ Terms and definitions related to quality of service and network performance including dependability, nternational Telecommunication Union‚ CH-Geneva‚ August‚ 1994.

[Jacobson‚ 1994]

Jacobson I.‚ Object-Oriented Software Engineering - A Use Case Driven Approach, Addison-Wesley‚ 1994.

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[Jeffris, 1997]

Jeffris R., “The Role of Task Analysis in the Design of Software”, in Handbook of Human-Computer Interaction, Helander M., eds, 2nd ed., 1997.

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Jokela T., Assessment of user-centred design process as a basis for improvement action - An experimental study in industrial settings, Department of Information Processing Science, University of Oulu, 2001.

[Jones, 2000]

Jones M.L.R., Hourd J. and Gower A., “Usability is not enough: bringing lifestyle research into industrial HCI”, in Proceedings of HCI 2000 Conference, vol. 2, University of Sunderland, 5-8 September 2000.

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Kaplelinin V., Nardi B.A. and Macaulay C., “The activity checklisl: a tool for representing the “space” of context”, ACM interactions, July, 1999.

[Ketola, 2000]

Ketola P., “Concurrenl Usability Engineering”, In Proceedings of HCI 2000 Conference, vol. 2, University of Sunderland, 5-8 September 2000.

[Kotler, 1997]

Koller P., Marketing management, Prentice-Hall, Inc, New Jersey, 1997.

[Korhonen, 2000]

Korhonen P., “Usability research at Nokia: evolulion, motivation and trust”, in Proceedings of CHI 2000, The Hague, The Netherlands, 1-6 April 2000.

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Kuutti K., “Activity theory as a potential framework for humancomputer interaction research”, in Context and Consciousness: Activity Theory and Human-Computer Interaction, Nardi B.A., ed., MIT Press, Cambridge, MA, 1996.

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Mantere J., Belitz S., Petäkoski-Hult T. and Strömberg H., “Usercentered concept design of electronic services for the elderly”, Accepted to be published in the proceedings of 7th ERCIM Workshop “User Interfaces For All”, Paris, 23 - 25 October, 2002.

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Maslow A.A., “A theory of human motivation” Psychological Review, vol. 50, 1943.

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Nardi, B.A. “Studying Context: A comparison of activity theory, situated action models and distributed cognition”, in Context and Consciousness: Activity Theory and Human-computer Interaction, Nardi B.A., ed., MIT Press, Cambridge, MA, 1996.

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Nielsen J., Usability Engineering, Academic Press, Inc, Harcourt Brace & Company, Publishers, Boston, MA, USA, 1993.

[Nielsen, 1990]

Nielsen J. and Molich R., “Heuristic evaluation of user interfaces”, Proceedings ACM CHI’90 Conference, Seattle, WA, 1-5 April 1990.

[Norman, 1998]

Norman D. A., The Invisible Computer, MIT Press, Cambridge, MA, 1998.

[Norman, 1988]

Norman D.A., The design of everyday things, MIT Press , London, 1988.

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Overbeeke C.J., Djajadiningrat J.P, Wensveen S.A.G. and Hummels C.C.M., “Experiential and respectful: Evocative research in design”, in Proceedings of Useful and Critical, Tuusula, Finland, 9-11 September 1999.

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Petersen M., Madsen K. and Kjaer A. “The usability of everyday technologies - emerging and fading opportunities”, ACM Transactions on Computer-Human Interaction,vol. 9, 2002.

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Reeves B. and Nass C., Media equation, CSLI Publications, Stanford, CA, 1996.

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Rosson M.B. and Carroll J.M., Usability Engineering: ScenarioBased Development of Human-Computer Interaction, Morgan Kaufmann Publishers, San Francisco, 2001.

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Sanders E. B.-N. and Dandavate U., in Proceedings of the First International Conference on Design and Emotion, Overbeeke C.J. and Hekkert P., eds., TU Delft, 1999.

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Schank R., Tell me a story: Narrative and Intelligence, Northwestern University Press, 1990.

[Somerville, 1992]

Somerville I., Software Engineering, 4th ed., Addison Wesley, Wokingham, England, 1992.

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Spool J.M., “Eight Is More Than Enough”, Eye for Design, May/June, 1998.

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[Ulrich, 2000]

Ulrich K.T. and Eppinger S.D., Product Design and development, 2nd ed., McGraw-Hill, 2000.

[Webster, 1992]

Webster J. and Martocchio J.J., Microcomputer playfulness: development of a measure with workplace implications, MIS Quarterly, June, 1992.

[Vuori, 1999]

Vuori M., “Havaintoja suomalaisen tuotekehityksen ja käyttöliittymäsuunnittelun tilasta ja kehittämistarpeista”, Työraportti 14, KATTI-hanke, VTT Automaatio, 1999.

Chapter 4 PRODUCT DEVELOPMENT GENERATIONS: Some Lessons from Personal Digital Assistants and Palmtop Computers Antti Ainamo, Jaakko Pöyry Consulting, Helsinki School of Economics, and the University of Art and Design Helsinki, Timo O. Korhonen, Helsinki University of Technology

4.1.

Introduction

In contrast to the and generation cell phones, the generation cell phones in the “Universal Mobile Telephones Standard” (UMTS) offer users not only voice and basic, low-rate data services, but also extensive seamless broadband and location independent (and also location based) high-rate multimedia capabilities. This development offers for customers a constant flow of new products and services, and for manufacturers a barrage of questions of how to integrate the technology into rapidly updateable, fashionable product and service concepts. What kind of vision will most likely be the basis of a successful business case? To address these questions, this chapter reviews how earlier advances in technology and user needs have been successfully channeled into everyday use and the mass market. The example we use is the development of mid1990s Personal Digital Assistants (PDAs) that were hyped in a similar fashion as the generation GSM phones. We analyze the emergence of the PDA market to show how and why the most successful PDAs were, for years, very much like the products that the PDAs were supposed to make obsolete. The transition into a distinct PDA market did not happen until years later. Once the market converged, it immediately showed signs of re-divergence. Through brokering solutions from earlier times to pressing managerial questions today [Rosenberg 1982; Anderson, 1990; Shapiro, 1999; Brown; 2000], this chapter strives to develop a “theoretical lens” about the general paths of high-tech market creation and evolution. 79

T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 79-97. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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By analyzing the market evolution in early PDAs, we make four predictions about market evolution in the generation1 cell phones: (1) Successful generation cell phones will be much like generation cell phones in the short term. (2) Originally competing technologies will gradually begin to complement each other. (3) The generation phones will radically differ from the generation phones in the long run, much later than industry and hype would appear to suggest. (4) Manufacturers that learn from the earlier case studies about the dynamics of channeling technologies into everyday use will be well-positioned in the competition for market leadership in generation cell phones - in comparison to manufacturers that try to create the new market without analyzing and understanding the past.

4.2.

Product development in rapidly emerging markets

Generally, historical studies of the convergence of new technological possibilities into everyday use show that it is strongly an evolutionary process [Rosenberg 1982; Brown, 2000]. In the initial stage of the process, products exhibit a radical emphasis on product design on the basis of “push” enabled by new technologies [Freeman, 1994; Roussel, 1987]. The receiving audience finds it difficult to connect new technological innovations to its existing ways of life and of using products [Brown, 2000; Hargadon, 2001]. Only when users and manufacturers develop a shared agreement or vision about the product concept and the way it is configured, volume sales start to increase. In the late century, automobile sales were slow until users and manufacturers developed shared agreement about the automobile as a “horseless carriage”. In the 1980s, personal computers began to sell in volumes only when customers began to see their advantages as highly developed typewriters and advanced calculators (as for instance in spreadsheet applications). In both cases, a new mass market ended up unfolding its final form through interaction with users and in the image of one or more earlier product markets rather than arriving out of the blue. Patterns of product development tend to be fairly constant from one emerging product market to another [Clark 1985; Hargadon, 2001]. For the perceptive eye, breakthrough products have concepts, features, and user interfaces very much similar to those of earlier products. They attract the users behind one overarching product concept, finally meeting only little resistance, and ultimately developing critical mass to be a dominant design. Breakthrough products include, rather than exclude competing standards, “build bridges” [Kelley, 2002] between the new and the old, and take hold of a new market fluidly and seemingly effortlessly. Radical product designs using mu-

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tually exclusive technological standards cannot benefit from the advantages of this bridging.

4.2.1.

How dominant design occurs

Through the mechanism of attraction and bridging, a breakthrough concept and the way it is configured folds gradually into a dominant design [Abernathy, 1978]. A dominant design is a common understanding across manufacturers, users, and stakeholders of the new concept, and the way it is configured for markets. Coming back to our earlier examples, we note that while the dominant design in automobiles or PCs was still critically in the process of emergence, there was still ambiguity and uncertainty about the product concept and its configuration. Today, only few would disagree that an automobile should have four or three wheels, a user interface enabling steering (as for instance a steering wheel), and a motor running on diesel, petrol, electricity or hydrogen. Only few would disagree that a standard PC has a display, keyboard, hard drive, and a pointing type input device, such as mouse. These products have long since consolidated, with fewer and fewer brands challenging the dominant designs because the search for optimality culminates to a dominant design (Fig. 4.1). The existence of industrial and market standards enable and accelerate manufacturers in incremental development, elaboration, and refinement of products. In the phase of dominant design, the market is surprisingly predictable and there is nearly absence of technical risk [Teece, 1986]. Dominant design become critical for success. (This importance of complementary assets refers to the fact that the manufacturers benefit from market stability and the low level of risk. This happens at the mature phase of the markets when manufacturers can exploit earlier investments, as in terms of money, time and other resources.) In this phase, manufacturers develop economies of experience and scale, as well as bargaining power with vis-a-vis suppliers and distributors. Also, they have superior capacity in certain assets such as in manufacturing, marketing, and administration. A period of industry consolidation is said to begin when the possession of these kinds of complementary assets present barriers to the entry of new manufacturers, and the number of exits by the manufacturers become larger than the number of entries by the new entrants [Suarez, 1995].

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Four key drivers

The chances of a manufacturer becoming a winner and a survivor in the consolidation phase are higher when the manufacturer ensures that it has the critical success drivers in place from the outset. Yet, until recently, the studies of the birth and evolution of earlier product markets conveyed only little of information for managers how a dominant designs emerges from new technologies. This is especially the case in deciding of how to carry out product development strategies in the pre-market stage in terms of preparation for the market after dominant design has occurred [Suarez, 1995; Abernathy, 1978].

Not so long ago, Roussel et al. (1987) suggested that product development in all product markets follows the same pattern. Firstly, new product markets are driven by technology push. Secondly, they are driven by marketpull. Finally, in the mature stage, technology-user interaction takes over (Fig 4.2). Roussel’s three-stage evolution model of product development drivers was for a long time elegant and obviously sufficient for the purpose of analyzing the birth and evolution across diverse product markets. However, more recent studies by other authors distinguish between product development practices in contemporary product markets and product development practices across product generations within one product market. Results from these more recent studies show that a new product market emerges through a consistent pattern. As shown in Fig. 4.3, there is first an introduction of innovations on the basis of technology advances or other push factors, representing variation on the market. This leads users to try out the new innovations and to communicate with each other what they think and feel about the new technology or product. Alternative versions of the technology

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compete with each another and with the related established products, until one of them becomes a standardized dominant design. This will also become a platform for the technology’s emergence to the mass market, as well as the focus for efforts of elaboration, refinement, and appropriation.

These recent studies can be summed up to suggest that the technology push, market pull, and user interaction - the cycle of innovation across product generations within one product markets - are factors that do not appear in the sequence suggested by Roussel and his colleagues. Instead, they appear in the order of: technology push, user interaction and, only in the last stage, high volume demand or the pull of a mass market. And, the new product markets do not appear from “out of the blue” or from a scratch on the basis of technology push, but are based on established ways of usage of earlier technologies and products. Established ways of product use. However, traditionally, high-tech manufacturers have sought to create a new market from a scratch. This contradicts with the old, well-established, ways to develop products that lean on present powerful legacies of appropriate product concepts and its configuration [Brown, 2000]. One should note that as far back as in the late century, Edison’s success in the electric light industry was based on his insight that consumers would be more likely to accept electric light if its appearance and use resembled that of gaslight as closely as possible [Hargadon, 2001]. If a key feature of an existing product or service is not new, neither is it disappearing [Brown, 2000]. Recent evidence shows that the use of The Internet started picking up momentum in the early 1990s when people in universities and businesses began to use it for writing email messages to each other that resembled conventional letters and postcards. With a time lag of only a few years, email also became a killer application of both PCs and The Internet in the home market when manufacturers and operators had a good sense to

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advocate its benefits. Similarly, especially in Europe, teenagers in the late of 1990s started to use short messaging service (SMS) of mobile telephony to pass notes from one to another at schools, and in free time. Telecom manufacturers and operators picked up on the fashion, promoted short messages as a value-added service, and the fashion turned into a gold mine and a new standard for inter-personal communication across all ages. We note, therefore, that links between new products and established products create meaningful starting points for successful product and service business cases.

Technology push. Like product and service users, also manufacturers tend to be locked into their earlier experiences [Sakakibara. 1995], routines [Nelson, 1982], and competencies [Hamel, 1994]. They tend to assume having in-house capabilities for participation in the emerging market, still their business models flow from the past [Sakakibara, 1995]. Surprisingly, this conservatism is sometimes a good driver for high-tech product development: it channels work in the direction of complementary assets that already exist. In the early 1990s, Linus Torvalds attempted a limited technological advance along with an available kernel of a Unix operating system, and pushed his preliminary achievement into a focused discussion in The Internet Relay Chat (IRC). Within a few years, his Linux operating system emerged into the

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leading open-source operating system in the world. The success of the Sony Walkman in the early 1980s is another example of using only modest investments and working capital on a wild goose chase without interaction with users or early user testing. User-technology interaction. There is a rule across new products markets, that at the outset of the product concepts, manufacturers and users are not able to master the high product diversity on the market. Bicycles attracted much attention already from the outset in the late 19th century, but the mass market failed to take root until the “user agreement” on the modern standard of a two wheels of equal size. Also, there was a high interest and market growth potential in the videocassette market, but sales failed to reach mass-market volumes until VHS of Philips von its battle of standards with Beta of Sony and others. When the standard by which to identify and sample the population of customers (eg profile of the users) is still critically in its emergence, traditional marketing research methods to guide the strategies of product concept owners do not work [Kelley, 2002]. Given this uncertainty about the standard, the best the manufacturers can do is to “make a partition” [von Hippel, 1990]. This means that the product development process leans on subcontracted components, assembly, software, and other such modules, and it interacts with as many interest groups and users as possible. When cell phones were still in their infancy in the 1980s, Motorola considered that the costs and risks indicated that it was wise to limit cell phone and network operations to the communications’ standards predominant being applicable and developed predominantly for the United States. Thus, it had access to the preferences of the American market. However, for a longer run, this blocked its market in Europe. In contrast to Motorola, Nokia developed simultaneously several marketing strategies, standardization and technologies around the world. By partitioning product development and thus spreading risk to partners, Nokia could afford to participate in the development of functional, well-timed and meaningful product configurations in more than one competing technological standards. So far, Nokia’s strategy of product development catering for different standards has proved to be good preparation for the time when 3G and Next Generation Networks (NGN) ultimately produce a synthesis that is the dominant design or “a universal communicator” of cell phones. Market pull. With a dominant design in place, data from the distribution chain flows on a regular basis to the manufacturers that are the market leaders, and the producers of the dominant design. The market leader has the most vital information at hand to segment the market, transform cheaper product versions into low involvement products where volume is possible, and to reach a critical mass in volume and expertise. Sony with its Walkman, IBM in PCs, Intel in chips, Microsoft in desktop PC software, and Nokia in 2nd gen-

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eration cell phones, are all good examples of these advantages of a market leadership. They have leveraged sales volume into ways to cope with the liability of newness, the high costs, and the immense risks associated with high-tech. They have develop superior branding, and locked users, distributors, subcontractors, assemblers, and other providers of services into their value chain.2

4.3.

Methods

History of product development is a powerful repository and there is “much to learn from historical examples”[Shapiro, 1999], even though contextuality of historical knowledge is a challenge of interpretation. This study builds on the research our team started in 1993 aiming to map market evolution in and around PDAs available on those days. For this purpose, we collected data by interviews (from the employees at Apple, Psion, Sharp and Nokia), using Internet press releases, and by the professional press in and around the information and communications technologies. Taking a market-evolutionary, real-time3 approach, we mapped high-tech product development strategies in the field. While we could not, at that time, identify the winner in the competition for dominant design, we did revealed the key players, strategic tradeoffs they faced, and the patterns of behavior by which they sought to deal with these tradeoffs [Sakakibara, 1995]. Seeing this all today suggests that on a rough level, Roussel’s third generation processes (Fig. 4.2) we investigated on those days are still the same. This includes the slowing down of product innovation rate, the growing importance of complementary assets, and market shakeout. (For additional discussion, see also [Rosenberg, 1982; Anderson, 1990].)

4.4.

PDAs, Palmtops, and 2G Phones

Computer manufacturers have since the 1960s expected computing technologies to merge with communication technologies. This was boosted especially by the development of new multimedia services. In the mid-1980s, Apple Computers launched an integrated handheld computing, communication and multimedia device. This Personal Digital Assistant was expected to result in huge sales, a new distinct market, and exceptional returns to Apple. John Sculley (the Chairman of Apple Computer on those days) refused to be worried about Apple’s lack of experience with palmtop size computers [Menuez, 1993]. Advances in computing power, battery life, and miniaturization at-

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tracted the attention of other computer manufacturers as well. The attention of industry observers focused on the few PDAs yet on the market. In 1992, even before the first PDA was introduced, there were products by Hewlett Packard (HP), Sharp, and Psion that resembled a PDA, for instance, HP marketed the LX-100 Palmtop Computer. The LX-100 was essentially a world-class calculator, extended with text and data features, running a special version of MS-DOS, and using a keyboard as the input device. HP had a superior brand in its palmtops, and a well-developed distribution system. The LX-100 was not pen-based and sold for £750, but in all other ways it was a PDA. Following a typical Japanese strategy, where each model is a small improvement over previous ones (Kagono 1985; Korhonen, in this volume), Sharp had produced for a long time “electronic organizers” for home market in Japanese. The Zaurus was Sharp’s first keyboard-based organizer, striving to meet the challenges of the handwriting recognition technology of Japanese kanji and Western Roman alphabets. Psion’s manufactured an easy-to-use Personal Organizer (Psion 3). Psion had a strong support from retailers, and therefore also a strong market presence. Like HP’s palmtop, Psion 3 was also keyboard-based. In 1993, Amstrad and AT & T were the first manufacturer to introduce a product that they called a PDA. Armstrad’s PenPad came to the market early in that year, and AT & T’s EO Personal Communicator soon after. Apple did manage to launch the Newton MessagePad before Casio launched its Zoomer Personal Organizer. The product development of Zoomer combined Casio’s capabilities in portable electronics, Tandy’s marketing organization on the American market, Geoworks’s expertise in innovative operating systems, and Palmtop Computing’s skills in handwriting recognition. Despite the differences in user interfaces, manufacturers and industry observers agreed by the end of 1993 that the above devices offered the same or the similar features and were effectively part of the same market.

4.4.1.

High product-concept and configuration diversity

The market of early PDAs was “hot” and “sexy”, attracting many manufacturers who wished to be part of the market that promised soon to converge into a multi-billion dollar industry. At the same time, it was still unclear how the technological possibilities would translate into a distinct PDA market with clear boundaries and rules of the game. Manufacturers’ visions differed vastly from one another. New entrants (Armstrad, AT&T, Casio, and Apple) had a pen-based user interface, while veteran manufacturers (HP and Psion) offered small-scale traditional keyboards. Apple’s market research showed that USD 500 $ was a maximum price, while most other manufacturers considered that

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computer screens alone questioned the validity of this pricing policy. In this fuzzy situation, there were four main PDA concepts: 1. At the core of the market was a pen-based PDA that had no keyboard and performed advanced text, drawing, spreadsheet, and calendar functions. Representatives of this category included the Armstrad’s PenPad, Apple Newton’s MessagePad, and AT&T’s EO personal communicator. Motorola showed also some interest in this category. 2. The “palmtop computer” was a miniaturized PC that used a keyboard and a special, portable version of popular PC spreadsheet and word processor software. HP had a long experience in manufacturing palmtops and its LX-200 was a good example of this kind of a product. 3. The “electronic organizer” had a diary, name and address book and calculator, but no drawing or spreadsheet features. The Casio Zoomer personal organizer, basically a simple electronic diary, is a good example of this category. There were also devices combining the features of #1 #2 and #3. Sharp’s Zaurus was a half-organizer, half a pen-based PDA. Psion 3 was a half organizer, half palmtop. 4. The “smart phone” is an expanded mobile phone integrating for instance computing, radio, CD-player and camera features.4 Bell South, IBM, Nokia and Sony were expected to make a product launch in this category. In those days they adopted a wait-and-see strategy and suspended product launch. This happened probably due to both technological and marketing aspects.

4.4.2.

Signs of dominant design in sight

In the days of early PDAs, the retailer’s margin was typically only 15 or 20 percent of the total price tag of about £400. Therefore, the retailer made about £60 to £80 on each sold unit, and refused to provide much of customer service. In this situation, the new market made trusted brands out of products that were both reliable and user friendly, such as those of Sharp’s, Psion’s, and HP’s. Other manufacturers, such as Apple and Psion sought most clearly to appropriate returns from product sales, seeking to control products’ hardware and software. Apple suffered from the fact that many of the key components microprocessors, flat screens, and batteries, etc. - involved exclusive knowhow that was not in the possession of Apple’s suppliers.5 Psion was much more successful than Apple with its own powerful, memory-efficient and

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easy-to-use operating system and applications. This meant, that the early PDA market began to polarize into “early winners” and “early losers”. The “early winners”. HP, Psion and Sharp emerged in 1994 as the three companies that escaped mutual competition through unique price positioning. HP’s LX-100 dominated the upper segment of the market where it competed with laptop PCs. HP addressed the high-price issue by launching the LX-200 model that carried a lower price tag, improved software, and 2MB of memory. The HP LX series sold about 350,000 units in 1994.6 Psion represented the mid-price segment. It took some distance from the electronic organizers by launching the Series 3a, an improved and more expensive version of Psion Series 3. The Psion Series 3 sold 300,000 units in 1994.7 Sharp’s Zaurus took the lower end of the PDA market and the top end of the organizer market. Sharp focused on maximizing value for money and on the incremental introduction of new features, a strategy that had made Zaurus a huge success in Japan (Table 4.1). Sharp’s Zaurus sold about 370,000 units in 1994.8 The “early losers”. Apple’s Newton won several awards and applied numerous novel and radical technologies, especially in the user interface and operating system as for instance its RISC technology based handwriting recognition system. However, the Newton performed unsatisfactorily in sales, and its actual value for money turned out to be surprisingly poor. Despite of the launch of the cheaper and improved models, the Message Pads 100 and 110, and many other promises and attempts, Apple ultimately lost much of its brand name in these battles.9 Approximations of the sales of 1994 vary between 80,000 units10 and 120,000 units.11 Also Casio’s Zoomer failed to meet its sales targets and sold approximately 80,000 units in 1994.12 Amstrad was one of the first ones in the market 13 but failed to translate this advantage into a sustainable advantage, probably due to technological problems, and sold approximately of 50,000 units only. The AT&T EO Personal Communicator failed to reach the critical mass that would establish it as a serious contender, and was withdrawn from the market by the mid-1994, before selling well under 15,000 units. New competitors entered the market at the very end of 1994. Motorola had some earlier experience in mobile phones and related handheld electronics and it introduced the Envoy, an extended palmtop computer with seminal communication features. Southern Bell was a leading company in cellular technologies in the American market and gave us the Simon, an extended cell phone with some computing features. Sony launched the MagicLink, an attempt of a fully-fledged PDA. IBM had succeeded in creating the personal computer we now call the PC, yet the market gaps in critical components and other valuable entry points appeared to be already filled and nowadays IBM compatibles are manufactured by various other companies, not so much by IBM. Motorola, Sony, IBM and Southern Bell all failed to match the compe-

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tencies of HP, Psion and Sharp especially in calculators and palmtop computers.

None of the four developed “a killer application” in PDAs that would have become the dominant design, and soon pulled out of the market. They would eventually withdraw from the market like AT&T (1994), Armstrad (1996), Casio (1996), and Apple (1997).

4.4.3.

The occurrence of dominant design

By 1996, it appeared clear that the successful strategies of HP, Psion and Sharp had accumulated sufficient understanding of which kinds of brands, components, product architectures, and retail services could be winners. The market began to take on systemic cohesion and identity.

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It was precisely at this point that Palm Computing, established only in 1992, began its sudden and phenomenal rise to market leadership with Palm Pilots. Palm Computing’s Pilot 1000 cost only US $299, but was still bundled with such extras as a “hot cradle”, Windows or Macintosh information exchange software, and extended PC connectivity. Essentially a stripped down Apple Newton MessagePad, these extras greatly alleviated problems of data entry typical for hand-held personal computing and communication devices. The Palm Pilot series became a huge success, and effectively became the dominant design. How did Palm Computing do it? Palm Computing began its existence with work at the Grid System, arguably the world-first commercial laptop computer. It worked on the handwriting recognition of both Apple Newton and Casio Zoomer. It also worked on a PC connectivity kit for the HewlettPackard LX-200. With intimate connections to developments in the PDA market, Palm Computing’s product developers became frustrated with the fact that nobody in the PDA business appeared to be addressing such “obvious” issues as shirt pocket size, connectivity, easy expansion, and an end-user price of less than US $300. Using an internal software team of 30 people, external teams in engineering and manufacturing, and US $ 2 million, Palm Computing developed and successfully market-tested between 1994 and 1996 what it called a memory-efficient and fast “3rd generation software”. In 1995, industry consolidation and complementary asset building began with the acquisition of Palm Computing by US Robotics. In 1996, the same year that the Palm Pilot was launched, Nokia launched its Communicator 9000, a generation smart phone with Internet connectivity. The vision was that the “Communicator” would be a platform for developing competencies and exploring opportunities in the creation of integrating smart phones, palmtop computers, and handheld multimedia devices. In contrast to the optimal “here and now” orientation of the Palm Pilot, the Communicator series was a low-key statement, with a bias towards the future. At the same time, the Nokia Communicator in comparison to the Apple Newton MessagePad was also reliable. It met the level of expectations, leveraged the trusted-brand status that came from Nokia’s success with its mainstream cell phones, and created a sound basis for sustained user-Nokia interaction in the further development of the product concept. In 1998, Jeff Hawking, the founder of Palm Computing, spun off Handspring from Palm Computing, creating another new winner in the PDA market14. While Palm Computing exploited fully the benefits of the original PDA concept in what can be called an “optimal design”, Handspring’s Visor series had an open architecture that, by 2002, would evolve to integrate computing and voice in a single device. In this way, Handspring resembled Nokia’s

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Communicator. If Palm Pilot 1000 had been a generation PDA, Handspring and Nokia were platforms in generation product development. In 2002, HP acquired Compaq (a recent entrant in PDAs). Sony joined forces with Ericsson to create “SonyEricsson”. Nokia continued with the Communicator 9000 series, while competing with SonyEricsson on camera features in a cell phone.

4.5.

Conclusion

The story of early PDAs is about imagining and communicating exciting visions of new devices and market, rallying stakeholders to support the product visions, and elevating customer demand for these products. This is also a story of major drawbacks: exciting new products failing to work reliably and losing even to conservative designs. Generalizing from the discussed PDAs to the generation15 terminals and services one can sketch the following predictions of market evolution: In the short-term successful generation terminals and related services will closely resemble the generation approaches. Originally competing technologies will gradually complement each other. generation terminals will radically differ from the generation terminals in the long run, later than industry and hype would to suggest. Manufacturers that study and learn from the earlier dynamics of technology channeling into applicable business cases will be better positioned in the generation competition (Fig. 4.4). A message of this chapter is also to invest on gradual improvements. A manufacturer ought to develop generation services and terminals slowly and step by step. Rather than attempting to identify a killer application all at once, a strategic manager ought to consider the benefits and wisdom of commercializing only one product, and one new feature, at a time.

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A fact is that the latest generation cell phones have a plentitude of multimedia features of generation cell phones, such as multimedia messaging services (MMS), e-mail, camera and MP3 player. Thus, the earlier market experience should be preferably leveraged for development, optimization and exploitation of service market rather than just focusing on novel or combined technology. Despite the probable imminent shake-out and consolidation of the generation device and service markets, each manufacturer should establish a direct link with the unfolding market on a continuous basis in order to be included in the next generation cellular terminal and service market. Manufacturers ought to develop in-depth latitudinal and longitudinal knowledge of user preferences and sentiments in close cooperation with key suppliers and customers. Learning from the successful ideas in the product offerings of competitors is a useful exercise to explore user sentiments and market trends (Fig. 4.5.). To conclude this chapter, managers, industry observers, and consultants in and around 3rd generation cellular telephony ought to consider that: Imagining and communication of exciting new product concepts is a powerful way to vision and understand the evolving PDA market.

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Manufacturers focusing on investments in market-creation phase will lose to those pioneers that can access and exploit superior competence. In mature markets, when dominant design stands out, manufacturers that broker and recombine lessons from the surviving ideas will be winners.

The current PDA market is far from being stabilized to yield a solid dominant design. Industrial, corporate, and academic researchers in the development of 3rd generation PDAs and related services ought to have a look especially at Handspring and its pioneering role in opening Palm Pilot’s product architecture. Also, Nokia’s and Sony’s current joint effort with Ericsson in exploration of new MMS and other multimedia services deserves continuous attention. Japanese testimonials on PDAs (as with the I-mode phones) are indeed a convincing evidence that generation terminals will incorporate a significant market potential, and an important challenge left for Europeans is to interpret this to the European languages of telecommunications service profiling.

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NOTES 1.

In technological terms, generation phones count (especially in physical level) on incompatible technologies (GSM, IS-95, I-mode, and PCC), and give dissimilar data rates and network accessibility. In the (GPRS, EDGE, HSCSD) and in the generation networks (WCDMA, cdma2000), advanced services from one or several of generation standards build on earlier standards: for example, the Short Messaging Services (SMS) of GSM is implemented within the generation standards as the Multimedia Messaging Service (MMS). It builds on the SMS and WAP platforms and, in turn, is a highly probable platform for future platforms.

2.

Of course, it is strategically unwise to underestimate the role of assemblers or component suppliers. Initially, user terminal markets may serve as platforms to create economies of scale and experience and to establish a position at the core of the market. Yet, in branded goods it can be considered a general rule that providers of parts, subassemblies and services will often have a less important role in the development process, because the value the assemblers adds is often a limited one..

3.

By “real-time”, we mean that most of the evidence has been reported as it has been reported by insiders and on The Internet, as well as by the professional and business press.

4.

The Simon was a portable phone with computer capabilities launched in late 1994. An outcome of this was a joint venture between IBM and Southern Bell.

5.

Apple abandoned Sharp for a cheaper assembler in Taiwan, but the price of the screen dropped little from the 30 percent of total product cost demanded by Sharp.

6.

Investor’s Business Daily, August 3, 1994.

7.

Personal interview with Stephen J. W. Rogers, Strategic Sales Manager, Psion plc, by Christian Lindholm, on 9 March 1995.

8.

Nihon Keizai Shimbun, July 23, 1995.

9.

Apple launched another improved model, MessagePad 120, in January 1995.

10.

Business Week, July 11, 1995

11.

DIME, September 15, 1994, p. 95.

12.

This number is based on [Dataquest, 1995]. That survey announced sales of 61,000 Zoomers. We have topped up that number by thirty percent, which we know is Dataquest’s understatement of unit sales of Sharp’s, Psion’s and Apple’s products.

13.

