EDITORIAL
103
Editorial
A
s is becoming a regular way of working, this June issue of Creativity and Innovation Management again contains a special section plus a number of regularly submitted contributions. ‘Product Development and Innovation Management’ is the title of the special section in this issue. It contains a carefully selected set of six papers, originally presented in 2005 at the EIASM’s International Product Development Management Conference (IPDMC), hosted by John K. Christiansen, Professor in Management of Projects and Product Development at the Department of Operations Management, Copenhagen Business School (CBS). This section is guest edited by John Christiansen and Claus Varnes, who is assistant professor in the same department at CBS. Below, the two guest editors introduce the special section and the process leading to it, and we will also elaborate on the three noteworthy additional papers in this issue. Before that, we would like to point your attention to what we feel is an important step for CIM: a new award for the best paper published in Creativity and Innovation Management in 2006.
Tudor Rickards Award The 15th volume of Creativity and Innovation Management was published in 2006, and this was commemorated by the January issue containing contributions from various members of our editorial board, including our founding editors, Tudor Rickards and Susan Moger. Their article, a review of creative leadership, is now already one of CIM’s most downloaded articles! We found it only fitting to further commemorate 15 years of CIM by announcing a new, annual award for the best paper published in CIM. To honour our founding editors, and on the occasion of his 65th birthday, we have decided to name this award the Tudor Rickards Award. Five 2006 CIM papers were nominated by the editorial team, working together with Christian DeCock, Silviya Svejenova, John Bessant and Rosa Chun (all members of the editorial board and involved with one of the 2006 issues). We then asked the full editorial board to vote and list their top three. This voting, by a majority © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
of the board, led to the identification of two manuscripts which stood out among the nominated five. Since both of these papers received the same number of votes, it was decided to have two winners of the 2006 award: • ‘A Review of the Effectiveness of CPS Training: A Focus on Workplace Issues’, by Gerard Puccio, Roger Firestien, Christina Coyle and Cristina Masucci (15.1, pp. 19–33). • ’Team Polarity and Creative Performance in Innovation Teams’, by Jan Kratzer, Roger Leenders and Jo van Engelen (15.1, pp. 96–104). We congratulate Gerard Puccio and Jan Kratzer and their respective co-authors. The three other nominated papers were: • ‘Identity Sniping: Innovation, Imagination and the Body’, by Bent Meier Sørensen (15.2, pp. 135–42). • ‘Creativity (Ideas) Management in Industrial R&D Organizations: A Crea-Political Process Model and an Empirical Illustration of Corus RD&T’, by Han Bakker, Kees Boersma and Sytse Oreel (15.3, pp. 296– 309). • ‘Phronesis and Creativity: Knowledge Work in Video Game Development’, by Peter Zackariasson, Alexander Styhre and Timothy Wilson (15.4, pp. 419–29). All authors will receive a certificate and be mentioned on the CIM website. Votes are already open now for the 2007 Tudor Rickards Award: any reader who wishes to nominate one of the papers from the March and June 2007 issue can do so now by e-mailing us via
[email protected]. The 2007 award will be presented at the 2nd CIM community meeting, which will be held in 2008 in Buffalo, 28–30 May. The Call for Papers can be found in this issue.
Product Development and Innovation Management It has been a stimulating and interesting experience for us to be guest editors on this special issue of Creativity and Innovation Management.
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00434.x
CREATIVITY AND INNOVATION MANAGEMENT
104
We are grateful for the invitation from the editors, for the administrative support from the secretary, the most critical assistance from the groups of international reviewers and last but not least from the authors of the papers presented here. The authors have been through the challenging task of developing their research from conference papers into full journal papers, which are now ready for a wider audience with the assistance of the journal’s editors and referees. A few words are in order on some of the obstacles and challenges when converting conference papers into journal papers. As the present papers are all from the 12th IPDMC in Copenhagen in 2005, they were all included in the Proceedings from that conference together with the other 120 papers from that conference. Being selected for the IPDMC requires that an extended abstract is accepted in advance, and that the full paper is later submitted for inclusion into the Proceedings and then presented. As the full conference paper, in most cases, has not undergone a full review, the original selected papers from the conference all had areas that needed improvement. Among these were issues such as improvement of use of and references to existing research; improved explanation of data collection and analysis; improving the focus and explanation of limitations of a study; improvement of relationship between theories or models and the analysis and conclusions; and improvement of structure and presentation of the work. As a consequence most of the papers went through two rounds of reviews and comments from the international reviewers and editors, and a few even up to four rounds. Again, we are grateful for the support of the reviewers and the persistence of the authors. Selecting papers for a special issue is an interesting job. Originally ten papers were selected to be submitted for the first review, and finally we ended up with six papers presented here in this publication. As the IPDMC is open to research papers that deal with many different aspects of management of product development in companies and organizations, we wanted to mirror that diversity in our selection. We focused on papers which addressed topics of current interest for the readers of Creativity and Innovation Management and which were able to address interesting issues in a solid methodological and empirical way and had theoretical reflections that were on a high international academic level – or which could be developed to fit these requirements. We believe that all of the papers in the present collection are of a high quality, and that they are related by the passion of the authors for
Volume 16
Number 2
2007
developing our knowledge on managerial issues of creativity and innovation. Not all the issues that are dealt with are new, but they are dealt with on very different levels and in different ways, thus demonstrating the diversity of the area and also how important it is to be able to master several approaches and methods when trying to understand a phenomenon. Some might argue that it might be the other way round: that the different approaches and methods each produce different types of insights, and each provides us with different pairs of binoculars. Anyhow, as the theme of creativity and innovation management is a truly complex and multifaceted one, we really need different pairs of binoculars to help us to grasp and analyse the various issues at stake here. The special is started off by Maria Elmquist and Blanche Segrestin, who draw upon an in-depth case study to explore the role of front end innovation in the European pharmaceutical industry. Their concern is the manageability of these early innovation activities where the management challenge under high uncertainty can be described by a design-oriented framework: C-K theory. Focusing on how knowledge is produced, the framework lays out the experimentation process of a drug design and demonstrates how different approaches to the use of concepts and knowledge produces different types of more or less successful results. In the second contribution, Daniel Henneke and Christian Lüthje take as their theme the correlation between educational diversity in teams and product innovativeness with the strategic planning process as an intermediate variable. By investigating high-technology sectors in Canada through a survey, the authors find support for a correlation between educational heterogeneity of a team, strategic openness in strategic planning, and subsequent innovativeness. Among the implications is that venture capitalists and academic incubators can – as part of the team – increase innovativeness. The management challenge of developing multi-branded platforms is addressed by Christer Karlsson and Martin Sköld. Based on a dichotomy between multi-branded platforms and product architecture, the article presents the results of a longitudinal field study of a major European company employing a multiplatform strategy with three brands and a common architecture. This particular situation requires the counteraction of forces drivenj by the respective dimensions. A pursuit of a design standard is counteracting the force of a unique design, for instance. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
EDITORIAL
The article by Povl Larsen and Alan Lewis draws upon eight case studies of design award-winning SME companies. The purpose of the study is to explore whether these apparently successful companies are overcoming the barriers of innovation to SMEs. The article suggests that companies are as likely to ignore barriers as they are to address them through deliberate courses of action. Helen Perks investigates inter-functional integration and decision making at both project and portfolio level. Based on case studies of three projects, the article suggests different criteria are used for resource allocation decisions through the development process, but also that decisions are influenced by a number of factors such as experience, level of formality and enthusiasm, among other things. What is more, portfolio management is influenced by the nature of interfunctional integration. The special section is concluded by an article by Stefanie Bröring and Jens Leker, dealing with industry convergence and the implications for managing the front end of hybrid product innovation. A survey approach is used to explore 54 projects grouped in four types depending on the position in the value chain and the scope of technology development. The article identifies the different influences of factors such as trends, experience in technology development and marketing, and finally strategic partners on the groups. These analyses enabled the formulation of a number of propositions on different contingencies, suggesting that market experiences and competencies in idea generation and selection, are especially important with a B2C focus.
Additional papers As the first of our additional papers, Jongbae Kim and David Wilemon’s ‘The Learning Organization as Facilitator of Complex NPD Projects’ tackles a relevant and interesting aspect of NPD organizations – how to establish a learning organization in order to better cope with the complexity of NPD projects and improve future projects. Based on their research, they advance several suggestions for implementing a learning organization designed specifically to capitalize on the
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
105
experiences of development firms’ efforts in dealing with complexity and its consequences. Next a contribution from one of the guest editors of the March issue: EACI secretary Han van der Meer, based also on a presentation at the 9th ECCI in Lodz, Poland. Under the appealing title ‘Open Innovation: The Dutch Treat: Challenges in Thinking in Business Models’, the author presents the first set of results of a survey on open innovation practices in Dutch companies. The survey consisted of a written questionnaire (n = 814) followed by in-depth interviewing of 24 highly innovative companies. The research shows that Open Innovation needs a deep involvement to really pay off, and in this respect Dutch companies find it hard to find a good fit. The value added by the Open Innovation paradigm is thinking in business models, but handling them in an open way is the real challenge for Dutch industry. This issue concludes with an article by Jan Buijs, the other guest editor of the March issue, and Chairman of EACI. His article on innovation leaders is an intriguing read. The term ‘controlled schizophrenics’ is used to highlight the balanced kind of special leadership innovation leaders need, with a high tolerance for ambiguity and paradoxes, in which people come first. Partly tapping in on one of his own earlier contributions in Creativity and Innovation Management (‘Modelling Product Innovation Processes, from Linear Logic to Circular Chaos’, June 2003, pp. 76–93), the author stresses innovation as a multi-process process, a view which has become even more important within the Open Innovation paradigm. The article also forms a nice prelude to our next issue, which will contain a special section on ‘Leadership and Creativity’ guest edited by Gian Casimir and Tudor Rickards. At the end of this issue you may also find a relevant review of the book: ‘The 7 Laws of Innovation – The Human Side of Innovation in Organizations’, this time written by Marcus Keupp from the University of St Gallen. Do not forget to regularly check our website for news, and events organized by our affiliated partners CINet, EACI and PDMA: http:// www.blackwellpublishing.com/caim. John Christiansen Claus Varnes Petra de Weerd-Nederhof
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
106
Towards a New Logic for Front End Management: From Drug Discovery to Drug Design in Pharmaceutical R&D Maria Elmquist and Blanche Segrestin Under pressure to innovate and be cost-effective at the same time, R&D departments are being challenged to develop new organizations and processes for Front End activities. This is especially true in the pharmaceutical industry. As drug development becomes more risky and costly, the discovery departments of pharmaceutical companies are increasingly being compelled to provide strong drug candidates for efficient development processes and quick market launches. It is argued that the Fuzzy Front End consists less of the discovery or recognition of opportunities than of the building of expanded concepts: the notion of concept generation is revisited, suggesting the need for a new logic for organizing Front End activities in order to support sustainable innovative product development. Based on an in-depth empirical study at a European pharmaceutical company, this paper contributes to improved understanding of the actual management practices used in the Front End. Using a design reasoning model (the C-K model), it also adds to the growing body of literature on the management of Front End activities in new product development processes.
Introduction
A
s the development of innovative products is becoming more and more crucial, organizations are putting much effort into improving the efficiency of their R&D activities. In most industries, companies have adopted project management in order to structure their development activities through stage-gate processes, e.g., those introduced by Cooper (1988), with predefined gates and specific requirements which the projects must fulfill in order to move on. They are continuously seeking to improve these processes by reducing uncertainty, shortening development lead times and cutting costs. At the same time, however, there are growing concerns that efficient new product development (NPD) processes are not sufficient to foster innovation and sustain economic growth in competitive markets. In contrast to the linear NPD process, innovation is now recognized as a rather chaotic process (Cheng & Van de Ven, 1996). It has been shown that new organizational structures or mechanisms are needed in order to support the innovative ideas emerging within the organization. There is also a growing interest in the
Volume 16
Number 2
doi:10.1111/j.1467-8691.2007.00424.x
2007
very early phases of product development where it is still possible to introduce new concepts at low cost, sometimes referred to as the ideation phases or the Fuzzy Front End (FFE) of innovation (Reinertsen & Smith, 1991; Khurana & Rosenthal, 1997, 1998; Nobelius & Trygg, 2002). The main objective of these Front End activities is to provide strong product concepts that can be refined and developed during the NPD process. Previous literature on the FFE has developed models for structuring these pre-project phases (e.g., Khurana & Rosenthal, 1997; Koen et al., 2001) and reducing uncertainty, while other authors argue that there is no one Front End process which is suitable for all situations (Nobelius & Trygg, 2002). Despite the impact of this phase, there are still few empirical studies clarifying FFE practices (e.g., Kim & Wilemon, 2002), with a couple of exceptions (e.g., Börjesson, Dahlsten & Williander, 2006). Also, the generative processes that lead to innovation are seldom addressed and there is a call for new investigations (Cheng & Van de Ven, 1996; Khurana & Rosenthal, 1998). The aim of this paper is to contribute to the field of innovation management during the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
early phases by presenting an empirical study from the pharmaceutical industry, one which is highly representative of current challenges to organize the FFE. Pharmaceutical companies are under pressure to find new ‘blockbuster drugs’ – the rare, exclusive and efficient drugs that are so profitable that they can finance the entire operation of the company. Innovation has become a key factor of profitability and there has been a greater focus on the efficiency of R&D, mainly due to a disturbing trend towards diminishing productivity (Grabowski & Vernon, 2000; DiMasi et al., 2003). Stricter regulatory demands have led to less product exclusivity, less flexible prices and new patent regulations that have created fiercer generic competition. Simultaneously, requirements for extensive clinical trials have resulted in increasing costs for drug R&D while many of the successful products from the 1980s are now going off patent, creating space for new competitors profiting from the incumbents’ previous investment. All these changes have increased the focus on shortening development times in order to make the most of patents obtained (Sundgren, 2004); but, even more importantly, this has put tremendous pressure on the efficiency of discovery departments, i.e., the Front End of pharmaceutical R&D. Companies are looking for new organizational and managerial models better suited to these immediate challenges (Tapon & Cadsby, 1996). Based on this empirical study of a European pharmaceutical company, where managerial practices at the Front End were analysed, the objective of this paper is threefold: first, its aim is to contribute to improved understanding of actual management practices in pharmaceutical drug discovery, proposing the use of drug design strategies instead of the notion of drug discovery; second, its aim is to contribute to the growing literature on the management of Front End activities in NPD, by discussing the prevailing notions of concept development and opportunity recognition, using a design reasoning framework (the C-K model); and third, based on the analysis of the empirical case, it suggests the need for a new logic and alternative tools for managing and organizing Front End activities in order to support sustainable innovative product development. The paper is organized as follows: in the first section, the literature on managing the Front End of product development is presented, together with a theoretical framework of design reasoning (the C-K model) which will be used to analyse the empirical data. In the second part, the case study is presented, beginning with the context of the pharmaceutical industry, followed by the method of data © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
107
collection and analysis, as well as the empirical study of a leading European pharmaceutical company, where different attempts to manage discovery work have been studied; i.e., a scouting process as well as two more exploratory projects. In the following section, the scouting process and the two projects are analysed and discussed, based on the design reasoning framework. The insights gained from the empirical case are then used to discuss and elaborate on the existing models of managing Front End activities. Finally, further research into how design reasoning can provide managers with a much needed tool for balancing innovation and efficiency at the Front End is discussed.
Theoretical Framework Managing the Front End of Innovation The need for developing innovative products is incontestable in most industries and the ability to create novel product concepts has become essential for long-term survival (Drucker, 1988; Thomke, 2001). Due to shorter product lifecycles and intense competition, there has been an increased focus on the rationalization of NPD activities, with cost reductions and the shortening of time plans being the main objective. In this respect, most NPD organizations have been profoundly transformed during recent decades, mostly being based on the stage-gate model proposed by Cooper (1988), whereby the development project follows a planned schedule containing tollgates that require specified deliverables in order to allow the continuation of the project. However, it is now recognized that innovation is a rather chaotic process (Cheng & Van de Ven, 1996), in contrast to the linear NPD process. Kline and Rosenberg (1986) suggest that the management of innovation varies throughout the lifecycle of the development project. During the early phases (where uncertainty is high), the main task of management would be to bring order to the chaos, whereas during the later phases (when the dominant design is determined), the task of management would be to prevent the loss of the ability to create radical innovation. In order to enable a reflexive capability and a context that fosters innovation, new organizational structures have been suggested which focus on the roles of individuals (e.g., gatekeepers) or various organizational mechanisms (Van de Ven, 1986; Iansiti & West, 1997; Colarelli O’Connor & Rice, 2001). Some authors have argued that companies need the ability to rapidly introduce changes late in the process, a planned
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
108
flexibility (Verganti, 1999), while others have proposed that development projects should be considered a part of product families (Sanderson & Uzumeri 1995) where learning can support future development projects (Maidique & Zirger, 1985; Lynn et al., 1998). The dual striving for innovation and efficiency during NPD has put a greater focus on the very early phases leading up to the development process, where innovative concepts can still be included at relatively low cost. These phases are often referred to as the Front End, or even the Fuzzy Front End (Reinertsen & Smith, 1991). The FFE is described as the stage where ‘new product ideas gain their shape, justification, plans and support leading to their approval and subsequent execution’ (Khurana & Rosenthal, 1997, p. 103) or the ‘period between when an opportunity is first considered and when an idea is judged ready for development’ (Kim & Wilemon, 2002, p. 269). By definition, the FFE has a chaotic nature: ‘the front end is inherently fuzzy because it is a crossroads where complex information processing, a broad range of tacit knowledge, conflicting organizational pressures including cross-functional inputs, considerable uncertainty and high stakes must meet’ (Khurana & Rosenthal, 1998, p. 72). Three aspects of the FFE literature are summarized below: 1) idea selection as an important activity during FFE processes; 2) the expected outcome of FFE processes; and 3) the main managerial issues surrounding FFE processes. 1) Idea Selection as an Important Activity of the FFE The predevelopment phase is initiated ‘when the idea for the product first surfaces’ (Griffin, 1997, p. 28) and companies ‘first recognize, in a semi-formal way, an opportunity’ (Khurana & Rosenthal, 1997, p. 106). It ends when ‘a product concept is selected for downstream development’ (Burchill & Fine, 1997, p. 467). Selecting which ideas to pursue is the essential activity of the FFE: ‘the critical activity is to choose which ideas to pursue in order to achieve the most business value’ (Koen et al., 2001, p. 51). The challenge of recognizing and evaluating ideas and opportunities has been an important issue in the literature: ‘ideas are screened against a set of largely qualitative criteria to assess the appropriateness of the idea’ (Cooper, 1997a, p. 22). Alternative screening methods and checklists have been presented (cf. Reinertsen, 1999), e.g., ‘calculating the probability the project will meet the firm’s profitability objectives, predicting market size and growth rate and assessing the risks of
Volume 16
Number 2
2007
alternative scenarios’ (Rice et al., 2001, p. 410). The importance of an organizational setting capable of recognizing potential ideas to evaluate has also been put forward, in combination with individual abilities: ‘Opportunity recognition for radical innovation is highly dependent on individual initiative and capacity, rather than routine practices and procedures of the firm’ (Colarelli O’Connor & Rice, 2001, p. 103). The recognition and evaluation of innovative ideas, using specific evaluation grids to filter out the strongest concepts, are framed as important activities of the FEE. 2) The Expected Outcome of the FFE Pre-project activities basically consist of idea generation (conceptualization of the product idea), preliminary assessment (defining the product) and concept definition (estimation of the probability of success) (Cooper, 1997a). During the concept generation phase (also called concept definition or concept development), uncertainties are reduced and the concept is refined and developed for final evaluation, presenting ‘a business case based on estimates of business potential, customer needs, investment requirements, competitor assessments, technology unknowns and overall project risk’ (Koen et al., 2001, p. 51). The elaborated result is a ‘well-defined product concept (clear and aligned with customer needs), a product definition (explicit and stable) and a project plan (priorities, resource plans and project schedules)’ (Khurana & Rosenthal, 1997, p. 106). The expected outcome of the FFE is a clarification and a detailed specification of a product concept that is ready to enter the NPD process. 3) The Main Managerial Focus of the FFE The main problems of the FFE are often summarized as unclear product strategies, inadequate product definitions, technical and market uncertainties, unclear project objectives, shortages of resources, a lack of planning, and unclear organizational roles (Khurana & Rosenthal, 1998). With the intention of improving the efficiency of FFE processes, some researchers have presented models for structuring these early phases, e.g., the Front End model (Khurana & Rosenthal, 1997), the New Concept Development Model (Koen et al., 2001) and a Concept Engineering process (Burchill & Fine, 1997). Models for optimizing FFE processes have also been introduced (Cooper, 1997b). Common traits in these models include the aim of developing a structured and generic model for the Front End processes, thus reducing uncertainties © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
as early on as possible. However, this anticipation approach has been contrasted by a reaction approach, focusing on the ability of companies to rapidly introduce changes late in the process. For instance, Verganti (1999) argues that anticipations and reactions are linked through a mechanism named ‘planned flexibility’, which is the capability to build flexibility into the development process due to decisions taken during the early phases. Some authors also argue that there is no one Front End process which is suitable for all situations, rather that the type of project and overall company situation must have an influence (e.g., Nobelius & Trygg, 2002). The debate about how to manage the FFE reflects the difficulty of organizing extensive but sustainable explorations. According to Reinertsen, the objective of the Front End is to ‘alter the economic terms of the bets’ for the new concepts based on ‘the probability for success, the upside of success and the downside associated with failure’ (Reinertsen, 1999, p. 26). In the literature, other ways have been proposed for shortening the lead-times of the FFE, e.g., common vision, formalization and better communication (Kim & Wilemon, 2002). Some authors have also indicated the need to link the FFE to an integrated new product portfolio (Khurana & Rosenthal, 1997). The focus is on reducing risks: ‘If the up-front homework has been well executed, resulting in a solid business case, then the odds of making the right decision at Gate 3 are much higher’ (Cooper, 1997a, p. 3). The main managerial focus of the FFE is on reducing uncertainties and obtaining a high probability of success at minimal cost. These central lines of reasoning from the FFE literature show that the remaining challenges lie in understanding the generation of ideas and managing the dimension of efficiency in parallel with the dimensions of creativity and innovation. Using the progress of theories on design reasoning, these challenges can be addressed from a new perspective and notions such as ‘opportunity recognition’ and ‘concept generation’ can be revisited. In the following section, the theoretical framework of design reasoning is presented.
Managing Innovation Through Design Reasoning When introducing the notion of bounded rationality, Simon first discussed the nature of human reasoning, especially in unstable environments when alternatives cannot be listed in advance but must be progressively created (Simon, 1986). Pursuant to these ideas, a framework of design reasoning has been elaborated © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
109
Concept (C)
K0
C0
C1
Knowledge (K)
C2
K1
Figure 1. A Generic Representation of the C-K Theory Source: Based on Hatchuel, Le Masson & Weil, 2004. by Hatchuel, Le Masson and Weil (Hatchuel, Le Masson & Weil, 2004, 2005; Le Masson, Hatchuel & Weil, 2006; see also Hatchuel & Weil, 2001; Hatchuel, 2002; Kazakci & Tsoukias, 2005). Studying products or organizational structures is not enough to understand how designers ‘think’ and develop a new concept. Therefore, in their ‘C-K model’, two expandable spaces are distinguished: a space of concepts (C) and a space of knowledge (K). Concepts are defined as something which does not yet exist in reality but which can be formulated (in a concept) based on the available knowledge. The knowledge space contains propositions that are considered true. Design reasoning is then modelled as the co-evolution of C and K. The available knowledge (K0) is the basis for the formulation of new concepts (C0). Within the C-space, concepts can be refined or expanded by adding or removing attributes, i.e., through defining partitions of the concept (C1, C2 . . .). These alternative concepts address issues that lead to the creation of new knowledge in the K-space (through experimentation, enquiries, etc.). This new available knowledge enables the continued refinement of the concepts and/or the abandoning of concepts with certain attributes. This iterative process enables the efficient identification of the knowledge needed to proceed and can thus be used to guide learning processes. The iterative expansion of the two spaces is illustrated in Figure 1. Based on existing knowledge (K0), an initial concept (C0) is developed. Transitions to the K-space are necessary in order to find new knowledge (K1) which in turn may reframe the concepts into alternative concepts (C1, C2 . . .). The design reasoning stops when a concept is fully specified by a succession of attributes and accepted as true in K (there is a ‘conjunction’). This presentation of the theoretical C-K framework,
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
110
although simplified, illustrates the core of design reasoning, i.e., to work on the combined expansions of concepts and knowledge. This framework will be used to analyse our case study of a European pharmaceutical discovery department, which is introduced in the next section.
Exploring Management Practices at PharmaCorp Discovery The Pharmaceutical Industry and the Challenge of Discovery Departments Despite heterogeneous scientific backgrounds, e.g., chemistry, pharmacology, microbiology and biochemistry (Walsh, 1984; Liebenau, 1987; Moulin, 1991; Drews, 2000), the organization of pharmaceutical R&D has converged over the last century into a somewhat generic process consisting of two distinct phases: the discovery process and the development process. During discovery, the main objective is to identify drug candidates with a great potential for both treating targeted diseases and comprising important market prospects. During development, drug candidates are tested according to a rational stage gate process that validates both their efficacy and safety in accordance with regulatory patterns and proceedings.1 Very few of the drug candidates entering this development process achieve satisfactory results and actually reach the market. The rate of success is miniscule; as early as in 1995, it was shown that only one in 5,000 compounds made it all the way through the maze (Studt & Casssidy, 1995), illustrating the extreme uncertainty characterizing the pharmaceutical industry throughout the drug development process. The situation is not improving2 (Sundgren, 2004). The entire 1
Each step is thoroughly controlled and documented, a requirement in order to receive the necessary authorization from the regulatory authorities to continue the development process. Each drug candidate under investigation must be validated on several animal models (usually at least two species) before an authorization for trials on humans can be issued. These pre-clinical studies test both the efficacy and the toxicological aspects (identifying any unwanted side effects). If good results can be shown, clinical trials on healthy volunteers will follow including further tests to prove the efficacy and exclude any toxic effects, followed by clinical trials on volunteers from the targeted disease group. Finally, larger quantitative studies are performed on numerous patients, allowing statistical analysis of the drug’s efficacy. 2 Of the molecules examined during the pre-clinical phases, only one per cent will continue to a clinical trial, and of this small percentage, only 22 per cent
Volume 16
Number 2
2007
drug development process is also very lengthy (8–12 years) and extremely costly, $125–200 million for each drug candidate reaching the market (DiMasi, Hansen & Grabowski, 1991, 2003). Despite increased investment, research is not creating the desired results and today the decreasing level of productivity is the main problem facing the pharmaceutical industry. The likelihood of the development process finding viable drugs is dependent on the input supplied by the Front End processes – the discovery processes – which are under pressure to support and foster innovation in a more efficient way (Seget, 2002). During discovery, the focus is on developing as many potential drug candidates as possible to treat the targeted disease and then choosing the ones with the best attributes and the greatest potential using portfolio management and real option theory. As a result, discovery has become increasingly project-oriented, using stage gate models (Cooper, 1988; Schmid & Smith, 2002) to deliver drug candidates that meet several parallel requirements, similar to prototypes with well-defined properties (Federsel, 2000). For example, drug candidates should be synthesizable, enjoy a good intellectual property situation (be far removed from previous patents), indicate what materials to use (potential suppliers identified, ideas for raw materials), enjoy good economic projections (based on cost and market estimates), align with safety, health and environmental issues, possess good chemical properties (solid state characterization), and also show promise as regards the scalability and technical engineering aspects (process design). Methods of discovering new drugs have also evolved tremendously during recent decades (Gambardella, 1995). Instead of randomly screening identified drug candidates, a rational drug design process is applied (Thomke, Von Hippel & Franke, 1998), whereby scientists are able to analyse the structure of the disease-causing receptors and then design molecules that might bind them correctly. This approach involves advanced technologies such as computer-aided drug design, combinatorial chemistry, high throughput screening, and genetic engineering (Sundgren, 2004). Previous research has shown that rational drug design and combinatorial chemistry have widely increased the performance of mass screening (Thomke, Von Hippel & Franke, 1998). As a consequence, major investments have been made in new research areas and technologies, e.g., biowill be approved for sale, with only one-third of these being successful enough to result in a positive return on investment (Carbone, 2003). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
informatics, genomics, molecular biology and combinatorial chemistry. The results of this rational drug design, and its progress, are – to some extent – renewing the processes of the discovery organizations (Drews, 2000), but it is still unsure whether this will enable the expected sustainable flow of innovation.