There were manufacturers that tried to enter the market earlier than Armstrad, such as the ABC, a Swedish handheld and a desktop computer, but these received only a little attention on the global market.

96 14.

Handbook of Product and Service Development in Communication and Information Technology Jeff Hawkins had also been involved in the development of the Casio Zoomers, as well as the Grid, one of the earlier notebooks on the market.

REFERENCES [Abernathy, 1978a]

Abernathy W. J., The Productivity Dilemma: Roadblock to Innovation in the Automobile Industry, The Johns Hopkins University Press, 1978.

[Abernathy, 1978b]

Abernathy, W.J. and Utterback J.M., “Patterns of Industrial Innovation,” Technology Review, June/July, 1978.

[Anderson, 1990]

Anderson P. and Tushman M.L., “Technological Discontinuities and Dominant Designs: A Critical Model of Technological Change,” Administrative Science Quarterly, vol. 35, 1990.

[Baldwin, 2000]

Baldwin C. and Clark K., Design Rules, vol. 1, MIT Press, Boston, 2000.

[Bartlett, 1989]

Bartlett C.A. and Ghoshal S., Managing Across Boarders: The Transnational Solution, Harvard Business School Press, 1989.

[Baum, 1994]

Baum and Singh, Evolutionary Dynamics of Organizations, [In: Ainamo 1996], 1994

[Brown, 2000]

Brown J. S. and Duguid P. The Social Life of Information, Harvard Business School Press, Boston, 2000.

[Clark, 1985]

Clark K. B., “The interaction of design hierarchies and market concepts in technological evolution,” Research Policy, vol. 14, 1985

[Dataquest, 1995]

Dataquest, “Handheld Computer Market Gathers Momentum,” Dataquest 1995 Focus Report, Dataquest, Inc., U. S. A., 1995.

[Freeman, 1994]

Freeman J. “Innovation: Review”, [in Ainamo 1996], Cambridge Journal of Economics, 1994,

[Hamel, 1994]

Hamel G. and Prahalad C.K., Competing for the Future, Harvard Business School Press, 1994.

[Hargadon,2001]

Hargadon A. and Davis “Edison”, Administrative Science Quarterly, 2001.

[Kagono, 1985]

Kagono T., Sakakibara K., Nonaka I. and Okumura A., Strategic vs. Evolutionary Management: A U.S. – Japan Comparison of Strategy and Organization, Amsterdam, 1985.

[Kelley, 2002]

Kelley T. and Littman, The Art of Innovation, London, 2002.

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[Menuez, 1993]

Menuez D. and Kounalakis M., Defying Gravity: The Making of the Newton, Beyond Words Publishing, Oregon, 1993.

[Nelson, 1982]

Nelson and Winter, An Evolutionary Theory of Economic Change . Cambridge. Mass: Harvard University Press.

[Rosenberg, 1982]

Rosenberg, Nathan, Inside the Black Box, 1982.

[Roussel, 1987]

Roussel P., Saad K., and Erickson T., Third Generation Product Developmen: Managing the Link to Corporate Strategy, Harvard Business School Press, Boston, 1987.

[Sakakibara, 1995]

Sakakibara K., Lindholm C., and Ainamo A., “Product Development Strategies in Emerging Product Markets: The Case of Personal Digital Assistants’ (PDAs)”. Business Strategy Review, Winter, 1995.

[Sanchez, 1995]

Sanchez R., “Strategic Flexibility in product Competition,” Strategic Management Journal, 1995.

[Shapiro, 1999]

Shapiro and Varian H., Information Rules!, Harvard Business School Press, 1999.

[Suarez, 1995]

Suarez F.F. and Utterback J.M., “Dominant Designs and the Survival of Firms”, Strategic Management Journal, vol. 16, number 6, 1995.

[Teece, 1986]

Teece D.J., “Profiting from Technological Innovation: Implications for Integration, Collaboration, Licensing and Public Policy,” Research Policy, vol. 15, 1986.

[von Hippel, 1990]

von Hippel E., “Task partitioning: An Innovation process variable,” Research Policy, vol. 19, 1990.

[Ward, 1995]

Ward A., Liker J.K., Cristiano J.J. and Sobek II D.K., “The second Toyota paradox: How delaying decisions can make better cars faster,” Sloan Management Review, Spring 1995.

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Chapter 5 PROJECT PORTFOLIO MANAGEMENT IN TELECOMMUNICATIONS R&D Taru Aalto, Nokia Ventures Organization, Finland, Miia Martinsuo, Talent Partners Oy, Finland, Karlos A. Artto, Helsinki University of Technology, Finland

Abstract Research and development in telecommunications is increasingly conducted through target-oriented projects. Project management systems and tools have been implemented to improve efficiency and general manageability of activities. In a dynamic business environment, however, the biggest challenge is in deciding what to do, in addition to how. Project management discipline has recently expanded its scope towards multi-project management, frequently referred to as project portfolio management. Since projects in the same organization compete for the same resources, they together should be steered to fulfill strategic business objectives. Project portfolio management is about managing the entire set or subset of projects towards strategic objectives. During the past decade, project portfolio management literature has introduced tools and frameworks for steering R&D project portfolios effectively towards business goals. These methods are no longer merely about rational and numerical decision making, but more about skilled, multi-disciplinary criteria, evaluation and strategy-driven choices. Due to the contingent nature of human decision-making, it is likely that project portfolio management should be different at the different stages of R&D: research, technology development, and product development. Such research has not been reported earlier. We examine three Finnish telecommunications organizations and their approach to project portfolio management. Our aim is to analyze whether project portfolio management practices differ, 99 T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 99-147. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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or should differ across the different R&D stages, and to suggest good practices for each stage. In addition to presenting an overview of R&D and project portfolio management literature, this chapter discusses the differences identified across R&D stages and proposes some ideas for future research.

5.1.

Introduction

During the past decade we have witnessed the emergence and phenomenal growth of the mobile communications industry. Intense competition and constant changes in the business environment have forced companies to renew themselves and their offering continuously [Jelinek, 1990]. In practice, renewal has meant heavy investments in research and development. Computer, electronics and software industries continue to exhibit a trend towards higher levels of R&D spending in large firms. The increase of R&D spending and the number of filed patents suggest that knowledge intensive industries will remain dynamic in the future [Bowonder, 2000]. While information technology and telecommunications industries converge, however, past victories will not guarantee future successes. Gary Hamel (2000) claims that progress in the form of continuous improvement is no longer enough. We now live in the era of revolution. Unless companies renew their entire business concept, new, unforeseen entrants will likely replace them. New business designs and early-stage innovation experiments are seen as options for the future – no longer as mere operative costs. Hamel, therefore, raises the question whether a company’s innovation portfolio is unconventional enough to reveal potential revolutions early enough. The urgency to introduce new business concepts and new products fast to the market has forced companies to consider more carefully, how to carry out their product development. An increasing number of companies are organizing their R&D activities as target-oriented projects, and the R&D- centered project management discipline has indeed matured well during the past decade. Basic project management principles, including project process, resource management and product management, have been adopted well by new product development departments in large firms. The need for business concept innovation directs attention to technology and channel choices. Besides ways of conducting R&D, companies must consider which technologies and products to compete with, whether to make the products or technologies themselves, subcontract or buy them, and how to deliver the products to the market. How can these business objectives be included in the project management frameworks of companies?

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R&D projects should implement corporate strategy, in addition to operative objectives. This means that we should look at the whole set of projects in the company, and take into account their interrelations and alignment with business objectives. Managing the collection of projects is called project portfolio management. It is a response to the challenge of finding the right ideas and the projects that meet the strategic goals of a company, and making sure that they progress from an idea into the market place [Stevens, 2000]. In a dynamic industry such as telecommunications technology, an overflow of potential ideas and technologies is more challenging than the lack of ideas. Therefore, one critical success factor in creating competitive advantage is to have a good system for deciding which ideas to pursue [Stevens, 2000] and to make sure they end up to end products and to the market. Companies must be able to choose the right technology areas and products for R&D. They must also abandon the projects that bring less value to the company or consume scarce resources without future promise. When making these decisions, the strategy of the company must be taken into account, as well as the number of resources available. This paper reviews relevant literature and analyzes management practices in corporations on managing R&D, with an emphasis on project portfolio management. We aim to highlight factors that are important in implementing project portfolio management in R&D organizations. Project portfolio management is typically discussed in the context of product development, meaning the latest, best-defined stage of R&D activities. As large telecommunications enterprises are likely to have split their R&D activities based on technology maturity into, e.g., research, technology development and product development, we specifically look into the requirements set to project portfolio management by the different R&D stages. Three case examples are presented on project portfolio management, representing the different stages of telecommunications R&D. Based on these sets of evidence, we make some propositions regarding the good practices of project portfolio management in telecommunications R&D and explore ideas for future research.

5.2.

Managing business-oriented R&D

R&D refers to research and development, two intimately related processes by which new products and new forms of old products are brought into being through technological innovation [Encyclopaedia Britannica Online, 2001]. R&D outputs are new or improved products or technologies, or improved ways to produce the products. These R&D outcomes, as well as resources, are closely governed by business strategies. The mix and flow of products and technologies can be managed in different ways.

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In management literature, R&D often refers to product development. This is very understandable since R&D in many organizations and industries is about product development. However, in larger organizations such as the leading telecommunications companies, R&D covers everything from longerterm research to short-term product development.

5.2.1.

Stages of research and development

This paper adopts an R&D content that covers both new product development and all other research and development activities that aim finally towards an end product. Thus, we use the term R&D to include research, technology development, and product development. The three R&D stages have their special nature [Turner, 1999; Bailyn, 1988; Cooper, 2001]. Product development is the shortest term and best-known activity in the R&D funnel.

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Fig. 5.1 presents an illustration of the R&D funnel and the changing nature of R&D activities in the funnel. Product development activities normally consist of product programs that aim towards a complete verified and tested end product. Since end products in telecommunications can be very complicated, the size of product programs may be very large. The goals and final specifications of the end product are clear as well as is understanding of the target end users’ needs and the target market. Radical innovations are rare at this stage, and the technologies used are quite mature and verified by the earlier stages of the R&D process. In product development, the methods are formal and management processes well defined, and the risk level is quite low due to less uncertainties regarding technologies, markets or end-user. Technology development is more volatile by nature than product development and the projects are typically more focused on certain technologies or their combinations (e.g. product or technology platforms). Technology development aims to create new knowledge or a capability that supports or spawns new products or processes [Cooper, 2001]. In technology development, the results of corporate research or academic research are utilized but still major innovations are possible. Compared to product development, the goals are less strict, the time scope longer and the management practices less strict. The risk level is also higher due to more uncertainties and the difficulty of predicting the future. Technology development is often organized into business unit research or technology development departments. Research is the longest-term activity of R&D. In telecommunications corporations it is typically organized as corporate research units. The goals of research activities are often not as definite as in product or technology development and they are primarily technological or knowledge-oriented [Betz, 1993]. In a research organization the project size can be fairly small due to a limited scope or risks and uncertainties. The methods that are used also allow more freedom. Research personnel prefer and can cope with a lot of freedom and uncertainty. When efficient, research can result in radical innovations that promote renewal and new kinds of solutions towards an improved competitive advantage. Especially in new and emerging industries, including the converging telecommunications sector, R&D evidently represents a core activity of organizations. The different stages of R&D take place simultaneously, and they should all contribute to the goals of the firm. Therefore, two critical success factors in R&D are process clarity and the alignment of R&D with business objectives [Davidson, 1999; Cooper, 1999]. Concurrency of the different stages makes R&D management complex. Fig. 5.2 illustrates how the different stages of R&D are interlinked (modified from [Groenveld, 1997; Kostoff, 2001; Groenveld, 1998].

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Understanding the different stages of the technology lifecycle helps to simplify the challenge to organize business-oriented R&D in large firms. However, other mechanisms are needed as well. Project management, resource management and product management have offered practical tools and systems for goal-directed innovation.

5.2.2.

Project management

Projects are adopted in many corporations as major vehicles for organizing work. According to the latest research by Project Management Institute nearly 25% of the world’s GDP is spent on projects [PMI, 2001]. Projects represent operational devices that fit well to the networked business environment, including R&D. The PMI Body of Knowledge defines a project as a “temporary endeavor undertaken to create a unique product or service” [PMI, 2000]. In R&D, the product may have multiple meanings: a new technology, a veri-

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fied technology, a new process, improvement of existing technology or product, or the actual end product delivered to the customer. Project management is about making sure that the activities in R&D are done efficiently and that they follow correct guidelines. In a way, project management ensures that the resources allocated to certain tasks are used in a correct manner and that the goals are reached. The goals for projects can be defined with the help of a variety of tools, and available resources and time limit their scope. Project management covers several different areas, such as project integration management, scope management, time management, cost management, quality management, human resources management, communications management, risk management and procurement management [PMI, 2000]. For success in managing a project, management in these areas must be carefully balanced to match the project type, management culture and business environment. A more detailed examination of good project management practice is available in Turner (1999), and more specifically in the new product development field in Cooper (2001). Projects are limited by time and they have a defined start and end. Project process in the R&D field typically consists of stages that are controlled on gates ([Cooper, 2001], also referred to as phases and milestones, or phases and reviews). Typically, R&D projects include ideation, preliminary investigation, detailed investigation, development, testing and validation, and full production and market launch [Cooper, 2001]. On the gates, accomplishments are measured against goals, and decisions regarding the future are made. The content of each stage varies according to the nature and stage of the R&D activity. A typical project process for managing new product development is presented in Fig. 5.3. The stage-gate type of process approach is often applicable even if R&D is not organized as projects.

5.2.3.

Resource management

A central element in R&D projects and processes is the management of the different resources of the company. The most important of these resources are human and monetary resources that typically are scarce by nature. Effective resource allocation is necessary for the projects’ chances to succeed. Moreover, resource allocation must be interconnected with strategy. Effective strategy implementation requires that resources be allocated according to strategic directions [Cooper, 1997b]. Top management typically sets certain overall limitations and guidelines that are defined in more detail on the lower levels of the organization.

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The way resource management is organized varies across organizations. Hendriks et al. (1999) have split the process of resource allocation into five elements: long term resource allocation, medium term resource allocation, short term resource allocation, links, and feedback (Fig. 5.4).

Long-term resource allocation is based on the strategic objectives of the company and is made yearly. Medium-term rough-cut resource allocation is done quarterly and its main tasks are to check the overall status and situation of the project and to decide on the decision rules to be followed by the group leaders when deciding on short term resource allocation. If the project portfolio or company strategy has changed during the previous three months, some adjustments might be made on the original resource allocation plan, and thus, the project portfolio might change. The planning horizon of the medium term resource allocation is one year. Short-term resource allocation is linked to the day-to-day planning of individual resources for the following weeks. It is done every two weeks and its planning horizon is about six weeks. The long, medium and short-term resource allocation processes each have their own tasks but they are also interconnected by information flows. Additionally, they all follow the same process of planning, doing, checking and acting, with differing time intervals. The reader is advised to consult Van Arnum (1998) to identify criteria for credible resource estimates. Human resources are one of the most challenging resources to manage since managing them is not only about providing the projects with the right number of people but also about allocating the right type of resources to proj-

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ects (competence management). For successful implementation, it is crucial that the people in the project possess the required skills and can operate together [Hendriks, 1999].

In addition to allocating the existing human resources, it is also important to actively search for new potential resources and educate the existing personnel, to acquire the competencies needed in the future. Regarding employee selection, important aspects include the employees’ ability to complement each other, work smoothly together, develop knowledge together, and share knowledge with each other [Anell, 1998]. Resources can also be attained temporarily from external partners. Alliances, partnerships and subcontracting have an important role in managing R&D.

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Human resource management is tightly linked to budgeting, i.e. the management of monetary resources, but in some companies these two processes are separated. The people responsible for each process may be different, and the time intervals and reporting might be different. In most project-oriented organizations, resource plans are parts of project planning and management. However, the financial departments of organizations most likely require budget figures based on the yearly financial reporting cycle while project length and milestones are very seldom organized that way. This causes a challenge in matrix-type organizations, frequently solved through agreedupon negotiation procedures and division of responsibility between project management and line management.

5.2.4.

Product management

R&D outputs are new or improved products or technologies, or improved ways to produce the products. A critical success factor in product development is having a unique, differentiated superior product that delivers unique benefits and value to the customer [Cooper, 2001]. R&D outcomes, as well as the above-mentioned resources, are closely linked to business strategies. McGrath (2001) identifies two strategic changes that have clear implications for product strategy. Firstly, growth or continued competitive advantage at current markets may require new product capabilities, achievable through developing a new product generation, i.e. product platform replacement. Secondly, expansion into new markets may require the introduction of a totally new product platform. The impact of strategic choices on products, competencies and resources should always be considered. One central element in product strategy is the choice of strategy type and its relation to changing external conditions. Organizations differ in the speed of responding to changing market conditions. In terms of product strategy, they can be categorized into four types: prospectors who are the first to innovate in the industry; analyzers who monitor the industry and follow prospectors fast; defenders who attempt to identify a secure position or niche in a stable area to protect; and reactors who respond to market changes only when forced [Miles, 1978]. Firms may position themselves differently in different product areas. A PDMA study [Griffin, 1996] recognized that the strategy type influenced what kind of product development projects the companies were involved in. The mix and flow of products and technologies can be managed in different ways. The strategic approach emphasizes three views dealing with product strategy: product platforms, product offering, and product or technology roadmaps.

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Especially in high technology firms, it is typical to utilize the same technology for several different products. Therefore, they often build their product strategy upon a product platform strategy. Product platform is a collection of common elements and technology implemented across a range of products. It is not a usable product per se, but rather a foundation upon which the functionalities of a product can be configured or added. The choice of platform technologies, platform uniqueness at the market as well as the relation of platform components and add-ons has an important role in product strategy. Even if product platform strategies enable products to be deployed faster and more consistently, they also have a more long-term view to the business. [McGrath, 2001] Product offering refers to the product mix, as well as options for configuring and using the product, the way of purchasing, positioning of the product at the market, and product support [McGrath, 2001]. The term product portfolio may also be used, to denote the offerings available or under development in the firm [Cooper, 2001]. Product offering may be based on one or several platforms. The products together should ensure success at the market for a longer term, by maximizing the value of the portfolio, balancing it in terms of e.g. risks and rewards, and aligning it with business strategy. In practice the combination of product offerings should guarantee the following: Old products continue to remain attractive and supported, or are withdrawn from the market in time New products or replacements emerge at the right pace, for the right customer segments Complementing technologies and services are developed at the right time for new products (e.g. after market services) Effort is divided correctly between new products, replacements, new technologies, and longer-term research, to ensure new products and solutions also in the future Roadmapping is one way for companies to outline the availability and development path of technologies and products or features in relation to time. Roadmapping is a well-known practice; some corporations, such as Motorola, have decades of experience using roadmaps [Kappel, 2001; DeGregorio, 2000]. Technology roadmaps specify the features and technologies available for and used in the future products. They may also group the identified key technologies into a limited number of alternative scenarios that help in determining the winning development paths, as well as competition. Products and usages can be described through combinations of functionality, performance,

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features and applications of future technologies. Product roadmaps characterize the product launch path between product versions and modifications, platform use and added functionality, often in relation to customer segmentation. At best, product and technology roadmaps are interlinked, and based on market forecasts, component supply, and end-user needs. To ensure the correctness of the roadmaps, they should be designed in co-operation between the different stages of R&D [Betz, 1993].

Product strategy in terms of which products to develop, how and when has a direct impact on the portfolio of projects. Particularly, the balance and timing of activities is dealt with through project and portfolio management practice. Fig. 5.5 illustrates the connection between product management and project portfolio.

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Challenge of aligning R&D with business objectives

Project, resource and product management have provided excellent ways to improve the efficiency of R&D. However, they do not offer solutions as to how all activities together contribute to business objectives. A more strategic perspective to R&D activities is needed, as well. Strategic management of R&D strives to align a company’s product development, research and technology strategies with the business goals of the company. The company’s top management normally states demands and expectations towards R&D strategy in its objective setting. R&D strategy includes vision, objectives and goals for R&D activities. It may cover, for instance, choices on: total R&D investment; which technologies and products to focus on; which technologies and products are developed inside the firm; and where subcontracting and alliances are utilized. R&D strategy should be created based on the capabilities of the company as well as its environment and the resources available elsewhere [Dumbleton, 1986]. R&D strategy implies decisions on how to allocate the resources within R&D. This can include determining desired balance between basic research, applied research and product engineering; setting priorities across technology areas; and identifying priorities across product categories. The choices are always influenced by the current allocation of resources to projects, and changes may imply the need to modify the entire portfolio, and technology and product roadmaps. New strategy may require setting new criteria for selecting projects and new goals for projects. Fig. 5.6 illustrates the hierarchy and responsibilities in strategic R&D decision-making. Implementing the strategy in projects is a difficult task since the number of projects may be high and there may be many decision-making layers between the actual project work and strategic R&D management. This is why we need to look at projects more holistically, from a strategic viewpoint, as portfolios. Project portfolio management aims to align the projects and their goals with strategy. It also aims to link the different management approaches in a company by bringing a holistic view on all operations and their management. The most important of the different management approaches were discussed earlier in this section. Poor methods for strategic alignment of projects have been identified as one of the root causes for problems in R&D (Fig. 5.7). Managing projects as portfolios could be a solution. It should be considered in competitive business environments where mere effective project management of single projects does not suffice.

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Project portfolio management helps companies to master the right number of projects and of the right size, select the best projects, improve performance in projects and thereby ensure that more projects succeed, cycle times get shorter and profit is increased. [Cooper, 2000] Research and literature in project portfolio management has recently increased [Dye, 1999]. This increasing number of studies introduces new tools and methods to link projects with the strategic business objectives of companies. However, current portfolio management approaches introduced in the literature try to encompass simultaneously all types of R&D activities. This is somewhat simplistic, knowing that strategic decision making is heavily dependent on the context, situation and even managers’ characteristics [Papadakis, 1998]. As the different stages of R&D all have their special nature, we propose that research, technology development, and product development need differ-

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ent approaches for project portfolio management. Other situational factors should be considered as well [Martinsuo, 2001]. The following sections first take a closer look at the different contents and methods of portfolio management and then proceed to inspect the implementation of project portfolio management in the different stages of R&D.

5.3.

5.3.1.

Project Portfolio Management

Project portfolio management as a mature way to manage a business

While traditional project management is focused to optimizing and managing the results of single projects, project portfolio management concentrates on the entire collection or a subset of projects in the organization. Project portfolio means a collection of projects carried out in the same business unit sharing the same strategic objectives and the same resource pool [Dobson, 1999; Elton, 1998]. Typically these resources are scarce, and there are more project ideas in the company than it has resources for [Archer, 1999]. These two issues make portfolio management both challenging and worth implementing. Project portfolio management is particularly relevant in the R&D environment where the company’s strategy is operationalized in the form of products, and the building blocks for the future are established. Portfolio management offers a more mature way for project-oriented organizations to manage their operations. Fig. 5.8 is an illustration of how the maturity of business management in project-oriented organizations evolves. Portfolio management offers the means for truly managing the business through its operative units, the projects. Portfolio management emphasizes that projects should not only be evaluated separately but also in the context of the whole portfolio since they very seldom are independent of each other [Ringuest, 1999; Archer, 1999]. The dependency between projects can deal with resources, goal setting, or timetables. Managers can utilize portfolio management methods in considering what is possible in terms of capabilities, and what is demanded by company’s strategy, mission and vision [Hutchinson, 1998]. In other words, portfolio management deals with balancing strategic intent and competencies. Additionally, project portfolio management helps in achieving the right balance and mix of projects against different objectives. It also offers a means to maximize the value of the portfolio [Cooper, 2000]

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To function both effectively and efficiently, portfolio management requires that the strategic direction of the organization be quite well elaborated. Furthermore, the processes for managing individual projects should be in place before starting to implement portfolio management and considering the interactions of multiple projects.

Even though implementing portfolio practices can be difficult, the results gained in companies that have started to implement it are very positive. For example, Weyerhaeuser [Comstock, 1999] has been using a portfolio decision type model already for some time, and has reported the following benefits: Researchers and project managers are more business-oriented Effective use of technology assessment has improved the understanding of the impact of external change to the company and new core research projects have resulted from this. Increased involvement of businesses resulted in more project ideas Ability to measure the success.

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These benefits can bring considerable value to the company, which makes implementing portfolio management an interesting option. Traditionally, project portfolio management is related to the management of internal projects and therefore it is well suited for R&D. However, the principles of portfolio management can also be implemented in delivery or subcontracting project portfolios.

5.3.2.

Project portfolio management process

Project portfolio management is a dynamic decision process aiming at updating and revising the list of active projects in the organization. In the literature, there are a few examples of portfolio management processes used in companies [Cooper, 1997b; Spradlin, 1999] as well as at least one theoretical model developed by Archer and Ghasemzadeh (1998; 1999). An R&D-oriented modification of the Archer and Ghasemzadeh framework has been developed in an R&D environment and presented by Aalto (2001), illustrated in Fig. 5.9. Aalto’s (2001) version of the framework emphasizes the importance of the early stages of portfolio management: ideation,

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idea screening and further development of ideas. After opportunity screening, individual projects are evaluated. This leads to a prioritized list of active and new projects. After evaluating projects against several criteria, the portfolio is visually modeled and the balance regarding different objectives and parameters is ensured. The final decision regarding the portfolio can be made, which means selecting the projects to be implemented or continued, as well identifying projects requiring acceleration, killing, or de-prioritizing. Additionally, resources are allocated and reallocated to active projects. If the adjustments to the portfolio are considered large, it may be useful to return to the previous phase of the framework to recalculate new portfolio parameters. The process is characterized by uncertain and changing information, dynamic opportunities, multiple goals and strategic considerations, interdependence among the projects and multiple decision makers and locations [Cooper, 1997a]. While the framework does not illustrate all the linkages of portfolio management to the other processes in the company or take a strong stand on the tools and measures, it provides a good general illustration of the main phases of portfolio management. To some extent, the system is always company specific and therefore a detailed all-purpose process would be impossible. The project portfolio management process is closely linked to ideation and the stage-gate process of project management. All decisions are influenced by the organization’s strategy in the form of objectives, methodologies and resources. In their article, Archer and Ghasemzadeh present some propositions on portfolio management practices. The model by Aalto (2001) largely agrees with the propositions and develops them further. Among the most important assumptions is that implementing portfolio management is very difficult without: well-planned and clear strategic objectives; fitting the portfolio practices to the other existing management practices and organizational culture; and management commitment through easiness and minimal time requirement of decision-making. The basic phases of the portfolio process, i.e. pre-screening, individual project analysis, screening, optimal portfolio selection and portfolio adjustment, require that good project management practices are applied to individual projects. There should be milestone or gate evaluations of the projects and the organization should be able to successfully complete the projects that have been selected to the portfolio. An example of a project management process was presented in Section 5.2. Different options for integrating project management process with portfolio management have been presented in Cooper et al. (2000) and Aalto (2001).

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Responsibilities in decision making

An important ingredient of portfolio management are responsibilities. The responsibilities regarding decision making, project management and steering and other tasks should be defined and communicated with everyone involved in the process. Examples of ways to define responsibilities in strategic R&D management are presented in the Fig. 5.10-5.11. Fig. 5.10 shows what kind of roles and responsibilities different personnel groups have at the different stages of portfolio management in HRB Systems. Identifying personnel groups’ roles as part of the portfolio process is especially useful in demonstrating interdependencies and potential bottlenecks during the process. Fig. 5.11 shows how Weyerhaeuser has divided tasks across the different organizational levels. Instead of process, the focus is on management groups and their roles with respect to the portfolio. This kind of a hierarchical pres-

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entation can be considered useful especially if a systematic portfolio process has not been defined or the portfolio is very dynamic. Project portfolio management related responsibilities include project management, strategic and technological project steering, project evaluation, project selection, project reporting, deciding on the priorities, and participating in certain decision-making forums among other things. Moreover, communication is an important responsibility for all of those participating in portfolio management. When assigning the responsibilities across different stakeholders, the competencies and availability of each decision maker should be considered. For example, when making decisions on technologies to be used, people with understanding on the limitations related to the specific technologies should be present or their understanding should otherwise be utilized. People should be informed about their responsibilities and they should be given the necessary insight to the field so that they can take care of their responsibilities. For example, people participating in analyzing portfolios based on different tools should be informed on how the tools work and what they are for. In general, when making decisions it is very important to have the right people present. This means that certain people must be present while others should not be present. Remembering both aspects, making sure that important people participate and unnecessary ones do not, is very important [Pasmore, 1997]. Yet, it is possible to ask the opinions of other people that come from different organizations, even if they do not participate in portfolio decisions. Decisions that influence other organizations can especially benefit from earlystage co-operation [Pasmore, 1997].

5.4.

Methods for Project Portfolio Management

A variety of methods and practices are available for the different phases of project portfolio management. At best, project portfolio management can leverage or complement the methods used in project management, strategy process, and general management of the organization. The following chapters introduce some alternative methods for the main phases of portfolio management and discuss what is important in each of the stages.

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Ideation and opportunity screening

Project portfolio management starts with ideation and screening for opportunities. There are several methods for generating new ideas and solving problems. These include, among others, brainstorming and morphological analysis. A more thorough list of the techniques is presented in Aalto (2001), with more detailed descriptions by Dumbleton (1986), Souder and Ziegler (1988) and McAteer (1997). A major issue for R&D organizations is whether idea generation and opportunity screening is systematic or not. Effective portfolio management leans towards systematic approaches where strategy-based ideas for new projects are screened at regular intervals. However, new ideas may come up at any time, and their implications to the portfolio may need to be considered outside of a formal portfolio cycle. To get the best results, companies should not only utilize proper ideation techniques for their business but also guarantee that all relevant information is considered. Efficiency of idea generation can be promoted by utilizing formal external information sources and channels on market trends, potential product ideas, and science and technology trends [Betz, 1993]. It is equally important to understand the customer needs and translate them into technology requirements and challenges. Additionally, the atmosphere within the company should be open and the ideas must be further developed to make full use of internal knowledge and capabilities [Souder, 1988]. Beyond naming ideas, the ideation and screening phase should also further develop ideas. The ideas should enter the actual portfolio evaluation phase only when the necessary research for the idea’s feasibility has been conducted. This is a good example of how project and portfolio processes are linked: the first, preparatory project milestone should not be passed unless the screening phase of portfolio management process has been completed.

5.4.2.

Project evaluation

After finding the best new project opportunities, the identified opportunities and on-going projects are evaluated and scored against defined criteria. Both the new opportunities and on-going projects should occasionally be scored against the same criteria to ensure that the results are comparable. Finding the right scoring criteria for R&D projects is critical for the success of portfolio management. The criteria should be suitable to the organization and its strategy, and they should be somehow measurable and comparable. The criteria should also be such that they enable taking along all the different kinds of projects into the portfolio decision process since projects compete for the same scarce monetary and human resources [Cooper, 1997b; Stevens, 1997; Cooper, 1997a]. The evaluation of the projects should not be

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constant but rather concentrate on certain milestones in the projects [Cooper, 1997b]. Of course, if the company’s strategy changes substantially between the evaluations, all the projects should be re-evaluated regardless of their stage.