Methodology The research behind this study is part of a broader collaborative research project (Adler, Shani & Styhre, 2003) at a large European pharmaceutical firm, subsequently called PharmaCorp. A collaborative set-up enables an interactive knowledge search mode. Interactive research is based on joint knowledge production by practitioners and researchers and focuses on knowledge of the practices in use. The main criterion is that the knowledge produced should be both relevant (Starkey & Madan, 2001) and actionable (Argyris, 1993; Argryis, Putnam & Smith, 1995; David, 2002). Interest in understanding the managerial processes used by the discovery department of PharmaCorp led to the design of an exploratory study investigating three different approaches to managing discovery processes. The first part of the study focused on a process for identifying and evaluating drug candidates outside the traditional therapeutic areas, known as the scouting process. It was also decided that the study would investigate two internal but exploratory projects (subsequently called ‘the resting project’ and the ‘unmasking project’) outside the established areas of expertise. The study of these three initiatives is based mainly on interviews, but supplemented by discussion seminars and the interpretation of internal documentation. A total of 39 interviews were conducted at PharmaCorp, 24 of which dealt specifically with the ‘resting project’ and the ‘unmasking project’. The interviews were all open-ended, semi-structured, and always undertaken in pairs. All interviews were summarized and reflected upon in a structured way by both interviewers. The data collection and the analysis were iterative processes whereby intermediate ideas were discussed with managers at the company in an abductive analysis approach and several presentations and discussion seminars were held with key people at the company. An abductive approach implies that the empirical data was viewed against intermediate conceptual models and that an increased understanding was being developed continuously when analysing the data and applying the theoretical framework. For case studies, this has also been referred to as systematic combining (Dubois & Gadde, 2002). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
111
This paper is based on the application of a theoretical framework on the exploratory study of a discovery department, to enable an increased understanding of the challenges facing discovery and how these may be addressed. In the paper, the generic designoriented framework (the C-K model) is presented, followed by the case and then an analysis of the studied managerial approaches from a design-oriented perspective. This analysis is useful for showing how simple frameworks can help managers to structure what would seem to be unpredictable and chaotic processes using a learning perspective.
PharmaCorp Case Background In order to better understand the management of discovery processes, an exploratory study was initiated at a large European pharmaceutical firm (PharmaCorp) with a long history of success in a few specific therapeutic areas. The context of PharmaCorp was considered representative of the challenges that discovery departments are facing because: • The development process was seen as too costly and the rate of failure considered too high. There had also been many candidates with unwanted side effects. • The discovery department’s ability to innovate was being questioned internally. • The shift from small chemical entities to biopharmaceutical molecules had created a need for both new competencies and the rapid diversification of assets. Facing the innovation revolution of the pharmaceutical industry (Seget, 2002), PharmaCorp had launched some major organizational initiatives in order to renew the traditional development and discovery logics. The company was searching for ways of diversifying its research portfolio. In the R&D organization, new structures had been introduced to manage innovation during the drug development process. For instance, Therapeutic Areas had been put in charge of managing consistent lineages of products in order to develop new expertise and foster innovation during development. In discovery, new teams were in charge of capitalizing on ‘assets’ and generating new concepts for further projects, known as Asset Teams. Since the development processes are heavily regulated by economic pressures and legislation, the focus was mainly on the discovery process. This study mainly focused on one of the asset teams which had been assigned the task of building a biopharmaceutical project portfolio through disease-driven research, focusing on prioritized therapy areas. The objective
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
112
of this biopharma asset team was described in an internal strategic paper in May 2003: ‘the long-term aspiration is to identify a limited number of new “core-proteins” around which a product and project portfolio can be established’. The main role of the biopharma asset team was twofold: first, to diversify the existing core capabilities in order to foster innovation in biopharmaceuticals, and second, to capitalize on these assets by suggesting sustainable strategies in the new fields. Three managerial initiatives within the biopharma asset team were studied in order to better understand the practices in use at PharmaCorp, i.e., the scouting process and two of the projects in the biopharma project portfolio.
The Scouting Process In order to explore possible diversification strategies, the biopharma asset team quickly identified five plausible new therapeutic areas. It seemed necessary to map ongoing research projects in order to rapidly explore the possibility of entering these new fields. A scouting process was launched; different scouting teams were in charge of scanning different therapeutic areas and evaluating existing external earlyphase projects which could potentially be acquired. An additional objective was to obtain a global picture of the ongoing research programmes and the actors, as well as a thorough understanding of the patent and regulatory situation existing in the various fields. Although not explicitly formulated, the scouting teams used the same basic criteria as in traditional screening when evaluating the projects: • Robust scientific rationale: established evidence and/or reliable data • Feasibility • Patent situation: need for freedom to operate • Clinical trials: suitable subpopulations, established clinic network • Production: available technologies • Market situation • Portfolio: need to balance early and later phases. In the beginning, the scope of the scouting was quite broad within the different areas. More than 600 companies were screened in order to identify actors and drug candidates that could fit in with the PharmaCorp strategy. Although highly promising and rigorously organized, this initiative eventually turned out to be both costly and very time consuming relative to the outcome. Around 60 companies (each one working on many potentially suitable projects) were considered interesting during an initial
Volume 16
Number 2
2007
stage. For each of these identified projects, the evaluation was extremely time consuming; the relevance of the data, the patenting situation, and the scientific rationale and market position required much analysis work. However, one year after the launch of the scouting process, none of the existing projects in the biopharma portfolio had actually been launched based on the input provided by the scouting process. Despite major investment, the scouting process did not result in any projects being pursued as potential drug candidates during the discovery process.
Two Explorative Projects within the Biopharma Portfolio In our empirical analysis, two exploratory projects in the biopharma portfolio were examined in more detail. The first exploratory project, subsequently called the ‘resting project’, aimed at a pathology which can take several forms, depending on the patient, and which is due to a disability of the body to digest a specific component. In a healthy person, a natural hormone is secreted and helps this digestion; thus the pathology has been treated by hormone injections for a long time. However, recent academic work had shown that some patients are ill due to a hormone secretion disorder (the secretion process becomes ‘tired’ when intensively stimulated). An alternative approach which consisted of stopping the regular natural hormone secretion had been shown to be of interest as regards to letting the body ‘rest’. The research results even showed that, in the long run, systematic rests could help maintain a normal level of secretion activity. PharmaCorp had already developed an initial drug candidate compound where the scientific goal was to help the body to secrete the natural hormone, and thus avoid synthetic hormone injections. Unfortunately, there were too many side effects, thus a new version was needed. The new objective of the resting project was to deliver a selective drug candidate that was simultaneously (i) patentable, (ii) similar enough to the previously developed drug, but (iii) with properties different enough to enable the avoidance of the side effects. The second exploratory project, subsequently called the ‘unmasking project’, concerned a therapy to fight a highly mortal disease which develops by escaping the immune system. Much research, both academic and corporate, focuses on understanding how this disease can escape the immune system, which remains passive when facing this particular disease. The ‘unmasking project’ was based on original research results © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
from a small biotechnology firm which PharmaCorp knew about thanks to the network of one of the PharmaCorp researchers. Its academic work had shown that one of the ways in which the disease cells escaped the immune system was by developing a protein that fooled the immune system into believing that the sick cells belonged to the body, like a sort of disguise or mask. The objective of the unmasking project was thus to explore ways of preventing the cells from developing this protein (the mask). The immune system would then be able to recognize the sick cells and thus function normally. Both the unmasking project and the resting project were considered counter-intuitive at PharmaCorp: the underlying mechanisms of action went against all previous attempts to apprehend the pathologies (stimulating the secretion during the resting projects, and targeting the sick cells directly during the unmasking project). The projects were supported by small teams who had only very few scientifically proven elements to support their claims. The teams also lacked clear and strong strategies for organizing their investigations. Consequently, they were both internally controversial and considered by many to be unrealistic endeavours. Yet, these projects appear to be more promising than the outcome of the scouting process. In order to discuss the managerial choices made during these projects, and compare them to the scouting process and the literature on FFE practices, all three managerial approaches will be analysed using the design reasoning framework.
The Pharmacorp Initiatives from a Design Reasoning Perspective The Scouting Process Within the Limits of Existing Knowledge Analysis of the scouting process using the design reasoning framework shows that it is restricted to the space of available knowledge, seeking candidates that match the predefined demanding criteria of the screening process. The objective of identifying drug candidates with predefined properties is based on the assumption that potential blockbusters exist and can be found. This is illustrated in Figure 2. Using this framework, three problems affecting the scouting process are highlighted: • The scope of the investigation is potentially infinite and difficult to structure. • The approach is based on the assumption that blockbuster candidates are available. • The approach assumes that methods of evaluation are already known. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
113
Figure 2. The Scouting Process from a Design Reasoning Perspective: Illustrating that Searching Through Given Knowledge did not Provide any Innovative Concepts In the context of the biopharma asset team, the very objective of the scouting process was to explore unknown therapeutic areas, which means that there was not enough available knowledge to evaluate external projects. If it is easy to kill ideas when you know something about them, it is much more difficult to do this when you do not know anything, which has been shown in previous research (Arora & Gambardella, 1990; Zucker & Darby, 1997). New evaluation criteria could be necessary in order to value innovative performances and there is the obvious risk of turning down ideas which could have been successful drug candidates. Although PharmaCorp did gain some new knowledge during the search process, there are no guarantees that this knowledge will be actionable since it is not necessarily related to a research programme.
Projects Exploiting Existing Knowledge in Order to Create Knowledge in New Areas Looking at the resting and unmasking projects which were undertaken in parallel by the discovery department, neither of these had stemmed from the scouting process; instead, they were examples of how previous knowledge had led to further exploration in new areas. They show that the actual discovery work carried out within the biopharma portfolio was less about identifying existing drug candidates (prototypes) and more about elaborating on the assets needed as well as designing compounds and mechanisms of action, through the renewal of the representation of the pathology. Using the same kind of reasoning for the two projects being studied at PharmaCorp, the double expansion of actual knowledge and existing concepts can be analysed. In the resting project (illustrated in Figure 3), new academic knowledge initially
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
114
Figure 3. The Resting Project from a Design Reasoning Perspective: Showing the Co-expansion of Evaluation Criteria, Mechanisms of Action and Means of Experimentation created an expansive partition of the initial concept of a therapy to fight the digestion problem (C0), suggesting that the existing concept of injecting hormones (C1: adding hormones) could be replaced by the alternative concept of regulating hormone production (C2: regulating hormones). Chemists then looked for analogue but specific compounds, while toxicologists looked for an appropriate animal model (e.g., small pigs). Clear research questions, based on the concept, thus guided the acquisition of knowledge. Medical doctors studied the destructive process of natural secretion and a new expansion appeared, this time on the knowledge side (K1). In addition to patients with the secretion disorder, people who had dysfunctional receptors of the hormone could be treated and prevented from becoming ill in the first place. This new knowledge opened up new market opportunities and further explorations could be justified for all three indications. In the resting project, the targeted function was still a therapy, but the actual properties and functionalities of the drug were expanded to include new alternatives (new concepts). The potential scope of indications could also be seen more broadly: studying the effects of the compound on the organism, scientists observed some further impact on other organs that could potentially pave the way for new indications (creation of new knowledge, K2).
Volume 16
Number 2
2007
The unmasking project started in a similar way (see Figure 4). The company was already working on the concept of developing a therapy to fight this disease (C0) in accordance with traditional concepts of passive immunotherapy (C1) (injections of antibodies that fight the sick cells) or active immunotherapy such as vaccine (C2) (where the body is stimulated to defend itself by activating the immune system). At this point, a researcher who had a large network in the field learned about results which showed how the disease cell could escape the immune system by disguising itself as a human cell. This new knowledge (K1) enabled an expansive partition of the C2 concept – active immunotherapy could be based on either stimulating the performance of the immune system, e.g., through vaccine (C2a), or on enabling the immune system to unmask the disease cells which would then just function normally (C2b). External research had also suggested antibodies that could stop the development of disguises (K2). Scientists at PharmaCorp studied the mechanisms of action behind the creation of the disguise and new antibodies were synthesized in order to start testing different antibodies that would prevent the development of the disease. Early tests showed that each antibody appeared to interact only with very specific sick-cells, depending on the patient. The creation of this new knowledge (K3) initiated the develop© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
115
Figure 4. The Unmasking Project from a Design Reasoning Perspective: Showing the Parallel Expansion in the Concept Space and the Knowledge Space ment of a detailed stratification of patients in order to define the scope of potential indications for each antibody. The concept thus helped the scientists to define what they needed to learn, i.e., what knowledge to develop in order to proceed. Thus, both projects are examples of the interactive and combined parallel generation of new concepts and new knowledge helping to advance the discovery process. The expanded concepts have created new questions for researchers and, conversely, the new knowledge has helped to evaluate the concepts in new ways. In addition to this, the knowledge created may also be used to generate other concepts in the future. While the scouting process stayed within the space of existing knowledge, the two exploratory projects used the knowledge available to define what other knowledge they would need in order to proceed, as illustrated by the generated concepts. The projects not only generated drug candidates for predefined targets, but also knowledge of new mechanisms of action and the targeted pathologies.
Discussion When analysing the empirical data, two contrasting FFE processes appear. The first one, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
the scouting process, follows the classic path: vigilance and attention to potential external opportunities (no internal ones as it is a new field for the company), clear evaluation criteria, a board of experts with various functional backgrounds. Conversely, the second one is more original and difficult to model, closer to the random or chaotic models described in the literature. Using the analysis of the empirical data, some of the main arguments from the FFE literature can be revisited.
Revisiting the Logics of the FFE – From Opportunity Recognition to Design The recognition and evaluation of innovative ideas, using specific evaluation grids to filter out the strongest concepts, are framed as important activities of the FEE. In the literature, the birth of an innovative concept is often described as ‘opportunity recognition’, i.e., the interpretation of some signals of an existing potential to develop further. Some authors have shown that it may be difficult to interpret various phenomena as an emerging concept of a future product, as this involves various stakeholders and heterogeneous competencies. The recognition often requires several ‘occurrences’, i.e., several repeated signals that lead to the recognition of an opportunity, based on
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
116
a ‘conceptualization of what the delivered benefits of the technology might be and how rich and robust those are’ (Colarelli O’Connor & Rice, 2001, p. 104). In this perspective, the birth of a concept is the formulation of an existing potential, or even a ‘discovery’ of a given but unformalized project. Recognition is then inseparable from evaluation; successive steps of evaluation are necessary in order to depict and select the relevant candidates. The scouting process studied is based on a similar logic, seeking to recognize opportunities among existing candidates. The molecules are evaluated according to their capacity to treat identified pathologies with defined therapeutic indications and predetermined mechanisms of action. The screening approach is far from new within the pharmaceutical industry; it dates back to the very beginning of the biotechnologies (Gaudillière, 2004). Historically, this logic has been very efficient in areas where much knowledge is already available and the objective is to refine existing therapies. Yet, the use of the design reasoning framework highlights the fact that the screening logic relies on the assumption that the concepts of therapy as well as promising candidates already exist, and are available to select. It thus presumes a strong pre-existing knowledge base. In the empirical study, the PharmaCorp scouting team screened about 600 companies using the same type of criteria as in other screening efforts in known therapeutic areas. However, despite this major effort, the existing portfolio contains no projects resulting from the scouting process, showing that this approach was insufficient. Those working on the scouting teams also said that they found it difficult to evaluate potential projects without knowing very much about the therapeutic areas. In highly innovative environments, further research and the generation of new knowledge are necessary to enable researchers to reframe the therapeutic mechanisms of action and the scope of indications, as well as renew experimental know-how. The screening logic is thus insufficient to support the discovery process. The projects in the biopharma portfolio stemmed instead from the exploitation of existing knowledge and research networks. Methods of generating and selecting drug candidates, e.g., rational drug design, combinatorial chemistry and mass screening logics, may be more reliable and perform better than ever, but the underlying assumption that concepts are pre-existing is seldom verified. When entering areas where the knowledge base is weak, the selection logic is thus insufficient since the evaluation criteria are unknown. The
Volume 16
Number 2
2007
scouting process can still serve to channel in-house expertise and inspire the exploration of new mechanisms of action or therapeutic indications, but it does not serve its intended purpose of identifying new candidates. The selection logic is insufficient in the FFE and must be complemented by an alternative logic during innovative product development.
Revisiting the Notion of Concept Generation: What is Generated? The expected outcome of the FFE is a clarification and a detailed specification of a product concept that is ready to enter the NPD process. It is broadly acknowledged that the FFE is a highly uncertain stage, where concepts are identified and clarified enough to be introduced into the NPD process. During the FFE, the level of ‘fuzziness’ is lowered by reducing uncertainties in the dimensions of markets, technology, required resources and fit with corporate capabilities and limits (Kim & Wilemon, 2002). However, the analysis of the empirical case study enables the refining of this proposition. The product concepts were not pre-existing, and the optimal attributes were not there to filter out. Instead, the attributes specifying the initial concept were added during a design process where additional concepts were also generated in parallel. The analysis of the two exploratory projects shows that the FFE process is far from random and unpredictable, rather it is an iterative learning process where concept attributes do not pre-exist but are designed on the basis of the generation of new knowledge illustrated by the design reasoning framework. At least three types of attributes enrich the initial concept (an innovative therapy to fight a disease), not only by choosing between interesting features or alternatives, but also, and more importantly, by expansion of the former scope of alternatives. First, new proposals regarding the mechanisms of action were generated. In the resting project, this was illustrated using the concept of resting the secretion process, generated through the new knowledge of the consequences of shutting down the hormone secretion function. In the unmasking project, improved knowledge of how the disease develops helped researchers to characterize a new way of addressing the disease. Second, proposals for new therapeutic indications were designed. In the resting project, the new mechanism of action (resting the secretion process) opened up a new field of investigation where scientists observed new and unexplored biological phenomena: they concluded that this mechanism of action could © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
have various physiological impacts and that it could be used to address several indications. This new knowledge opened up new market opportunities for treating or preventing different pathologies. Hence, the market segments were not defined in advance but created through knowledge expansion. In the unmasking project, further investigation was necessary in order to identify which populations were likely to be treated with the new mechanism of action. A third type of attribute is the experimental methods needed to develop the concepts. For instance, the projects revealed a need for more adequate methods of developing human antibodies that could meet specific requirements (e.g., high affinity, binding capacity, etc.). It was also necessary to develop relevant animal models and assays that could provide evidence of the efficacy of the drugs. Additionally, the way of designing relevant clinical trials, other than in vitro and animal models, needed improvement in order to find sustainable ways of testing efficacy and side effects. The need to develop methods of carrying out the relevant stratification of patient populations can also be stressed. These examples illustrate that the specification of a new concept includes both learning and development of the experimental methods. The generation of new methods is thus a third dimension of the notion of concept generation. The analysis of the two projects shows that knowledge generation is often guided by investigations initiated by the new concepts. For instance, to make use of new knowledge provided by academic or internal research (K0), new concepts are formulated, but further understanding of the mechanisms is often required in order to proceed (i.e., what causes the pathology or what regulates the immune system). This was illustrated by the resting project where it was necessary to obtain a deeper understanding of the different types of the disease and how the hormone secretion dysfunction varied between them. During the unmasking project, it was critical to capture the interaction between the immune system cells and the cells carrying the disease and, during a later stage, the need for detailed stratifications of the populations emerged, depending on the progression of the disease and the heterogeneity of the patient population. The creation of new knowledge also leads to new opportunities: during the resting project, instead of preventing the inhibition of the immune system, the drug was also able to activate it. As a consequence of this new knowledge, new conceptual proposals could thus be created. Using this logic, the expected outcome of the FFE is less the clarification of a © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
117
given concept than the generation of knowledge that will enable the expansion of original and broad concepts into families of concepts with new attributes.
Revisiting the Pharmaceutical FFE – From Drug Discovery to Drug Design The main managerial focus of the FFE is on reducing uncertainties and obtaining a high probability of success at minimal cost. The analysis of the scouting process and the two projects illustrates that clear ideas regarding drug candidates or target cells do not constitute the starting point of drug discovery processes, rather it is the result of broader design processes. Managing the pharmaceutical Front End as a ‘discovery’ and selection process thus appears restrictive. It is not only the recognition and evaluation of candidates that needs to be managed, but also the design process itself. The study showed that the design reasoning framework can be used to guide knowledge creation in the pharma FFE in three ways: 1. Fostering knowledge creation regarding the mechanisms of action for opening up the scope of the indications it can address. 2. Fostering physiological knowledge production in order to organize an exploration of the alternative concepts of mechanisms of action. 3. Stimulating knowledge creation regarding experimental methods in order to reopen previously terminated projects using new techniques. This way of reasoning in the FFE, based on the generation of alternative concepts, enables the development of more innovative products by expanding the knowledge base. The notion that both new knowledge and new concepts are generated during NPD is not new, but the C/K model allows the systematic organizing of a process wherein the expansion of alternatives can be illustrated. Furthermore, in line with previous literature, our study suggests that investments in learning processes are necessary in order to explore new attributes despite the inherent uncertainty: ‘firms should continuously explore new territories even if the risk of failure is magnified. The payoff is the learning that will pave the way for future success’ (Maidique & Zirger, 1985, p. 312). This necessitates a longer managerial horizon than traditional portfolio management and a focus on a collective learning process within the organization, where projects are used to define what knowledge needs to be generated, in conjunction with the NPD process. From an economic point of view, the exploration strategy sup-
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
118
ported by the design reasoning perspective could appear both risky and expensive since the output is uncertain and not always directly applicable. However, if the knowledge needed to identify and evaluate drug candidates already exists, this will be due to previous investments in the area. When exploring new and highly innovative fields, where the potential to develop innovative drug candidates is great, investment in these assets is an inevitable cost – it is the price of being first. The FFE processes of innovative product development are better described as drug design processes than discovery, inducing the need for new managerial logics and economic calculation methods where expansion, in combination with cost-effectiveness, is in focus.
Proposals for Further Research The study shows that existing FFE management models are insufficient when the aim is to develop innovative products that are based on knowledge that the company does not yet possess. To succeed in doing that, a different logic is required and more research is needed in order to better understand how the FFE can enable development processes that are simultaneously creative and cost-effective. Experiments on management models and comparisons between industries are necessary in order to better capture the prerequisites of design reasoning in the FFE. For instance, the implications for management concern a shift away from the selection of which projects to fund, among a set of proposed projects, toward the use of a design structure that will guide the emergence of a set of projects that will be prioritized later on. The knowledge produced could also be memorized and recombined in many different ways, using a representation of the C-K iterations for visualization. Instead of considering the termination of uncertain explorations to be a waste of time and resources, this could be used to evaluate other concepts or to give birth to new concepts that may be further explored. Instead of just valuing the expected cashflows of a compound given an estimated risk, the C-K model could also support a discovery-specific portfolio management strategy by means of valuing both the knowledge produced and the expansion of conceptual proposals. The objective would then not be solely to reduce the level of uncertainty in ongoing projects, but also to map the field of opportunity, to identify areas where learning processes are needed, and to effectively organize the expansion of products (therapies) as well as capabilities in a consistent way. These proposals will be the focus of future studies.
Volume 16
Number 2
2007
Conclusions In this paper, an empirical study of the managerial practices of a pharmaceutical discovery department was presented. Modelling a scouting (screening) process initiative as well as two exploratory projects from a design reasoning perspective enabled widely contrasting Front End activities to be highlighted. The analysis suggests that the screening logic is insufficient when entering highly innovative fields. In such contexts, investment in strong collective learning processes seems necessary in order to explore physiological mechanisms and specify new mechanisms of action capable of leading to the development of successful drug candidates. The analysis of the two projects suggests that the discovery process is more of a design process whereby the iterative generation of new concepts and new knowledge leads the endeavour; the product concept is not selected or narrowed down to one optimum candidate, rather concept generation is about expanding the attributes into a range of concepts. Thus, the notion of drug design strategies is proposed to better mirror the actual process than the term discovery does. The analysis suggests that the existing literature on the FFE does not fully cover the management of innovative product development, with the need for an alternative logic being highlighted. This analysis is based on a very limited number of cases at one single pharmaceutical company. However, it provides some interesting insights for guiding further investigation at other companies and within other industries. Further research is also needed in order to develop generic organizational tools for mapping innovation fields and supporting the actors in charge of this process. It would also be useful to reflect on the tools and actors relating to knowledge capitalization and reuse, in order to identify promising areas of investigation and to orientate further research during the early phases of innovative product development.
References Adler, N., Shani, R. and Styhre, A. (2003) Collaborative Research in Organizations, Foundations for Learning, Change and Theoretical Development. Sage Publications, New York. Argyris, C. (1993) Knowledge for Action: A Guide to Overcoming Barriers to Organizational Change. Jossey-Bass, San Francisco. Argryis, C., Putnam, R. and Smith, D.M. (1995) Action Science – Concepts, Methods and Skills for Research and Intervention. Jossey-Bass, San Francisco. Arora, A. and Gambardella, A. (1990) ‘Complementarity and External Linkages: the Strategies of the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
TOWARDS A NEW LOGIC FOR FRONT END MANAGEMENT
Large Firms in Biotechnology’, Journal of Industrial Economics, 38, 369–80. Börjesson, S., Dahlsten, F. and Williander, M. (2006) ‘Innovative Scanning Experiences from an Idea Generation Project at Volvo Cars’, Technovation, 26, 775–83. Burchill, G. and Fine, C.H. (1997) ‘Time Versus Market Orientation in Product Concept Development: Empirically-based Theory Generation’, Management Science, 43, 465–78. Carbone, J. (2003) ‘Ethics, Patents and the Sustainability of the Biotech Business Model’, Journal of Law Computers & Technology, 17, 203– 18. Cheng, Y-T. and Van de Ven, A.H. (1996) ‘Learning the Innovation Journey: Order Out of Chaos’, Organization Science, 7, 593–614. Colarelli O’Connor, G. and Rice, M.P. (2001) ‘Opportunity Recognition and Breakthrough Innovation in Large Established Firms’, California Management Review, 43, 95–116. Cooper, R.G. (1997a) ‘Fixing the Fuzzy Front End of the New Product Process’, CMA Magazine, 71, 21–23. Cooper, R.G. (1997b) ‘Taking the Fuzziness out of the Fuzzy Front End’, Research Technology Management, 42, 25–31. Cooper, R.G. (1988) ‘The New Product Process: A Decision Guide for Management’, Journal of Marketing Management, 3, 238–55. David, A. (2002) ‘Intervention Methodologies in Management Research’, paper presented at the EURAM Conference 9–11 May, Stockholm, Sweden. DiMasi, J.A., Hansen, R.W. and Grabowski, H.G. (1991) ‘Cost of Innovation in the Pharmaceutical Industry’, Journal of Health Economics, 10, 107– 42. DiMasi, J.A., Hansen, R.W. and Grabowski, H.G. (2003) ‘The Price of Innovation: New Estimates of Drug Development Costs’, Journal of Health Economics, 22, 151–85. Drews, J. (2000) ‘Drug Discovery: A Historical Perspective’, Science, 287, 1960. Drucker, P.F. (1988) ‘The Coming of the New Organization’, Harvard Business Review, 66, 45–53. Dubois, A. and Gadde, L.E. (2002) ‘Systematic Combining: An Abductive Approach to Case Research’, Journal of Business Research, 55, 553– 60. Federsel, H.-J. (2000) ‘Building Bridges from Process R&D: From a Customer–Supplier Relationship to Full Partnership’, Pharmaceutical Science Technology Today, 3, 265–72. Gambardella, A. (1995) Science and Innovation, the US Pharmaceutical Industry during the 1980s, Cambridge University Press, Cambridge. Gaudillière, J.-P. (2004) ‘Hormones, régimes d’innovation et stratégies d’entreprise: les exemples de Schering et Bayer’, Entreprises et Histoire, 36, 84–102. Grabowski, H.G. and Vernon, J. (2000) ‘The Distribution of Sales Revenues from Pharmaceutical Innovation’, PharmacoEconomics, 18, 21–23. Griffin, A. (1997) ‘The Effect of Project and Process Characteristics on Product Development Cycle Time’, Journal of Marketing Research, 34, 24–35. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
119
Hatchuel, A. (2002) ‘Towards Design Theory and Expandable Rationality: The Unfinished Program of Herbert Simon’, Journal of Management and Governance, 5, 260–71. Hatchuel, A. and Weil, B. (2001) ‘A New Approach of Innovative Design: An Introduction to C-K Theory’, in Proceedings of 14th International Conference on Engineering Design (ICED’03), Stockholm, Sweden, pp. 1794–1805. Hatchuel, A., Le Masson, P. and Weil, B. (2004) ‘C-K Theory in Practice: Lessons from Industrial Applications’, in Proceedings of the 8th International Design Conference, Dubrovnik, pp. 245– 57. Hatchuel, A., Le Masson, P. and Weil, B. (2005) ‘The Development of Science-based Products: Managing by Design Spaces’, Creativity and Innovation Management, 14, 345–54. Iansiti, M. and West, J. (1997) ‘Technology Integration: Turning Great Research into Great Products’, Harvard Business Review, 75, 69–79. Kazakci, A.O. and Tsoukias, A. (2005) ‘The C-K Design Theory: A Theoretical Background for Personal Design Assistants’, Journal of Engineering Design, 16, 399–411. Khurana, A. and Rosenthal, S.R. (1997) ‘Integrating the Fuzzy Front End of New Product Development’, Sloan Management Review, 38, 103–20. Khurana, A. and Rosenthal, S.R. (1998) ‘Towards Holistic “Front Ends” in New Product Development’, Journal of Product Innovation Management, 15, 57–74. Kim, J. and Wilemon, D. (2002) ‘Focusing the Fuzzy Front End in New Product Development’, R&D Management, 32, 269–79. Kline, S.J. and Rosenberg, N. (1986) An Overview of Innovation. In: Landau, R. and Rosenberg, N. (eds.), The Positive Sum Strategy, National Academy Press, Washington, DC. Koen, P., Ajamian, G., Burkhart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., Johnson, A., Karol, R., Seibert, R., Slavejkov, A. and Wagner, K. (2001) ‘Providing Clarity and a Common Language to the “Fuzzy Front End” ’, Research Technology Management, March–April, 46–55. Le Masson, P., Hatchuel, A. and Weil, B. (2006). Les processus d’innovation. Conception innovante et croissance des entreprises. Hermès, Paris. Liebenau, J. (1987) Medical Science and Medical Industry, the Formation of the American Pharmaceutical Industry. The Macmillan Press, Baltimore, MD. Lynn, G.S., Mazzuca, M., Morone, J.G. and Paulson, A. (1998) ‘Learning is the Critical Success Factor in Developing Truly New Products’, Research Technology Management, 41, 45–51. Maidique, M.A. and Zirger, B.J. (1985) ‘The New Product Learning Cycle’, Research Policy, 14, 299– 313. Moulin, A.M. (1991) Le dernier langage de la médecine, P.U.F., Paris. Nobelius, D. and Trygg, L. (2002) ‘Stop Chasing the Front End Process – Management of the Early Phases in Product Development Projects’, International Journal of Project Management, 20, 331–40.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
120
Reinertsen, D.G. (1999) ‘Taking the Fuzziness out of the Fuzzy Front End’, Research Technology Management, November–December, 25–31. Reinertsen, D.G. and Smith, P.G. (1991) ‘The Strategist’s Role in Shortening Product Development’, The Journal of Business Strategy, July/August, 18–22. Rice, M.P., Kelley, D., Peters, L. and Colarelli O’Connor, G. (2001) ‘Radical Innovation: Triggering Initiation of Opportunity Recognition and Evaluation’, R&D Management, 31, 409–20. Sanderson, S. and Uzumeri, M. (1995) ‘Managing Product Families: The Case of the Sony Walkman’, Research Policy, 24, 761–82. Schmid, E.F. and Smith, D.A. (2002) ‘Should Scientific Innovation be Managed?’, Drug Discovery Today, 7, 941–5. Seget, S. (2002) Pharmaceutical Innovation: An Analysis of Leading Companies and Strategies, Datamonitor PLC. Simon, H.A. (1986) Decision Making and Problem Solving, Research Briefing. National Academy Press, Washington, DC. Starkey, K. and Madan, P. (2001) ‘Bridging the Relevance Gap: Aligning Stakeholders in the Future of Management Research’, British Journal of Management, 12, 3–26. Studt, T. and Casssidy, R. (1995) ‘The Realities of Drug Discovery, from an Insiders Viewpoint’, R&D Magazine, November, 58–60. Sundgren, M. (2004) New Thinking, Management Control and Instrumental Rationality. Managing Organizational Creativity in Pharmaceutical R&D. PhD thesis, Department for Project Management, Chalmers University of Technology, Gothenburg. Tapon, F. and Cadsby, C.B. (1996) ‘The Optimal Organization of Research: Evidence from Eight Case Studies of Pharmaceutical Firms’, Journal of Economic Behavior & Organization, 31, 381–99. Thomke, S. (2001) ‘Enlightened Experimentation – The New Imperative for Innovation’, Harvard Business Review, February, 67–76. Thomke, S., Von Hippel, E. and Franke, R. (1998) ‘Modes of Experimentation: An Innovation Process – and Competitive – Variable’, Research Policy, 27, 315–32. Van de Ven, A.H. (1986) ‘Central Problem in the Management of Innovation’, Management Science, 32, 590–607. Verganti, R. (1999) ‘Planned Flexibility: Linking Anticipation and Reaction in Product Development Projects’, Journal of Product Innovation Management, 16, 363–76.