Technological newness, value potential, and probability of success are examples of possible evaluation criteria, more of which can be found in the literature [Miller, 1999; Tipping, 1997]. Deciding upon the organizationspecific criteria or estimating their value may be very difficult [Henriksen, 1999]. For example, estimating the probability of success of projects may re-

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quire taking into account alternative uses of new technology, potential supply problems, and available skills or problems in partnerships [Tritle, 2000]. The persons scoring the projects should be gathered together for the evaluation purpose and they should represent the stakeholders involved in the specific R&D portfolio [Miller, 1999]. With the help of clear guidelines, everyone can evaluate the situation with similar scale and with less bias [Tritle, 2000; Van Arnum, 1998] and people in the different projects can themselves analyze and score their project regarding the different criteria. To make the evaluation as non-biased as possible, the criteria and tools should be clear and objective, and it should be ensured that right and good data is available for the evaluation [Stevens, 1997]. This means that, for example, if the criterion is probability of success, it should be evaluated on a well-defined scale, an example of which is presented in Fig. 5.12. Tools typically used for evaluating individual projects are numerical, but they are not necessarily enough for portfolio-related decision making. Numerical tools include Expected Commercial Value (ECV), Productivity Index (PI), Rank Ordered Lists and different kinds of scoring models [Cooper, 1997a]. The last two succeed better than the first two in comparing different factors simultaneously [Cooper, 1997a]. More qualitative, descriptive strategic objectives can be transformed into measurable and comparable values by using a list of questions [Hall, 1990]. It is also possible to divide a criterion into subcriteria and hereby estimate the magnitude of the criterion. Subdivision also forces the evaluator to think about all the aspects of the specific criterion, which is very useful, too. In addition to the measures presented above, some companies use, for example, Net Present Value (NPV) and Return on Investment (ROI) to rank projects. These tools offer a very limited perspective on profitability of the project since estimating returns in the long run is difficult and the estimates are very often uncertain [Cooper, 1997a; Stevens, 1997], especially in longer term R&D activities. Some of the numerical values and strategic estimates can be built into project documentation, to make scoring easier.

5.4.3.

Balancing and prioritization

Business objectives and strategy should define an ideal balance and priorities for the R&D project portfolio. For example, if the company has a strategic goal regarding high-risk investments, it should also utilize risk taking as one scoring criterion. Other examples for balancing and prioritization dimensions are probability of success (technical and commercial), financial reward, research area, time scope, technology/business maturity, and aimed technology change [Stevens, 1997; Cooper, 1997a]. When screened and scored by

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some or these criteria at evaluation stage, the interdependencies or the projects and the balance of the entire portfolio can be analyzed and improved. The best tools for balancing are different kinds of matrices, which visually present the different characteristics of projects together and demonstrate their strategic alignment. Graphical presentation also enables taking into account interrelations in projects regarding e.g. timing, resource sharing, performance targets, commercial and market interactions, and technical risks [Howell, 1998]. Matrices can be created based on the different criteria that were used in evaluating the individual projects by presenting the different criteria on the axes of the matrix. The matrices used for balancing are quite often variations of the BCG matrix (Fig. 5.13), GE/McKinsey matrix (Fig. 5.15) or the like (Fig. 5.14).

Since projects are often related to each other, it is necessary to be able to somehow display their interdependencies. One way to do this is to use bubble sizes, colors or shading, and so on. [Cooper, 1997a]. In general, there is always some uncertainty related to the portfolio decisions. Matrices can help in presenting the uncertainty of different criteria regarding different projects, for example with the help of bubble sizes [Tritle, 2000], and thus also make decision making easier. To find the best balance, one should preferably use more than one matrix. Then projects can be simultaneously evaluated against several objectives, as proposed for Third Generation R&D in Fig. 5.16 [Roussel, 1991].

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The advantage of different kinds of matrices is that they force the management to think about the limited number of resources: the sum of the bubble areas is constant and if one project is added, another project must either be terminated or its size decreased [Cooper, 1997a]. They also offer the decisionmaker a visual presentation of all the projects, their interdependencies, resource consumption and timing while also presenting their strategic importance. These are all matters that must be taken into account when making the final decision and comparing projects. In addition to matrices, roadmaps can also support portfolio selection. Although portfolio-balancing models are not perfect, their use can have many advantages, as long as the charts and maps are chosen carefully and not trusted blindly but used as decision-making support [Cooper, 1997a]. Project selection from a single project’s perspective also requires other analyses and considerations (see e.g. [Henriksen, 1999]). When developing project selection, one should bear in mind that project selection methods must be adapted to the existing organizational processes and that R&D managers should communicate more precisely the critical parameters and information needs of these processes within their own organizational context [Hall, 1988].

5.4.4.

Decision making

After mapping the projects into the different matrices or other graphs, decisions on the project portfolio are made. The decisions should, in addition to

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the use of various graphs and tools, be based on the business and technology expertise of key personnel. Formal tools should just be decision aids that make sure everything relevant is taken into account and that help compare the projects by presenting them visually. Negotiation, voting, scenario analysis and other interactive techniques may be used as well. When analyzing the portfolio and making the final decision, one should not only concentrate on measuring the current status but also actively monitor the variables influencing the development of the situation and possibly try to control them [Luehrman, 1998]. The final decision with regards to an individual project proposal or project can either be to start or continue with it unchanged, start or continue it with modifications, to freeze it, or to reject or terminate it. Project process handles these choices on milestone review or gates, while portfolio management may take the issues up at paced intervals or depending on strategy process, irrespective of what the project stage is. Fig. 5.17. shows the different choice and the respective actions required from management, while Fig. 5.18 illustrates how such decisions may influence the portfolio.

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The most difficult of the choice alternatives is the decision to terminate a project. However important these choices are, current project completion oriented reward systems do not necessarily encourage identifying losing propositions early. When a project or a project proposal is terminated, it is important to have alternative project proposals at hand to guarantee that untied resources continue to have meaningful tasks. When the decision to terminate a project has been made, it is important to complete all the documentation of the results so far. The documentation can then be used, for instance, to evaluate new ideas, or to return to the topic if the situation on the market changes [Miller, 1999]. Portfolio decision-making usually indicates the resource-committing milestone for projects, or other choices along the project process, depending on the project stage. It also sets a clear path for the implementation of strategy, but only if the criteria for the portfolio were designed to be based on strategy.

5.5.

Applying Portfolio Management in the Different Stages of R&D

In the previous sections, we have introduced various frameworks and methods for managing a project portfolio. Real-life experiences with organizations have shown that the ideal path of portfolio management is not always taken. Implementing project portfolios, as well as any other decisions in organizations, are highly dependent on the people and events involved (e.g. [Papadakis, 1998; Martinsuo, 2001]). Successful portfolio management requires expanding the scope beyond the company’s own technology and expertise, beyond the “easy and fast” projects, and past the ones merely with the most charming or persuasive presenter. Developing good project selection and termination criteria should be emphasized, as well as good communication, and adaptiveness to strategy [Stevens, 1997; Verish, 1998]. Moreover, management support and commitment is essential in portfolio management, as well as in product development in general [Pasmore, 1997; Bobrow, 1994]. The following sections discuss project portfolio management in portfolios of different R&D project types: product development, technology development, and research. Empirical case examples from the different types of R&D environments are included.

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Product development

Many recent studies have witnessed that successful companies do employ formal project portfolio management systems to align product development with business objectives [Cooper, 1997a; Cooper, 1997b; Cooper, 2000; Davidson, 1999]. Especially in the latter stages of product development, or product development as a whole, portfolio analyses and reviews have been well aligned and integrated with a project process and company goals. Responsibilities have also been agreed upon for making final decisions, with the help of organization-specific tools and techniques.

One example of a well-defined portfolio management system in R&D in the telecommunications area on product development is exemplified by Tellabs in Finland. We briefly introduce it below (based on [Hyppänen, 2000], also www.tellabs.com). In addition to review practice, link with project process, and clear roles and responsibilities, it highlights the decisive role of management. Tellabs helps the world’s leading communications service providers build tomorrow’s converged networks for voice, data and video. It designs, builds and services optical networking, broadband access and voice-quality enhancement equipment. Tellabs has 7,400 employees worldwide and is present

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in more than 80 countries around the globe. Product development at Tellabs covers most R&D stages, ranging from technology development to product engineering. At Tellabs, product development projects are often interconnected through common deliverables, resources or technologies. The projects use shared resources in globally dispersed teams. Due to the limited nature of these resources, it is crucial that projects focus on the right topics and lead to intended results. Therefore, product development project initiation is tightly linked with the business strategy. Tellabs portfolio process has three levels of decision-making. On the strategic level, decisions on prioritization are made. This requires management effort, negotiation and time, not so much information technology. The strategy is converted to a list of strategic projects that are prioritized based on predefined criteria. On the second, tactical level, methods are tailored. Here, it is about making sure that the day-to-day activities are proceeding as planned. The third level, the project interface management, is about deciding on the interfaces of the dependent projects and programs and assigning the product areas. Fig. 5.19 shows the three levels of decision-making as well as the review process at Tellabs.

Portfolio decisions are mainly governed by strategy, and planned product introductions. If projects are progressing according to plans, products and programs portfolio management group has no need to intervene after the initial decisions. Projects follow a phase-review process with regular reviews and decision points. If problems are noticed on the quarterly reviews especially between portfolio management gates 2 and 4, the project is taken to the portfolio management group.

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All new projects are initiated through the management group. The approach, therefore, is quite top-down oriented with the top management in a decisive role. Clarity of responsibilities, process, and review practice makes the system reliable and easy to steer. While functional with the smallish R&D organization, this systematic approach may not be applicable in larger organizations with more projects due to time constraints. Lack of periodic crossproject reviews, personnel participation and shared tools may indicate poor flexibility. The systematic approach of Tellabs fits well to shorter-term, goaloriented product development portfolios where reliable implementation is the key objective.

5.5.2.

Technology development

Decision-making literature proposes that the more uncertain and less controllable the environment, the less likely will formal decision support be of help [Allaire, 1989; Eisenhardt, 1992; Martinsuo, 2001]. Political and structural methods may be more appropriate, or formal methods may be supported with other systems. Therefore, one should not follow the frameworks too rigidly but instead use them, especially in making sure that the right issues are considered and as a way to communicate the situation to all stakeholders. It is possible that mid-term technology development portfolios cannot be as formally steered as more short-term product development. The case of Delta [Aalto, 2001] is an example of business-oriented technology development where project portfolio covers a majority of activities, and is strongly tied to general strategy and project management processes, but excludes more loosely planned assignments. Delta (an acronym) is a technology development department of an international mobile communications company, responsible for medium term applied R&D. The organization consists of a few laboratories, each of which is divided into teams. Each team represents one technology competence area, and the size of a team varies quite much. Sometimes teams are also divided into sub-teams to help co-ordination. The organization has three kinds of activities: competence-centric projects, cross-competence programs, and small or continuous R&D assignments, where projects represent a majority. Cooperation between different teams and laboratories is not very common. While this might sound hierarchical, in reality the organization is fairly informal and communication is open. Delta has an established stage-gate project process for project management (Fig. 5.20). Project portfolio process has not been specified, so far. Delta management has identified a need to focus on the right ideas and projects, and possibly cancel or postpone less important activities early. Therefore, Delta

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examined how it could better align projects with strategy: choose the right ideas to pursue, implement projects well, and terminate activities early, if needed.

New ideas enter Delta’s project process in a fairly informal manner: they are discussed within and across teams, their feasibility is explored, and if considered beneficial, a project is initiated. Project generation may therefore depend on the intuition, enthusiasm and sales capability of a person rather than the project’s suitability to Delta’s strategy. Technology and product roadmaps and other material are used as information sources to some degree, but only project by project. For Delta, the potential political agendas in project generation signified a need to establish a more systematic review procedure for the starting phase of projects, and better definition of roles, criteria and support tools in the decision making process. At the start of the project, resource allocation decisions require that the projects be compared to ongoing efforts and available competencies and resources. Due to the competencies of dedicated specialists in the teams at Delta, there is a danger of focusing too much on the past and internal competencies, and not enough on the future and all available resources. In Delta’s

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case, this appeared as a need to build more flexibility into the organizational structure, learning to cross the boundaries of competence areas and utilize external resources better. Projects are not regularly put on hold or cancelled, and there are no clear criteria for project termination. While projects compete for the same resources, employee turnover, wrong timing, or location-specific strategies may determine cancellation without attention to the business importance of the project. In its dynamic business environment, however, Delta acknowledged the need for rapid adjustments in the activity portfolio, sometimes by crossorganizational resource arrangements and sometimes by tough choices on project postponement or termination. To better align projects with strategy and business interests, Delta concluded three practical suggestions on its project portfolio management. Firstly, clarification and communication of unit-level strategy was considered necessary for promoting ideation in the right fields, and better grounding ideas for new projects. Secondly, a periodic portfolio review was proposed, to maintain strategic alignment and portfolio balance also in the future. Thirdly, several important portfolio criteria needed to be included as part of the stagegate project process and its documentation. Hereby, the well-accepted project process could be utilized, and the strategic feasibility of all projects could be examined with minimal effort. By these means, Delta could maintain its culture of openness and informality while at the same time gaining more benefit from established and accepted project and business strategy processes. This balance seems appropriate for the business-oriented mid-term technology development.

5.5.3.

Research

Corporate research is often characterized in terms of creativity and science, even chaos. However, in an organizational environment some transparency to the portfolio is needed, as well as strategic linkages. In research, it is especially difficult to develop tools that take into account all the constraints and interdependencies as well as all other relevant issues. It has also been noticed that the implementation requires continuous effort and commitment from the management to use time in developing the practices, which can sometimes be very difficult [Comstock, 1999]. The portfolio management system of Nokia Research Center (NRC) has been described by Kilpi et al. (2001). The article highlights interactions between business units and corporate research, in other words the influence the client should have on the activities of the research organization.

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Nokia Research Center (NRC) is the corporate R&D unit of Nokia. The research center is located on ten sites in seven countries and employs over 1000 people from 40 nations. NRC is organized on a competence basis as seven laboratories. NRC conducts its activities as projects of varying sizes. A majority of the projects concentrate on a specific technology area within one laboratory, but cross-disciplinary projects exist as well. The role of NRC is dual: it should maintain and develop the company’s core competence while simultaneously seeking and exploring new business opportunities and competencies, that may be relevant to the firm. The process of new project generation, planning and resource allocation at NRC has evolved to its current format over the past 15 years. As the process has developed over time and is strongly influenced by the growth and culture of the organization, it is unique. Three of the distinguishing features of NRC’s portfolio management system are its interactive nature, different sources of funding, and the dynamics. To guarantee that research is targeted to topical business needs, Nokia’s business units fund about two thirds of NRC’s activities. They hereby actively participate in steering the research portfolio. NRC–business unit interaction is built into the portfolio management process in distinct yearly phases of vision creation, strategy sharing, project and portfolio proposals, funding negotiations, resource allocations, and portfolio decisions. Personnel at different levels of NRC and business units are involved in the process with different responsibilities and roles. Project process takes place parallel to the portfolio cycle. While business units participate in steering the projects, they may influence the content and direction of activities throughout the duration of the projects. Due to the regular portfolio cycle, projects may well be terminated or closed if new, more important ones come up in the same competence or strategic focus area. Some corporate and external funding is allocated to such longer term and strategic projects that are not, yet, within the scope of business units in terms of content or timing. Corporate funding, thus, has a compensating role compared to funding in more short-term business-oriented business units. Since this third of the budget is very flexible, it can also be used to balance the effects of business trends on research: saved for a bad day if business units need extra resources or put into full use when business units cut their subcontracting budgets. By having both business unit driven and corporate driven research, the portfolio aims to guarantee a strategic balance: covering the full timeframe, right competence contents, and results-oriented work continuously. Even if the portfolio is “frozen” once a year, its strategic alignment with changes in the environment is reviewed and adjusted upon need throughout the year. Changes are negotiated between the relevant NRC and business unit

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managers. As these situations do not follow any set pattern, they are dealt with in an ad-hoc fashion, largely relying on the leaders’ problem-solving, negotiation and decision-making capabilities. The portfolio of projects implemented may, therefore, aim towards a totally new strategic direction rather than implement an old strategy. This feature of portfolio management is illustrated in Fig. 5.21.

The portfolio management system has its drawbacks. It is not always elastic enough and in addition, it is time consuming and suboptimization remains a danger. Increasing the size of projects, defining steering and management responsibilities better, and refining the portfolio management process systematically are examples of how to improve the system. The dynamic and interactive approach, however, seems well suited to the complex and unpredictable technology research environment.

5.5.4.

Different practices

The portfolio practices in use in the case examples described above vary to some degree. While the development of portfolio is in progress in all of them, portfolio management maturity differs and so does the overall approach. While some of the differences may be explained by different corporate cultures or history, we anticipate that also the type of R&D efforts matter. The stage of R&D activities not only may influence the practices directly, but it has probably also influenced the type of people that work in the organizations. It is very likely that people in research can cope with and even desire more freedom where as people in product development are used to stricter practices and time pressure.

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The three examples support the statement in portfolio management theory that practices are highly dependent on the organization. For example, while Nokia Research Center has been able to successfully support Nokia’s business units, other organizations taking into use the same portfolio management practices would not necessarily benefit from them since the practices have evolved during several years and are very company specific. On the other hand, the systematic approach used by Tellabs would hardly serve the needs of a research organization.

5.6.

5.6.1.

Discussion

Project portfolio management in telecommunications R&D

Increasingly, projects offer an efficient means to manage R&D activities in telecommunications companies. Beyond project level, there is a need to integrate resource, product and strategy limitations and demands with project goals even across projects. Especially in large firms with established strategy and project processes, project portfolio management makes the strategyproject-connection possible and manageable. The operating environment of telecommunications companies sets high demands on their management practices. In such a dynamic industry, portfolio management likely provides a better, more adaptable solution for aligning activities than rigid organizational structures [Eisenhardt, 1999]. As the industry is slowly starting to mature, companies should pay attention to systems and practices that enable them to operate effectively also in the future. The portfolio of R&D projects today may well indicate what direction the entire business takes tomorrow. Therefore, the choices for conducting or declining certain R&D projects should have a close link to strategy. The development of project portfolio management practices in a company should start from examining and fine-tuning existing project processes and strategy. Additionally, necessary knowledge on the other relevant management processes should be acquired. When those things are in order, the definition of the tools, evaluation criteria and the actual portfolio management process can start. As the literature review in this chapter has demonstrated, there is plenty of information available on tools and methods for project portfolio management, primarily as support for decision-making. When adopting portfolio management, organizations should tailor the tools and criteria for their own

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needs, to guarantee organization-specific terminology and linkage to strategy. Additionally, they should either develop a portfolio process or build portfolio tools into existing management processes to ensure proper project selection and decision-making channels. Sometimes the quality of portfolios can be improved significantly simply by adding certain portfolio evaluation criteria to the gate review guidelines. The use of common tools and practices is encouraged to limit unnecessary power battles and politics in decision-making. Furthermore, enough effort should be invested to define strategy-based criteria for decision-making and build them into the portfolio management system. With the strategy, decision-making criteria and support tools in place, responsibilities and decision-making structures for portfolio management should be defined. This chapter gave some ideas on process-centered and hierarchical role and responsibility definitions. After these initial steps, it is time to try out project portfolio management through the stages of ideation and screening, evaluation, prioritization and balancing, and selection. A typical mistake is to implement a project portfolio process without ensuring the clarity of strategy and project process first. However, in such a case it is likely that taking up portfolio management only reveals the inherent problems in strategy or processes. The failure to commit decision makers can also be lethal to the success of portfolio management. Designing the portfolio management system interactively is an effective way to commit the key people. 5.6.2.

Propositions for project portfolio management in different stages of R&D

R&D strategy usually defines the overall balance and priorities between the different stages of R&D. Even if this were the case, project portfolio cannot necessarily be managed in similar ways across the stages in large telecommunications enterprises. Based on the examples from industry, both presented in this paper and in the literature, as well as the knowledge of managing different kinds of R&D activities in general, it seems that the different stages of R&D require different approaches. Arrow sizes in Fig. 5.22 illustrate the different degrees to which project portfolio is influenced through strategic forces and vice versa across the stages of R&D. On a general level, portfolio management methods and tools should permit more freedom in the earlier stages of R&D. Their usage should mainly be guided and encouraged, not necessarily enforced. With most matrices and graphs, one should settle with broad categories, even those being difficult to define. The definition of decision criteria as well as project categorization requires a lot of competence. In contrast, in the later stages towards product en-

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gineering, the tools should be well specified and clear. In later phases, numeric information is more easily available and more reliable which makes project evaluation and the use of portfolio tools easier. In research environment where the time span is longer and the uncertainty is greater, expert judgement, intuition and chaotic choosing can offer a good option for numeric decision-making. However, portfolio management can help the experts to make their decisions while also offering a good way to present status data and a good base for discussions.

One clear difference between the case examples presented earlier was the role of top management. In research, top management has merely an instructive role as the communicator of vision and strategy. Most ideas come from researchers who thus have an active role in strategy creation. In the later phases of R&D, the decision makers often represent top management, broad business understanding being the key requirement for decision-making. This is possible and actually caused by the large project size, lower number and higher influence of individual projects on the company’s success. As research projects are typically smaller, it is necessary for them to have less bureaucracy e.g. in project reporting. Along with shorter length of individual projects, in

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research it is possible to focus decision making on the early stages of portfolio management. The role of ideation, and therefore the importance of the earlier phases of portfolio management, is different in each R&D stage. Whereas ideation is the most important phase in research organizations, ideation can only partially fulfil the purposes of product specification in product development. In product development, it is technology and product roadmaps along with market understanding that guide the starting and goals of new projects. Fig. 5.23 summarizes the differences of project portfolio management at the different R&D stages. In addition to the type of R&D, the existing management process influences portfolio management practices and especially the speed and way in which they are implemented. To sum up, project management culture seems to lie deeper in the product development environment than in pure research organizations. This makes it easier for product development organizations to start building a portfolio management process.

5.6.3.

Conclusions and ideas for future research

Differences appear in the preferred nature of portfolio management practices in different R&D stages and organizations, but the basic prerequisites for portfolio management are valid for all organizations. These include a clear strategy and goals, in particular. Having the other basic R&D management processes, such as project management, in place is also important. Above, we concluded that different practices should be considered for project portfolio management in different stages of R&D. Whatever the stage is, portfolio management can significantly improve R&D performance by paying attention to doing the right things. Successful firms use formal portfolio management methods to align their activities with business objectives [Cooper, 2001]. However, we do not know enough about the applicability of such practices beyond large firms that have other than project-type activities, other primary strategy implementation methods, resource restrictions, or non-clear strategy [Martinsuo, 2001]. Clearly more research is needed on the factors that set requirements and influence project portfolio management in different kinds of organizations and business environments. This paper specifically looked at technology maturity or stage of R&D as a contingency influencing project portfolio management practices. Further research is needed to verify our propositions on the differences identified. As other future research topics, we suggest looking into the other contingencies. For example, projects at public organizations seem to have their own specific

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demands towards project portfolio management compared to private sector organizations [Martinsuo, 2002]. Portfolio size, firm size, stage of industry development (maturity) and competition, and organizational culture should also be considered as contingencies. Moreover, interactions of different portfolios need to be considered and better understood [Artto, 200lb]. Project portfolio management is a modern way to organize R&D management. Implementing it does not need to mean a radical change to existing ways of operating, especially if a clear milestone review process is already in place. It is rather about supporting personnel in their choices, implementing a more business-oriented mindset, and bringing strategic objectives closer to projects. When looking at the project portfolio management models in the literature, we could well conclude that portfolio management is an easy and straightforward way to improve a company’s R&D performance. However, even though the reasonable logic looks good on paper, it requires a lot of effort to be implemented. The barriers to easy implementation include the bias of decision-makers, attitudes of the personnel, the special nature of human resources, and the link with budgeting and business management. So far these constraints have not been discussed in the project portfolio management literature sufficiently. The influence of the constraints can, however, be mitigated and good results can be gained by planning both the practices and implementation well. Furthermore, well-organized communication plays a crucial role, especially in organizations like corporate research where authority depends on expertise and implementation of portfolio management requires each expert’s acceptance. As the field of portfolio management is gaining more attention both in industry and research, the topics of future research and development extend beyond tools and frameworks. For instance, managing change in project portfolios and utilizing portfolios to change strategic direction should be explored in addition to the portfolio’s role in implementing strategy. Portfolio management in company networks in the form of subcontracting and alliances is another potential research topic. Furthermore, Hamel (2000) has taken up the issue of innovation portfolios as a collection of R&D and venture activities. Managing the two different types of innovation activities within the same portfolio introduces another new challenge that should be considered in future research. While project portfolio management can improve project business maturity and performance, it alone does not guarantee future success even for correct strategy. The company must also have skilled employees doing high quality work, skilled project managers steering projects, a continuous flow of good project ideas, and an innovative environment. To balance the disciplines

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of portfolio management and freedom to innovate is one other concern for research (also [Foster, 2001]).

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Chapter 6 QUALITY IN HIGH-TECH PRODUCT DEVELOPMENT Antti Ainamo*, Pekka Järvinen**, Timo O. Korhonen**, Paul Lillrank** *Jaakko Pöyry Consulting, Helsinki School of Economics, and the University of Art and Design Helsinki, **Helsinki University of Technology

Abstract Quality management (QM) emerged in the century as a method to reduce errors and uncertainty in industrial mass production. The focus was on reducing variation in repetitive industrial processes and on fulfilling the requirements of rational market actors. At the innovative end of the modern high-tech environment, the basic assumptions of repetition and rationality will frequently not hold true. However, QM methods remain usable and useful at the routine end of the high-tech environment. By improving quality and success at the routine end they free up crucial resources for the frequent and rich communication that is required at the innovative end, thus improving the overall quality and success of the product or service.

6.1.

What is Quality?

Much of the development in QM was originally a practitioner-driven and methodology-oriented doctrine. Many of the taxonomies and formal definitions of quality remained for a long time vague, confusing, and, in some cases, even downright contradictory (Reeves & Bednar, 1994). Fortunately, this problem is now beginning to be a thing of the past. Over the past few decades, QM has evolved from being an airy fad into a well-defined body of knowledge. This was established especially in the 1990s in the codification of QM into ISO/GS9000 quality systems as well as in the quality awards, such 149

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as the Malcolm Baldrige National Quality Award (MBNQA) in the US and the European Quality Award (EQA) in Europe. As shown in Table 6.1, modern QM encompasses an integrated array of management principles, practices, and techniques.

Besides developing internal coherence, the QM doctrine has established links to a number of other management methods and principles, such as lean production, reengineering, customer relationship management (CRM) and gap analysis [Berry, 1991]. The principles, practices and techniques of QM are now seamlessly linked to other disciplines of industrial management forming the modern doctrine of total quality management (TQM). QM’s coming of age somewhat paradoxically shows how its practices are still traceable backwards for decades with the three outstanding characterizing dimensions: Quality as the conformance to requirements, fitness for use, and as an experience of excellence:

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1. Quality as the conformance to requirements. Assuming that quality requirements are reasonably well known in advance, quality is the relation between intended and the actual output. Deviations between intentions and outcomes are caused by the inherent variations found in the process inputs (such as material, energy, and labor) and the process conditions (such as resource allocation, production techniques, or factory layout). The essential phenomenon under study is the deviation from target values [Crosby, 1979].

2. Quality as the fitness for use. Quality is essentially an emergent outcome, determined by customers and users, rather than only being designed in from the start. Within this context, the management of quality must include a definition and formalization of how the emergent customer and user requirements and inputs will be channeled into quality outcomes during the process of adoption and use. The total process is a collection of systematic methods for capturing and articulating customer needs [Juran, 1992]. 3. Quality as an experience of excellence. Quality is a connotation of excellence, a sense of superior value, beauty, or style. Quality is sometimes very hard to articulate, but ‘you know it when you see it’ [Pirsig, 1974].

It has taken a long time for the QM doctrine to reach coherence due to its polarization at the two extremes: The first extreme, quality as the conformance to requirement, and as the fitness for use, underlines the importance of tractable and measurable quality control. This part of the QM doctrine made the following assumptions: At first, the producer strives to determine customer’s requirements and as time goes by, customer’s feedback, as well as selling figures, ultimately specify the fine-tuning of the successful product. At the other extreme, literature of branded consumer goods focused on the fact that assumptions of the user requirements and properties were often insufficient for high quality product or service design. The claim of the quality as an experience of excellence insisted that the quality should be the first and the foremost subjective experience of the product of service. Actually, it looked like the quality would be something so mystical and transcendental that its systematic analysis or management would rise beyond the capacity of a mortal. High-tech product development projects are risky ventures, in which product reliability and usability requirements are often not known from the start. They emerge in the close interaction between producers and customers

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and other stakeholders. Producers and stakeholders specify their needs as they gain experience about the product or service and learn what they require from the product. Using QM at the routine (production) end of the modern hightech product development frees up resources for the frequent and rich communication that is critically required at the innovative end. In the conventional technology, ‘historical QM’ is still usable and useful in much of its original form.

6.2.

What is High-tech?

Since the beginning of industrialization, new knowledge has been the driving force of economic and industrial development. In the first phase of industrialization in the century [Douma, 1998], the division of labor began to take place in the move from craft-based work to mass-production. During the second phase in the century, the focus shifted to the possibilities offered by the new sources of energy, such as steam, internal combustion engines, and electricity. The taming of these energy sources was a complicated task and required sophisticated management systems. Economic incentives replaced coercion, and smart new management systems replaced brute force. The new management systems and incorporated technological advances led to many new innovations, such as low-carbon steel and newsprint. Today, these high-tech products of the past are bulk commodities, in other words, the very opposite of the modern high-tech. This historical dynamics is typical for high-tech and leads to an important distinction not only between the past and the current high-tech, but also within the sectors of current hightech industries. Rather than the amount of product knowledge involved per se, the essence of high-tech is in the amount of new knowledge that is appearing, and coming applicable at the particular instant of time. This new knowledge is the cause of uncertainty in modeling complexity, failure to take actions, to keep up in time schedules and budgets, and in making intelligent deviations to production plans. Once the newness of knowledge is domesticated, there are no longer excuses for sub-optimal quality.

6.3.

How to Deal with the Inherent Uncertainty of High-tech

There have always been certain business environments with a profound level of uncertainty. Today, these environments can be found in such areas of modern high-tech as in mobile telecommunications, information technology,

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nano-technology, and biotechnology. As within the earlier high technologies, the determination of user requirements, acceptable margins of error, and appropriate process description do serve to reduce uncertainty, decrease errors, and improve process and product quality also in today’s high-tech. There are four fundamentally different sources of uncertainty in high-tech that call for a different flavor of QM: (1) Process description, (2) commercialization, (3) complexity, and (4) time management. Process description should explicate the source of uncertainty in the new knowledge domain. For instance, there is an inherent, larger uncertainty when entering a radically new knowledge domain, as into some research-intensive technologies. Product and process development problems may turn out to be insurmountable, promising pathways may turn into dead ends, and even promising solutions may fall flat for a reason that is left unknown. However, entering a radically new knowledge domain is rare in practice. Innovative individuals or organizations will typically be successful in this entrance only once or few times during the entire course of their life. This kind of domain shift requires, what Peter Senge (1990) calls ‘generative learning’ that is able to develop something essentially new by the virtue of cross-pollinating new scientific inventions as well as by using radical social discoveries.

6.3.1.

Commercialization calls for adaptive learning

Commercialization of development efforts is the second source of uncertainty. In order to attract customers, novel high-tech services and products should fulfill an existing or created need, provide more than the perceived value, and own a highly developed user interface. Marketers of high-tech products and services can meet the commercialization challenge by starting from the user scenarios that are inherently related to the high-tech products and users in question. (This is a part of the usability point of view as noted in Chapter 3.) They strive to point out the links between the extant contexts of infrastructure and usage, customer taste and requirements, and the properties of the products and services to be marketed. The associated creative linking calls for what Peter Senge (1990) defines as ‘adaptive learning’. This is a style of learning that is driven by the desire to recombine and apply known elements to lower the level of risk, in comparison to being content with the procedures, inventions or configurations that are all new.

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6.3.2.