Volume 16
Number 2
2007
Walsh, V. (1984) ‘Invention and Innovation in the Chemical Industry: Demand-pull or Discoverypush?’, Research Policy, 13, 211–34. Zucker, L.G. and Darby, M.R. (1997) ‘Present at the Biotechnological Revolution: Transformation of Technological Identity for a Large Incumbent Pharmaceutical Firm’, Research Policy, 26, 429– 46.
Maria Elmquist (formerly Backman) (maria.
[email protected]) is a researcher at the division of Project Management at Chalmers University of Technology and the Fenix research programme (Stockholm School of Economics and Chalmers) and a research fellow at the Centre for Management Science (CGS) at Ecole des Mines de Paris in 2004. Her research mainly concerns innovation management, concept development and new product development and she will present her dissertation on prerequisites for innovation in complex R&D processes in February 2007. Recent publications include articles in R&D Management, European Journal of Innovation Management and Knowledge and Process Management and she has published a book on a concept car project (2005, Liber). Blanche Segrestin (blanche.segrestin@ ensmp.fr) is Assistant Professor in charge of research in industrial design and innovation management at the Centre for Management Science (CGS) at Ecole des Mines de Paris. She holds a PhD in Management Science from the Ecole des Mines de Paris and was fellow research associate at the Fenix research programme (Stockholm School of Economics and Chalmers) in 2002–2003. Her main research interests are design activities, innovation management and inter-firm relationships. Recent publications include articles in Research Policy, R&D Management and International Journal of Automotive Technology and she has recently published a book on innovation and inter-firm cooperation (2006, CNRS Editions).
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
121
Interdisciplinary Heterogeneity as a Catalyst for Product Innovativeness of Entrepreneurial Teams Daniel Henneke and Christian Lüthje Although more and more ventures are successfully founded by entrepreneurial teams, the specific benefits of the team-based founding approach have received little attention in extant empirical studies. This study explores the relationship between the level of interdisciplinary heterogeneity in entrepreneurial teams and the level of product innovativeness in high-tech ventures. It is proposed that an interdisciplinary new venture team composition impacts the quality of the strategic planning process (scanning activities, planning openness) and thereby indirectly shapes product innovativeness. The hypotheses are investigated using data from a sample of Canadian high-tech ventures. The findings provide support for the proposed relationship between team heterogeneity, strategic planning and product innovativeness. Venture capitalists, university faculty and incubator institutions are therefore well advised to direct their attention towards fostering a heterogeneous composition of founding teams.
Introduction
N
umerous examples indicate that many of today’s highly successful companies were founded by teams. Anecdotal evidence such as Microsoft and Apple support the growing body of empirical findings. However, early studies widely neglected entrepreneurial teams as an issue of research, and this contributed to the myth of the lonely entrepreneur. Nevertheless, more and more work shows that the foundation of new companies by more than one person is a widespread phenomenon (e.g., Teach et al., 1986; Feeser & Willard, 1990; Roberts, 1991) – particularly in high-tech industries (Kamm et al., 1989; Francis & Sandberg, 2000). An increasing number of founder teams has prompted researchers to shift their attention to the entrepreneurial team as a determinant of venture success. Despite the various plausible arguments for the potential benefits of entrepreneurial teams, their impact on a firm’s subsequent performance is not as clear-cut. Although many studies show that firms founded by teams are on average more successful than those founded by single entrepreneurs (e.g., Cooper & Bruno, 1977; Tyebjee & Bruno, 1984; Teach et al., 1986; Roberts, 1991), others failed
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
to support a strong team–success relationship (Doutriaux, 1992; Sternberg et al., 1996; Der Foo, Wong & Ong, 2005). These results, although partially contradictory, suggest that a team-based venture foundation may be an important condition of success. They seem to indicate that the performance of new ventures is contingent upon the interaction of the team members and the activities of the team in the course of new product development. In the present study, interdisciplinary team heterogeneity is suggested to represent a central determinant of the product innovativeness of entrepreneurial firms. This suggestion is stimulated by existing research showing the positive effects of interdisciplinary team composition on innovativeness, strategic planning openness and, more generally, propensity for strategic change ( Bantel & Jackson, 1989; Lant & Milliken, 1992; Wiersema & Bantel, 1992; Bantel, 1994). However, these studies investigated almost exclusively top management teams (TMTs) in established companies. In contrast, the body of entrepreneurship research on this issue is scarce. In particular, there is only limited understanding of the impact of team demography on variables possibly mediating the relationship between interdisciplinary heterogeneity of a
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00426.x
CREATIVITY AND INNOVATION MANAGEMENT
122
venture team and its subsequent product innovativeness. In this respect, strategic planning posits an important aspect in the context of entrepreneurial ventures as strategic decisions of entrepreneurial teams are usually not – or only to a very limited extent – diluted by subordinates and, thus, directly impact the product innovation process of new ventures (Beaver & Prince, 2002). Therefore, it seems appropriate to examine how team heterogeneity affects intra-firm processes, namely strategic planning openness and environmental scanning, to understand their overall impact on the venture’s product innovativeness. Educational heterogeneity as a measure of the interdisciplinary composition of a founding team is proposed to directly affect the quality of the team’s strategic planning processes and indirectly influence the product innovation capabilities of a firm. A second rather exploratory purpose of the present study is to analyse the effects of different types of team formation processes on a team’s composition. How teams are formed and how this determines the interdisciplinary heterogeneity of new venture teams has so far received only limited research effort (e.g., Kamm et al., 1990; Cooper et al., 1997; Forbes et al., 2006). In a similar vein, only few researchers have argued for the continuation of team formation processes even after the instance of the formal creation of a new firm. Following this argument, we expect to find that differing levels of heterogeneity depend upon the process of team formation. The remainder of the paper continues with the development of our research hypotheses. Then, the research context and methods are reviewed. The findings are presented in the fourth section. The paper ends with a discussion of the implications and limitations of this study indicating directions for future research.
Hypotheses Development Empirical findings have so far provided evidence that TMT heterogeneity with respect to demographic characteristics plays an important role in explaining organizational outcomes (e.g., Hambrick, Cho & Chen, 1996; West & Anderson, 1996; Carpenter, 2002). Studies have investigated both the direct effects of team heterogeneity on organizational outcomes as well as its indirect effects through intervening process variables. Models addressing direct effects often employ educational and functional heterogeneity as a proxy for the cognitive diversity of a team. It has been suggested that heteroge-
Volume 16
Number 2
2007
neous teams comprising diverse experience and competencies exhibit a higher diversity of ideas than homogeneous teams which contributes to a higher level of creativity and a higher degree of innovation in the resulting problem solutions (Bantel & Jackson, 1989; O’Reilly, Williams & Barsade, 1998; Flatt, 2004). The direct effects are addressed in hypothesis 1. However, the exclusive focus on direct effects of team heterogeneity has been criticized as the interpretation of the relationship between demographic heterogeneity and the related dependent variables was based partially on mediating variables (e.g., team conflict, decision making in the team), although most studies neither measured the intervening variables nor tested the related inferences (Lawrence, 1997). In order to address these effects, hypotheses 2–5 introduce strategic planning variables as intermediates.
Educational Heterogeneity: Innovativeness In the present study, we employ educational heterogeneity as the measure of an entrepreneurial team’s interdisciplinarity. Regarding the potential impact of formal academic skills and knowledge, we suggest that teams with an interdisciplinary educational background have at their disposal a wide set of procedural and instrumental knowledge. Technology-related educational knowledge, therefore, provides the foundation for substantial technological inventions, while marketing skills help to monitor the competitive landscape. It is suggested that an educational background in general management enables potential team members to integrate market-related opportunities with a firm’s actual technological developments. Finally, financial skills should provide an essential basis for acquiring funds necessary to conduct development and marketing activities. Hence, the combination of diverse competencies is expected to contribute to the team’s product innovation capabilities (Freel, 2003). For TMTs in established companies, Bantel and Jackson’s (1989) study revealed that heterogeneous TMTs with respect to their educational background tend to initiate more substantial innovation projects. Therefore, we propose a positive relation between the diversity of formally acquired knowledge in terms of a team’s academic education and its product innovativeness. H1: The level of educational heterogeneity of an entrepreneurial team is positively related to the level of its product innovativeness. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
Educational Heterogeneity: Strategic Planning A core assumption of this study refers to strategic planning variables mediating the effect of educational heterogeneity on product innovativeness. An interdisciplinary educational background of a team is supposed to allow for comprehensively assessing the market, the technological, as well as the financial environment of a company. Miller and Friesen (1982) highlighted the importance of environmental scanning as a prerequisite to recognize and adapt to changing requirements of the environment in order to innovate successfully. This requires an entrepreneurial team member to be able to adequately perceive and process external information which partially reflects the need for a comprehensive set of skills and competencies based on their educational backgrounds. This, in turn, results in a selective exposure, perception and interpretation of environmental information (Hambrick & Mason, 1984). Thus, varying backgrounds – such as technology, marketing, or sales backgrounds – seem to be beneficial in order to conduct a comprehensive gathering of external information. In addition, it is further suggested that the relation between a team’s interdisciplinarity and its product innovativeness depend on the team’s ability to adapt to perceived changes in the competitive landscape. To address these changes, the entrepreneurial team has to remain flexible in the planning process. It needs to show the willingness and ability to reformulate existing strategies and to develop new plans. Bantel (1994, p. 407) defined this kind of openness as the ‘deliberate attempt on the part of the top management team to systematically be open and responsive to environmental information’. However, the development of new plans for strategic actions requires sufficient relevant knowledge. Hambrick et al. (1996) showed that teams, heterogeneous with respect to their educational backgrounds, exhibited a higher level of propensity, noteworthiness and scope of strategic action. Other studies found further support for the hypothesis that the combination of diverse experiences and knowledge fosters the propensity of a team to formulate flexible strategies and to initiate strategic reorientation processes (Lant & Milliken, 1992; Wiersema & Bantel, 1992). Hence, it is suggested that the extent of gathering external information (environmental scanning) and the subsequent openness of an entrepreneurial team to respond comprehensively to this information by modifying its strategy (strategic planning © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
123
openness) depend on the diversity of the formally acquired academic knowledge present in the team. H2: The level of educational heterogeneity is positively related to the extent of environmental scanning conducted by the entrepreneurial team. H3: The level of educational heterogeneity is positively related to the level of strategic planning openness of the entrepreneurial team.
Strategic Planning: Product Innovativeness We propose that team heterogeneity is indirectly related to product innovativeness through the quality of the intervening strategic planning processes. Environmental scanning has been examined with respect to its impact on innovativeness, although predominantly in a TMT or strategy/ marketing research context. Several studies provided support for a positive environmental scanning–innovativeness linkage (e.g., Hurley & Hult, 1998; Crick & Jones, 1999). The positive implications of environmental scanning for the venture team’s product innovativeness are assumed to be due to the team’s recognition of technological as well as market opportunities. Market-related information provides insight into potential needs of customers. Furthermore, environmental scanning with respect to the state-of-the-art technology sheds light on potential future trends that may open avenues to substantial technological product innovation. Hence, combining market- and technology-related scanning activities enables an entrepreneurial team to identify and address potential competitive opportunities. The findings of Koberg et al. (1996) as well as Khan and Manopichetwattana (1989) support the notion that technology- and marketrelated environmental scanning activities enhance a new venture team’s level of product innovativeness. In a similar vein, it is suggested that strategic planning openness fosters a firm’s product innovativeness. It refers to the team’s degree of responsiveness towards changing environmental conditions as it fosters the assimilation of formal and informal environmental information. Maintaining strategic planning openness enables the team to assess the need for an alteration of existing strategic plans in order to incorporate new strategic perspectives or challenges, respectively. This allows entrepreneurial teams to continuously recognize and evaluate newly arising market opportunities or technology concepts – hence, innovations.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
124
Figure 1. New Integrated Model
Thus, strategic planning openness seems to be particularly conducive to success in the context of high-tech ventures as it ‘would allow managers to make the on-going, necessary changes in the strategic direction, that are critical to firm viability in today’s business environment’ (Bantel, 1994, p. 407). Drawing upon the suggested indirect relation between educational heterogeneity and product innovativeness, environmental scanning and strategic planning openness are proposed to positively mediate the effects of heterogeneity on product innovativeness. H4: The extent of environmental scanning is positively related to the venture team’s level of product innovativeness. H5: The extent of strategic planning openness is positively related to the venture team’s level of product innovativeness. Based on empirical evidence, the present study focuses on variables that measure the type and quality of strategy formulation mediating the relation between the team demographic variables and product innovativeness. We therefore propose that new venture teams influence organizational outcomes – such as product innovativeness – primarily by their strategic decisions. By developing an understanding of the indirect effects of interdisciplinary heterogeneity on product innovation through the strategy formulation process, researchers should be in a better position to anticipate organizational outcomes of newly founded ventures. Figure 1 integrates our hypotheses into a model.
Methodology Sample The study was conducted in the Waterloo region of Ontario, Canada. The population selected for the study included start-up firms established in high-tech sectors such as
Volume 16
Number 2
2007
advanced manufacturing, IT, biotechnology, pharmaceuticals and automotive technology. We conducted eight semi-structured, exploratory interviews with members of the founding teams in eight companies preceding the survey. The purpose was both to develop valid scales for certain constructs in the model and to assess the appropriateness of the model hypotheses. The interviews provided preliminary support for the existence of a relation between the demographic composition of the founding teams and their strategic planning activities. The survey sample was compiled from two sources: a research database provided by the Office of Research at the University of Waterloo and another published by the Canada Tech Triangle Inc. (CTT). The initial sample consisted of 397 companies. After eliminating closed or moved businesses and firms that did not match the research criteria, the final sample included 311 firms. The data were collected through an online questionnaire addressed to the CEOs of the firms. All potential participants were initially contacted by personalized emails. After two weeks, the addressees received a reminding follow-up postal letter. In a third round, firms were contacted through telephone asking for their participation. We finally obtained 43 usable responses, a response rate of 13.8 per cent. This small number of responses means that the results may have limited transferability to other situations. IT-oriented companies, with a share of 64 per cent, dominate the sample. The next largest groupings are the automotive and advanced manufacturing sectors and the biotechpharma-environmental group, both with 11 per cent. The group of other businesses accounts for a 13 per cent share. This group includes sectors such as laser technologies, gaming technologies and the food industry. The average age of the companies was seven years with a median of five years. The current average number of employees is 31 with a median of seven employees indicated rather small companies with few exceptions. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
Measures
N/A 18%
Educational Heterogeneity Educational heterogeneity was used as a measure of interdisciplinary team composition. The decision to focus on this variable was guided by the result of the explorative interviews. Many firms in our sample were founded by scientists formerly working in research. Additionally, a significant fraction of the founders started their businesses shortly after their graduation. For these founders, the knowledge and experiences acquired in the course of their academic education represents the bulk of their total amount of professional knowledge. Hence, educational experience is assumed to be a very relevant measure of team demography. The respondents were asked to provide information about the educational background of all founding team members. Each member of the team was assigned to one educational specialty as outlined in the Appendix. Blau’s index was used for the educational heterogeneity (Blau, 1977). The heterogeneity was computed using the formula: H = 1 − Σpi2 , where pi2 represents the squared proportions of all present competence categories.
Strategic Planning The type and quality of the strategic planning process were assessed using two different scales. The firms’ engagement in environmental scanning activities was measured using a nine-item scale. Four items referred to activities to gather market information, and three items were associated with the scanning of the technological environment. These items were adapted from scales developed by Miller and Friesen (1982) and Crick and Jones (1999). During the interviews, ventures capitalists stated that entrepreneurial teams frequently had problems in acquiring first- and particularly second-round funding. Therefore, two items were added addressing the external exploration of funding. This is based on the assumption that venture teams engaging in a comprehensive and proactive scanning of external sources of capital should be in a better position to develop and commercialize innovative products. An index was calculated combining the means of the items in the three scanning areas (market, technology, funding). Cronbach’s a for the environmental scanning scale resulted in a value of aES = 0.757. The openness of the strategic planning process was measured using a five-item scale developed by Bantel (1994) with minor adaptations in wording. Cronbach’s a for the strategic openness scale resulted in a value of aSO = 0.654. The © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Friendship 23%
125
Ext. Investor 14%
Prior Working 45%
Figure 2. Proportions of Team Formation Modes
actual measure applied for strategic planning was the overall mean of all items. Product Innovativeness This variable refers to the measurement of product innovativeness as an important outcome of the venture team’s strategic actions and a main indicator for venture success (Hult, Hurley & Knight, 2004). It represents a team’s capacity to develop product innovations. The items applied in this study refer to product innovativeness as part of an overall organizational innovativeness. They were taken from a scale developed by Wang and Ahmed (2004) to measure different sub-forms of organizational innovativeness. Cronbach’s a for the product innovativeness scale resulted in a value of aPI = 0.701. Again, we used an index by calculating the mean over all items.
Results Descriptive Findings The proportion of different team formation modes in the sample are illustrated in Figure 2. About half of the teams (45 per cent) emerged out of groups that had professional relations prior to the firm’s foundation. Often, they were colleagues at university or collected joint working experiences in previous ventures. Some 23 per cent of all teams were formed drawing upon family members and friends. Only 14 per cent of all founding teams were formed under the lead of an investor deliberately searching and enlisting persons to join the team. In total, the predominant mode of team formation was the so-called ‘group approach’ in which venture teams form based on professional and personal relations. This finding is in accordance with existing empirical evidence (e.g., Timmons, 1999; Chandler & Lyon, 2001).
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
126
External Investor
0.66
Prior Working
0.46
0.31
Friendship
0
0.2
0.4
0.6
0.8
Figure 3. Educational Heterogeneity Depending on Different Team Formation Modes In entrepreneurship research, a growing interest in processes of team formation has evolved with particular attention to their association with team behaviour and the subsequent venture performance (Kamm et al., 1990; Cooper & Daily, 1997). One research issue refers to the question whether the nature of team formation is related to its level of interdisciplinary heterogeneity. It seems reasonable to assume that team formation processes based on the ‘group approach’ should, on average, lead to lower levels of team heterogeneity because the criterion of prior relationships is expected to superimpose the need for finding people with different educational backgrounds. In contrast, if the team formation process is dominated by an investor employing a deliberate recruitment process, a higher probability exists that knowledge ‘gaps’ are filled in order to assemble a functionally balanced team. The findings presented in Figure 3 support this proposition. The numbers indicate the calculated values for Blau’s heterogeneity index that is standardized between 0 and 1. The average educational heterogeneity exhibited by teams formed under the influence of an external investor was 0.66, whereas teams formed based primarily on friendship or prior working relations were more homogeneous (0.31 and 0.46, respectively). These results are supported by the findings of Vanaelst et al. (2006) who found indications that academic start-up teams are usually more homogeneous with respect to their experience during the early stages of a venture.
Correlation Analysis The relationships proposed in the model were tested by calculating partial correlations between the variables. This was assumed appropriate owing to the small number of responses as multivariate methods of analysis (e.g., hierarchical regression analysis) require a larger sample to provide reliable correlations.
Volume 16
Number 2
2007
The results are presented in Figure 4. Educational heterogeneity (H) was proposed to be positively related to innovativeness (I), environmental scanning (S), and the openness of the strategic planning process (O). Hypothesis 1 proposed the existence of a direct relation between educational heterogeneity and innovativeness. The proposed link is not supported by the findings. Therefore, hypothesis 1 has to be rejected. Hypothesis 2 stated that educational heterogeneity is positively related to the intensity of environmental scanning activities. This relation is weakly supported (p < 0.1). Educational heterogeneity was further expected to be positively related to strategic planning openness. This relationship is significant at a 5 per cent level providing support for hypothesis 3. The findings suggest that educational heterogeneity of new venture teams in fact impacts the strategic planning processes of the ventures. The two strategic planning variables were expected to be positively related to the level of the venture team’s product innovativeness. Hypothesis 4 stated that environmental scanning is positively related to innovativeness. Given the significant correlation coefficient (p < 0.05), hypothesis 4 is supported. Also the level of strategic planning openness was proposed to show a positive effect on innovativeness. The link is found to be significant at the 5 per cent level. Therefore, hypothesis 5 can be accepted.
Discussion The present study aims to provide empirical evidence for the relationship between the interdisciplinary educational composition of new venture teams and their product innovativeness. The results do not support the hypothesis of a direct link between educational heterogeneity and product innovativeness. In fact, we find that this relationship is mediated by strategic planning variables. In formulating our hypotheses we distinguish between the comprehensiveness of environmental scanning activities and the openness of the planning process as two key characteristics of strategic planning. With respect to the first variable, we find weak support for the relationship between educational heterogeneity and environmental scanning. Founding teams that encompass diverse educational backgrounds seem to have a higher level of ‘absorptive capacity’ to identify and interpret relevant pieces of information in different sub-areas of the company (Cohen & Levinthal, 1990). The presence of people with differing knowledge and experi© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
127
Figure 4. Results of the Correlation Analysis
ences stimulates the consideration of a larger set of information relevant to strategic decision making. Jointly monitoring the market, technological, as well as the financial environment facilitates retrieving and evaluating opportunities for product innovations. The lack of stronger effects for educational heterogeneity may be attributable to the specific contextual forces that act upon many high-tech start-up firms. In fast-paced settings like the industries investigated in this study, the technological dynamics, competitive turbulence and demand change seem to prompt venture teams to strive for rapid strategic decision making. The team members might decide to reduce the comprehensiveness of information gathering by obtaining input from only a limited number of sources and by focusing on only a few environmental fields. This shows that the team members follow the commonly held perspective that comprehensive environmental scanning slows down the strategic planning process. It is important to note here that this assumption is not necessarily true. Eisenhardt (1989) showed in her inductive study of microcomputer firms that making fast strategic decisions does not imply using less information. On the contrary, the findings suggested that fast decision makers tend to use more, not less, real-time information. Nevertheless, we believe that most new venture teams, including heterogeneous ones, intuitively choose to reduce the environmental scanning activities when confronted with high levels of environmental dynamic. With respect to the second strategic planning variable, the findings strongly indicate that a heterogeneous composition of the team fosters strategic planning openness. Diversity in cognitive perspectives seems to facilitate the consideration of a wider range of strategic options for the firm. This shows that heterogeneous teams lower the barriers to adapt the business strategies appropriately to changing technological trajectories, emerging competitive challenges or shifting customer demand. Making necessary strategic changes is, there© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
fore, critical for the development of innovative products. Contrary to the line of argument with respect to environmental scanning activities, the propensity of business founders to meet the changing demand of a turbulent environment does not necessarily impede the aim of heterogeneous teams to maintain strategic openness since high velocity industries are characterized by changes with respect to technology, demand and competitiveness. Thus, new venture teams should not presume an incompatibility between strategic openness and fast-pace environments. The present study helps to develop a better understanding of the relation between the demography of new venture teams and organizational outcomes. The rejection of hypothesis 1 assuming a direct effect of heterogeneity on product innovativeness underscores the importance of opening the ‘black box’ of organizational demography in the context of new ventures (Bantel, 1994; Lawrence, 1997). The findings lend support to the perspective that intervening processes mediate the relationship between entrepreneurial team characteristics and firm outcomes. The heterogeneity of a new venture team with respect to educational backgrounds is an antecedent to strategic planning, which is itself an antecedent to product innovation outcomes of young firms. In other words, strategic planning partly mediates the relationship between team characteristics and the organizational outcome.
Implications The relevance of the results of the model is highlighted by the findings of the descriptive analysis. On the one hand, the model test reveals that team heterogeneity is an important antecedent to product innovativeness. On the other hand, we found that most founding teams are formed on the basis of personal and professional relationships and, therefore, are likely to be rather homogeneous in terms of the educational backgrounds of the partners. This problematic situation indicates the need
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
128
for action. We consider two major implications of the results for practitioners, one referring to the pre-founding and one to the post-founding stage of new ventures. The most apparent implication for the prefounding stage is to underscore the importance of fostering heterogeneous compositions of founding teams. Before a team has been formed, there is still the possibility of paying careful attention to its composition. In light of the finding that the formation of entrepreneurial teams is often a ‘random’ process based on prior private and professional relationships, it seems necessary for organizations involved in the pre-founding stage to ensure a more conscious assembling of entrepreneurial teams. First, actors such as universities, research institutions, venture capitalists or business angels have to foster the willingness of a given leading entrepreneur or technical-oriented core team to integrate partners with complementary capabilities. Particularly in hightech ventures, the people directly involved in developing the technological solution the new firm will provide may often be hesitant to integrate partners with business management backgrounds. To offer ownership and to share decision making control with others who have not contributed to the business concept may be perceived as unfair. This indicates that influencing organizations have to stress the importance of a well-balanced team and have to help the leading entrepreneurs to undergo a systematic self-assessment in order to identify the skills needed to generate successful innovations. Venture capitalists apparently already act according to this recommendation and in fact tie their funding decisions to the interdisciplinary character of the new venture teams (Tyebjee & Bruno, 1984; Der Foo, Wong & Ong, 2005). However, academic incubators, in particular are well advised to further emphasize the assembling of heterogeneous entrepreneurial teams when supporting potential business founders. Second, incubators, funding organizations and consultants need to foster the possibility for team builders to recruit partners from different disciplines. If many entrepreneurial teams emerge from existing relationships it seems reasonable to foster relationships between potential business founders across disciplines before they actually decide to start a new business. We believe universities can play a key role as enablers of cross-disciplinary contacts. A promising avenue is to implement educational programmes that foster the development of interdisciplinary work experience among students. Such courses may increase the probability that social integration processes between ‘unfamiliar’ individuals
Volume 16
Number 2
2007
from different knowledge domains start to develop long before these individuals become entrepreneurs. By offering individuals from different disciplines the opportunity to meet and cooperate, they may be prompted to develop a ‘common ground’ which is an important antecedent to interpersonal attraction and trust. To conclude, the findings of the present study imply that influencing organizations need to encourage and help potential business founders in the pre-founding stage to close potential gaps in their competency maps. The second implication of the present study refers to already established young entrepreneurial teams in the post-founding stage. In this stage, there are fewer possibilities to realize compositional heterogeneity by attracting and selecting additional partners with complementary experiences and/or by the forced exit of partners with redundant knowledge – particularly in the short term. We find the quality of the strategic planning process to mediate the relation between team heterogeneity and product innovativeness. This finding implies that homogeneous teams need to pay attention to their strategic planning behaviour when attempting to compensate for their lack of specific knowledge and experience. By carefully assessing their environmental scanning abilities, as well as their ability to achieve strategic openness, and by correcting for the identified deficiencies, entrepreneurial teams should be able to enhance the product innovativeness of their firms. If teams identified weaknesses in their strategic planning process, they should be able to address them through seeking external consultancy, by making use of their personal networks or by engaging in specific training activities. Again, venture capitalists, university faculty, or incubator institutions can offer helpful guidelines for homogeneous entrepreneurial teams to improve their planning activities. In particular, teams that consist predominantly of engineers and scientists run the risk of focusing on technology-oriented scanning activities and underestimating the need for strategic flexibility in order to meet changing competition and demand. For such ventures, external advice in strategic planning seems to be vital for successful product innovation.