Complexity calls for identification of simple building blocks

Complexity is the third source of uncertainty. Complexity as a phenomenon can be defined as a large number of activities, issues, actors and tasks that interact in a non-trivial way. The more activities, issues, actors, and tasks there are, the more inter-relationships there will potentially be. Dynamic complexity refers to the case in which these relationships are non-linear, have a lot of feedback, and involve more than a single time frame. In dynamic complexity, the links between cause and effect are not fully known, and effects may appear long after their causes. For example, changes in employment or promotion aspects of personnel policy may show up their effects after several years in unpredictable ways, as for instance in a shift in company’s core assets. A way to handle both complexity and dynamic complexity is to inspect and develop ways to break down the complex process and by focusing attention to the resulting sub-problems one by one. Identifying these simpler building blocks enables the inspection of a collection of separate, modular subsystems, and identification of their interfaces. Each one of these building blocks will then entail some new knowledge, but hopefully in a more manageable degree.

6.3.3.

Time pressures call for pacing

Time is an ever-important source of uncertainty. It results for instance price erosion, that is a constant threat in high-tech businesses such as manufacturing of mobile handsets, microprocessors, and development of drugs. Producers can expect to make money only during a narrow time window that will close as new competitors move in and prices start to fall. A good example can be found in mobile handset business: In the turn of the millennium, Ericsson and Motorola started to experience a significant reduction of revenues due to the delayed, important launch dates. In the same business, Nokia, and Samsung used time-based performance indicators, such as time-totechnology, time-to-production, time-to-market, and time pacing to strengthen their positions. In order to succeed under intense time pressures, a good idea is to foster predictability and a pressure-cooker environment. The objective is to make design team members to behave both speedily and confidently. Rhythm or pace of entry into new knowledge domains, complexity management, and commercialization ought to be at least loosely coupled. Fig. 6.1 summarizes the four sources of uncertainty in a schematic matrix, with our strategy propositions for their treatment. New knowledge domains

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are the most challenging to treat, while commercialization is the easiest. In these and in the intermediate situations, identifying the four sources of uncertainty, and differentiating and balancing between them helps to generate ideas, identify building blocks, adapt to the changing market situations, and pace product launches. When successful, this results fluent and effective entry into new knowledge domains, visionary management of complexity, orderly mastering of time pressures, and profitable commercialization.

6.4.

The Emergence of QM for the Modern High-tech Environment

Only seldom do generative and adaptive learning meet as dramatically as in a modern high-tech product development. It is an arena of violent collisions of investors’ and inventors’ visions, as well as the pressure of continuos organizational arrangements. However, as we have stated earlier, traditional QM has its roots in industrial mass production, and aims at systematic reduction of variation meaning uncertainty management. The difference between modern QM and traditional QM is best understood through a comparison of these two.

6.4.1.

Traditional QM

In their original form, all traditional general management methods were based on several rather vaguely articulated theories and rules of thumb. Some of the first proper theories were Max Weber’s theory of rational bureaucracy, Frederick Taylor’s principles of scientific management, and Henri Fayol’s

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engineering approach to organizations [Jackson, 2000]. These general management methods can be summarized as follows: a. the world is basically in order and the laws guiding it can be known b. progress is possible, desirable, and fully quantifiable c. the world is divisible into analyzable categories d. knowledge can be accumulated at the top of organizations e. human beings are reasonable and driven by incentives, and f.

the future can be forecast and planned.

Within this context, traditional QM became understood as a form of quality control. Most of QM still tends to follow the assumptions that all work is performed in processes and many of these processes exhibit quantifiable variation [Deming, 1994; Gitlow, 2001]. A process for, say, machining metal parts may aim at a target value of 12 mm for a critical dimension of a part. The actual dimensions produced will not in each and every individual part be exactly 12 mm. In some parts, the dimension will be slightly more and, in other cases, slightly less. Should the actual dimension fall beyond a given range of tolerance, say +/- 0.01 mm, the part will be considered defective, and eliminated by ‘quality control’. The control-oriented QM methods dominated well into the mid-1970s. That is when the Modernist age of seemingly unlimited progress ended. The “Great Divide” [Piore, 1984] in terms of QM was brought about by the oil crisis, the abandonment of the gold standard, and the liberalization of world markets. Similarly important contributions to paradigmatic change were the diffusion Japanese consumer electronics and automobiles in the American markets and personal computers, The Internet, and mobile telephony around the Western world. Despite of the new era, many aspects of traditional QM are still valid for many aspects of high-tech product development. For example, consider that with shorter developments times for a new product, there will still be a target date. Should the launch take place more than three months behind schedule, the project will be considered a failure. There will always be some minuscule differences from time to time that cause variation in both process and product. Within this context, the essential task of modern QM methods is still to see to it that processes and launch dates stay within their given tolerances.

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6.4.2.

157

QM in the modern high-tech environment

However, volume expansion to meet market demands means avoidably both price competition and differentiation in terms of quality, functionality, product variety, customer-friendliness, and service. The ensuing shift from sellers’ to buyers’ markets and improved communication capabilities has transformed management practices and philosophies. Management now focuses on quality in a new way, increasing customer choice, and providing variety based on flexible production systems and customization in terms of products that are mass-produced but appear innovative and unique to consumers. In today’s hyper-competitive world, variation is ever-present and multidimensions. It is not possible to replicate a process step in a mechanical fashion. For the sake of our argument, the word “modern” refers to an attempt to deal with situations and environments where the assumptions, principles, and tools of traditional QM do not work very well. Technology can be a cause and an effect, an independent as well as a dependent variable. Some high technologies will emerge as responses to perceived needs, such as high-speed railway technology as a response to airport congestion, while others seem to pop up as independent events, such as superconductivity. Management can be a spectator, in the passenger seat, or the driver of time pressures. The issue is that choosing between the available options can be a more immediate managerial task than the discovery of new options. A typical characteristic of a modern high-tech environment is the everincreasing abundance of possibilities. Every technological solution, say, broadband communications or a new generation of microprocessors, opens up more new possibilities than it closes, and raises new questions. Whether the technology is the chicken or the egg in the coevolution of technology and society is not a managerial issue. The modern high-tech environment can be described as follows: a. The world is partly chaotic and driven by unknown forces b. Progress can be defined in many ways and it is not wholly positive c. The world is made up of fuzzy sets that are not analyzable from one ob-

jective viewpoint (beauty appears to lie in the eye of the beholder) d. Knowledge and its accumulation have a life of their own (the applicable

knowledge and wisdom is not necessarily found at the top of a hierarchy) e. Human beings are driven by a variety of motives

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f.

The future forecast carries a lot of uncertainties - long-range planning gives way to flexibility and adaptability

Table 6.2 summarizes the differences between traditional and modern QM. There are more ways in which a high-tech service or application may not work or to provide services than in the case of a conventional service or application. As Sitkin and his colleagues (1994) have suggested, modern QM or TQM must have the focus not only at the aspect of technical control but also in the adaptive learning about customer requirements. For instance, customers may want to personalize their user interfaces individually, and producers will learn by realizing the property the customers want. What are called the high technologies increase the sources of uncertainty of the new knowledge domain and the complexity variants. By minimizing variation in every part of the process about emerging preferences where elimination is possible, predictability is increased, uncertainty is reduced, and increased control and learning are achieved. Elimination of uncertainty frees mental capacity and resources for learning new things; that is, for generative learning. The result is the cycle of control and learning as depicted in Fig. 6.2.

6.5.

Sequential and Repetitive Processes

In the 1950s and 1960s, Japanese manufacturers took the idea of continuous improvement very seriously. To this end, they successfully devised many innovative organizational arrangements, such as quality circles and policy management. Continuous improvement in the Japanese model of QM involved all employees. As Kaoru Ishikawa (1985), the father of the Japanese

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quality movement put it: “if standards are not revised every six months, it means that they are not taken seriously”. The Japanese model of QM was well suited to situations where there were ‘trivially many’ sources of poor quality [Juran, 1992].

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Even today, Japanese-style continuous improvement is a traditional QM method that is able to draw on workers’ experience and their common-sense thinking in order to improve the conditions of production and thus to raise productivity. However, the Japanese model reaches its natural limits when it makes processes fully programmable, fully controlled, and fully closed-off from external influences. In its highly developed state, continuous improvement has become a controlling apparatus that has fully eliminated variation that formed the bases for both adaptive and generative learning. Within this context, a fundamental aspect of the modern QM doctrine is its property to help managers to design organizational arrangements (crossfunctional management, teams, benchmarking, etc.) that facilitate learning in and between organizations, meaning creation of variation. Otherwise, all traditional quality methods are valid also in the modern QM in one form or another, but designers and developers need to carefully consider the degree they will want to execute them. An effective QM system will continuously scan for vital sources of new problems that may be treatable, but will not overkill problems that resist identification, analysis, and treatment. Sophisticated QM methods and tools, such as multivariate statistics and Design of Experiments (DOE), are often suitable for particular purposes. For more generic purposes, it is worth to revive a general emphasis on increasing understanding of the commonalties and differences of control, continuous improvement, and diverse kinds of learning. While the QM literature is not very explicit on this point, care should be taken to distinguish between three different kinds of processes related to traditional QM: sequential processes, repetitive processes, and interaction between the two.

6.5.1.

Sequential processes

Sequential processes include different steps, such as fuelling, loading, catering, and boarding an aircraft. Many administrative and sales processes are also of this type. The order, type, and configuration of each step and sequence vary from one process step to another. Each step is different (Fig. 6.3). Sequential processes are managed with the aim of making them more explicit and thereby predictable. Various types of flowcharts and checklists are used. For example, the punctuality of airline departures can be increased by listing the exact requirements of each step of the preparation process, allocating responsibilities to specified individuals, and measuring performance against targets. The reduction of variation and the explication of processes form the core of QM systems and models of excellence.

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6.5.2.

161

Repetitive processes

In partial contrast, repetitive processes consist of steps that are repeated in an identical fashion, for example the manufacturing of a batch of ten thousand components. For example, Statistical Process Control (SPC) is a method used to minimize variation in repetitive processes. Processes are brought under statistical control by eliminating process-external sources of variation, such as poor raw material or changes in temperature and humidity. When this has been accomplished, a process may still exhibit a significant amount of internal variation. When amounts of internal variation can be predicted, uncertainty can be reduced. Given a reduction in the internal variation of a step, the next step works with its internal variation. Finally, one works with variations across steps.

Usually a more exact practical theory of the process needs to be developed. With increased learning, commonalties are identified and unnecessary variation is reduced (see Fig 6.4: Repetitive processes). In metal fabrication, for example, there may be advantages to analyzing metallurgical properties in relation to cutting tools, rotation speeds, temperature, and, finally, all of them in combination.

6.5.3.

Interaction between sequential and repetitive processes

The modern QM should take into account not only the interrelating sequential and repetitive processes for increased control and predictability, but

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also to the diverse type of learning facing both the manufacturer and the customer in order to understand the product appropriately. With regard to the conformance to requirements, a necessary assumption is that the production targets should be known before production. With regard to fitness for use, it is however a typical feature of high-tech, that customer’s need vary in great deal from customer to customer, and thus there exists a demand for high degree of product customizability. When customers can, as traditional QM assumes, articulate their needs for one seller, they can do the same also for a competing seller [Slater, 1998]. The result is typically that all sellers provide the same quality and features. Price competition ensues. It is not always wise to treat quality as conformance to requirements or fitness for use with only a control- or a variation-reducing frame in mind. Often it is better to accept some of the inherent uncertainty regarding interactive processes between producers and consumers, with the aim of generating understanding about future products and processes.

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Customers may be opportunistic, ignorant, or calculating. They may not know what they want. Customers are, as Hamel and Prahalad (1994: 99) put it, ‘notoriously lacking foresight’. To this end, in what can be called a ‘service-marketing’ approach to QM, Berry and Parasuraman (1991) and Grönroos (2000) have developed tools such as gap analysis to identify and analyze gaps in perception between producers and consumers. Making a distinction between the typically sequential value chains of producers and repetitive routines of users opens up possibilities for management to improve their company’s performance (Fig. 6.5a: Interaction building and Fig. 6.5b: Interaction between sequential and repetitive processes)

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6.6.

The Practice of QM in the Modern High-tech Environment

The modern high-tech QM, in many ways, different from the traditional QM, established during the emergence of mass production. However, whereas QM of those by-gone days effectively modeled and controlled repetitive processes, QM in the modern high-tech environment appears to suite in a very similar fashion also for identifying, modeling, and eliminating unnecessary variation. At the same time, the biggest managerial challenge is to be able to understand how the processes actually interact. The question remains: “Does the QM map at least the repetitive aspects of high-tech The answer starts with ‘Yes, but...’ and ends by generating several solutions especially regarding the management of a modern high-tech company.

6.6.1.

Team effort and resources for innovative work

The first ‘but’ comes from the nature of high-tech endeavors. The lonely inventor with extraordinary creative capabilities may occasionally spearhead innovative work. However, nowadays inventions are predominantly generated and finalized by intense group work. In order to be commercially and technically applicable, the innovative ideas that have been generated need to be worked on, tested, expanded, and verified. Most of the processes of information gathering, assessment, and comparison in a modern high-tech environment are routine processes. Generative learning must be backed up with a sizable amount of adaptive learning. There will be ample room for QM for many tasks even in the most creative environment. QM can contribute, by standardizing and stabilizing repetitive processes, to the freeing up of resources that can be spent on more innovative work.

6.6.2.

Qualitative methods and multi-tasking

The second ‘but’ relates to the nature of high-tech products. Levitt (1980) presented a multi-level product concept in his seminal Harvard Business Review article. The ‘generic product’ is the core benefit to the customer, i.e. the basic product concept and functionality, such as a mobile handset having the function of allowing mobile communication. The ‘expected product’ is what the customer considers the minimum acceptable benefits and performance standards, such as the minimum acceptable failure rate. The ‘augmented 164

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product’ comprises benefits that a customer may never have considered, i.e. benefits that satisfy latent needs, for example the status value associated with a smartly designed handset. To find out what the ‘augmented product’ might involve, softer, qualitative methods are applicable. Finally, the ‘potential product’ includes everything that might be done to attract and hold a customer, such as brand identification and membership clubs and associated services. QM, with its uncertainty reducing control focus, has to give way to an assurance that the ‘expected product’ fulfils expectations, and that the ‘potential product’ includes the kind of responsiveness required of a high quality product or service. There is a need for multi-tasking across the generic-core, augmented, expected, and the potential product.

6.6.3.

Networks and the recombination of learning and control

A way to deal with complexity and uncertainty on a broader level is to create and nurture social and organizational networks. Modern QM literature emphasizes that supplier relationships and partnering may evolve into social and organizational networks that combine the flexibility of market relations with the stability of a hierarchy. In such a network, responsibility is distributed among a number of specialized actors who are constantly in touch, adapting to changing situations and learning together. Several small boats can change course faster than one big ship. Uzzi (1997) classifies social and organizational networks into three basic types. The first one is only slightly different from traditional subcontracting, in which price, required quality, and delivery time form the minimum acceptance criteria and the foundation of the relationship. Cooperation and even trust may emerge as relationships mature, but deeply institutionalized forms of networks are lacking. The second type is totally based on the cooperation of trusted and established partners and competitive conditions are seldom directly considered. It is important to note that this second type of network has always a core company taking care of the customer interface, and, through this, the quality requirements of external customers. The third and final type of a network is an intermediate position between the two extremes. This third type, called the ‘integrated network’, includes both competing one-off suppliers and fully trusted partners. Various types of institutional arrangements and trust levels emerge as relations in the integrated network improve.

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6.6.4.

Integrated networks and the leveraging of core competence

Traditionally, outsourcing meant the spinning out of non-core activities to independent suppliers and partners. This allowed companies to concentrate on their core competencies. Due to uncertainty and unexpectedly changing conditions, the need for heavily explicated contractual relations, such as supply contracts with all conceivable occurrences covered by legal fine print, are increasingly giving way to trust-based relationships. In integrated networks, where the relationships between partners are both institutionally structured and managed with fiat, trust between any combinations of partners in the network is as an essential element, continuously reified and created. From a quality perspective, the four fundamental elements of integrated networks are the initial conditions, the negotiation process, interaction, and market tests. First, the initial conditions surround an exchange, and include demographic and institutional characteristics, reputation, and the prior expectations of the parties to the exchange. Second, the negotiation process is carried out in a way that further enhances trust. Third, once a relationship has been established, partner interactions under various conditions take place. Expectations are formed, circumstances are anticipated, and partner exchange information in the relationship of mutual good is exchanged. Finally, external events, systemic, corporate, and individual, put the integrated network subject to constant tests of the market and emerging possibilities, opportunistic behavior of the customers, subcontractors, and partners [Arino, 2001; Hargadon, 2000].

6.7.

Final Words

QM is one of the major management innovations of the 20th century. It has provided a systematic methodology for dealing with errors in production, placing emphasis on customers, and involving employees in continuous improvement, and, to this end, has devised various systems, methods, and models of excellence, participatory approaches, and organizational arrangements. Traditional QM, as we have seen, has been based on the assumption of repetitive processes and rational market actors. The modern high-tech environment is characterized by innovation and intense risk-taking under harsh conditions of uncertainty and time pressure. The assumptions of the traditional QM are challenged, and it seems not to work across the board. Especially, to apply the traditional QM to the innovation-intense processes of high-tech would not be wise. However, In the modern high-tech environment, traditional QM methods, approaches, and concepts

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can and do find new applications. Although high-tech is often seen as an area of rule-breaking creativity, it is nevertheless based on a substantial foundation of supporting processes that are not as themselves necessarily uncertain. There are no reasons to overlook the traditional QM methods of uncertainty reduction through standardization and general reduction of product variations. Also, teams were already an established method in traditional QM. In the modern QM integrated networks are partnership-based ways to reduce uncertainty and improve quality. The very speed and flexibility sought for in integrated networked structures comes from the replacement of stodgy contractual relations with trust-based relations. Therefore, the integrated networks are a partnership-based way to reduce uncertainty and improve quality. The future of QM, we believe, is tied to the concept of new and emerging ways to define, measure, and manage networks, their interactions and quality. In the modern high-tech environment the quality of knowledge and its exchange across highly variable domains becomes a crucial issue. The recent rise of integrated networks and partnerships as experienced in Finland, is partly a reaction to the failures of previous central planning to handle increasing amounts of new knowledge and complexity of the modern, global, knowledge-intensive environment. A market composed of innumerable links between buyers and sellers manages the task much better than central planning. Integrated networks and partnership are not akin to free markets in which anonymous traders deal with each other at arm’s length. Rather they can be compared to a regulated market that operates within a framework of enforceable institutional rules of the game. These rules do not necessarily have to be explicit or legally defined. They may consist of elements such as shared values, mutual trust, and traders’ honor; a handshake is as good as any signed document - a tradition already long evolved in the East. The regulation of quality in an integrated network is not an element that emerges as a matter of fact; it requires conscious management. Rather than only one rule of the game, integrated networks have many, mutually reinforcing self-regulating mechanisms in place. Integrated networks and partnerships are not fully self-organized or anarchistic; other players swiftly remove a player who violates the rules of the game or breaks the trust [Uzzi, 1997]. The value of trust is continuously shaped and tested particularly by market tests, possibilities for opportunistic behavior, and unanticipated situations that none of the partners at the core of the integrated network could have planned or prepared for. Sometimes, however, these conditions may require managerial fiat in terms of negotiation, interaction with other players, and intentional testing of market for ‘information quality’. While the concept of ‘information quality’ is still elusive [Lillrank, 2003], it is beginning to be apparent [Wigand, 1997] that both reliability integrated

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networks and partnership are considerations to be taken seriously by any hightech manager. To only decrease variation and increase reliability in terms of fulfilling requirements with traditional QM methods (principles, practices, and techniques) will not suffice in the modern high-tech environment. The constant negotiations and interaction in the integrated networks of the modern high-tech environment makes us believe that the key to overall quality and success in modern high-tech environment is to foster also the validity of information, and not only its consistency and reliability. This will be way to systematically analyze and manage quality also in the modern high-tech environment, despite the many sources of uncertainty.

REFERENCES [Arino, 2001]

Arino A., de la Torre J. and Ring P.S.,“Relational Quality: Managing trust in corporate alliances”, California Management Review, vol. 44. No 1, Fall 2001.

[Berry, 1991]

Berry L.L. and Parasuraman A., Marketing Services. Competing Through Quality, The Free Press, New York, 1991.

[Crosby, 1979]

Crosby P.B., Quality Is Free - The Art of Making Quality Certain, New American Library, New York, 1979.

[Cusumano, 1998]

Cusumano M. and Yoffie D., Competing on Internet Time, The Free Press, New York, 1998.

[Deming, 1994]

Deming W.E., The New Economics for Industry, Government, Education, 2nd ed., Massachusetts Institute of Technology, Center for Advanced Educational Services, 1994.

[Douma, 1998]

Douma S. and Schreuder H., Economic Approaches to Organizations, 2nd ed., Prentice Hall, London 1998.

[Gitlow, 2001]

Gitlow, Howard S., Quality Management Systems - A Practical Guide, St.Lucie Press, Boca Raton, 2001.

[Hamel, 1994]

Hamel G. and Pahalad C.K., “Competing for the Future”, Harvard Business Review, July-August 1994.

[Hargadon, 2000]

Hargadon A. and Sutton R., “Building the Innovation Factory”, Harvard Business Review, June-July 2000.

[Ishikawa, 1985]

Ishikawa K., What is Quality Control?: The Japanese Way, Prentice-Hall, Englewood Cliffs, 1985.

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[Jackson‚ 2000]

Jackson‚ M.C.‚ Systems Approaches to Management , Kluwer‚ New York‚ 2000.

[Juran‚ 1992]

Juran J.M.‚ Juran on Quality by Design - The New Steps for Planning Quality into Goods and Services, The Free Press‚ New York‚ 1992.

[Levitt‚ 1980]

Levitt T.‚ “Marketing success through differentiation of anything”‚ Harvard Business Review‚ vol. 58‚ No 1‚ 1980.

[Lillrank‚ 2003]

Lillrank P.‚ “The Quality of Information”. International Journal of Quality and Reliability Management‚ vol. 20‚ No 5‚ 2003. (forthcoming)

[Piore‚ 1984]

Piore M.J. and Sabel C.F.‚ The Second Industrial Divide - Possibilities for Prosperity, Basic Books‚ New York 1984.

[Pirsig‚ 1974]

Pirsig R.M.‚ Zen and the Art of Motorcycle Maintenance: An Inquiry Into Values, William Morrow and Company‚ New York‚ 1974.

[Senge‚ 1990]

Senge‚ Peter M.: The Fifth Discipline. The Art and Practice of the Learning Organization. Doubleday‚ New York‚ 1990.

[Sitkin‚ 1994]

Sitkin S.B‚ Sutcliffe K.M. and Schroeder R.G.‚ “Distinguishing Control from Learning in Total Quality Management: A Contingency Perspective”‚ Academy of Management Review‚ vol. 19‚ No 3‚ 1994.

[Slater‚ 1998]

Slater‚ S.F. and Narver J.C.‚ “Customer-led and market-oriented: Let’s not confuse the two”. Strategic Management Journal‚ vol. 19‚ 1998.

[Uzzi‚ 1997]

Uzzi B.‚ “The Problem of Embeddedness”‚ American Journal of Sociology, 1997.

[Wigand‚ 1997]

Wigand R.‚ Picot A. and Reichwald R.‚ Information, Organization and Management, Wiley‚ New York 1997.

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Chapter 7 INNOVATIONS IN THE INTERNET AND MOBILE ERA: The real dot.com revolution Web Jussi Autere‚ Timo O. Korhonen‚ Helsinki University of Technology

7.1.

Introduction

A study conducted by KPMG International (2000) found that one-third of the 331 company executives surveyed expect that e-business will change the definition of their core businesses. Although the first attempt to bring about a dot.com revolution flopped‚ there will be new ones. The recent hype surrounding web-based start-ups and their subsequent falls is not exceptional or surprising in a historical sense and the emergence of new technological infrastructures has created overreactions and disappointments on numerous previous occasions. The year 1983 witnessed the bursting of the so-called PC software bubble‚ but the most successful PC manufacturer‚ Dell‚ was only founded in 1984. Additionally‚ the fundamental changes in business processes due to the new PC infrastructure started to happen only after the bursting of the first bubble. In a similar manner‚ it can be expected that the really big changes in the operations of established companies are just emerging. The changes driven by The Internet and open mobile technologies are changing industry boundaries. The most important threats and possibilities are coming from new industries and technologies. This is forcing established companies to start analyzing their competitive environment from new points of view. The companies need to understand what their core assets are and whether new technologies can enhance their profit-generating capability or challenge it. The main question for established companies facing technological changes is how to increase their capability to react to change. The mainstream of research suggests that in situations of high-speed change‚ firms should be171 T.O. Korhonen and A. Ainamo (eds.)‚ Handbook of Product and Service Development in Communication and Information Technology‚ 171-192. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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come more specialized and utilize loose coupling to be able to use such production activities that are not in their core specialization area. They should increase their modularity - the possibility to disaggregate and recombine organizational parts into new configurations with little loss of functionality of their organizations [Schilling‚ 2001]. The main ways to increase modularity are contract manufacturing‚ alternative work arrangements‚ and alliances [Hitt‚ 1998]. When there is an environment characterized by major technological change‚ the benefits of vertical integration have been shown to diminish [Harrigan‚ 1984; Balakrishnan‚ 1986]. Firms can use alliances to obtain technologies more quickly than they could develop them in-house [Harbison‚ 1998; Heinsl‚ 2000; Powell‚ 1996]. Still‚ a simple strategy of outsourcing all new technologies is not necessarily always the most feasible‚ but closer analysis of the situation and development trends is needed [Afuah‚ 2001a]. It is not only the established companies that need to understand what the relationship is between existing business assets and the possibilities brought about by technological change. New ventures should also understand the industry structure and what kinds of innovations form potential foundations for totally new companies and what kind of innovations are better exploited by established companies. The most visible failures in the Web bubble‚ such as Webvan or Pets.com‚ are good examples of what happens if the analysis is not performed. Webvan was a delivery-to-home grocer that took orders via the Web and Pets.com was a Web-based pet supplies retailer. The value they created with new technologies and innovations was not sufficient for them to be able to compete against established players that already had all the complementary assets needed to run an efficient business. For new ventures‚ technological change is the very opportunity on which they were founded‚ and they should be interested in how to be proactive rather than how to react to change situations. Still‚ one of the most critical questions for the start-ups is whether they should form strategic alliances to get access to the complementary assets needed to capitalize their innovations or try to survive of their own and not let established players share the profits they generate. The following sections give insights into how companies can analyze and act in the situation when they need to start to address new Internet and open mobile communications technologies. The main decision‚ whether to integrate vertically or to forge alliances and business networks‚ depends on whether the change only means changes in a product‚ service‚ or delivery component‚ or whether there is a change in the architecture of how products are built and delivered. Section 7.1 handles the situation when the change does not affect the product architecture‚ whereas Section 7.2 inspects reasons why product architectures become more common. Sections 7.3 and 7.4 help to choose strategies for enhanced architectural and industry change.

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7.2.

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New Possibilities to Mass-customize Existing Products

New technology is commonly applied by adding more value to existing products. The following types of products belong among those with the greatest potential to receive added value from new Internet and mobile technologies [Eisermann‚ 2002]: Information-rich products. Websites can offer graphics and detailed text to help prospective buyers to better understand product’s features and benefits; Easily customizable products; Products with rapid changes in stock availability‚ demand‚ or price; Products with a replenishment-driven buying process‚ and Products that are sold in an unpleasant brick-and-mortar retailing environment. One of the major ways in which Internet and mobile technologies can add value to existing products is through the low-cost customization of products. Previous mass-product manufacturers are now able to meet the needs of narrow customer segments or even individual customers [Tiihonen‚ 2001]. There are two major ways of providing mass customization: By adding physical configuration capabilities to the order and delivery processes‚ or by increasing the intelligence of the products. Order and delivery process-based mass-customization systems must have three key-capabilities. The first is elicitation‚ a mechanism for interacting with the customer and obtaining specific information. The second is process flexibility‚ production technology that fabricates the product according to this information. The third is logistics‚ subsequent processing stages and distribution that are able to maintain the identity of each item and to deliver the right one to the right customer [Zipkin‚ 2001]. Dell Computer has been a champion of the mass customization performed by an enhanced order‚ configuration‚ and delivery process. All the key-capabilities are affected by The Internet and mobile technologies. The most straightforward is elicitation. It is rather easy to offer customers Web-based order forms and to take orders automatically from these systems. The other two capabilities demand greater operational changes. It is much more difficult to adapt one’s own processes to make it efficient to deliver the product that a customer has ordered. Still‚ logistics can be made more

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efficient by‚ for instance‚ mobile terminal-based systems that control the exact locations of goods and guide actions on the basis of the information they have.

Mass customization is expected to reduce shipment size. Unfortunately‚ most of the current distribution facilities were built to handle bulk shipments [Alaniz‚ 1999]‚ therefore not all companies can sell directly to end customers and bypass existing arrangements‚ as Dell could. They have to rely on their current delivery infrastructure. What may happen in the future is that warehouses will take on more of the processes currently performed at assembly plants. The factory will produce the basic platform and customer-specific modules will be added as specified via on-line orders. Customization performed by the intelligence embedded in the product will be many times more lucrative than changes carried out during the process until the logistics infrastructure changes. Even though a basic need is to change process‚ the most difficult problem most companies face in increasing process flexibility for mass customization is the modularization of product structure. Very often the product structures include information that was not previously coded anywhere‚ even though the degree of modularization is sufficient for product configuration to be carried out by the firm’s own sales representatives. An example of such information

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may be the fact that the smallest PC chassis on sale cannot accommodate the largest PC cards. Salespersons usually cope with this kind of tacit information by drawing on their experience‚ but this information must be coded‚ if the company wants to build a system that customers can use to automatically select the options they need. Strategically‚ the modularity of products and operations is most feasible when both the inputs and outputs of the company are heterogeneous [Schilling‚ 2000]. If inputs are heterogeneous but demands are homogeneous‚ there will be one optimal bundle and thus little to be gained from modularity. If demands are heterogeneous but inputs are homogeneous‚ modularity may enable significant variation in available configurations‚ provided there is more intelligent in the complete product.

The breadth of variations in demand that can be addressed with the same physically delivered product grows if its intelligence is increased. Making such intelligent products usually happens by adding software or electronics to the products‚ but sometimes communications services too can make products intelligent. As the price of electronics and the related telematics is dropping‚ many traditional mass products are becoming intelligent. This enables the creation of new services. Adding a controller to a sauna heating system makes it possible to turn the sauna heating on and off by a text message from a cellular phone. This can bring more flexibility to services‚ for example the way in which a hotel sells the service of its sauna. Whereas previously the sauna was always heated to the same temperature and guests were unable to change the setting‚ the reservation confirmation can now include a text message asking: “How hot do you want us to make your sauna?” The sauna is then auto-

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matically heated‚ with the help of information and communications technology‚ to the temperature the customer prefers. The intelligence need not always reside in the product itself‚ but it can be provided by remote services. For example‚ the information blood sugar measurement devices provide to diabetes patients can be enhanced by a service to which the values can be sent as text messages. As a response to the message‚ a recommendation for an insulin injection can be sent. The service center can have a sophisticated logic in its calculations and the patient’s doctor can also update treatment instructions there. The same system can be used to remind the patient about any necessary measurements and injections. The service can also take care of calculating the average blood sugar estimates‚ which will have been estimated earlier by a sophisticated laboratory test that demands a visit by the patient to the laboratory every three months. This way a standardized blood sugar measurement device transforms a part of a system that provides the user with a customized service. The most demanding type of mass customization is in cases where both the product and the delivery process need to be changed. If the product customization can be addressed by increasing the intelligence of the product‚ the problem is reduced to the need to have a mass customization-enabled process. But the more intelligent products are not always the answer; products need to be designed to make orders‚ not only to follow orders. Currently‚ the majority of custom-designed products are produced manually and building them often demands an expensive systems integration process. There is clearly a lot of room for new innovations that make automation‚ and‚ hence cost savings‚ possible. Modularity and standardization can help to automate production‚ but the next big challenge of mass customization is how to automate custom design. Good examples of mass-customized physical products replacing manually integrated one-of-a-type offerings are lacking‚ but in the realm of services there are already examples. In the airline industry the product itself has already long been mass-customized; it is common to find dozens of different rates for a trip in an aircraft carrying hundreds of passengers. Each of them is enjoying a service package tailored for their needs (or Web browsing skills!) and priced accordingly. Now the processes of airlines and some travel agencies are making it possible also to configure the exact complete travel package to the customer needs. A Finnish booking systems provider‚ BookIT‚ is starting an experiment in which the traveler tells the system only that she needs to travel from place A to place B at a certain time. She does not have to figure out that she needs a flight ticket from an airport close to A to an airport close to B. The mass customization process takes care of ordering taxis and hotel accommodation on the basis of the traveler’s profile‚ in addition to booking the flight ticket. A set of reservation rules

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needs to be defined in the system to make this kind of automatic provision for one-of-a-kind journeys.