Limitations Although the results of the present study provide interesting implications, some limitations need to be considered. First, it is necessary to consider the relatively small response rate. We cannot preclude that our sample shows deficiencies in terms of representativeness. It is obvious that this limits the transfer© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
ability of our results onto the full population of high-tech ventures in Canada. In addition, owing to the limited number of responses it was not appropriate to conduct multivariate data analysis simultaneously including all model variables. In light of the strong partial correlation coefficients basing on a comparatively small data set, we are optimistic that the findings will be confirmed when applying more sophisticated analysis methods. This is, however, an open question. Replicating this study with larger samples of new venture teams would increase the confidence in the preliminary results. Despite these limitations, this work is valuable as a pilot study because it involves an advance towards a better understanding of the effects of organizational demography in new ventures which, so far, has received only limited attention. Another limitation concerns the omission of variables measuring additional aspects of team heterogeneity. As operationalized in this study, heterogeneity referred exclusively to the diversity of educational backgrounds. As noted before, the decision to focus on this variable was guided by the result of the exploratory interviews. We found many teams in our sample lacking considerable functional or career experience as they frequently started their ventures out of academic environments. Thus, the educational backgrounds seemed to be a valid measure for the type of knowledge and experience of the entrepreneurs. However, an interesting question for future research is whether different types of heterogeneity, particularly heterogeneity in terms of functional backgrounds and career profiles, may have different consequences for the innovative capabilities of entrepreneurial teams. The research on TMTs in large and established companies indicates that not all composition variables facilitate innovation in the same way (Bantel & Jackson, 1989). In a similar vein, we investigated only a limited number of promising intervening variables. In particular, we did not consider social group factors, such as the level of task conflict or the intensity of communication between the team members. The inclusion of social group factors has provided promising results for TMTs in established companies. Interestingly, the results have been partly contradictory indicating that team heterogeneity has to be interpreted as a double-edged sword. While increased heterogeneity may produce productive group tension and avoid group thinking, different educational and functional backgrounds may also render effective group functioning more difficult (Murray, 1989; Williams & O’Reilly, 1998). We decided not to focus on social group variables due to the © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
129
assumption that severe affective conflicts and a lack of communication between the team members are less relevant for entrepreneurial teams. The common history of the team members, which plays a fundamental role when jointly starting a new venture, may reduce the danger of social disintegration. Based on shared experience, new venture teams can develop trust and group cohesiveness (Eisenhardt & Schoonhoven, 1990), which should reduce affective conflict (Ensley, 2002). In fact, the only existing study in the new venture team research which directly investigated the relationship between heterogeneity and the level of conflict found no support for a heterogeneity–conflict linkage (Ensley, 1999). Nevertheless, it seems promising to explore whether social group variables, in fact, play only a minor role when explaining the effects of heterogeneity on product innovativeness. The last limitation is that our model does not consider dynamic effects. It seems reasonable that the relationship between team heterogeneity and organizational outcomes is not unidirectional. From a dynamic perspective, the heterogeneity of entrepreneurial teams might produce outcomes, then organizational outcomes might alter team heterogeneity, then a new effect on organizational outcomes might result, and so forth. Specifically, we expect to see changes in the interdisciplinary team composition over time as a reaction to problems in generating and commercializing product innovations which, in turn, should improve the innovative capabilities of the teams. When a venture grows, the focus shifts from technological product development towards manufacturing and operating procedures. Founding teams, particularly those dominated by members with a background in engineering and science, should, therefore, often realize the need for help in general management, finance and legal aspects of their business (Berry, 1996). A dynamic model of team composition could rely on learning theories and a rational-economic argument: entrepreneurial teams do not sustain their tendency to be homogeneous simply because their firms face a growing external pressure toward diversity. In the present study, we found preliminary support for this rational-economic argument and the existence of group dynamics with respect to the educational heterogeneity of the teams. We compared the team composition at the time of founding with the current management team composition with respect to their educational backgrounds. We found that on average the proportions of team members with a background in engineering or science decreased over time, while the proportions of people with business, finance and legal back-
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
130
grounds increased in our sample teams. Therefore, a need for future longitudinal studies is apparent to carefully examine the dynamics of team composition. Such research may provide important insight into the long-term performance of new ventures.
Acknowledgements The authors gratefully acknowledge the support of Paul Guild and Douglas Sparkes from the Center of Business, Entrepreneurship, and Technology at the University of Waterloo, Ontario, Canada.
References Bantel, K.A. (1994) Strategic Planning Openness. Group and Organization Studies, 19, 406–24. Bantel, K.A. and Jackson, S.E. (1989) Top Management and Innovations in Banking: Does the Composition of the Top Team Make a Difference? Strategic Management Journal, 10, 107–24. Beaver, G. and Prince, C. (2002) Innovation, Entrepreneurship and Competitive Advantage in the Entrepreneurial Venture. Journal of Small Business and Enterprise Development, 8, 157–75. Berry, M.M.J. (1996) Technical Entrepreneurship, Strategic Awareness and Corporate Transformation in Small High-tech Firms. Technovation, 16, 487–522. Blau, P.M. (1977) Inequality and Heterogeneity: A Primitive Theory of Social Structure. Free Press, New York. Carpenter, M.A. (2002) The Implications of Strategy and Social Context for the Relationship between Top Management Team Heterogeneity and Firm Performance. Strategic Management Journal, 23, 275–84. Chandler, G.N. and Lyon, D.W. (2001) Entrepreneurial Teams in New Ventures: Composition, Turnover, and Performance. Academy of Management Proceedings, Washington, DC. Cohen, W.M. and Levinthal, D.A. (1990) Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35, 128–52. Cooper, A.C. and Bruno, A.V. (1977) Success among High-Technology Firms. Business Horizons, 20, 16–22. Cooper, A.C. and Daily, C.M. (1997) Entrepreneurial Teams. In Sexton, D.L. (ed.), Entrepreneurship 2000. Upstart Publishing, Chicago, IL, pp. 127–50. Crick, D. and Jones, M. (1999) Design and Innovation Strategies within ‘Successful’ High-tech Firms. Market Intelligence & Planning, 17, 161–8. Der Foo, M., Wong, P. and Ong, A. (2005) Do Others Think You Have a Viable Business Idea? Team Diversity and Judges’ Evaluation of Ideas in a Business Plan Competition. Journal of Business Venturing, 20, 385–402. Doutriaux, J. (1992) Emerging High-tech Firms: How Durable Are Their Comparative Start-up Advantages? Journal of Business Venturing, 7, 303–22.
Volume 16
Number 2
2007
Eisenhardt, K.M. (1989) Making Fast Decisions in High-Velocity Environments. Academy of Management Journal, 32, 543–76. Eisenhardt, K.M. and Schoonhoven, C.B. (1990) Organizational Growth: Linking Founding Team, Strategy, Environment, and Growth among U.S. Semiconductor Ventures. Administrative Science Quarterly, 35, 504–29. Ensley, M.D. (1999) Entrepreneurial Teams as Determinants of New Venture Performance. Garland Publishing, New York. Ensley, M.D. (2002) Understanding the Dynamics of New Venture Top Management Teams: Cohesion, Conflict, and New Venture Performance. Journal of Business Venturing, 17, 365–86. Feeser, H.R. and Willard, G.E. (1990) Founding Strategy and Performance: A Comparison of High and Low Growth High-tech Firms. Strategic Management Journal, 11, 87–98. Flatt, S.J. (2004) When Opposites Attract: How Top Management Team Heterogeneity and Homogeneity Influence Innovativeness. University of California, San Francisco, CA. Forbes, D.P., Borchert, P.S., Zellmer-Bruhn, M.E. and Sapienza, H.J. (2006) Entrepreneurial Team Formation: An Exploration of New Member Addition. Entrepreneurship Theory and Practice, 30, 225–48. Francis, D.H. and Sandberg, W.R. (2000) Friendship within Entrepreneurial Teams and Its Association with Team and Venture Performance. Entrepreneurship Theory and Practice, 25, 5–26. Freel, M.S. (2003) Sectoral Patterns of Small Firm Innovation, Networking and Proximity. Research Policy, 32, 751–70. Hambrick, D.C. and Mason, P.A. (1984) Upper Echelons: The Organization as a Reflection of Its Top Managers. Academy of Management Review, 9, 193–206. Hambrick, D.C., Cho, T.S. and Chen, M. (1996) The Influence of Top Management Team Heterogeneity on Firms’ Competitive Moves. Administrative Science Quarterly, 41, 659–84. Hult, G.T.M., Hurley, R.F. and Knight, G.A. (2004) Innovativeness: Its Antecedents and Impact on Business Performance. Industrial Marketing Management, 33, 429–38. Hurley, R.F. and Hult, G.T.M. (1998) Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination. Journal of Marketing, 62, 42–54. Kamm, J.B., Shuman, J.C., Seegar, J.A. and Nurick, A.J. (1989) Are Well-Balanced Teams more Successful? Frontiers of Entrepreneurship Research, 9, 428–9. Kamm, J.B., Shuman, J.C., Seegar, J.A. and Nurick, A.J. (1990) Entrepreneurial Teams in New Venture Creation: A Research Agenda. Entrepreneurship Theory and Practice, 14, 7–17. Khan, A.M. and Manopichetwattana, V. (1989) Innovative and Noninnovative Small Firms: Types and Characteristics. Management Science, 35, 597–606. Koberg, C.S., Uhlenbruck, N. and Sarason, Y. (1996) Facilitators of Organizational Innovation: The Role of Life-cycle Stage. Journal of Business Venturing, 11, 133–49. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INTERDISCIPLINARY HETEROGENEITY AND PRODUCT INNOVATIVENESS
Lant, T.K. and Milliken, F.J. (1992) The Role of Managerial Learning and Interpretation in Strategic Persistence and Reorientation: An Empirical Exploration. Strategic Management Journal, 13, 585–608. Lawrence, B.S. (1997) The Black Box of Organizational Demography. Organization Science, 8, 1–22. Miller, D. and Friesen, P.H. (1982) Innovation in Conservative and Entrepreneurial Firms: Two Models of Strategic Momentum. Strategic Management Journal, 3, 1–25. Murray, A.A. (1989) Top Management Group Heterogeneity and Firm Performance. Strategic Management Journal, 10, 125–41. O’Reilly, C.A., Williams, K.Y. and Barsade, S. (1998) Group Demography and Innovation: Does Diversity Help? In Gruenfeld, D., Mannix, B. and Neale, M.A. (eds.), Research on Managing Groups and Teams, Vol. 1. JAI Press, Greenwich, CT, pp. 183–207. Roberts, E.B. (1991) Entrepreneurs in High Technology: Lessons from MIT and Beyond. Oxford University Press, New York. Sternberg, R., Behrendt, H., Tarnásy, C. and Seeger, H. (1996) Bilanz eines Booms – Wirkungsanalyse von Technologie- und Gründerzentren in Deutschland. Dortmunder Vertrieb für Bau- und Planungsliteratur, Dortmund. Teach, R.D., et al. (1986) Software Venture Teams. Frontiers of Entrepreneurship Research: Proceedings of the Sixth Annual Babson College Entrepreneurship Research Conference, Babson College, USA. Timmons, J.A. (1999) New Venture Creation: Entrepreneurship in the 1990’s. Irwin, Homewood. Tyebjee, T.T. and Bruno, A.V. (1984) A Model of Venture Capitalist Investment Activity. Management Science, 30, 1051–66. Vanaelst, I., Clarysse, B., Wright, M., Lockett, A., Moray, N. and S’Jegers, R. (2006) Entrepreneurial Team Development in Academic Spinouts: An Examination of Team Heterogeneity. Entrepreneurship Theory and Practice, 30, 249–71.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
131
Wang, C.L. and Ahmed, P.K. (2004) The Development and Validation of the Organisational Innovativeness Construct using Confirmatory Factor Analysis. European Journal of Innovation Management, 7, 303–13. West, M.A. and Anderson, N.R. (1996) Innovation in Top Management Teams. Journal of Applied Psychology, 81, 680–93. Wiersema, M.F. and Bantel, K.A. (1992) Top Management Team Demography and Corporate Strategic Change. Academy of Management Journal, 35, 91–121. Williams, K.Y. and O’Reilly, C.A. (1998) Demography and Diversity in Organizations: A Review of 40 years of Research. In Commingsand, L.L. and Staw, B.M. (eds.), Research in Organizational Behavior. JAI Press, Greenwich, CT, pp. 77– 140.
Daniel Henneke (daniel.henneke@imu. unibe.ch) is Research Assistant and PhD Student at the Institute for Marketing and Management (IMU-Innovation) at the University of Bern in Switzerland. His research interests focus on the relationship between strategic planning and innovativeness in entrepreneurial ventures. Christian Lüthje is Professor of Innovation and Marketing at the University of Berne in Switzerland. His main research interests lie in the areas of Innovation Management and Entrepreneurship. A significant part of his work focuses on the effect of cross-functional teams in established and new firms on innovation success. He has published in Research Policy, R&D Management, International Journal of Technology Management and International Business Review.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
132
Appendix: Survey Instrument General Company Information When was your company founded? Which area(s) is your company competing in? IT – Biotech – Environmental – Pharma – Advanced Manufacturing – Automotive – Other Management Team How did the members of the founding team meet? Friends from university – Friends general – Colleagues from university – Colleagues from prior ventures – Introduced through investors How many members are/were in the . . . ? Founding Team versus Current Team? How many founding team members had formal education related to . . . ? Engineering/Science – Business – Finance/Accounting – Marketing/Sales – Legal – Other How many founding team members had prior working experience related to . . . Management – Marketing/Sales – Finance/Accounting – Operations/Production – Research/ Development How many ventures in total were previously started by the founding team? Scanning (1: never used – 4: occasionally used – 7: always used) – routine gathering of opinions from customers? – explicit tracking of activities and tactics from competitors? – sales forecasting? – special market research studies? – scientific literature (technical, scientific, patents . . .)? – the knowledge of external industry experts? – information exchange with academic researchers? – specific monitoring or surveying approaches to identify new potential investors? – external financial knowledge in terms of, e.g., professional advice? Openness (1: No emphasis – 3: moderate emphasis – 5: very strong emphasis) – reaching new markets? – qualitative rather than quantitative goals? – defining the nature and business of your firm? – examining long-term variances from prior plans? – developing contingency plans? If you conduct strategic planning, how much do you emphasize . . . – the involvement of R&D expertise vs. the involvement of marketing expertise? – the involvement of finance expertise vs. the involvement of R&D expertise? What do you consider as being your competitive advantage in terms of your marketing skill/ customer orientation vs. your technological superiority? Innovativeness/Performance (1: strongly disagree – 4: neither disagree nor agree – 7: strongly agree) In new product introductions, we are often first-to-market. Our new products are often perceived as very novel by customers. In comparison with our competitors, we have introduced more innovative products during the past five years or since starting operations. In comparison with our competitors, we have had a lower success rate in new product launches. Our firm’s R&D/product development resources are not adequate to handle the development need of new products. We actively respond to the adoption of ‘new ways of doing things’ by main competitors.