7.3.

New Technologies Make Companies Disintegrate

When you look beneath the surface of most companies‚ you find three kinds of businesses: a customer relationship business‚ a product innovation business‚ and an infrastructure business. Although organizationally intertwined‚ these businesses are actually very different [Hagel‚ 1999]. The role of the customer relationship business is to find customers and build relationships with them such as branding‚ targeted marketing‚ and systems integration. The role of the product innovation business is to conceive of attractive new products and services and decide how to best bring them to the market. The role of the infrastructure business is to build and manage facilities for high-volume‚ repetitive operational tasks such as logistics and storage‚ manufacturing‚ and communications. The different kinds of businesses have a different operational logic and base objectives. There are natural fault lines in organizations between the different kinds of parts. The more heterogeneous inputs and outputs are‚ the more modular organizations need to be‚ especially in the situations of high technological change [Schilling‚ 2001]. Value chains disintegrate. This disintegration is not limited only to information-based products or services. Besides new communications technologies‚ it has been speculated that the simultaneously increasing process of globalization would encourage organizational disaggregation [Snow‚ 1992]. Any industry can find potential for new value chain configurations‚ thanks to new infrastructures. With the new technology‚ even such a traditionally non-differentiated commodity as electricity can be changed to a branded service. Ouman Finland Oy‚ a small and innovative Finnish building automation company‚ has specialized in telematics applications. They have developed heating‚ hot water‚ and air conditioning regulators that are easy to use and accurate‚ and have put Ouman products on the road to potential success. Ouman have created a controller for devices in buildings demanding scheduling and management‚ such as sauna heaters‚ air conditioning‚ and locking and burglar alarms. Essentially‚ Ouman products are used to turn energy into services that end customers need. Ouman regulators can be managed remotely by SMS messages. An innovative utility can start selling its facilities management service to the almost half a million Finnish vacation cabin owners.

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The utility installs Ouman regulators into its customer’s cabin and offers the customer a Web- and SMS-based service through which the customer can schedule the heating of her cabin and sauna to be ready just in time before she arrives there for a weekend. When there are problems with the cabin‚ such as a burglar alarm going off‚ the controller can alert the utility‚ whose repairman can then visit the cabin. In this way the utility sells a total service package to the customer instead of just trying to get the customer involved in a bidding competition where only the price of kWhs matters. In this way the utility’s customer intimacy business is separated from its operational electricity delivery capability. In some regions‚ the utility can then even outsource the electricity delivery part of its total offering to its previous competitors. In a situation of fast technological change‚ there is an increased possibility that first-class sales and logistics partners will be ready to make deals with start-ups even in the early phases of a company’s development. The improved availability of product information on The Web means that strong customer intimacy can no longer compensate for out-of-date or second-class technologies or operations. The technology organizations inside large companies will face increasing competition from start-ups offering OEM products to their companies. Neither can strong operations support a second-class customer intimacy organization any more. For instance‚ in postal services‚ the bundling of customer relationship management and logistics services has traditionally been strong. The main customer interfaces have been connected to physical logistics; postal services have been marketed and bought at the same place where the physical logistics chain of postal delivery started‚ the post office. The business of postal services has been to carry letters and packets from the sender to the recipient and

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nationwide physical transportation reaching all the residents has been at the core of the organization. The situation is now changing dramatically. Many postal delivery processes can be replaced with new ones that do not demand an in-house logistics organization. Quite a lot of letters contain only information that can be delivered totally electronically. For instance‚ invoices are such letters. In Finland‚ instead of sending invoice letters‚ the invoicing company can send invoice information electronically to the postal service’s system. The service then either prints out the invoice and carries it as a letter to the recipient or‚ increasingly‚ sends the information to the recipient by email. The recipients can then select whether their invoices are delivered physically or whether they receive them by email. The change means that a large part of postal operations is not dependent on logistics. The potential for using efficient physical logistics as a way to compensate for a customer service‚ which is not so good‚ is reduced. As customers can also select other service providers‚ the customer interface part of the organization has to be competitive in itself. Even though companies can react and sometimes even proact the changes by making their organizational setting more modular and thus increasing their capabilities to adapt to different customer needs and changes in technology‚ there are limits to these capabilities. A recombination of resources and core parts of companies is needed if the innovations change the architecture of the products (e.g. [Amit‚ 1993; Henderson‚ 1990; Winter‚ 1987]). Mass customization and outsourcing do not suffice to adapt to change‚ but a modern corporation can survive change if it acts as a truly dynamic community that reconfigures its resources as markets and corporate players co-evolve [Galunic‚ 2001]. The subsequent sections present potential choices in this situation.

7.4.

Who Is Going To Profit From the Innovations?

David Teece (1986) argued that two things determine the extent to which a firm can profit from its invention or technology: imitability and complementary assets (Fig. 7.4). Imitability is the extent to which the technology can be copied‚ substituted‚ or leapfrogged by competitors. Low imitability may derive from the intellectual property protection of the technology or from the failure of potential imitators to have what it takes. Complementary assets are all the other capabilities — apart from those that underpin the technology or invention — that the firm needs to exploit the technology. These include brand name‚ manufacturing‚ marketing‚ distribution channels‚ service‚ reputation‚ installed base of products‚ relationships with clients or suppliers‚ and complementary technologies.

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Fig. 7.4 suggests a profit-making model based on novel innovation. When imitability is high‚ it is difficult for an innovator to make money if the complementary assets are easily available or unimportant (Cell I). If‚ however‚ complementary assets are tightly held and important‚ the owner of such assets makes money (Cell II). For example‚ CAT (Computer Aided Topography) scanners were easy to imitate and EMI‚ the inventor‚ did not have the complementary assets‚ such as distribution channels and relations to U.S. hospitals‚ that are critical to selling such expensive medical equipment. General Electric had these assets and quickly captured a leadership position by imitating the innovation. Coca-Cola and Pepsi were able to profit from RC Cola’s diet and caffeine-free cola inventions because they had the brand-name reputation and distribution channels that RC did not had‚ and the innovations were easy to imitate. When imitability is low‚ the innovator stands to profit from it if the complementary assets are freely available or unimportant (Cell IV). These are the engineer’s classic dreams: products based solely on isolated‚ patented or copyrighted inventions that customers come to buy in masses. These kinds of innovations are very rare in technology-based industries. The best examples can be found among artistic works and in the ‘snake oil’ type of consumer products. During recent years one of the most visible of such innovations has been the Harry Potter characters invented by J. K. Rowling.

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When imitability is low‚ as in Cell III‚ and complementary assets are important and difficult to acquire‚ whoever has both‚ or the more important of the two‚ wins. The better negotiator can also make money. Pixar’s interaction with Disney’s studios is a good example. The imitability of some of its digital studio technology is somewhat low‚ given the software copyrights it holds and the combination of creativity it takes to deliver a compelling animation movie. But offering customers movies made with that technology requires distribution channels‚ brand-name recognition‚ and financing‚ which are tightly held by the likes of Disney and Sony Pictures. Before the Toy Story movie‚ produced using Pixar’s technology‚ Disney had the bargaining power because it had all the complementary assets and the technology had not been proven. After the success of Toy Story‚ when Pixar proved that it could combine technology and creativity — something that was more difficult to imitate than plain computer animation — there was a shift in bargaining power to Pixar‚ which was able to renegotiate a better deal [Crane‚ 1998]. Understand the importance of complementary assets is especially important for Web and mobile service developers. When existing business models and products are being enhanced‚ Web pages or mobile applications alone seldom produce enough added value to become the core of the business. The applications need supporting activities to become part of a profitable business model. There is a need to reach customers‚ a need for physical logistics‚ and a need to be able to provide the base products and technologies that are then enhanced with the new Web page contents enrichments and communications technologies. These complementary assets usually belong to established players in the industry. They must have economic reasons to start co-operation with new product or service providers. The innovator has to find ways how to co-operate with established players. Usually‚ if none of the latter’s core assets are affected by the new innovative service‚ they can just enhance their operations by building their own corresponding service or by starting a partnership with one of the new players and having a clear lead role in that partnership.

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The Generic Strategies Possible for Innovators and Asset Owners

Strategies when complementary assets are hard to obtain and your own technology is imitable (Cell II): Team up! A very typical feature for novel Web and communications product and application developers is that their technology is easy to reach‚ easy to imitate and that its commercialization demands have difficult-to-obtain complementary assets. This is especially true with Web applications‚ where providers of developing tools such as BEA‚ IBM‚ and Microsoft sell the majority of the technologies that are hard to imitate. The core competence of an Internetcompany is usually its capability to build systems and applications by using middleware and other tools provided by third parties. These tool technologies are usually also available for their competitors. The application of the technology is easy to imitate and substitute. There is nothing new in the situation the most Internet and mobile application and service developers are facing. And although it is easy to fail into desperation in this rough competition situation‚ we have seen that there is nothing that would prevent also huge success. Many software developers faced this in the 1980s. The Web related high-tech does not depend on expensive or esoteric equipment‚ nor does it depend on carefully guarded trade secrets or require training that‚ by the way‚ is especially difficult to obtain [Siwek‚ 1995]. Throughout the 1980s and 1990s‚ a continuous stream of successful new startup companies such as Autodesk‚ Bentley‚ or Oracle emerged. These firms were able to develop complementary assets internally or to team-up with someone possessing the critical assets‚ so that they could take advantage of their imitable technology capabilities. Usually‚ the most appropriate strategy for new technology-based companies to get complementary assets is to team-up with the owners of the assets. If the negotiation position of the new company is good‚ it can forge a jointventure with‚ or even acquire‚ the owner of the complementary assets. If the owner of the complementary assets feels that the technology has sustainability long enough to be a source of competitive advantage‚ it can acquire the provider of the technology. And if the owner of the complementary technology sees that the new technology is a critical part of an architectural innovation‚ it must acquire a technology provider if it is not already developing it by itself. Thus the new venture should search for partners whose core operational

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structure is not threatened and concentrate its own resources in the area where its technology brings architectural innovations. An example of a successful teaming-up strategy is Comptel Inc. Comptel is a subsidiary of an incumbent local exchange carrier in the Helsinki region‚ Elisa Communications. Comptel offers software solutions that make service management‚ use‚ and charging in diverse technological environments more efficient. At the beginning of the 1990s Comptel was collecting the majority of its revenues from projects and services sold to Elisa. In these projects‚ the company created the code base and product concept for mediator software‚ connecting telecommunications equipment‚ and ICT systems. In the area of equipment configuration and services provisioning‚ the approach was an architectural innovation. Instead of trying to expand the software in each of the types of networked equipment‚ such as telephone exchanges and invoicing systems‚ to build one-to-one interfaces between different systems‚ specialized mediator software connects the systems. The product does not contain features that are highly difficult to imitatebut it represented a new way of combining capabilities to build services provisioning systems. The advantages of Comptel were that the code for new architecture was available and proven and its operational model fitted the logic of the new innovation. In the mid-1990s‚ Comptel lacked a global sales network that would have enabled it to sell its products outside Finland. Comptel decided to team up with the providers of telecommunications equipment and ICT systems it was used to working with: Nokia and IBM. Neither of these had done much business in the technologies previously used to connect telecommunications equipment and computer systems. They saw that mediator technology would not change the architecture of their core products. They were ready to start representing Comptel’s software as their solution to mediator software. With these sales channels Comptel was able to get some key foreign customers from new GSM operators. Then it started to build its own sales network and by then had created enough credibility that it could forge similar reselling deals with other ICT systems and telecommunications equipment manufacturers. The company gathered revenues of 60.8 Million Euros in 2001‚ mainly from mediator business from foreign customers. The key issue in team-up attempts for technology-based companies with imitable technology is timing. The firm must forge an agreement before firms with complementary assets have had a chance to copy the technology or get it from someone else. If the owner of complementary assets sees that a recombination of resources in the industry that threatens the position of its core products or services is not going to happen‚ then it should usually choose to buy technology to be integrated into its own systems.

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A typical example of owners of complementary assets with a strong position and in no real hurry are existing retail bankers in Finland facing the growing popularity of Web banking. The retail banks typically have all the complementary assets needed: brand‚ a large customer base‚ customer support personnel‚ financial assets‚ and back-office systems. In Finland the banks have also built programmable interconnections to other retail bankers so that their customers can pay all their bills electronically without needing to use checks. They can build their Web and even mobile end-user banking solutions as an extension to their legacy systems. The Web is not going to demand changes in their basic money-making logic. The majority of their customers are slow to change their banking habits. This situation means that the question of how to handle the new technologies is not a strategic one‚ but a tactical make-or-buy decision. If there are new technologies needed in Web banking‚ established banks are in a good negotiating position vis-a-vis the technology providers‚ thanks to their complementary assets. As expected‚ the transition to Web banking has happened in Finland without any technology-based retail banking or money transfer start-ups emerging or major changes in market shares. In countries where retail bankers do not have such strong complementary assets‚ money transfer or Web banking start-ups have more room to operate‚ for instance in the USA‚ where wired payments have not been common for paying bills and new money transfer companies like Paypal have emerged. In the first wave of dot.com firms‚ the internal development of complementary assets was tried many times. For dot.com:s this happens through advertising‚ promotion‚ and selling references. By using these‚ the start-up firm can build brand names‚ a large number of clients‚ customer databases‚ or communities before their competitors have had time to imitate their technologies or build similar complementary assets. It was assumed that The Web would mean the recombination of resources for everyone‚ but the assumption was wrong. For the strategy of developing complementary assets to be successful‚ it is important that the firm builds in switching costs for its clients and customers. Many times the main mechanism the first generation dot.com companies tried‚ was to exploit the networks externalities feature of The Internet. They perceived that the switching costs were directly linked to the size of the network. The larger the community of clients‚ the more valuable it is to members and the more difficult it is for a member to switch to a lesser community. Unfortunately‚ the majority of these efforts failed. Huge financial resources are needed to build networks and it is still many times more difficult to provide a sustainable high switching cost to customers‚ because no real architectural innovation was presented along with the new offerings. The difficulty Amazon.com has faced in becoming profitable is an example of how difficult it is

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to build high switching costs when the added value the company provides is basically imitable. Successful examples of exploiting network externalities are companies such as AOL and eBay. They operate in value network architectures where the network externalities are a natural part of the business logic. Many times‚ even though the innovation is an architectural one‚ one company cannot build a large enough network to make a recombination of resources covering the whole value chain possible‚ but a group of companies is needed. Together they create a business system. Only with many interconnecting players that offer enough customer base coverage can network externalities really start to show their power. The most visible recent example of the power of network externalities is the popularity of SMS messages. Almost all the GSM networks provide SMS messaging capability and this capability was practicable within all the phones of different vendors before the application started to take off. For one operator‚ or maybe even handset manufacturer‚ it would have been an impossible task to create a large enough network.

Strategies when complementary assets are hard to obtain and your own technology is hard to imitate (Cell III): Team-up or block! Almost all those technology-based companies that are not located in Cell II in Teece’s matrix are in Cell III; the technology is difficult to imitate‚ but complementary assets are also important. One Finnish example of a company that had a difficult-to-imitate technological invention but no complementary assets is a security software provider‚ SSH Communications. SSH provides best-of-breed cryptography and authentication technologies and products for secure Internet communications. In the mid-1990s SSH Communications Security developed an SSH terminal software application that made it possible to have secure terminal connections to Unix machines. The software quickly gained popularity in the non-commercial Unix user community. Because the software was provided on a free-of-charge basis‚ the company lacked financial resources. The company also lacked a global marketing‚ sales‚ and support network. So as to be able to exploit their technological edge before alternatives gained ground‚ the company started to search for a partner that could provide complementary assets. The company selected F-Secure‚ which had some of the key competitive assets and was geographically and culturally close to SSH‚ even though FSecure itself was also a rather small company with limited resources. The cooperation with F-Secure provided SSH with the initial commercial sales and revenues that it needed to get credibility‚ customers‚ and financing in order to continue developing the technology.

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In the next stage‚ SSH developed‚ on the basis of its security competencies‚ a toolkit for OEM customers to build IPSec standards-based VPN services into their communications equipment or software products. With this innovation SSH moved from Cell III to Cell II‚ because IPSec functionality is specified in standards and some of the larger equipment manufacturers‚ such as Ericsson‚ have been able to develop their own solutions. But through the initial team-up with F-Secure‚ SSH was able to build sufficient resources and credibility to have a good brand name among customers. After the Cell II innovation provider phase‚ SSH tried to achieve an independent position and do business directly with end users‚ as its complementary assets ownership was increasing. Unfortunately its ownership of complementary assets was not sufficient and SSH returned to an OEM sales-based business model. Generally‚ in Cell III‚ a firm can pursue one of two strategies: block or team up. If it has both the technology and complementary assets‚ it can protect both. This position has frequently been the springboard for a very successful period in a company’s life. Cisco Systems in the mid-1990s is an example of a company that was in the position of owning both the critical complementary assets and core technologies that were not easily imitable. The company entered the communications market when it began to be possible to do business with a totally new technological architecture‚ routed IP networks‚ and ever since it has had a dominant market position and brand recognition among the buyers of routers. It also had technologies which were not easily imitable and which its customers needed when they operated their routed IP networks; it owned a proprietary improved routing protocol and the IOS software that the majority of IP network operators used to manage their routing devices. The company was able to adapt to the use of new technologies by acquiring Cell II and Cell III innovator companies continuously. The result was a hugely successful business that made Cisco‚ for a short period of time‚ the most valuable company in the world. In the team-up strategy‚ the innovator forges cooperation with either one complementary assets owner or many of them. Complementary asset owners facing the emergence of new technology that is not easily imitable should also include in their decision-making the knowledge as to whether the technology demands the recombination of complementary resources. If such teaming-up is not needed‚ the owner of the complementary assets should pursue a strategic alliance with the owner of the technology and exploit its complementary assets to get as good a deal as possible. If the technology brings with it an architectural innovation‚ the owner should acquire the owner of the technology‚ because this ownership can help the company to survive to the next technology generation. The risk for Cell III blocking strategy companies is that sooner or later their technologies become a commodity or become obsolete. There might also emerge new technologies that are essential and difficult to imitate. If no re-

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construction of structures has happened‚ the owner of the technology never reaches a dominant position but is forever the provider of an add-on kind of product. This is what has happened to SSH with its SSH and IPsec Express products. This started to happen to Cisco in the late 1990s as it became possible for other equipment manufacturers to copy IOS manageability. At the same time Juniper Networks was able to bring on to the market superior core routing technology long before Cisco was able to deliver similar products. These developments have moved Cisco closer to Cell II‚ where its complementary assets still provide it with good possibilities to succeed. The case of SSH also shows the problem Cell III innovator companies often face in their later development because they had to use team-up strategies in the early phases of the company’s development. SSH gave nonterminable exclusive reselling rights for SSH products to F-Secure in their initial agreement. As it turned out‚ F-Secure’s success in selling SSH was limited and after a couple of years SSH wanted to have the right to sell SSH products. Then SSH found out that the agreement‚ which had been necessary in its earlier phase of development‚ now limited its freedom to do business and its growth in the later stages of the company’s development. This is rather typical. As research into alliances shows‚ the long-term sustainability of alliances is weak and this is especially true with Cell III alliances.

Strategies when the role of complementary assets is low: Run or block! Companies doing business in the situations when the role of complementary assets is low‚ also have a set of generic strategies they can successfully pursue‚ as can be inspected in Fig. 7.5. The figure maps the feasible generic strategies in different imitability-complementary asset configurations. A firm in Cell I can pursue a run strategy. For an innovative firm that means that‚ since its technology can be easily imitated‚ the firm keeps innovating. By the time a competitor catches up with yesterday’s technology‚ the firm has moved on to tomorrow’s technology. A firm in Cell I that has based its strategy on achieving high operational efficiency‚ as many electronics subcontractors have been doing‚ can also apply a run strategy. These firms pursue efficiency by trying to increase productivity‚ increasing volume by acquiring competitors. Adapting to new technologies happens through investing in more productive and cost-efficient machinery. The run strategy with companies whose core competence is in operational efficiency leads to an industry structure of a limited number of large global companies.

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In a world where technology is difficult to imitate but complementary assets are easy to come by‚ a firm has to protect that technology if it is going to make money. Very few firms‚ especially those exploiting The Internet‚ can be found in Cell IV. The analysis of one’s own company’s position towards providers of complementary assets is important when an innovator company develops and executes its business model. Established companies too‚ if they are the owners of complementary assets‚ can use the same framework to analyze how to handle emerging new technologies and innovations.

7.6.

Conclusions and New Trends

The conventional wisdom for technology strategy for existing firms in the communications industry in the 1990s was to let new start-ups develop the first products in the next technology area‚ and then‚ when the technology began to approach the mainstream‚ to add the products to their portfolio through either an OEM deal or acquisition. As the pace of change has been fast and Web and mobile technologies have made the disintegration of value chains possible‚ this model has been working rather well. Teece’s matrix (Fig. 7.4.)

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has given advice as to what generic strategies to pursue‚ especially in forming alliances. The 2000s are bringing two new approaches to the field. Firstly‚ in those situations when the innovations do not demand the recombination of complementary resources‚ e-business technologies make it possible to connect new product innovations to the value network that provides mass-customized solutions. The established players no longer gain operational advantages from internal processes but from their capabilities to re-engineer networks of companies so as to be an efficient provider of configurable solutions. Secondly‚ when the innovations are architectural ones‚ then a new approach to acquisitions and diversification might start replacing the ‘team up initially and acquire when ripe’ model. The approach is to concentrate R&D resources on new technologies and spin-off mature technologies [Afuah‚ 2001a]. The basic reason why it is wise for established players to spin-off the technology when the business model and product architecture have stabilized is to ensure that the company can react properly to new technologies. The technology on which a new generation of products rests usually evolves from a period of flux with high uncertainty [Tushman‚ 1986; Utterback‚ 1994]. This period of flux and high uncertainty is usually ushered in by a discontinuity that may be competence-destroying‚ not only to producers but also to their suppliers. When a new technology enters the markets‚ the management of an established player turns most naturally to the R&D department‚ which develops products based on the existing technology in the area. In a situation of high uncertainty‚ experts in previous generation technology tend to underestimate the potential of the new technology compared to the old one‚ in such a way that the management underestimates the need for the technology until it is too late. In such a case‚ the firm is better off if it has not been vertically integrated. The logic behind integrating new technology R&D inside an established player is that in order to keep abreast of technological developments‚ firms must invariably acquire skills and knowledge in the new technology and turn them into new products. This process of knowledge acquisition and exploitation often entails frequent interaction with suppliers that is most effectively conducted through vertical integration [Afuah‚ 2001a]. The more uncertainty that the firm faces in the relationship with its supplier‚ the more it should integrate vertically into producing its own input [Masten‚ 1988; Monteverde‚ 1995; Pisano‚ 1990; Williamson‚ 1985]. Lower stock prices currently make it more difficult to pay for acquisitions and lower exit valuations are reducing the amount of venture-funded start-ups. This changes the focus as to how to use instability versus complementary analysis. As demonstrated in the previous sections‚ existing companies are

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more likely to develop innovations themselves‚ but at the same time complementary assets may become more easily available through spin-offs. This may result in the increasing popularity of block and run strategies and the decreasing popularity of team-up strategies.

REFERENCES [Afuah‚2001a]

Afuah A.‚ “Dynamic Boundaries of the Firm: Are Firms Better Off Being Vertically Integrated in the Face of a Technological Change”‚ Academy of Management Journal‚ vol. 44‚ 2001.

[Afuah‚ 2001b]

Afuah A. and Tucci C.L.‚ Internet Business Models and Strategies—Text and Cases, McGraw-Hill Irwin‚ New-York‚ 2001.

[Alaniz‚ 1999]

Alaniz S. and Roberts R.‚ “E-procurement: A Guide to Buy-Side Applications”‚ Industry Report, Stephens Inc.‚ December 27‚ 1999.

[Amit‚ 1993]

Amit R. and Schoemaker P.J.H.‚ “Strategic assets and organizational rent”‚ Strategic Management Journal‚ vol. 14‚ 1993.

[Balakrishnan‚ 1986]

Balakrishnan S. and Wernerfelt B.‚ “Technical change‚ competition and vertical integration”‚ Strategic Management Journal‚ vol. 7‚ 1986.

[Crane‚ 1998]

Crane C.‚ Johnson W.‚ Neumark‚ K. and Perrigo C.‚ “PIXAR 1996”. University of Michigan Business School case, 1998.

[Eisermann‚ 2002]

Eisermann T. and Brown A.‚ “Online Retailers”‚ in Internet Business Models: Text and Cases, Eisermann T.‚ McGraw-Hill Irwin‚ New York‚ 2002.

[Galunic‚ 2001]

Galunic D.C. and Eisenhardt K.M.‚ “Architectural innovation and modular corporate forms”‚ Academy of Management Journal, vol. 44‚ 2001.

[Hagel‚ 1999]

Hagel III J. and Singer M.‚ “Unbundling the Corporation”‚ Harvard Business Review, March-April‚ 1999.

[Harbison‚ 1998]

Harbison J.R. and Pekar P.‚ Smart alliances: A practical guide to repeatable success, Jossey-Bass‚ San Francisco‚ 1998.

[Harrigan‚ 1984]

Harrigan K.R.‚ “Formulating vertical integration strategies”‚ Academy of Management Review‚ vol. 9‚ 1984.

[Heinsl‚ 2000]

Heinsl M.‚ “Buying into new economy”‚ Wall Street Journal, July 25‚ 2000.

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[Henderson‚ 1990]

Henderson R. and Clark K. “Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms”‚ Administrative Science Quarterly‚ vol. 35‚ 1990.

[Hitt‚ 1998]

Hitt M.A.‚ Keats B.W. and DeMarie S. M. “Navigating in the new competitive landscape: Building strategic flexibility and competitive advantage in the 21st century”‚ Academy of Management Executive‚ vol. 12‚ 1998.

[KPMG‚ 2000]

KPMG Global Study‚ “Majority of Companies See Internet Transforming Their Industry Role”‚ Press Release, KPMG‚ September 20‚ 2000.

[Masten‚ 1988]

Masten S.‚ “A legal basis for the firm”‚ Journal of Law. Economics‚ and Organization‚ vol. 4‚ 1988.

[Monteverde‚ 1995]

Monteverde K.‚ “Technical dialog as an incentive for vertical integration in the semiconductor industry”‚ Management Science, vol. 41‚ 1995.

[Pine‚ 1993]

Pine J.‚ Mass Customization - The New Frontier in Business Competition, Harvard Business School Press‚ Boston‚ 1993.

[Pisano‚ 1990]

Pisano G.‚ “The R&D boundaries of the firm: An empirical analysis”‚ Administrative Science Quarterly‚ vol. 35‚ 1990.

[Powell‚ 1996]

Powell W.‚ Koput K. and Smith-Doerr L.‚ “Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology”‚ Administrative Science Quarterly‚ vol. 41‚ 1996.

[Rumelt‚ 1984]

Rumelt R.P.‚ “Towards a Strategic Theory of the Firm”‚ in Competitive Strategic Management, Lamb R.‚ ed.‚ Prentice Hall‚ New Jersey‚ 1984.

[Schilling‚ 2000]

Schilling M.A.‚ “Towards a general modular systems theory and its application to inter-firm product modularity”‚ Academy of Management Review‚ vol. 25‚ 2000.

[Schilling‚ 2001]

Schilling M.A. and Steensma H.K.‚ “The Use of ModularOrganizational Forms: An Industry-Level Analysis”‚ Academy of Management Journal‚ vol. 44‚ 2001.

[Siwek‚ 1993]

Siwek S.E. and Furchtgott-Roth H.W.‚ International Trade in Computer Software, Quorum Books‚ Westport CT‚ 1993.

[Snow‚ 1992]

Snow C., Miles R., Coleman H.J., “Managing century network organizations”, Organizational Dynamics, vol. 20, 1992.

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[Teece‚ 1986]

Teece D.J.‚ “Profiting from Technological Innovation: Implications for Integration‚ Collaboration‚ Licensing and Public Policy”‚ Research policy, vol. 15‚ 1986.

[Tiihonen‚ 2001]

Tiihonen J.‚ “Web Configured Products”‚ Lecture at Helsinki University of Technology, Espoo‚ September 27‚ 2001.

[Tushtnan‚ 1986]

Tushman M.L. and Anderson P.A.‚ “Technological discontinuities and organizational environments”‚ Administrative Science Quarterly‚ vol. 31‚ 1986.

[Utterback‚ 1994]

Utterback J.M.‚ Mastering the Dynamics of Innovation, Harvard Business School Press‚ Boston‚ MA 1994.

[Williamson‚ 1985]

Williamson O.E.‚ The economic institution of capitalism, Free Press‚ New York‚ 1985.

[Winter‚ 1987]

Winter S.G.‚ “Knowledge and competence as strategic assets”‚ in The competitive challenge: Strategies for industrial innovation and renewal, Teece D.J.‚ ed.‚ Ballinger Cambridge‚ MA‚ 1987.

[Zipkin‚ 2001]

Zipkin P.‚ “The limits of mass customization”‚ MIT Sloan Management Review, Cambridge‚ Spring 2001.

Chapter 8 PATENTING AND INTELLECTUAL PROPERTY RIGHTS IN ACADEMIC INDUSTRIAL VENTURES Panu Kuosmanen‚ Timo O. Korhonen‚ Helsinki University of Technology‚ Antti Ainamo‚ Jaakko Pöyry Consulting‚ Helsinki School of Economics‚ and the University of Art and Design Helsinki

8.1.

Introduction

A patent is an exclusive right to exploit an innovation commercially. In its full meaning‚ patenting is one of the most complex and sophisticated areas of legal practice. In the core‚ the motivation for patenting is to protect inventors against unfair exploitation of their invention by imitators and competitors. By patenting‚ product and service developers obtain exclusive rights for their creative insights and hard work. When a company holds a patent directly‚ or by the virtue of having received rights to use it‚ the patent can help to gain a foothold in a marketplace or to maintain a commercial advantage‚ during which time the company can further develop its products. Patenting can also serve to enhance company’s reputation and image‚ especially when the patent is internationally granted. Like other intellectual property rights‚ patents are an important part of financial valuation and competitive advantage‚ especially in high-tech industry. Competitors‚ who do not own the patent rights of particular technology‚ must invest more money and capital to develop new‚ competitive solutions‚ or to pay the patent holders for the rights to utilize the patent. The patent holder can also adopt a pricing policy that is more beneficial for a company in terms of regular rents‚ or pay on demand per use. Besides licensing‚ the right to use a patent against payments in the above way‚ patent holders can also sell the patent. In both cases‚ the patent becomes an object of trade as in itself (a commodity of exchange). A patent is granted for a limited time. In many countries‚ the maximum time of validity is twenty years from the date of application‚ providing that the annual maintenance fees are paid. 193

T.O. Korhonen and A. Ainamo (eds.)‚ Handbook of Product and Service Development in Communication and Information Technology‚ 193-209. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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Despite of the many advantages of patenting‚ there is often only a scant‚ general knowledge about them in many high-tech companies. This is the case in terms of legal‚ and technological considerations‚ as well as with the practicalities‚ as how to apply for a patent‚ what is patentable‚ and how to appropriate a patent. This chapter aims to inspect why the developers ought to know the basics of patenting and‚ especially‚ how patents can contribute to the overall performance of high-tech product development and business. Note‚ that our goal is not to strive to give you a fully developed “How to do it?” - guide‚ but preferably to focus on the general framework of patenting. We will review the basics of international and national patenting and map the similarities and differences between patenting and licensing. An objective is to make you aware of the general benefits of high quality patent management and to make you to understand the relating threats and challenges.

8.2.

Defining Patenting

Patents were introduced for the first time in Venice in the century, when the board of doges granted exclusive privileges for some chosen firstmover entrepreneurs, on how they should perform successful commercial operations. Once this privilege had been granted, exclusive manufacturing rights could be obtained for a certain period. Later, in the century, the first actual utility patents were granted for inventors in England, by the government of England. Ever since, government has granted patent rights to inventors and applicants to promote invention and innovations and, as an underlying goal, to enhance national competitive power. Since the century, patenting has become highly institutionalized, with fairly universal practice across the globe. The universal practice, known also in countries with the most elementary patent legislation, is that the statutory patent rights are granted to the Father of the Inventive Step, i.e. the designated inventor. Present practice is that the government grants the patent rights to the applicant who can be the inventor or his assignee that is most typically a company, but can also be a research institution or a team of researchers. (Note that we can designate a company as an patent applicant only when there is clear and undisputable contract between the research team and the company.) There are some general guidelines to define a good, potentially patentable invention, as summarized in Table 8.1. However, in practical patent practice, good inventions are more specifically defined. In order for the government to grant the patent right to the applicant, three terms stipulated by the patent law (the Patenting Criteria) must have been met:

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Inventive step means that the invention is not obvious for a person skilled in the art‚ that means a professional or/and an expert in the field. New combination of existing components constitutes an innovation only when there is a truly new creative insight how the components are fitted together. Industrial Applicability

The second requirement‚ industrial applicability‚ means that the invention must be reproducible. This means‚ that whoever has the necessary means or equipment must in principle be able to reproduce the invention according to the technical description in the patent. Within this context‚ a patentable invention‚ as such‚ has not been defined in the patent laws. Here‚ the patent laws merely state‚ that a patent can be granted for an invention which is industrially applicable.

Novelty

This means that the invention has not been publicly available or that it has not been published outside the definitions specified in the patent laws. The inventive solution must be a novel combination in comparison to the existing technology and new in comparison to what has been publicly available before the application date. Within this context‚ the technical problem and its solution are crucial requirements for a patent. Therefore‚ one can obtain patents to protect the intellectual insight of medical instruments‚ chemical substances

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and compositions‚ as long as the invention meets the Patenting Criteria. In most countries‚ patents for computer programs can be obtained if the invention involves features performed by a computer‚ a computer controls them‚ or equipment consists partially of computer hardware. In contrast‚ software without a technical hardware dimensions are usually not covered by patent rights. Plants‚ animal varieties‚ or essentially biological processes may be protected only in terms of the related microbiological processes or the final artificial products‚ if the Patenting Criteria are met. If the invention turns out to be non-patentable‚ there may be other ways to protect the intellectual property rights. For instance‚ the product of an artist’s creative act is in most cases protected automatically by copyright. Sometimes the intellectual property rights can be protected by a design patent. Despite of these wide‚ almost universally applicable patenting practices and the unanimous format of the patents as themselves‚ there are notable patenting differences between countries. Some of the basic properties of unpatentable and patentable inventions following the European practice are summarized in Table 8.2.

8.3.

Applying for a Patent - Formal Procedures in European Countries

In a European country‚ like in Finland‚ a patent application must be filed in the National Patent Office (The National Board of Patents and Registrations‚ or PRH). The office provides application forms that are required to be filled to start the formal patenting process. In Finland‚ the application consists of the four major parts: “1. The Description”‚ “2. Claims”‚ “3. Drawings” and “4. Abstract”. The inventor or inventors must be designated in the application form. The patenting process (Fig. 8.1) can be conducted by the applicant himself or by a patent attorney‚ which is recommendable‚ but more expensive. After filing the application‚ the national patent office performs the formal examination. The authorities ask always the same questions: “Does the application fulfill the patenting criteria specified in the patent law and in the patent act? Have the payments been made?” If they observe any deficiencies in terms of the criteria‚ they will give a formal notice to fill the prerequisites before processing of the application further. After this initial stage‚ a technical examination is performed by the technical section of the national patent office. This procedure takes usually 6-8 months. After the technical examination‚ the national patent office will send a technical examination report to the applicant. The applicant has an opportunity to comment on the technical examination and to make a written response for the office. It is also possible to amend the application according to the report. Based on the response‚ the examiner may update the examination report

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or to accept the application. In the case of acceptance‚ the patent will be granted‚ made public‚ and it can be circulated to those of interested.

Within nine months from the granting of the patent‚ any person may oppose the patent. The opponent must present arguments explaining why the patent should have not been granted. The national patent office then examines the opposition‚ and gives the patent applicant an opportunity to comment the opposition. Based on the argumentation and documents cited‚ the patent office then either rejects the opposition and upholds the patent in force‚ or accepts the opposition‚ and revokes the patent totally or partially. After the patent has been granted and the opposition period has ended‚ the only way to revoke a patent is to lodge a case for revocation. In Finland‚ the place for lodging the case is the Helsinki City Court. The process can further be appealed to the Supreme Court‚ if the permission for appeal has been granted. Validity of a granted patent requires paying annual maintenance fees. In Finland‚ as also in many other countries‚ these fees are rather inexpensive during the first years (a few hundred of per patent) but they increase towards the end of the 20-year term. In the year 2003‚ the final annual maintenance fee in Finland for the 20th year of a patent is 805 .

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Comparing Patenting in Europe and in the US

A comparison of European and the North American patenting reveals that the patenting procedures differ in many important aspects. In Europe‚ developers will in most cases apply for the patent in the name of their company or for the institution they work with. Only seldom‚ will they do this in their own names. Typically‚ there is a mid-range arrangement‚ whereby the patent will not be legally in the name of the inventors‚ but they receive a share of the economic returns. The American patent system emphasizes the personal rights of the inventor. The inventor is‚ at the same time‚ the inventor and the applicant. In the US‚ the firm or institution acts only as an assignee and the patent must always be officially applied for a person-inventor or the related workgroup. An important feature of the US patent law is that‚ before the 1997‚ all the US patent applications became public only when the patent was granted. Now‚ like in Europe or in Japan‚ they become public after 18 months of their filing date‚ making them potentially an excellent source of technical information. Unfortunate for international competition‚ there is however an important limitation in this new practice: If an inventor limits patent protection for the US only‚ he or she has the option to apply for the patent application to be kept

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secret until the patent is granted. About nine per cent of patent applications in the US are handled in this way. Besides the differences in the roles of inventors and patenting publicity‚ another major difference is the concept of Grace Period. In the US‚ the Grace Period refers to the fact that the inventor can publish or present his invention in journals‚ exhibitions or otherwise to make it public and to file a patent application up to six months after its publication. In Europe‚ making an invention public before filing a patent application will generally serve to hamper patenting‚ and should be avoided at all cost. Disclosure ought to be restricted to the patent attorneys and other trusted parties. There is also a difference in the very definitions of what constitutes an “Inventor”. In Europe‚ the critical definition is First-to-File‚ while in the US the critical definition is First-to-Invent. In other words‚ in Europe‚ the patent will be granted to the inventor or the entity that was first to file the application in the patent office. In the US‚ the date of invention plays a crucial role. This means that the inventor is the person who has made the invention and is able to show an earlier date of invention. Among other things‚ this role of inventor means that a granted patent can be revoked later by claiming that all the inventors have not been designated in the application. There are also differences in some other‚ important practices. The US system has a feature called as the Continuation Practice. This means that the application can be maintained in force by filing new‚ modified application that includes not only the latest inventive results obtained after filing the latest patent application‚ but also an elaboration of the inventive step described in the previous application. The filing date of the continuation application will be considered to be the same as in the initial application. The Continuation Practice can be repeated many times and thus the final granted patent could include all the relevant technology in the field‚ say from 1970’s to 1990’s. Patents based on the Continuation Practice are valid in the US only. Other countries do not have this practice as part of their patenting system. There are many suspecting that this practice is designed to protect the US national interests. This is because due the Continuation Practice a foreign applicant can never be 100 % sure whether any foreign inventions are sufficiently novel by the US standards. There are also big differences in defining what is patentable. European patent laws stipulate this quite clearly‚ as well as the relating patenting practices‚ as we noticed earlier. In contrast‚ almost Anything Under the Sun can be patented in the US. The US Patent Office has granted thousands of patents for computer programs and business methods‚ despite of the difficulties in integrating these patents into the traditional framework of what can be patented. Therefore‚ when a foreign inventor‚ developer or a company enters the US market‚ it is extremely important to examine previous and present patent pub-

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lications and the state-of-the-art thoroughly. This is especially the case in the rapidly developing fields like telecommunications in order to avoid unpleasant surprises in terms of conflicting patents. In practice‚ these difficulties mean consuming a lot of time and money for patent infringement procedures. As a practical rule‚ it is wise to obtain a lawyer’s statement and a comparison of the status of one’s own patent portfolio in relation to the existing patent publications and other state-of-art technology in the field. Finally‚ in the US‚ patenting new business methods has only a little in common with the requirements of industrial applicability‚ inventive step‚ and novelty as comprehend in the European patenting practice. For instance‚ many companies have been able to patent procedures for shopping in The Internet or in a telephone network. These include for instance the “One-Click” patents by Amazon.com and the “Reverse Auction” patents by Walker Asset Management Limited Partnership‚ numbered 5‚960‚411 and 5‚794‚207 patents‚ respectively‚ granted in 2001.

8.5.

Patenting Abroad – Some Practical Advises

A single national patent is often insufficient in the scope of international marketing and competitive advantages. Patent protection is required especially in countries where significant competitors exist or where the operations of such competitors need to be suspended or blocked. There are three ways to seek for a patent protection abroad: 1. File a national application separately for each target country 2. Use the international patenting system (PCT‚ Patent Cooperation Treaty)‚ 130 member countries

3. Exploit the European patenting system (EPC‚ European Patent Convention)‚ 20 member countries Irrespective of the selected patenting approach‚ the patent must be‚ as a rule‚ granted‚ registered‚ and maintained in force in each of the target countries separately. For an optimum protection‚ this requires precise timing‚ and there is a method to assist international patenting by using so called Priority System. This means that the foreign patent applications ought to be filed during 12 months from the date when the domestic application was filed in the national patent office. If the priority system is claimed‚ the latter applications are considered to have arrived to the office at the same time as the earlier domestic application. The novelty and patentability will be assessed according to the time of the first application.

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Generally‚ the inventor or the company should start considering the feasibility of international commercialization immediately after filing the patent application. Within this context‚ it may sometimes be possible to use first (national) official actions as a test bed for the international potential of the invention and‚ hence‚ to scan the need to seek for international protection. Person(s) or companies may also need to seek external funding‚ if their own funds are insufficient. This means extensive mapping of applicable industrial suppliers‚ partners‚ intermediaries‚ and end-customers. When the appropriate partners have been found‚ the next steps ought to be initiated immediately. The applications made for financing organizations‚ for example need at least two months (often much more) for technical and commercial evaluation. Applying for a patent abroad causes significant expenses and takes time. Costs ought to be mapped well in advance. On the other side of the coin‚ it is normally sufficient to seek protection only in those countries where the product or the license will later be sold or marketed‚ or where the potential competitors operate. From the commercial and practical point of view‚ the sufficient extent of foreign protection has traditionally been about in 2-7 countries. When the national and possible international patenting system has been selected‚ and the necessary financing obtained‚ it is advisable to consult a registered patent attorney. A characteristic feature of telecommunications is that its hard- and software utilizes standardized signals and interfaces. (Often designed by international organizations‚ as for instance by ETSI‚ IEEE or ITU.) Emerging standards serve as a platforms on which companies strive to focus their intensive and costly investments in product development and‚ thus‚ to gain a competitive advantages for themselves. Practical application of patented inventions should then result for instance improved utilization of network resources‚ a higher user rate‚ and ultimately increased cash flow. A Case Study

The players who collected most of the profits in the boom of the 1990s were developing their technology already decades before. An example is the first patent that presented the Wireless Application Protocol (WAP) that was granted to Nokia already in 1984‚ in the US. Nokia is a company that has invested in cellular telecommunications by working with the Nordic Mobile Telephony (NMT) terminals already in the 1970’s. For Nokia‚ it was natural to continue with the GSM system in the 1980s resulting finally a very strong cash flow and market foothold boosted especially by the global ICT-boom in the late 1990s. At the same‚ Nokia’s rank in patenting statistics rose steadily indicating its awareness of the related competitive benefits.

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It seems to be a characteristic of the telecommunications industry that larger companies tend to patent relatively small devices and methods that they then integrate into patent families and patent portfolios for the purpose of patent protection and trade. Extensive patenting enhances competition protection, and brings additional cash flow for companies in the form of license incomes or royalties. This can form an important part of economical and technical bases of product development that are resilient against fluctuations of markets. Even single patents can be very useful. This is especially the case for start-up companies that are just building their intellectual capital, where these can form the implementational core of their business cases.

8.6.

Patenting in New Market Areas

How then, should a small, start-up, telecom-oriented company act in terms of protecting its knowledge when entering into a new market area with its first product? Let us suppose that the business strategy of a small start-up says that the company ought to strive to extend its operations into foreign countries and challenge strong, international competitors. As we have pointed out, in telecommunications, developing and protecting software is important. It is wise to consider applying patent protection for key innovations that cover software, if the target is in the US. If the company targets mainly for the European markets, then the software patent protection can be more complicated and is anyhow probably less important. (Often software can be protected by incorporating it into custom designed hardware-based circuits, whose reverse engineering takes time.) In any case, the company ought to carefully examine whether somebody has already created related patent barriers. This can be accomplished by examining the relevant patent databases and by checking preliminary patent examinations within the national patent office. Currently, the most common patent databases are Delphion, or the former IBM patent database and Espacenet (a publicly funded European patent database). It is recommended to carry out this research even when the company plans not to enter a foreign market - just as precautionary move to have an overview of the general status on the field. Patent literature includes many excellent references to chart domestic and foreign competitors key products and processes.

Chapter 8 University Based Research and Patenting

8.7.

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University Based Research and Patenting

When a research outcome contains at least one inventive step “not so obvious for a persons skilled in the field”, the commercialization steps depicted in Fig. 8.2. should be considered. Let’s assume that a telecom company is established based on an innovation. Presently, in university-based high-tech research projects in Finland, intellectual property rights, such as rights to patents, are given automatically to the inventor, if no other agreements are settled with the associated parties. (Contrary to the academic tradition, the core contents of an invention should never been disclosed to any scientific or commercial publication, if one wishes to patent it later.) In order to utilize the invention commercially, all the relevant patents and other intellectual property rights must be transferred or licensed from the inventor to the newborn company by assignments and license agreements. This is required also to enable appropriate funding because access of governmental resources and venture capital markets will thus be much easier. The company can then show its intellectual property rights on its balance sheets and can thus pass any “diligence tests” swiftly. When the IPR transferring agreements have been successfully executed (or even before the negotiations of technology transfer have started), the company or the researchers ought to reassure inventions’ novelty by examining patent databases. When evaluating the invention and reference patents and developing the business case, pertinent questions include: Is the life cycle of the potential technology, invention, or market sufficient to enable a payback of the investments?

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Are the challenges of patents in nearby areas easy to treat? Will the goal be to just produce products and software for sale to customers, or can the patented technology or solutions be also sub-licensed to third parties? Is the patent likely to be sued for patent infringement in the United States or elsewhere? Are there resources to go to court to defend the patent and ought there be insurance policies for possible court cases? Is the development rate sufficiently slow so that patenting will not become obsolete or unnecessary before commercialization? Are there enough reserves for a long-term patenting process that may take up to five years, as well as cost 100 000 for each application, as well as the additional amounts for possible prosecutions? If the answer is “yes” to most of the questions above, then the patenting process may be initiated by contacting a patent attorney. Often, universities use the services of several patent attorneys and are familiar with a multitude of disciplines. When the answer is “no” to most of these questions, there are probably some hits to former patents that partially or totally block the current patenting process. The patent examiner may have discovered other patents that restrict validity time of the patent, or even prevent its grant. In the former case, one must carefully examine the content of the prior patents and help to outline potential, feasible solutions. This consultation may be expensive, but at this early stage, every Euro is probably worth it. It can enable, for instance, to draw up the former patents or to redefine their area of applicability such that the validity time of the patent under consideration can be extended. If somebody has piled up barriers for a new patent, there is a need to consider whether it is worthwhile for anybody else to strive to operate in this particular field. An alternative is to search for new points of view for being able to call the field as some new one and thus to get around the obstacles. When drawing up the necessary paperwork for the start-up, there is a need to make sure that the company really has the patents at its disposal.

8.8.

Covering Patenting Costs

The patenting process is rather expensive. In some countries, it is possible to apply and to obtain patenting funding from public sources (in Finland, for example, from the Foundation for Finnish Inventions). In other countries, sources of private venture capital might need to be sought. External funding is

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usually required when a small company considers patenting abroad. At the same time with legal costs, there is often a need to start marketing and commercializing the invention. Product development, as software engineering, and testing requires financial and other resources. The company needs to make contacts to potential cooperation partners, possible subcontractors and maybe vendors depending on the considered project. The process of partner search and the negotiations may last a long time, perhaps 3–12 months, and for international patents even more. It is important to note that consideration of foreign patenting should be postponed until the technical evaluations of the domestic patent application have been received, that takes for instance in Finland, about 6-10 months from the patent application filling date. Even after this, the present market situation and company’s own funds available for product development should be considered. If the technical evaluation turns out to be favorable, filing the PCT application should be considered for international patenting. The PCT can provide patenting protection for as many as 130 different countries and delay the following higher patenting costs up to 30 months from the national application date. This period should then be used as efficiently as possible for product development and marketing. Generally, patent policy ought to be an essential part of a corporate business strategy. The natural aim is to protect product and company’s image and reputation against imitators and infringes. Another important aim is to safely enter new markets and also to defend the existing ones. Patent policy assists the company and the inventor in creating barriers against possible competitors and in increases potentially the market share of the patented product. It makes often sense to file new patent applications for product improvements during patenting process. When there are several domestic applications in progress simultaneously, only some of these may be worth the higher costs and effort of international patenting. Even large corporations and multinationals cannot afford to protect every improvement in their product pipeline. Neither should a small start up attempt such a feat.

8.9.

Licensing: Alternative for small start-up companies

In the event that the inventor or the company does not have financial or technical resources to develop the invention, the business potential can still be exploited with a licensing agreement. The license agreement gives the licensee a right to produce and sell a certain product or method protected by a patent or other intellectual property rights. Note that the license does not typi-

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cally give the licensee the right to deposit the patent or sell the rights to commercially exploit the patent to a third party. The license agreement specifies rights and obligations of a company to exploit a patent or other intellectual property rights, such as a design patent, a trademark, a utility model or technical know-how, that is not within its possession. Therefore, the “licensor” or license seller can secure cash flow from a licensee or a license buyer with a license agreement. The agreement gives the licensor also the opportunity to follow business development of the invention at the licensee’s end and hence to monitor its commercialization. There are also other motivations to consider licensing. The licensee wants perhaps to launch new products, or to expand contact network to enter in a new market, or to improve product’s position in old markets. It is also possible that one wants to expand product range without significant reinvestments in R&D. Licensing has proved to be one of the most successful methods by which both large corporations and small start-ups bring new inventions into the market. However, drawing up the agreement demands both highly developed legal and commercial expertise. Consequently, it is strongly recommended that you consult a professional, a lawyer, a patent attorney or a licensing expert before starting licensing measures or negotiations. The foundation of successful technology transfer by licensing is almost without exception based on a positive and progressive relationship between licensor and licensee. A good agreement satisfies both parties – from a technical, functional and legal point of view. The essential information to be considered in licensing negotiations include:

1. Parties and their background 2. Who has applied for the patent, who maintains the rights? 3. Exclusive, non-exclusive or sole license? 4. Scope of the license in terms of: a. The whole invention, or a part thereof b. Production, marketing, and/or selling c. Territory d. The time frame 5. Payments like down-payments, royalties and minimum royalties 6. Further co-operation, technical assistance 7. Validity of the agreement

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Entering a satisfactory agreement demands flexibility from both the licensor and the licensee. The licensee will often be most ready to pay the licensor’s money based only on the cash flow obtained from the sales of the licensed products or methods. On the other hand, the licensor will desire a down payment to make sure that the licensor will cover investments in product development and patenting. If the licensee’s profit is high, it makes sense that the royalty paid to the licensor can be high too. In contrast, if the sales profit is relatively low, the licensee may not be willing to pay the licensor a high royalty. The typical accounting rule of thumb for patenting and licensing professionals is that a suitable royalty percent is somewhere between two and eight percent of the revenue generated by the sales, not including the value added tax. Royalties in some sectors, such as chemical and process technology, are typically below two percent. When defining the royalties, one should take into consideration the possible further development costs to enable practical product launch. If these costs are considerable, royalty fees should be adjusted accordingly. If the invention is just a mere idea with a poorly developed industrial applicability, a reasonable solution is sometimes that there is no down payment at all. Special care must be paid to the exclusiveness or non-exclusiveness of the licensing agreement: The agreement can be exclusive so that the licensee has the exclusive rights for exploitation, while the licensor loses those rights or retains those rights. The agreement can also be non-exclusive so that there are more licensees than one, as well as possible commercial utilization by the licensor.

8.10.

Valuating Patents on the Balance Sheet

We can clearly allocate patenting protection costs in a company’s balance sheet, if the patents are assets assigned to the company. One applicable method is to calculate the application costs and sum them together, especially if no money have been generated with the assistance of the patent or the patent application. It is also possible that the inventors hold the patent rights but the company utilizes them and maybe sub-licenses the rights. If the company’s financing consists just of the investments by the owners or inventors in the firm, this method is recommendable. It will ensure that the patents will survive through the company’s possible bankruptcy because related assignments cannot be withdrawn, and the licensee’s patent rights return to the licensor. One should note that often there is not a single method to valuate the IPR. Even if the company is the original patent owner, there are no universal valuating rules. Whatever funding decisions there will be made in the firm, it is recommended for the company to apply for external venture capital when

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considering the patents and intellectual property. A couple of years ago investment bankers and analysts gave their estimates of a market value of multitude of dot.coms as being worth of billions of Euros or even more. As we presently know, many of these estimates have now changed drastically. A safe method in evaluating the long term value of a future technology in telecommunications sector seems to be to have a look at the incurred development, to use sense and vision, as well as to follow the relating patenting development.

8.11.

Conclusions

The process of patenting is a valuable asset in a high-tech company’s survival and profiling. However, in order to be successful, one needs to analyze the extent that a company really needs to seek patent protection, and especially to seek for foreign patents. The costs, the risks, and the possible infringements must be thoroughly evaluated. The mere patenting of an invention does not necessarily lead to the proper exploitation of the invention. It is important to remember that the most crucial challenge for the entrepreneur and inventor is to ultimately convert the invention and technology into a business case and revenue. In a well-known proverb, attributed to Thomas Alva Edison, inventiveness and creativity is claimed to contribute only one percent of the actual work. The other half, 99 percent is perspiration, filled with blood, sweat, and tears. The significance of proper, practical technology evaluation cannot be over emphasized. Often other patents form significant obstacles for ones own patenting. There are plentitude of cases, especially in the US, where somebody has already filled new, evolving field of high-tech with numerous patents, by thus practically blocking newcomers to enter the field. Sometimes, however, one succeeds to overcome this, sometimes penetration efforts go in vain, and sometimes a new technological focus is required for successful IPR policy. You should note that there are very good examples of high-tech telecom products and concepts, which have not succeeded commercially in the markets, like Apple Newton, HDTV and WAP, despite their proper patenting policy. One probable reason of failure has been in an over-confidence in the power of patenting and technological push. Patenting is a most useful tool in a high-tech company’s repertoire of protecting and developing its products, but in order to flourish, business always requires facts and a true vision of the meaning of the innovation.

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RECOMMEND READING How to get a European Patent? The Guide for Applicants. European Patent Office, http://www.european-patent-office.org, 6 Feb., 2003 Jones-Evans, D. & Klofsten, M. (ed.). Technology, Innovation & Enterprise - The European Experience, Macmillan Press Ltd., London, 1997. Paija, L. (ed.). Finnish ICT Cluster in the Digital Economy. Taloustieto Oy, Helsinki, 2001. Patent Application Guide. Foundation for Finnish Inventions, Espoo 1998 Virkkala, A. Protection of software-related intellectual property rights. Helsinki University of Technology, Lifelong Learning Institute of Dipoli, Espoo 1996.

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Chapter 9 FINANCE AND VENTURE CAPITAL MARKETS Peter Kelly, Helsinki University of Technology

9.1.

Introduction

In this chapter, we introduce the various sources of finance available to an entrepreneur from two distinct but related vantage points. We will first explore the sources of financing available at particular stages of venture development relying on a five stage model presented in the section that follows. After this, we discuss particular sources of finance including: own funds, family and friends, commercial banks, business angels, venture capital funds and public equity markets in more detail. In view of the focus of this book on the communications industry, a more detailed overview of market conditions in the venture capital and public equity markets is provided. The ability to successfully raise finance to support the transformation of an idea into a thriving entrepreneurial business implies that an entrepreneur knows where they are in the venture development process, who they should be asking and what should they be asking. Our aim in this chapter is to give some practical insights to address these very important questions.

9.2.

A Five Stage Model

The availability and appropriateness of particular financing sources depends a great deal on where you are in the process of developing your idea into a commercially vibrant business. The process can best be visualized as five highly iterative steps as shown in Fig. 9.1. We shall discuss in more detail each of the five steps in the sections that follow. 211

T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 211-234. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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Chapter 9 A Five Stage Model

9.2.1.

213

Idea conception phase

Look deeply into the genetic code of any successful technology-based firm and the DNA will reveal the strong presence of a great idea. Universities, research institutes and company laboratories provide particularly fertile ground for idea conception. Some companies, such as 3M, have even gone so far as to encourage employees to take time out of their workday to “think out of the box”. One of 3M’s most successful products ever, PostIt Notes, was in fact a commercial application of a failed product in a mainstream business, adhesives. 3M is not alone, however, as many large firms across a variety of different industrial sectors encourage their employees to think creatively by providing the organizational slack necessary to stimulate idea conception. The presence of organizational slack “by design” is one of the defining features of universities and research institutes and a major reason why higher educational institutions assume such a dominant role as “idea generators”. Look through the history of many prominent companies and you will find prominent “university ties” including such names as Cisco Systems (Stanford University), Netscape (University of Illinois), Nokia (Helsinki University of Technology), among others. In fact, when you think about every highly innovative area in the world, without exception, prominent universities are “fixtures”; Silicon Valley (Stanford, Berkeley), Route 128 Boston (MIT, Harvard), Southeast England (Oxford, Cambridge), Canada’s Technology Triangle (University of Waterloo), Research Triangle (University of North Carolina, Duke, and NC State), and countless others. Regardless of where the research is undertaken, the same discernable funding pattern emerges. In the conception phase, funding is usually provided by university internal funds, research funding councils and a variety of charitable foundations, particularly here in Scandinavia. The importance of external funding sources is pronounced outside of the USA as comparatively few universities have endowments on the scale of a growing number of largely private institutions in the US. Having said this, organizations like the National Science Foundation and DARPA do play a prominent role in the US research funding scene. What potential financiers at the idea conception phase will want from you is a completed application form and detailed research plan. Often these financing programs are run on a “call for applications” basis on pre-determined dates and evaluated by academic peers. The prospect of commercial benefit may be a consideration but the formative nature of much of the work completed in this phase makes this “informed speculation” at best. Having said this, if the proponents have a desire to explore commercial applications, great care must be taken to preserve the potential intellectual property to be created from the outset. What that means in practice is that proponents must exercise

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due care and diligence in documenting what they do and how information is disseminated.

9.2.2.

Idea validation phase

The idea validation phase is best described as the “R” in R&D. The public sector in many countries have encouraged research activities with a decidedly applied bias, leaning towards “D”, in a number of sectors including telecommunications, biotechnology, nanotechnology, information technology, and many others. By providing grants, the public sector is providing encouragement for subsequent development efforts by existing companies or new ventures. Corporate funding of research can also become available at this stage, particularly if test results are to be incorporated into the development of a prototype. Public sector financing organizations, like the National Technology Agency in Finland (TEKES), typically require the submission of an application that is subject to expert review. Increasingly, funding is also provided on a shared basis implying that a portion of the required finance be raised from other sources. Corporations are also keen to support research projects, particularly those that could have a material impact on their business operations. However, in view of the growing importance placed on intellectual property as a strategic asset, corporations typically impose stringent conditions on proponents as to the scope, timing, dissemination and ownership rights of the research results. In my experience, the bargaining power of the proponent in such situations is greatly enhanced as the number of companies potentially interested in the research project increases.

9.2.3.

Idea modeling phase

The focus of this phase shifts from the “R” in R&D to “D” efforts. In practice this distinction is very blurry given the iterative nature of the process of evaluating “what the research results tell us” and “how they can be used in practice”. Knowledge created gets embedded into tangible things (prototypes) that can be demonstrated to interested parties. In this phase, we begin to cross the chasm between “concept” and “market”. A paramount concern in this phase is to protect, to the extent allowable, the intellectual property created as a result of the research activities. Who owns the rights depends on where the research is undertaken and the nature of the funding. In some countries, like Finland and Sweden, residual ownership rights confer to the individual researcher unless specified otherwise. In the USA and in EU founded projects, residual ownership rights are

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typically contractually transferred to the university as a condition of employment. The ownership of intellectual property is a major, and often contentious, negotiating issue in situations where a research project is receiving funding from a corporation. Regardless of how intellectual property rights are developed, external financiers will want assurance from the outset as to who has legal commercialization rights. Securing patent, trademark and copyright protection rights is both complicated and costly and you are well advised to seek out competent legal advice on these matters. Patenting is further discussed in Chapter 8. For the purposes of the remaining discussion in this chapter, we will assume that an individual has the legal ability to exploit the intellectual property created as a result of their research activities and wants to start a new independent venture based on it. Where can this individual turn for guidance and funding patent and related activities? Many universities have established technology transfer offices that are well placed to provide help in this regard; a growing number of these have also set up “patent:funds” to cover legal, application and registration fees. In some countries, there are organizations, such as the Finnish Foundation for Inventions, that advises and funds entrepreneurs on such matters.

9.2.4.

assessment phase

In this phase, an individual has decided to pursue a new venture and may have established a company in which to embed intellectual property and other valuable assets. Prototypes developed in the modeling phase continue to be tested and refined with the aim of transforming something that “works” into something that “sells”. The entrepreneur must also begin fleshing out a business plan that is the necessary ingredient to garner resources in the exploitation phase. For many aspiring entrepreneurs, the assessment phase is an important milestone as successfully navigating through this phase implies increased personal commitment both in terms of time and money to the venture. In the formative stages of venture development, financial resources need to be provided by the entrepreneur and from “friends and family”. Putting your own capital at risk is a necessary signal to demonstrate your commitment to the venture particularly if private financiers are approached later on.

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9.2.5.

Exploitation phase

In many respects, the terms “exploitation” and “execution” are interchangeable in this phase. High growth new ventures share a number of common traits: They are led by a balanced team of individuals with relevant industry, sales and new venture experience They target profitable niches in high growth markets with products or services that compellingly and uniquely address genuine customer needs They support rapid growth by raising external finance early on to continually invest in research & development activities and, critically, their most important resource, people They embrace opportunities in markets other than their home Irrespective of whether funds are raised from private individuals, venture capital funds, institutions or public markets, financiers are attracted to proposals that consider growth to be a strategic imperative. The information requirements at this stage are considerable. In later sections we will highlight some of the differences between different funding sources in more detail. 9.2.6.

To summarize

Taken as a whole, the objective to be achieved in expending financial resources, regardless of the stage, is the same: obtaining useful information. Information is useful inasmuch as it helps proponents and financiers alike to decide whether to commit the time, energy and additional financial resources to a project. Critically, useful information also helps to reduce, but not eliminate, risks inherent to a project, be they of a technical, market, or production related nature. In these early phases, individuals need to rely on “failure tolerant” financiers like universities, research funding bodies, charitable foundations and government. The private sector becomes heavily engaged in the commercial phases of a project. However, they will expect the proponent to signal their financial commitment before they are prepared to invest themselves. To many investors, this is the “acid test” of whether an individual is genuinely interested in commercially pursuing their idea. In the sections that follow, we focus our attention on identifying the primary external sources of finance that are available for ventures intent on commercialization.

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9.3.

217

Sources of External Finance

In many respects, the question of “where can I raise finance” and “where is my business now” are integrally related. Businesses in their formative stages of development are very difficult to finance externally unless a prototype has been developed and tangible evidence of market demand exists. In the diagram that follows, the availability of various sources of finance are plotted in two dimensions; the horizontal axis representing the stage of venture development and the vertical axis representing the level of investment risk faced by the investor (read prospect of failure). What is abundantly clear is that the more developed the venture, the more choice an individual has with respect to deciding how to finance it. We now discuss each of the major funding sources available in turn.

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9.4.

Demonstrating Personal Commitment: Sweat Equity

To outside investors, the initial acid test of a “good idea” is whether the entrepreneur thinks it “good enough” to invest their own time and money into it. Personal commitment is a powerful signal to other resource providers of your intentions towards building the venture. In the words of a particularly successful private investor: “If the entrepreneur has nothing to lose, I have everything to lose by investing in them”. Many entrepreneurs mistakenly believe that the capital requirements for new ventures are especially large at the formative stages, but nothing could be further from the truth. Consider the results of a survey of the 500 fastest growing companies as identified by Inc. magazine. A quarter of the businesses started with less than $5,000, half with less than $25,000 and threequarters on less than $100,000. Fewer than 5% of the businesses began with more than $1 million in capital. Moreover, almost 80% of the Inc 500 companies relied on personal savings as a basis for starting. In almost every instance I have been aware of, entrepreneurs also contribute valuable time to the venture, so-called sweat equity, in lieu of salary or at substantially reduced levels of compensation than they could attain externally. Capital can be raised personally to invest in the business from any number of sources: Personal savings Severance packages Bank overdrafts Credit cards Pension plans Mortgaging the house Sale of personal assets A sound approach for entrepreneurs to take at the outset is to “bootstrap” the venture. Successful “bootstrappers” consider capital to be their most precious and scarce resource and in so doing display ingenuity in: Freeing up capital from any and all available sources

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Restricting cash outlays to those areas that are critically important to winning over support from external financiers, and by Designing a business model that minimizes capital requirements from the start, for example one start-up that I am familiar with was able to convince customers to “pre-pay” for services by charging a retainer fee up front

9.4.1.

Family and friends

As the entrepreneur exhausts personal funds, initial approaches are often made to those individuals best positioned to assess their personality and intentions, their immediate family members and friends. In fact, family and friends is the second most important source of capital after personal funds. Approximately one in ten of the Inc 500 fastest growing companies relied on family and friends for seed capital. Typically, family members and friends are financially unsophisticated, place small amounts of capital at risk and exercise little real influence over the business. Two caveats need to be raised, however. The presence of a large number of active, minority shareholders can dissuade professional investors from participating later on. As importantly, if you decide to bring on family and friends as investors, you must be prepared to lose them if things go wrong down the road, as they often do with new ventures. If you wish to raise capital from family and friends, I have two bits of advice. First, be very clear with the family member or friend that you do not want their active involvement in the business unless their skills and experience investing in or managing a new venture warrants it. Second, I recommend that you draft a shareholders agreement clarifying your joint understanding of each other’s rights and responsibilities. Of great importance at an early stage, is to agree on the manner in which family and friend investors can be bought out.

9.4.2.

Commercial banks

For many entrepreneurs, the logical first place to seek out “equity capital” is a visit to the local bank. In most instances, this initial approach is a disappointing one for entrepreneurs as they discover two fundamental truths about debt. First, debt instruments by design are not well suited to finance the needs of young businesses. Second, the return earned by the bank on debt finance is far lower than that required by external equity investors. In short, banks are in the business of low risk, low return lending not high risk, low return investing. Banks exist by ensuring that loans are made to applicants who can and do

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repay. Their very existence depends on their ability to avoid costly “loan mistakes”. When advancing any loan, banks look to the applicant’s character, capacity to repay, and the collateral or security available to pledge in support of the loan. In assessing character and capacity, an established track record, as demonstrated by financial reports, is often a necessary prerequisite for any deal. Not surprisingly, a start-up or very young venture has not been in existence long enough to establish a “track record” to evaluate. Moreover, as the asset base of many new ventures is largely intangible in nature, there is little in the way of “hard security” (such as land, buildings, equipment) to support a loan request. A few words of advice when considering raising debt finance. First, approach the bank with the “right request”. Banks are most comfortable providing working capital loans and fixed asset financing. Second, approach the bank at the “right time”. By this I mean, when your venture has an established track record of performance. Third, be prepared to be asked to pledge your personal assets in support of business loans, so-called “personal guarantees”, particularly in situations where the relationship with the bank is relatively new. Fourth, a proportion of the finance required to acquire assets on a term loan basis will need to be provided by you from outside sources other than the bank. Finally, fifth, bankers do not like surprises, you are well advised to keep them thoroughly informed of your plans and progress well before and particularly after raising debt finance. 9.4.3.

Business angels

There is growing international awareness of and appreciation for the important role played by private individuals, so-called business angels, as a source of equity capital for entrepreneurial firms. Many prominent firms including Ford Motor Company, Amazon.com and Apple Computer, among countless others, have been started on the back of capital provided by business angels. Collectively referred to as the informal venture capital market, business angels are by far the largest source of external capital for particularly early stage firms in most major capital markets, including the USA and UK. By some accounts, there are more than three million business angels in the USA who invest more than $50 billion per year in thirty to forty thousand businesses. To put these figures into perspective, compared to the entire US venture capital industry, business angels invest five times as much capital in thirty to forty times as many ventures as do venture capitalists. Based on extensive international research, the emerging portrait of a “typical” business angel is a middle-aged male who has started, and likely

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successfully cashed out, of at least one venture in which they have had a direct role in building. They are attracted to situations in which their business experience and contact base is of relevance and where the prospect of capital gain in four to seven years is present. From the outset, most business angels are also intent on being actively involved in the businesses in which they invest. Rather than being a way for investors to “check up” on the entrepreneur, active involvement is a key non-financial driver for the investor. They see their involvement as potentially improving the odds of success and, as importantly, being a “fun thing to do”. Much like venture capitalists, a proposal must offer the prospect of substantial capital gains on invested capital and hence must be a “growth” story. Both want to see a detailed business plan that will be critically reviewed. Unlike venture capital funds, that invest other people’s money, business angels place their own capital at risk and as we shall see in the section that follows, they “do not need to invest”. Aside from this, another critical difference between these markets is that of visibility. There are many public directories available providing contact details of venture capital funds. However, in an effort to control the level of unsolicited deal flow being brought to their attention, business angels prefer to keep an anonymous profile. The challenge for entrepreneurs, therefore, is to find the right business angel and the task is not easy as the informal venture capital market has been aptly described as: “a giant game of hide-and-go-seek with everyone playing blindfolded!” Business angels are an integral element of a firm’s financing strategy because they place smaller sums of capital at risk at earlier stages of development than do venture capital funds. More importantly, the breadth and depth of business, industry and new venture experience are critical resources in the inceptive stages of venture development for any business. But how can you find a business angel if the market is practically invisible? First, there are a number of organizations that provide forums to bring together entrepreneurs and business angels. For instance, here in Finland, there is a Business Angel Matching Service managed by SITRA. In the UK, Professor Colin Mason compiles a listing of business angel matching services on an annual basis available on line from the British Venture Capital Association (www.bvca.co.uk). Second, specialized publications have emerged profiling potential investment opportunities to business angels. The longest established of these is Venture Capital Report (www.vcr1978.com). Third, entrepreneurs have been able to identify potential business angels by asking companies that have raised finance externally from these individuals and through intermediaries such as lawyers, accountants and consultants. From my long experience of dealing with business angels in the UK, USA and elsewhere, here are a few words of advice. First, your business plan must not only be a convincing growth story but must captivate the imagination of

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the private investor; expect a long fundraising process and numerous false leads because many individuals will respond “nice opportunity but not for me”. Second, you must want more than the business angel’s money: if it is just money you are after, look elsewhere. Active involvement is a major nonfinancial motivation for investors, you must specify very clearly what you want from them. Third, you must be able to demonstrate that the prospect of substantial capital gains is available. Business angels are not philanthropists, at least not the successful ones, and need to be convinced of the business merits of the deal presented. Fourth, entrepreneurs should do their own background checks of the investor as the investor will do of them. Ask to speak to entrepreneurs who have raised money from this individual before. Fifth, the personal chemistry between the parties has to feel right or the deal is not worth doing at all. Finally, sixth, the most productive way to meet private investors is to be referred to them from an individual who is known to them and trusted by them. Most successful deal completions start from an introduction made by a close business associate or personal friend of the investor.

9.4.4.

Venture capital funds

Venture capital has been in existence for hundreds of years but in its modern organized form has only flourished in the past decade or so. A venture capital fund is typically a tax efficient vehicle for institutional investors, such as pension funds, insurance companies and banks, to pool their resources together around a team of fund managers who acquire equity stakes in aspiring entrepreneurial ventures. Most venture capital funds are arranged as term limited partnerships. The fund is established in a way that “limits” the potential losses of fund investors to the amount of their capital contribution and is set up with a limited lifespan, typically ten years. Fund managers are incentivized by a small annual fee to cover operating costs and, more importantly, by a percentage carried interest in the capital gains realized by the fund, typically 20% - 25% net of any preferred returns to fund investors. Over the term of a fixed life fund, the focus of activity moves from finding new deals, through to follow-on investing in existing portfolio companies and finally to realizing value through exits (trade sale, public listing). While the odds of finding a venture capital fund is highly probable, the prospect of actually securing venture capital backing for your venture is very remote. When a prominent venture capital fund manager in London was asked: “What proportion of deals presented to you actually get funded?” His reply was: “Two or three in a hundred.” When asked how the odds would change if the business plan were simply sent to him “cold” (no referral), they lengthened to: “One in five thousand or practically zero!” Why is this the

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case? Experience has shown that for every ten deals a venture capital fund actually does do, two are failures (involving some capital loss), six are disappointing (the so-called “living dead”), and two offer spectacular returns (“golden geese”). The search for “golden geese” is the essence of venture capital investing. How do fund managers compensate for their inability to always pick “golden geese”? They evaluate the merits of proposals on the basis of very high hurdle rates to compensate for the risk. To them, the younger the company, the greater the risk and thus the higher expected return. While difficult to generalize, the expected returns on a first round seed investment (no sales yet) is in the order of 80%+ per year compounded. Expected returns for companies that are selling and profitable can also be as high as 30% - 40% per year compounded. To put this in perspective, a $1 seed investment made today would have to grow to almost $20 in five years just to meet the return expectations of investors. This illustration reinforces the importance of a strong growth story if an entrepreneur is seeking out venture capital.

9.5.

Fund Raising Climate

There has been a virtual explosion in both the number of new funds being formed and the amount of capital inflows into the US and European venture capital markets in recent years as demonstrated in Table 9.1.

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Without doubt, the USA is the most developed and by far the largest venture capital market in the world. Up to the end of 2001, the cumulative amount raised by private partnerships based in the USA stood at $360 billion. However, what is truly astounding is that fully 60% of this total has been raised since 1 January 1999. To get a sense of how the capital pool has dramatically changed in size, in 1991 (10 years ago), only 44 new funds were established that raised a total of $1.6 billion in capital. A number of individual funds were able to successfully raise in excess of $1 billion apiece in 1999 and 2000! It is also important to note that the average fund size has increased dramatically from $35 million in 1991 to spike at $175 million in 2000. Even in the relatively difficult fundraising conditions that followed the market correction late in 2000, the average fund raised in 2001 still was a healthy $150 million. Comparatively speaking, the venture capital market in Europe is generally much younger and smaller than the USA. Since 1990, the cumulative capital raised by private funds based in Europe totaled a little more than $80 billion. The average fund size is generally much smaller but has been somewhat more stable than in the USA; increasing from $43 million (1991) to in excess of $70 million by 2000. Similar to the situation in the USA, almost 70% of the capital funneled into private funds have occurred since 1 January 1999.

9.6.

Investment Focus

If there is some key distinguishing characteristics of the US venture capital market as compared to Europe’s in terms of investment activity, it is these: In a “typical year”, more than one-third of the deals completed in the USA are at seed or start-up stages attracting 20% and more of the capital invested in that year. While comparable figures vary across individual European countries, the proportion of deals in formative stages of venture development is roughly similar (30%+), however, the proportion of capital invested in such deals is only half of that observed in the USA (10%). Recent evidence suggests that the average seed deal size in the USA ($5 million) is more than double that observed in Europe ($2 million), In the early stage, US venture capital funds invest more than three times ($7 million) as their European counterparts ($2 million). Management buy-out transactions are the predominant focus of investor activity in Europe accounting for typically 60%+ of capital committed in any given year. In the US, venture capital funds appear not to participate in these transactions at all.

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US venture capital fund activity is more highly targeted on high technology sectors than is the case in Europe. In the ICT sector which includes: internet, communications, computer hardware and software, semiconductors and electronics industries, more than three-quarters of the deals and almost 80% of the capital invested is targeted to this sector alone. Typically less than one-third of the capital invested in Europe finds it way into high technology sectors; not altogether surprising given the importance of management buy-out activity. At the risk of over-generalizing, we can conclude that bigger funds make bigger bets in more highly targeted sectors at earlier stages of development in the USA than appears to be the case in Europe. There are indicators that this situation is changing as we shall see in the section that follows.

9.7.

Venture Capital and the Communications Sector

Of perhaps greater interest to the readers of this book is not overall industry trends but rather those relevant to the communications sector as a whole. Disbursement activity for the sector has been summarized for the period 1 January 1990 through to 31 December 2001 inclusive for the US (Table 2) and European (Table 3) markets based on data compiled by Venture Economics. Relying on their classification schemes, disbursements are also summarized by specialized sector as follows: wireless communications, data communications, commercial communications (radio, television broadcasting, cable, and the like) and telephone related (fixed line, long distance services and the like). In the USA, the amount disbursed has increased continually through to 2000, peaking at more than $16 billion. As with every other industry sector, there has been a significant pull back in disbursement activity in 2001 coinciding with the economic and equity market downturn in the US market. The proportion of capital invested in seed and startup companies is relatively consistent at around 20% with average deal size creeping upwards in the range of $10 million. Expansion and later stage financing rounds in excess of $15 million are now common.

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Data communications is the predominant target for invested capital but it is interesting to note the growing investor interest in the field of wireless communications. Communications sector funding in Europe was anemic in the 1990 to 1995 period as compared to the USA. While the situation has shown improvement, evidence from 2001 supports the view that the level of investment is less than one-tenth of that in the USA in absolute dollar terms. The propor-

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tion of funding targeted at seed and early stages is now in line with the USA (25%+) after a sustained period of relative inattention. The average deal size irrespective of stage appears to be one-half to two-thirds less than that of the USA. Consistent with the view that Europeans have more openly embraced wireless technology, the proportion of funding directed at that sector is markedly higher, particularly in the past two years. Unlike their US counterparts, European venture capitalists appear to be funneling proportionately less capital into data communications ventures. What can we conclude from this? Fewer numbers of firms are getting funded with fewer dollars in Europe on a consistent basis than is the case for the US based venture capital funds. In part, this is due to the fact that relative to their European counterparts, US based venture capital funds have: More capital available to invest Been in business a lot longer and are more experienced Greater pool of entrepreneurial businesses to back as a result of their sustained effort to invest in new ventures as opposed to restructuring existing ones as is the case in Europe The observed gap will inevitably narrow over time as: Restructuring opportunities dissipate; investors will increasingly have to focus on financing new as opposed to established ventures The substantial expertise European investors have gained over the years restructuring “old economy companies” is applied to the restructuring of “new economy companies” taking place as we speak European investors gain experience as investors thereby increasing the value-added they can bring to invested companies Established incumbents raise follow-on funds thereby expanding the available capital pool to invest Having said this, there has been a marked slowdown in investment activity post 2000, a fact that has been highly publicized.

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However, it should be noted, that compared to 1999, the level of investment activity has remained remarkably robust through 2001. In part, this is a result of the need for venture capital funds to provide follow-on capital for

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their portfolio companies, particularly as raising fresh capital from public equity markets is simply not an option at the present time. It is to a discussion of initial public offerings that we now turn.

9.8.

Initial Public Offerings (IPOs)

Many aspiring entrepreneurs dream of taking their company public. However, in reality, relatively few actually do. Throughout history, there have been periods where public equity markets have been able to offer investors spectacular returns and entrepreneurs access to large pools of capital to finance growth. In fact, we have just lived through an unprecedented period of “public equity frenzy” that peaked in 1999 and 2000. Past history also sug-

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gests that what rises also falls back to earth and such is the case with public equity markets in 2001 as we shall soon see. To give you a sense of just how unprecedented 1999 and 2000 actually were, consider the following example. Sycamore Networks (Nasdaq SCMR), a well-known Boston-based optical networking company, was established by Desh Deshpande and Dan Smith in early 1998. At the time of going public, eighteen months after starting (October 1999), Sycamore had never posted a profit yet was able to command a capitalization of $1.5 billion based on an offering price of $18 to $20 per share. The share offering was oversubscribed by a factor of 11, the offering price was subsequently raised to $38. On the first day of trading, the opening share price was $270, valuing the business in excess of $20 billion, a business that had been in existence less than two years and never produced a profit! In the judgement of investors Sycamore was worth as much that day as such established corporations as Kodak, Fuji Film, Nike, Heineken, BMW, or Seagram. Clearly investors were placing a lot of weight on the future prospects of this company. What has the stock done since you ask? As I write this, the stock is trading at under $20 per share, split adjusted; many investors are clearly “licking their wounds” from this story. What should you as entrepreneur consider in seeking to raise capital from public markets? It is to this question that we now turn our attention.

9.9.

Going Public: Some Considerations

We shall briefly summarize some of the key advantages and drawbacks associated with the decision to take a firm public. Some of the most often cited advantages or benefits from going public include: To enhance corporate visibility and profile as a means for securing new sources of finance, building strategic partnerships and attracting talented employees To raise large sums of capital to support future growth and development of the business To provide an exit mechanism for outside investors in the business To create partial liquidity for the entrepreneur while retaining a measure of managerial influence over business operations Among some of the most significant drawbacks of going public include:

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The costs involved in the process of going public including the preparation of a prospectus, legal documents, underwriting fees and the like can be quite large (up to 10% of the amount raised in some instances) Entrepreneurs are expected to retain a significant equity stake post IPO, thus they cannot expect to achieve total liquidity Being public implies increased time and attention being devoted by senior management to matters related to disclosure of material facts that could have some influence (positive or negative) on the share price An increased focus on meeting short-term earnings per share targets often to the detriment of the longer term growth of the business In my experience, the other factor that is absolutely critical in the decision to “go public” is timing. Companies that raised capital in 1999 and 2000 found investors that were eager to put their money down at valuations that would make any entrepreneur and venture capital investor breathless. What we do know from past experience is that the health of the venture capital market is inextricably tied to the health of public equity markets. When public markets are providing healthy returns and are receptive to initial public offerings, the level of venture capital fundraising and investing activity increases almost lockstep. However, the other thing that experience suggests is that “what goes up can and does go down”.

9.10.

Public Equity Market Overview

In Table 4, we provide an overview by year of the public equity market fundraising activity for the communications industry sector as a whole. Clearly, 1999 and 2000 were spectacular and atypical years for raising money. On average, firms raised in excess of $160 million by way of an initial public offering although it need be said that there is tremendous variation around this number. Of greater interest perhaps for entrepreneurs is the inherent price per % of equity sold, computed by taking the funds raised per venture divided by the size of the equity stake on offer. Between 1990 and 1995, the price per % of equity was remarkably stable in the range of $1.3 to $1.4 million give or take. This price rose dramatically beginning in 1996 to peak at just a shade under $11 million in 2000. Despite a substantial market pullback in 2001, two data communications companies were able to command valuations of more than $14 million per %. Having said this, we should not lose sight of the fact that public equity markets are effectively “closed” as a viable option for communications ventures at the moment.

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In Table 5.5, we provide a summary of public offering made by year and classified by industrial sector. In recent years, data communications companies appear to be the dominant source in terms of number and amount raised for public offerings. As a major target of venture capital investment, this is not altogether surprising as IPOs are a highly preferred mode of realizing on investments made. Wireless communications has also been a sector that has attracted a lot of capital particularly in 1999 and 2000. As we mentioned in our earlier discussion, investing in telephone-related proposals is experiencing a renaissance of sorts among venture capital funds and this is also broadly reflected in the renewed interest shown in this sector by institutional and individual investors at large. Cable television companies are also at the forefront of developments of the “broadband society”, particularly in the USA, and have regularly tapped into public markets for growth capital, especially so in 1999. What is the insight to be drawn from all of this? Simply this, look to the

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sectors in which venture capital funds are investing now to become the IPO candidates of the future, market conditions willing.

9.11.

Concluding Remarks

In my experience, the keys to successful fund-raising are in knowing what to ask, who to ask and when to ask. Making a clearly inappropriate request to the wrong source at the wrong time sends a very powerful signal to resource providers that you have not carefully thought through your fund-raising strategy, an easily avoidable mistake. In this chapter, our aim was to provide you with a framework for thinking about what types of finance are appropriate as the project develops. Your ability to successfully negotiate will critically depend on the information you can give resource providers as to the inherent risks of the project, and crucially your anticipated responses for dealing with them. In this respect, the experience of 3M in matching risk and resource commitments is insightful. Throughout much of its early life, the 3M philosophy was “spend a little, make a little, sell a little”, “spend a little more, make a little more, sell a little more”, and so on. In short, projects were financed as a series of experiments with 3M maintaining an option to abandon the project if circumstances warrant. Entrepreneurs are well advised to think about the major development milestones in their own ventures and tie fund-raising efforts to these milestones, such as developing a prototype, making the first sale, establishing an international office, and so on. In so doing, both you and your external financiers maintain the option to reevaluate whether to finance the next milestone based on information and experience from the previous one. In closing, here are four bits of advice. First, be prepared to face resistance. Few outsiders feel as passionately about the uniqueness and the pathbreaking potential of your ideas as you do. Second, be prepared for tough questioning, particularly from private sector financiers. The more information you can provide them about the associated risks and competitive landscape the better. Third, be prepared to hear “no” a lot. True entrepreneurs are not deterred by “no” and persistently seek out someone “more enlightened” who will say “yes”. Finally, “timing is everything”. As we have demonstrated in this chapter, private equity markets can be “white hot” (1998-2000) or “freezing cold” (2001). While it appears that venture capital funds have temporarily “lost hope”, I can assure you they have not “lost faith” in financing promising start-up ventures. Recent market sentiment cannot hide the fact that developments in the communications sector are both exciting and potentially disruptive. The question in every one’s mind at the moment is “when does the fun really start?”.

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REFERENCES [Adams, 2002]

Adams R., A Good Hard Kick in the Ass: The New Rules for Business, Random House, New York, 2002.

[Amis, 2001]

Amis D. and Stevenson H., Winning Angels: The 7 Fundamentals of Early Stage Investing, FT Prentice Hall, London, 2001.

[Benjamin, 1996]

Benjamin G. and Margulis J., Finding Your Wings, Wiley, New York, 1996.

[Benjamin, 2000]

Benjamin G. and Margulis J., Angel Financing: How To Find and Invest in Private Equity, Wiley, New York, 2000.

[Lang, 2002]

Lang J., The High-Tech Entrepreneur’s Handbook: How To Start and Run a High-Tech Company, Harlow: FT.com, 2002.

[van Osnabrugge, 2001]

van Osnabrugge M. and Robinson R., Angel Investing: Matching Start-up Funds With Start-up Companies, Jossey-Bass, San Francisco, 2001.

Chapter 10 ROLE OF UNIVERSITIES IN THE PRODUCT DEVELOPMENT PROCESS: Strategic Considerations for the Telecommunications Industry1 Alok Chakrabarti, Industrial Performance Center Massachusetts Institute of Technology & New Jersey Institute of Technology

10.1.

Executive Summary2

The competitive environment for most firms has been transformed by global competition, rapid changes in technology and shorter product life cycles. Innovation has become critical for survival in this competitive environment. The telecommunication industry is the best example of a dynamic global market environment. The average life cycle of the products in this industry has reduced to less than a year. The diversity of communication standards across the countries and rapid changes in the standards with the evolution of technology is exacerbating the uncertainty and complexity of new products. Successful companies have reduced the cost of innovation and risks by outsourcing. The problems of product development in a dynamic industry like, telecommunication can be explained in terms of newness of the technology, customers and trajectory of the technology development. Classical models of product development assume the process to be a linear one, although the process of technology development differs with these parameters. The role of the company changes with the novelty of the technology and novelty of the market. In cases of new technology intended for an existing market, the firm has a dominating role. Customers take an increasingly important role in situations where existing technology are modified for new applications. In the case of new technology intended for new customers, market and technology evolve in a symbiotic way. The mobile communication area is representative of this phenomenon. 235

T.O. Korhonen and A. Ainamo (eds.), Handbook of Product and Service Development in Communication and Information Technology, 235-254. © 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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New market opportunities have been created by the continued growth of the world economy. Better access to scientists and technologists in various parts of the world has provided great opportunities for outsourcing of technology development. Governments and financial institutions are providing new incentives for inter-organizational collaboration. Various research organizations, either contract research or cooperative research organizations, are also important partners in the product development process. University- industry collaboration provides access not only to leading edge technologies, but also to highly trained students, professors and university facilities. Faculty and students can keep up with the practical problems and gain access to knowledge developed outside the academe. Firms differ in their strategic orientation for developing a relationship with universities. Large firms are interested in working with universities in the areas of technologies that are not in the core of their business. They use universities for exploring technical areas that have a long-term perspective. Smaller firms are more interested in competence building in their core business areas and solving current problems. Working with universities also provides a level of flexibility in pursuing different technological trajectories either sequentially or in parallel. This is important in a dynamic technical environment. Internal R&D groups often become fixated in certain technologies and thus develop a culture of insularity whereas universities are often sources of new ideas. The faculty and students are unfettered by corporate culture and tradition and therefore are able to approach the technical problems from a creative perspective. Since the growth of the telecommunication industry is often driven by a young generation, students in universities are an important source not only for technical ideas but also for important market information. Building effective relationships with universities for technology and product development is a complex process. Universities also differ in terms of their capabilities and strategies. Policies related to management of intellectual property rights are areas of concern for both industry and universities.

10.2.

Introduction

The competitive environment for most firms has been transformed by global competition, rapid changes in technology, and shorter product life cycles [Ali, 1994; Bettis, 1995; Quinn, 2000]. The telecommunication industry is the best example of a dynamic global market environment. Innovation has become critical for survival in this competitive environment. The average life cycle of the products in this industry has reduced to less than a year. Moreover, the diversity of communication standards across the countries and rapid

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changes in the standards with the evolution of technology is exacerbating the uncertainty and complexity of new products. Successful companies have reduced the cost of innovation and risks by outsourcing. A few scholars [Parkhe, 1993; Pisano, 1990; Shan, 1994] have examined the interorganizational collaboration in development of new technology. The problems of product development in a dynamic industry, like telecommunication, can be explained in terms of newness of the technology, customers and trajectory of the technology development. Classical models of product development assume the process to be a linear one. But as LeonardBarton (1995) has shown the process of technology development differs in the following parameters. As shown in Fig 10.1, we observe that there are many different processes for product/ technology development. The role of the company changes with the novelty of the technology and novelty of the market. In cases of new technology intended for an existing market, the firm has a dominating role. Customers take an increasingly important new role in situations where existing technology is modified for new applications. In this figure the top right quadrant represents the process where market and technology evolve in a symbiotic way. The rapid development of the telecommunication industry, particularly in the mobile communication area is representative of this phenomenon. There are many compelling reasons for outsourcing innovation by a firm [Quinn, 2000]. New market opportunities have been created by the continued growth of the world economy. Most of the major companies in Europe and Japan have set up R&D centers in places like the Silicon Valley and Boston in the US and Cambridge in the UK. These centers are conduits for developing relationships with the premier universities in these regions. Better access to scientists and technologists in various parts of the world has provided great opportunities for outsourcing of technology development. The development of information and communication technology has helped effective interaction among the various individuals and coordination among geographically distributed groups. Finally, governments and financial institutions are providing new incentives for inter-organizational collaboration.

10.2.1.

Universities as engines of regional development

With the growing importance of knowledge-based industry, policy makers in the private and public sectors have realized the importance of universities in regional economic development [Chakrabarti, 2002]. The role of Massachusetts Institute of Technology in the growth of industries in the greater Boston area and Stanford University in the Silicon Valley area is quite well

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known. One can observe a similar experience with other universities in the US and elsewhere. After the economic collapse of Soviet Russia, Finland experienced a deep recession with high unemployment during the early nineties due the loss of this principal trading partner. Universities at that time became the important engines of economic development in Finland. Helsinki University of Technology became a major center for growth in wireless communication and information technology. The University of Oulu helped build up the Oulu region’s capabilities in electronics and information technology. Tampere focused on electro-mechanical and automation industries. The University of Turku contributed to the development of Pharmaceuticals and chemistrybased innovations. The contribution of Hermia, a university-based business development effort at Tampere can be seen through employment growth in the regions as shown in Table 10.1.

Although none of the regions we studied in which the US universities are located experienced economic reversals as dramatic as those in Finland, each has had its share of economic crisis. Newark and its surrounding area have a long history of economic stagnation, and NJIT has embraced economic development as one of its missions. Worcester Polytechnic (WPI), located in cen-

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tral Massachusetts, is a region that has experienced an erosion of its economic base with the demise of many mechanical and

electrical manufacturing industries. WPI has been a stimulus to regional growth through its contribution to the development of new industrial activity in information technology and more recently in biotechnology. In the Bethlehem area, long disadvantaged by the decline of the steel industry, Lehigh University has become a facilitator of economic development in the region. Rensselaer Polytechnic Institute (RPI) is located in the capital district region of the state of New York, which has struggled through a series of economic cycles and where the dominant company, General Electric, has continued to downsize its local operations including the corporate research center. Both RPI and the nearby State University have set up incubators for new companies and other related activities.

10.3.

Technology and New Product Development Process

Fig. 10.2 illustrates the process of technology and new product development. A concept for a new technology or product is developed through a fu-

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sion of the perception of the technical opportunity in hand and the recognition of potential market demand. Depending on the availability of technical information, further research is needed for development of the technology or product concept before it can be commercially exploited. The technological context is important and acts as a bank for information from where the researcher both receives information and contributes to it by advancing the state of the art in technology. The economic and social conditions of the country are important determinants for demand. Sources of technology and product concepts are quite varied. First and foremost are the company’s internal organizations, such as the corporate or divisional R&D centers, and new product groups. As observed earlier, customers are also important sources of ideas for technology and products. Various research organizations, either contract research or cooperative research organizations, are also important partners in the product development process. Scientists at CERN, the European cooperative research organization, conducted the pioneering work that has led to the development of The Internet. Fraunhofer Institute in Germany has been involved in the development of MP3 technology that has revolutionized the music industry and created many new possibilities in the telecommunication industry. The German chemical industry has benefited from contributions made by public research organizations, such as Fraunhofer Institutes, Max Planck Institutes and others. VTT, the Finnish National Research Organization, has played a significant role in the development of the mobile telecommunication industry in Finland. Finally, universities are also important sources of new technology and products. Universities of Technology at Helsinki, Tampere and Oulu in Finland have played a key role in the mobile communication industry in Finland. Competitors are also important sources of ideas for new products.

10.4.

University-Industry Relationship

University-industry relationship is not a new phenomenon. Germany was the pioneering country where a university-industry relationship helped create the pharmaceutical industry in the early 19th century. The United States has taken an active role in developing and fostering university-industry collaboration. There are many mutual benefits to a close relationship between a university and an industrial firm. Firms gain access not only to leading edge technologies, but also to highly trained students, professors and university facilities. A firm can gain prestige and acceptance in its stakeholder community through its association with a prestigious university. Polar Electro Oy, a manufacturer of a wireless heart monitor used by athletes and other fitness enthusiasts, has worked with a large number of universities and medical in-

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stitutions around the world for testing and developing its products. Polar Electro, headquartered in Oulu, is now an internationally known company in the sports industry.

Universities can augment their funding sources by working with the industry. This relationship has become an increasingly important consideration in most countries as the public level of funding for higher education has become scarce. Costs of operation of institutions of higher education have outpaced the other indices of price increase. University administration feels the pressure to supplement their funding by various means, one of which is of

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course sponsored research. Working with the industry provides other pedagogical and academic value for the students and faculty. Faculty and students can keep up with the practical problems and gain access to knowledge developed outside the academe. This is particularly important in many emerging fields where academic research and publication usually lags behind industry. Industry-university collaboration takes several forms. The National Science Foundation in the US identifies four inter-related components in the university-industry relationships: research support, cooperative research, knowledge transfer and technology transfer. Research support involves contributions of both money and equipment to the universities by industry. This type of contribution is valuable as it provides great flexibility to upgrade laboratories and develop programs in certain areas of interest. Recently, a consortium of 23 companies has contributed about 7.8 million Euros to several Finnish technical universities to upgrade their programs in information and communication technologies.4 Although corporate support of universities has been unrestricted in the past, it is more common now to have these funds targeted for specific purposes. Universities have developed many cooperative research consortiums with industry to pursue research and development in some common areas of interest. In the United States, the National Science Foundation has actively promoted such formation of cooperative research through the establishment of Engineering Research Centers (ERC) and Industry University Cooperative Research Centers (IUCRC). These centers provide formal structures to advance technology through various types of collaboration between a university and industrial firms. Contract research, by a research center or a professor, is often a vehicle for collaboration between university and a firm. In Finland, TEKES, the Finnish Technology Development Agency promotes the industrial collaboration by requiring that all of its projects be collaborative. The policy implemented by TEKES not only promotes interaction between a firm and a university, but also decentralizes the control and monitoring of the projects. Knowledge transfer involves many activities that include both formal and informal means of communication, interactions and personnel exchanges at student and faculty levels. Involvement of the firms in the academic programs of the universities is a major mechanism for knowledge transfer. Often, students work on corporate problems for their theses and dissertations in many technical universities in Finland. Cooperative education programs, internships and job placements for students and recent graduates provide means for knowledge transfer. Technology transfer is generally based on the collaborative research with the industry. The Department of Agriculture in the United States developed the agricultural extension service model for transferring agricultural technol-

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ogy to the farmers where the universities were key sources of information. The concept of “land grant” college was developed by an act of the US Congress in 1862 for “agriculture and mechanic arts, scientific and classical studies, and military tactics for the liberal and practical education of the industrial classes.” Major public universities in the US have been established as land grant institutions with a clear mandate for knowledge and technology transfer.

10.5.

Roles of Universities and the Nature of Scientific Research

Building effective linkage with industry is not easy. Universities are traditionally viewed as bastions of learning and knowledge creation. The culture of academic freedom cherished by the faculty creates problems when a firm or an agency dictates the terms and conditions of support for research. However, the culture is fast changing. During the Second World War, universities and professors were active participants in developing and implementing knowledge that went into the war effort. Since then, the military has been a big supporter of research and graduate education in many universities in the US.5 In discussing the type of research that should be done at universities, we often think in terms of basic vs. applied research. Such one-dimensional analysis does not help to understand the complexity of the issues involved. Stokes (1997) developed a quadrant model of scientific research as shown in Fig. 10.3. The upper left-hand quadrant includes basic research that is solely inspired by the academic curiosity of the researcher without any considerations for its practical value or utility. The work of Niels Bohr can illustrate this. Bohr’s work was solely dependent on his desire to model atomic structure. The initial work of Watson and Crick in discovering the DNA structure at the University of Cambridge also falls in the Bohr quadrant [Watson, 1991]. The lower right-hand cell represents the work of Thomas Edison that was inspired by the practical value of the work. Edison is credited with the concept of building an innovation factory. His laboratory became a constant source of new products and innovations. Work in this quadrant may involve sophisticated scientific discoveries, but they are narrowly targeted to commercially viable ideas. The top right quadrant represents the work that is best exemplified by the work of Luis Pasteur. Here the work is inspired by both a quest for understanding and considerations for use. The challenge for the universities now is how to balance these considerations and develop agendas for strategic research.

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As the universities change their role from pure basic research to more user-focused research, the culture and attitude towards different types of research needs to be modified. This requires some strategic adjustments for both the industry and the universities.

10.6.

Some Strategic Considerations

In a study of several university-industry research centers in the US, we investigated the strategic considerations for forming such collaboration [Santoro, 2001]. We identified the following factors that are important in building university relationships: a. Strengthening skills, knowledge and gaining access to university facilities for advancing core and non-core technologies; b. Organic and adaptable corporate culture; c. Flexible university policies for intellectual property rights, patents and licenses;

d. Presence of an I/U champion at the firm;

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e. Firm’s personal interactions and resource commitments for I/U relationships; f.

Level of tangible outcomes generated from I/U relationships.

Our study showed that the firms differ in their strategic orientation for developing relationships with universities. Santoro & Chakrabarti (2001) identified three categories of strategic orientations among firms: collegial players, aggressive players and targeted players. Characteristics of these three groups are summarized in Table 10.1. The firms in cluster 1 are network oriented. They are attracted by the university center’s high rankings and prestige and believe that this will be beneficial in terms of access to not only the students and professors within the university but also other firms within and outside the industry. In this context, universities become part of the public space or a forum for exchange of ideas and information that is seldom possible in other contexts6. Firms in cluster 2 want to use the universities’ resources for advancing their immediate business interests. Cluster 3 includes the firms that are motivated to develop relationships with a particular university for a very specific technical or problem area. For example, my own university, NJIT, is recognized for research in remediation of hazardous and toxic substance. Many firms are attracted to work with NJIT in this specific area, although NJIT is not highly ranked among all national universities. Corollary to the firms, universities also differ in terms of their strategic orientations. We observed two types of university research centers: networkoriented and problem-oriented. Universities with strong reputations, as exemplified their high ranking by the U.S. News and World Report, are networkoriented. Universities in the third and fourth tiers in US News ranking are problem-oriented. The level of interaction between a network-oriented center and its industrial collaborators remain at a low level and tangible benefit also remains low. The problem-oriented centers have a high level of interactions with their industrial collaborators and provide tangible outcomes. Large firms are more likely to be associated with network-oriented centers. Aggressive players and Targeted players are attracted to the problemoriented centers.

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In determining the university-industry relationship, one should also consider two other factors: the firm size and the centrality of the technology to the firm’s business [Santoro, 2002]. Large firms are interested in working with universities in the areas of technologies that are not at the core of their business. Studies in corporate strategy suggest that firms will seldom outsource the development of technologies that are at the core of the business. The same is not true for small firms. Small firms have many additional constraints including limitation of resources. Thus, universities are very important sources of technical competence for small firms. Fig. 10.4 provides a schematic diagram of the possible outcomes of university-industry relationships. As shown in Fig. 10.4, the two outcomes are either competence building or problem solving. This can happen either in the core technology or in the non-core technology areas. The dimensions of collaboration differ with the nature of the outcomes sought by the firms. For example, knowledge transfer and research support are more likely to be associated with competence building in ancillary and core technology areas. Technology transfer and cooperative research are more likely to be associated with problem solving.

10.6.1.

Product development in telecommunication: Opportunities for collaboration with universities

The telecommunication industry is a complex industry that is subject to rapid change due to a number of factors. Technological changes in various facets of the industry introduce a high level of dynamism in this industry. With the development of technology and realization of the potential for various applications, the expectations of customers are changing continuously. This creates both opportunities for new products and services and obsolescence of existing products. This co-evolution of technology and market opportunities posits great challenge to the firms for continually innovating. The convergence of computer, communication and contents industries epitomizes the telecommunication industry. Fig. 10.5 provides the technology value chain in this industry indicating the interaction among the various members of the value chain critically important for product development at each stage. Firms in this industry have the added challenge of working with multiple technical trajectories, as there is no “dominant” technological platform guiding this industry7. In such a dynamic environment it is almost impossible for any firm to be totally self-sufficient in developing a product and technology. Nokia, for example, maintains a relationship with 100 or so universities from Boston to Beijing. Universities help Nokia in terms of the long-term research needs. A large telecommunication operator elaborated this point by

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saying that the cost of duplicating the work done at universities would be prohibitive. Working with universities also provides a level of flexibility in pursuing different technological trajectories either sequentially or in parallel. Flexibility is important in a dynamic technical environment where the firm needs to explore several technologies in parallel.

Internal R&D groups often become fixated in certain technologies and thus develop what Leonard Barton (1995) termed as “core rigidity”. Core rigidity develops a culture of insularity leading to the following: (a) preferred technology, i.e. how to execute a certain problem; (b) preferred cognitive approach, i.e. how to set up tasks; (c) preferred tasks, i.e. what tasks should be worked on. Past success with certain areas of technology and products is the main cause for this. Politics of power and organizational habits also contribute to develop such fixation with past practices. Consider the case of Motorola, a once formidable company in wireless and radio communication. Motorola

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was a leader in analog transmission of signal and has been slow to change to a digital network [Crockett, 1998]. While Nokia and Ericsson were focused on new digital technology emphasizing better voice quality and greater privacy, Motorola attempted to hang on to it analog models emphasizing the size advantage. Motorola lost a substantial share of the cellular market to its European rivals [Snyder, 1998].

Why did Motorola ignore the digital technology? More importantly, how could it have avoided such a catastrophic mistake? These questions are relevant for many companies and that is why companies need to be aggressive in detecting changes in technology and use multiple sources for ideas. Universities often are sources of new ideas. The faculty and students are unfettered by corporate culture and tradition and therefore are able to approach the technical problems from a creative perspective. The growth of the telecommunication industry is often driven by a young generation. The success of the “iMode” service by NTT Docomo in Japan is credited to the young people who adopted it. Students in universities are an important source not only for technical ideas but also for important market information.

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10.7.

Conclusions

Building effective relationships with universities for technology and product development is a complex process. Universities are involved in generating knowledge as their primary mission in addition to their teaching functions. Knowledge can be theoretical or abstract in nature and generic in terms of its applicability. In other extremes, one can develop knowledge that is situation specific and primarily problem solving in nature. Traditionally, universities are involved in generic theoretical knowledge development that is disseminated through papers, publications and sometimes patents. In recent years universities have been encouraged to develop knowledge that is problem solving in nature and applicable in specific situations. As Fig. 10.6 shows, industry needs problem solving knowledge that should be applicable to specific situations as dictated by either the industry or the company. The gap between the generic theoretical knowledge and the industry’s needs are threefold. In many cases there is no proper communication structure for interaction between the organizations. There also appears to be gap at the cognitive level. Professors in universities and managers in firms do not share their respective concerns and points of view, leading to gaps in the contents of the communication. There has been a trend to steer universities to a more problem solving type of research and knowledge development. Institutional changes have been made in many cases to promote this. For example, the National Science Foundation in the US has developed funding programs that promote stronger collaboration between the university and the industry. Private foundations, such as Alfred P. Sloan Foundation, Ford Foundation, Pew Charitable Trusts, to name a few in the US, are significant institutions in promoting problem solving knowledge. In Finland there are several public organizations, such as TEKES and SITRA that are active in promoting university-industry interaction. Most importantly, TEKES-sponsored projects promote interpretation of the knowledge generated at universities for the firm-specific problem-solving purposes. As we have discussed earlier, large firms behave quite differently. They have access to more resources. They seldom outsource development of technology and products that are at the core of their business and existence. However, for the development of products and technologies ancillary to the core business, large firms tend to deploy the assistance of universities. In the US, firms, tend to use the help of universities in products in the pre-competitive stage. This practice is important for protecting the intellectual assets associated with the product and technology. Large firms often use universities as a forum for exploring ideas not only with the faculty and students but also with

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others in the industry. In this respect, universities help develop social capital for the industry that facilitates technology transfer and innovation8.

Small firms, on the other hand, interact with universities for the development of technology related to their core and ancillary business areas. Small firms generally lack munificence of resources and so try to make the best utilization of any available resources. It is also noted here that universities differ in terms of their capabilities and strategies. Large universities with a national reputation of high caliber, such as MIT, Carnegie Mellon or Stanford, can be better suited to add to the social capital of the industry. Smaller and less known universities become more suited as problem solvers. Cultural difference between universities and firms is an important issue that must be addressed properly. Industrial projects need to be tightly controlled and monitored more closely than universities are accustomed to. Policies related to management of intellectual property rights are areas of concern to both industry and universities. Universities thrive on the idea of publishing the research results, while firms may want to keep much of the information as a trade secret. To build an effective relationship, one needs to resolve these issues.

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Universities are potentially great resources for corporations for developing new technology and products. In recent years, there have been more reasons for these two types of organizations to collaborate for mutual benefit. In a dynamic global economy, this has become critically important as evidenced by the experience in Finland.

NOTES 1.

I thank Dr. Michael Santoro at Lehigh University for our collaborative research in this topic. Dr. Richard Lester, Director of the Industrial Performance Center at MIT has been a great source of ideas and help in my pursuit of this research.

2.

Key words: Technology, industry structure, innovation process, university research, academe, network, collaboration, telecommunication industry, research quadrant, communication, core competence, product development

3.

Source: Professor Ollie Niemi, Director of Hermia

4.

Personal interview at Nokia Oy

5.

As a biographical note, the US Army Research Office funded part of the cost of my education while I was a PhD student at Northwestern University in the late 1960s.

6.

Richard Lester at the Industrial Performance Center at MIT pointed this out to me. His work on “interpretive management” is relevant in this context. He and his colleagues claimed: “the most important contribution the research university can make to industry, above and beyond the quantity and quality of its graduates, is to help expose private companies to a broad range of new ideas. A company that demands an exclusive, proprietary research relationship may not only be damaging the university, it may also be reducing the value that it will ultimately derive from that relationship” [Lester, 1998]

7.

James Utterback provided the concept of “dominant design” in his book on product innovation. As an industry gets matured, there evolves a dominant design that wins the allegiance of the market, which is adhered to by competitors. There are many factors that help develop the dominant design. They are: collateral assets associated with the design platform, strategic maneuvering by the dominant firms, user-producer interfaces and most importantly government regulations [Utterback, 1996]. See also this book, Chapter four.

8.

Social capital has been broadly defined “as the goodwill that is engendered by the fabric of social relations and that can be mobilized to facilitate action” [Adler, 2002]. Social capital facilitates inter-unit resource exchange and product innovation [Gabbay, 1998; Hansen, 1998; Tsai, 1998], the creation of intellectual capital [Hargadon, 1997; Nahapiet, 1998], and cross-functional team effectiveness [Rosenthal, 1996]

Chapter 10

253

REFERENCES [Adler, 2002]

Adler P.S. and Kwon S.W., “Social capital: Prospects for a new concept”, Academy of Management Review, 2002.

[Ali, 1994]

Ali A., “Pioneering versus incremental innovation: Review and research propositions”, Journal of Product Innovation Management, vol. 11, 1994.

[Bettis,1995]

Bettis R. and Hitt M., “The new competitive landscape”, Strategic Management Journal, vol. 16, 1995.

[Chakrabarti, 2002]

Chakrabarti A.K. and Lester R.K., “Regional Economic Development: Comparative Case Studies in the US and Finland ”, Proceedings IEEE Conference on Engineering Management, Cambridge, UK, August 20,2002.

[Crockett, 1998]

Crockett R.O., “Wireless goes haywire at Motorola”, Business Week, March 9. 1998.

[Gabbay, 1998]

Gabbay S.M. and Zuckerman E.W., “Social capital and opportunity in corporate R&D: The contingent effect of contact density on mobility expectations”, Social Science Research, vol. 27, 1998.

[Hansen, 1998]

Hansen M.T., “Combining network centrality and related knowledge: explaining effective knowledge sharing in multiunit firms”, Working paper, Harvard Business School, Boston, MA, 1998.

[Hargadon, 1997]

Hargadon A. and Sutton R.I., “Technology brokering and innovation in a product development firm”, Administrative Science Quarterly, vol. 42, 1997.

[Leonard-Barton, 1995]

Leonard-Barton D., The wellsprings of knowledge, Harvard Business School Press Cambridge, MA, 1995.

[Lester, 1998]

Lester R.K., Piore M.J. and Malek K.M., “Interpretive Management: What General Managers Can Learn from Design”, Harvard Business Review, March-April. 1998.

[Myers, 1967]

Myers S. and Marquis D., Successful industrial innovations, National Science Foundation, Washington DC, 1967.

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[Nahapiet, 1998]

Nahapiet J. and Ghoshal S., “Social capital, intellectual capital, and the organizational advantage”, Academy of Management Review, vol. 23. 1998.

[Parkhe, 1993]

Parkhe A., “Strategic alliance structuring: A game theoretic and transaction cost examination of interfirm cooperation”, Academy of Management Journal, vol. 36, 1993.

[Pisano, 1990]

Pisano G., “The R&D boundaries of the firm: An empirical analysis”, Administrative Science Quarterly, vol. 35, 1990.

[Quinn, 2000]

Quinn J.B., “Outsourcing innovation: The new engine of growth”, Sloan Management Review, Summer 2000.

[Rosenthal, 1996]

Rosenthal E.A., “Social networks and team performance”, Unpublished Ph.D. dissertation, University of Chicago, 1996.

[Santoro, 2001]

Santoro M.D. and Chakrabarti A.K., “Corporate strategic objectives for establishing relationships with university research centers”, IEEE Transactions on Engineering Management, vol. 48, No. 2 May, 2001.

[Santoro, 2002]

Santoro M.D. and Chakrabarti A.K., “Firm size and technology centrality in industry-university interactions”, Research Policy (In press), 2002.

[Shan, 1994]

Shan W., Walker G. and Kogut B., “Inter-firm cooperation and startup innovation in the biotechnology industry”, Strategic Management Journal, vol. 15, 1994.

[Snyder, 1998]

Snyder B., “Digital revolution leaves Motorola playing catchup”, Advertising Age, October 19, 1998.

[Stokes, 1997]

Stokes D.E., Pasteur’s Quadrant: Basic science and technological innovation, Brookings Institution, Washington DC, 1997.

[Tsai, 1998]

Tsai W. and Ghoshal S., “Social capital and value creation: The role of intrafirm networks”, Academy of Management Journal, vol. 41, 1998.

[Utterback, 1996]

Utterback J.M., Mastering the dynamics of innovation, Harvard Business School Press, Cambridge, MA, 1996.

[Watson, 1991]

Watson J.D., The Double Helix, New American Library, New York, 1991.

Index A academe in university-industry collaboration academic-industrial joint ventures acceptability access technology-enabled provision of to knowledge activity theory design of computer systems long-term use of products outlining the big picture subject-tool-object model Apple advertisement as an early loser in PDAs appropriation associations Idea Generator in brain in Mind maps in Mnemonist Axon (software tool)

236 236, 240 46, 55

237, 240 53, 242

51 52 51 51 27 89 86 83 22 14 23 14 9, 10, 35–39

B 109 123

balancing dimensions benchmarking of learning processes tests boosting creativity bootstrapping in venture capital brain three stage thinking model brainstorming demands session participants software tools techniques brand and dominant design connection to vision consumer goods creating a retail bank as an example superior

160 70 22 218 11, 12, 40 28

18 25 10 25 81, 186 4 151 177 184 87

255

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Handbook of Product and Service Development in Communication and Information Technology

trusted business alignment of objectives angels case models objectives plan

88–92 187 111 220 202–3, 208 188 123 221

C cell phones (telecommunications terminals) clarity of practices collaboration in HUT university-industry commercialization adaptive learming international legal rights new domains of knowledge web products communications and information technologies convergence development in HUT diversity in standards in Web supported services knowledge transfer market Motorola research funding technology theory-practice gap competencies as a part of resource management balancing in portfolio management competition environment for market leadership global winners and losers complementary assets e-commerce getting imitability low weight profiting from innovations start-ups strategic alliance technology protection

80, 84–86, 92–93 131 240 236 153 201 215 154 182 86, 237 247 238 235, 236 181 242 186, 188, 235 248 242 172, 175, 177, 237 250 107 113 134 235 80 236 89 172 182 180, 182 187 179 172 186 188

Index

257

web and mobile services complexity dynamic handling in networked product development in quality management modeling recent trends Comptel computer programs in brainstorming in innovative processes in mind mapping computing in communications technology in PDA’s development concentration creativity boosting by software case studies classification cultivation techniques cycle of nonlinearity obstacles process tools for idea generator validating outputs customer for PDAs holding needs segmentation understanding the needs customization

181 154 154, 158 165 153 152 167 183 196 26 28 35

86 86 19 32 39 31 24 17 18 17, 19, 20 15 29 36 80 165 55 110 121 172–76, 179

D

debt finance decision environment levels in Tellabs project maker’s competencies role in management Delta’s competencies practical portfolio management project management strategy design cycle dominant

220 131 130 119 129 132 133 132 132

67 82

258

Handbook of Product and Service Development in Communication and Information Technology

inclusive iterative meaning of emontions Palm parallel activities patent solutions system architecture team members user interface user involvement dominant design definition development early PDAs formation market pull occurence optimality turning up doodles dot.coms complementary assets the first wave usual core competencies

53 57 47 91 73 196 57 67 72 72, 73 57 81 81 88 81 85 90 81 83 29 184 184 182

E

economy emotions for products in goal-oriented behavior negative positive social interactions three-stage thinking model usability entrepreneurs bringing together funding price per % of equity sold environment dynamic business high-tech networked business equality of citizens in design equity funding equity market equity stakes European adoption of wireless technology practice in patenting

236, 237, 252

49 48 48 50 50 42 50 221 215 231

99 157 104 53 219 225, 231 222 227 196

Index

259

venture capitalists everyday design evolution early PDAs early product markets from to generation PDAs

227 56

80 82 92

F feedback after design filters as a part of visual sense of thinking process finance for young businesses identifying sources private sources finance in different phases of project financing new funds personal funds venture capital funds firm benefits for university- industrial cooperation blocking or teaming up cognitive caps competitive environment cultural difference between universities differences in cooperative strategies difficult technological imitation dimensions of collaboration early stage how to profit form own inventions in cooperation with universities knowledge transfer organizing sales reasons for outsourcing innovation resources self sufficiency size and centrality small in research cooperation specialization switching costs to clients and customers vertical integration Fishbone diagram formation of social rules freedom in portfolio management frozen portfolio F-Secure funding corporate research

71 12 32 219 216 215 211 233 223 219 222 180, 246, 247 240 186 250 236 251 245 188 247 250 179 236 242 174 237 125 247 247 251 171 184 189 37 17 135 134 185 214

260

Handbook of Product and Service Development in Communication and Information Technology

formative stage private public sector role of corporate based shared bases technology transfer offices

217 216, 233 214 134 214 215

games and creativity global market difference to earlier market ICT boom

23

G

167 201

H

high-tech a definition environment description market modern environment new applications of traditional quality management price erosion quality management the past and the current human computer interactions creativity sensing society interactions

152 157 237 164 166 154 155 152

47 11 14 12

I idea generator ideation brainstorming idea validation in portfolio management model of creativity cultivation techniques imitability impact of resources in portfolio management inclusive design industry airline critical success factors new ventures product strategies Innovating by Brainstorming cost reduction product architectural integrated networks of quality perspective intellectual property rights interactions

11 24 214 121 15 24 179 129 53 176 101 172 108 9 235 186 166 203 11, 16, 51, 68

Index Internet early dot.coms product customization product elicitation products with added value start to address inter-organizational collaboration invention definition in the East and the West in European patenting making investors ’99-’00 banks European expectations family and friends good product ideas institutional involvement large returns outside participation taking ideas ahead commercially

261

184 173 173 173 172 237-247

11 195 20 231 219 227 223 219 218 222 221, 222 229 230 219 216

K

killer application

83

L language and creativity lateral thinking learning adaptive by eliminating uncertainties culture emotions from earlier development generative in networks in quality management in quality management networks Peter Senge to complete a task to reduce variation to use a technical device licensing exclusiveness flexibility requirements securing cash flow logistics in order and delivery process

21 34 153, 160 158 50 48, 50 80 153, 164 165 160 165 153 70 161 68 207 207 206 173

262

Handbook of Product and Service Development in Communication and Information Technology

making more efficient partners

173 178

M

management across organization business objectives company resources company specific competence cross-functional decision making layers goal directed innovations groups in portfolio management human resource in low risk levels objectives practices R&D role of top management self-regulating mechanisms uncertainty managers managing change in portfolios human resources project portfolio project process R&D stage-gate model manufacturers century, automobiles as a market leader blocked development for computers making a partition market stability product diversity while dominant design stand out market a definition and WAP evolution of high-tech global information society identifying segments research maturity of usability assessment meaning of architectural innovation of multidisciplinary teams MessagePad

106 100 105 116 107 160 111 104 118 108 103 113 101 102, 103, 111, 131, 139, 140 138 167 155 82, 93 140 106 128 105 107, 137 106

80 85 84 86 85 81 85 94 58 55 79 3 60 73 71 184 15 91

Index milestones and assessment phase and fund raising in portfolio management in projects and portfolio management mind mapping techniques Mnemonist modes of portfolio management modularity

263

215 233 121 126 36 13 99 172, 175

N

need finding networks 2.5 (G)eneration and Tellabs in learming in portfolio management next generation new ventures common traits of growth Nokia a Finnish corporation as a market leader concurrent process models connection to HUT funding of NRC launch of Communicator 9000 marketing strategy portfolio management portfolio management in NRC university relationships wait and see - strategy

60 95 129 165 140 85 216

2 85 57 213 134 91 85 136 133 247 88

O OEM - business operating environment of telecommunication companies outsourcing change adaptation innovation risks and costs innovations traditional

186 136 179 235 237 166

P patent applicant as a solution for a technical problem computer programs definition different countries good inventions industrial applicability

194 195 196 194 196 194 195

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Handbook of Product and Service Development in Communication and Information Technology

inventive step novel inventions owners performance against targets standards time based indicators personal digital assistant (PDA) development early market internet enabled market Polar Electro portfolio group portfolio management adopting balancing culture decision making defining structures definition demands drawbacks early phases establishing formal methods future developments good practises illustrating main phases implementation in product management methods and practises objectives practises practises prerequisites project R&D R&D projects responsibilities scoring strategy strategy process subcontracting tools and methods traditional price competition and deadlines as a stage of portfolio management balancing making decisions of

195 195 194 160 164 154

79 87 3 79 240 130 136 125 139 115, 139 137 101 140 135 139 115 139 140 128 116 113, 115, 140 110 119 111 136 116 139 116, 140 141 128 118 121 114 126 140 136 115 162 72 137 123 130

Index private companies equity markets funding investor life partnership research institutions sector venture capital problem framework recognizing solving by brainstorming solving by programming product design complementary assets freedom usability tests user needs product development after dominant design conservatism culture earlier assumptions generations in different market areas incremental marketing research model of four drivers partitioning PDAs Roussel’s three-stage model programmable creativity templates project management a good practice classification resource allocations systems project portfolio management project resources protection by international patents by patents in different countries of lPR public equity market

265

53 233 216 218, 222 15 224 213 140 204 16 24 9 82 54 71 56 82, 97 82 84 139 82 82 80 90 85 94 85 86 82 24, 26 28 99, 119, 131 105 105 105 99 112 121 201 200 179 231

Q quadrant quality as conformance to requirements

237, 243 151

266

Handbook of Product and Service Development in Communication and Information Technology

customer requirements quality management early development links to other disciplines motivation for traditional and modern

151 149 150 149 159

R

repetitive processes research environment reselling rights resource allocation competition in portfolio management responsibility review practice risk and banks and business angels and useful information inherent to the project investing own capital level in investments roadmapping

158 138 187

111, 116 99 108 129 219 221 216 233 215 217 109

S sales early video recorders increasing by shared agreement licencees PDAs start-ups usability design screening in portfolio management services convergence design providers telecommunications sessions short-term resource allocation Six Thinking Hats social creativity software design by cases design model for creativity boosting patent protection solving design problems SSH standards

85 80 207 86 178 45 121 55 58 179, 181 46 13 106 33 18 66 57 32 202 52 185

Index

267

competing industry meaning in development of user centered design strategic management strategy and resource allocation corporate driven choices evolution for R&D Japanese renewal in portfolio management selecting for a product three views to deal with wait-and-see students a creative perspective as a research resource knowledge transfer market information success clarity and alignment as a factor for interactive products probability secret of human summarizing a web page as a creativity tool synetics

80 54 81 69 111 105 101 99 108 111 87 135 108 108 88 249 236 242 249 103 51 122 12

41 38 30

T

technical design technology development sources of product concepts Teece’s matrix-complementary assets telecommunication industry driving its growth factors of its rapid changes in global market services Tellabs trust and market

61 131 240 185

236, 249 247 235 53 2, 129 167

U uncertainty commercialization complexity in portfolio decisions in quality management

153 154 124 151–55

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Handbook of Product and Service Development in Communication and Information Technology

reducing sources in high-tech time university-industry relationships components determination research centers untied resources usability changing definitions design evaluation everyday context evolution example from Nokia Telecommunications expert evaluations final tests FURPS model human thinking and learning models limitations of cognitive psychology Nielsen’s factors Norman’s general design guidelines relationship to product testing setting deadlines shared testing user involvement user satisfaction usage concept design concept testing Norman’s usability problems usability testing user’s experience VIRIKE project usefulness in usability design user centered design concept evaluation standards user experience in design in telecommunication services success factor user interface design guidelines prototyping today’s challenges usability testing user-involvement in design visibility

161 153 154 242 247 244 128

47 59–62 69 46 46 71 70 71 66 68 51 46 69 71 72 57 70 72 61 73 64 68 70 59 65 47 65 57 46 54 53 68 67 47 70 64 69

Index

269

V

value chain covering disintegration in telecommunications technology interactions between members sequential and repetitive processes Teece’s matrix variation elimination of internal reduction web and creativity venture capital communications sector financing in the US and in Europe informal market market venture capitalists ventures funding early stages Why-why diagram vision early PDA market getting more in developing Communicator 9000 updating Visor series

185 177 249 247 163 180 158 161 149, 162, 168 39 211 225 224 220 231 220, 221 218 38

87 22 91 16 91