Volume 16
Number 2
2007
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
COUNTERACTING FORCES IN MULTI-BRANDED PRODUCT PLATFORM DEVELOPMENT
133
Counteracting Forces in Multi-branded Product Platform Development Christer Karlsson and Martin Sköld Multi-branded product platforms represent a concurrently promising and challenging strategy to companies striving to get beyond possible economies of scale and scope within a single organization and brand. The strategic aim of multi-branded platform development is to create financial synergies by combining assets across several brands and product programmes. This research is based on a longitudinal field study using a clinical research approach in a global multi-product, multi-branded industrial group. Findings from the study explore two opposite forces counteracting the purpose of multi-branded platforms: the development of common product architecture, and product differentiation. The major challenge is that these two forces possess opposite characteristics, but they need to be handled jointly and concurrently in order to realize intended synergies.
Introduction
C
ompanies in mature industries face several challenges when trying to be competitive on the global market. One challenge comes from a need to combine strategies in order to meet concurrent cost and differentiation demands from customers, while the central idea with competitive strategies is not to combine several strategies since they demand totally different organizational skills and operations (Porter, 1980, 1985). Another challenge concerns changing established ways to produce and develop products causing a dilemma that has been described by Abernathy (1978) as indolence to change established and well functioning ‘productive units’. Product platforms are an important strategy to handle some of these challenges and to develop products more efficiently. From the Black & Decker story we have learned how companies can achieve financial synergies by developing several products from a common core (Meyer & Lehnerd, 1997). Product platforms facilitate the use of common resources, such as common components, systems and technology across several products. The benefit of commonalities is cost reduction in product development and production but also increased speed of new product development. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
The major challenge of product platforms is to balance commonality and product distinction (Robertson & Ulrich, 1998). Too much commonality may hamper product integrity and brand reputation (Kim & Chhajed, 2000). This article will explore the forces that have to be balanced; on the one hand the force towards commonality to achieve cost reductions in product development and production, and on the other hand the force to achieve or maintain product distinction and brand reputation.
Multi-branded Product Platforms While multi-branded product development is a fairly recent concept in the literature on innovation and product development management, it is certainly not new in areas such as strategy and marketing. A classic contribution was the book Strategy and Structure (Chandler, 1962) on the development of the divisionalized company exemplified, for example, by the creation of General Motors with its several brands such as Buick, Oldsmobile, Pontiac, Cadillac and Chevrolet. There are, of course, many examples of companies with many brands and, especially in consumer goods, Proctor & Gamble may be one of the most often mentioned. In the automobile industry
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00432.x
CREATIVITY AND INNOVATION MANAGEMENT
134
Table 1. Multi-branded Platform Development Challenges (Lundbäck & Karlsson, 2005) Main difficulties in product platforms and platform development 1. Product concept Translating the customer needs and product attributes into the concept of the platform
2. Platform
3. Architecture
4. Systems
5. Components
Developing a common language/view of what the platform includes
Making architec-tural concessions without jeopardizing brand uniqueness
Determining what systems could be common and what systems that should be unique
Determining the best common corporate engineering standard
well-known examples are Toyota/Lexus and the VAG-group with Volkswagen/Audi/ Skoda/Seat. From the services area one could mention brand architecture decisions as concerned with the number of brands to utilize the role of specific brands and the relationship between such brands (Devlin, 2003). What distinguishes a brand and creates differentiation may be very different from brand to brand but there may be some common characteristics if we look at what is a differentiator. A branded differentiator can be a feature, service, programme or ingredient (Aaker, 2003). However, it should be noted that a brand must be not only a name or marketing slogan but also meaningful to customers when purchasing and using the product or service (Aaker, 2003). Hence focusing the role of product development in multi-branding of products should be one important perspective. It is interesting to conclude that although multi-branded strategies and companies have been around for a long time, little has been published in the innovation and production management literature until recently. This is demonstrated by a search with the keywords ‘multi and/ or brand/branded, and/or platform(s)/ architecture(s)’ through databases of: Journal of Product Innovation Management (JPIM), International Journal of Operations & Production Management (IJOPM), International Journal of Innovation Management (IJIM), and Creativity and Innovation Management (CIM). Even searching for multi-brand platforms in the EBSCO database (http://www.ebsco.com) only adds a few brief and peripheral articles in popular magazines (e.g., Lefton, 1996; Wernle et al., 1999; Wright, 2000). It seems fair to say that a stream of research on product platforms started in 1997 with the publication of Meyer and Lehnerd’s The Power of Product Platforms:
Volume 16
Number 2
2007
Building Value and Cost Leadership. Likewise, it seems fair to say that multi-branded platform development was rarely mentioned before the paper ‘Challenges for inter-firm product platform development’, which Lundbäck and Karlsson (2003) later developed and published in International Journal of Innovation Management (Lundbäck & Karlsson, 2005). Because of its multi-faceted potential, product platforms have influenced product development in several industries (Sawhney, 1998). However, the majority of the existing research has focused on single-branded product platform development within one brand and organization. Empirical evidence shows that early adopters in mature industries are now developing platforms that are common between several brands, so called multi-branded product platforms. Multibranded product platforms may be a result of mergers, acquisitions, alliances and/or joint ventures. The potential benefits of multibranded platforms are increased cost reductions in product development and production since several more products may share a larger common core. Lundbäck and Karlsson (2003) notice a change in logics between singlebranded and what they call multiple-brand platforms. First, they identify multiple-brand platforms that combine several competitive strategies. Second, they note considerable price gaps between products that stem from the same platform. Findings from their study are interesting since they constitute a sharp contrast to Porter’s recommendation not to combine different competitive strategies. Lundbäck and Karlsson (2005) also developed a framework of five variables that challenge platform development (see Table 1). (1) At the product concept level the main difficulty is to convert customer needs into the platform concept. This area contains transformation of © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
COUNTERACTING FORCES IN MULTI-BRANDED PRODUCT PLATFORM DEVELOPMENT
soft variables from the customer perspective to technical areas within the organization. Also (2) the platform itself seems to be fuzzy and implies a need for a common language of what the platform really is and what it includes. (3) At an architectural level, combinatory logics and different organizational specialities including physical and non-physical elements of the products should be reflected without jeopardizing brand uniqueness. Likewise, (4 and 5) systems and components present tangible and intangible aspects regarding both commonality and distinctiveness. The review of the single-branded and multibranded product platform literature depicts some specific challenges that should be taken into consideration in order to realize intended synergies. Hence the purpose of this study is to explore the concept of multi-branded product platforms, and to identify counteracting forces in the development of multibranded product platforms.
Methodology and Research Design The present study is based on a longitudinal field study, inspired by a clinical methodology. The principal characteristic of clinical studies is that the researcher participates in and studies organizational change from within an organizational setting (Åhlström, 1997). The rationale of choosing a clinical approach is an assumption that studies of change processes, such as changing from single-branded to multi-branded product platform development, should be investigated as the change is taking place (Lawler, 1985). A specific feature was that the researchers were able to follow this particular case from the start before long-term processes had smoothened actual or potential conflicting issues. The case in question is on developing a common product platform as a first project after the merger of three independent manufacturers with three distinctly different brand positions. The clinical approach and the specific research focus imply that the case is sampled strategically in order to find a sample that both combines platform development and several brands. ‘Machine products’ is the anonymous name of an original equipment manufacturer (OEM) (i.e., end-product producer) that was selected for the study. The project facilitated data collection from different organizational meetings such as cross-functional meetings, concept reviews and informal meetings between people from different parts of the organization. Interviews were used as a second method, and these included 34 interviews with managers from functional areas from the three brands. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
135
According to the clinical approach, a steering group has validated data. The steering group consisted of seven members (including the two researchers) from three organizational and managerial levels. The group had regular meetings every second month and discussed different topics in relation to empirical findings. The purpose of the steering group was to channel input from the researchers into the daily operations of platform development. This means that the relationship between the researchers and the steering group explains the aggregated logic of the clinical approach (Schein, 1987).
Implications of the Research Design The major limitations of the study could be the combination of one longitudinal case, and the choice of research methodology. Few cases intensify longitudinal and in-depth data (Voss, Tsikriktsis & Frohlich, 2002), while lacking a possibility to create generalizable conclusions. In the opposite situation, several cases might reduce the possibility to generate rich data. Concerns of external validity were traded off against opportunities to gain insights into as yet incompletely documented phenomena (Burgelman, 1983). Since the study is limited to one case, validation and conclusions will be in relation to existing knowledge (Eisenhardt, 1989). But, since multi-branded product platforms are at an early stage, this can only be done to a certain extent. To overcome this situation, this study will have an explorative approach combining theories from single-branded and multi-branded product platforms.
Introduction of Machine Products Machine Products is a large company in a worldwide industry. Machine Products develops, manufactures and assembles products to professional customers and to end customers in an OEM industry. During the past ten years, Machine Products has witnessed a global pressure and change in several business fields. The change has been remarkable from at least four dominant aspects. The firm has been forced to reduce development time by approximately 35 percent, environmental demands have exerted pressure to invest heavily in new ‘green’ technology, the industry has witnessed a wave of mergers and acquisitions resulting in some very large and influential players, and some OEMs are under great pressure from large and powerful suppliers. To handle these changes, Machine Products has reformed its core activities aiming at
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
136
Products from Brand A
Brand A
Brand B
Products from Brand B
The platform
Brand C
Products from Brand C
Figure 1. The Multi-branded Product Platform Scope Table 2. Brand Characteristics Brand A
Brand C
Type of product
Individualistic products with a very high brand reputation
Range-products with an individualistic expression
Business strategy
Differentiation focus (as an applicator) Continent-specific market Medium–High
Cost strategy
Product family-concept with a homogeneous product expression Differentiation
Country-specific markets Medium
Diversified global markets High
Market scope Product price
strengthening its strategic direction in the industry, and has therefore acquired two firms (Brands A and B) in order to create synergies with its own brand (Brand C) by developing a multi-branded product platform (Figure 1). The total acquisition scope contains three brands and a total of fourteen different products apportioned between the three brands. Table 2 summarizes the characteristics of the three brands. Brand A is a company with a very long history in this industry, known for individualistic products with a strong brand reputation. Its business strategy can be described as differentiation focus in terms of an ‘applicator’ focusing on specific market segments. The term ‘applicator’ is used since Brand A has specialized in developing advanced applications for individual customer needs out of its product lines. Its products are priced between medium and high. Brand B also has a long history within the industry, focusing on products in specific product/ market ranges. Its products are characterized
Volume 16
Brand B
Number 2
2007
by an individualistic design at a moderate price directed to customers in few markets. Finally, Brand C is grounded on a product family concept, with a homogeneous product expression. Its products are differentiated in high performance and quality dimensions that are well known to customers. Products from Brand C have a high market price and are globally represented in several markets.
Structuring the Empirical Database The following sections will present data from the multi-branded product platform development process. In order to enhance external validity, data are structured in relation to themes from the previous review of the single-branded and multi-branded product platform literature.
Product and Market Scope The issue most frequently discussed in the multi-branded platform development process © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
COUNTERACTING FORCES IN MULTI-BRANDED PRODUCT PLATFORM DEVELOPMENT
concerned brand-related matters. Each brand represented a perspective of its own on platform development issues. This segmentation of brand perspectives demonstrated that each brand might represent very different views and knowledge on product offerings and market requests. Another issue was the multibranded scope of the platform. The brands questioned if a common platform could supply the uniqueness and associated characteristics of each brand. Such questioning divided the brands into two parties: Brand A, and Brands B and C. People from Brand A accused Brand C of not having enough market knowledge about specific rules and regulations that should influence the platform in relation to specific A-market conditions. The concerns raised mistrusts and worries that the platform could hamper business opportunities and force products into unwanted market segments. Lower organizational levels also questioned the multi-branded platform and its ability to create differentiated products on a price dimension. Managers, especially from Brand B with its lower market prices, underlined the importance of price flexibility. At these organizational levels, platform issues were more often related to physical elements, e.g., components and systems, since they constituted visual dimensions of how to differentiate products and designs.
Platform Dimensions The platform as a conception constituted a great obstacle at an individual level. The platform concept caused mistrust and whether it could capture the broad product scope was questioned. One platform debate concerned platform dimensions, e.g., interfaces, components, systems and technology. Individuals from the three brands claimed that they all had genuine experiences of the dimensions. One chief engineer from Brand B stressed that platforms are nothing new to our organization: ‘We have done this for many years, but we have done it differently in relation to the others, especially Brand C’. Issues related to platform dimensions were frequently discussed in global development meetings. Engineers from the three brands asked for clear definitions and examples of commonality and brand distinction. Differentiation possibilities and scalability in relation to high- and low-end solutions were questioned. At cross-functional meetings, managers followed up these debates and concluded that the organization was in need of new reference objects that could clarify the picture both in relation to specific development areas and in © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
137
relation to the platform. Other questions underscored a need for new organizational structures and channels of communication.
Analysing Forces in Multi-branded Platform Development The major rationale for the acquisition of the two brands was to create synergies in new product development and the development of the multi-branded product platform was the means to realize desired synergies. A comprehensive analysis at the brand level (summarized in Table 2), indicates that Machine Products had to handle three distinctively different brands in relation to Porter’s (1985) framework of competitive strategies: Brand A can be described as an ‘Applicator’, Brand B as a ‘Low cost producer’, and Brand C as a ‘Differentiator’. These findings validate the results from previous studies (Lundbäck & Karlsson, 2003, 2005). At the same time it is likely that the extensive product scope brings challenges that are related to differences in competitive strategies.
Brand and Product Level Previous theories describe the matter of balancing commonality and brand distinction as a major challenge even with single-branded platforms (Robertson & Ulrich, 1998). Here in multi-branded platform development, the challenge of distinction reaches another level since the three brands tackled development issues from their respective perspectives with divergent market segmentation and customer focus. Analysis at the level of individual engineers depicts more fragmented issues. What were typically observed were criticisms and scepticism about the ability of the platform to offer differentiated products in the broad product scope as well as concerns about the difference between single-branded and multi-branded platform development. This indicates that brand levels constitute one level of distinction, and individual products from each brand another and more nuanced level of differentiation. It seems to be important to differentiate products in relation to two dimensions. One dimension is within each brand, another dimension between products from other brands. Therefore, product differentiation seems to be a complementary perspective to secure unique product offerings between and within brands. Lundbäck and Karlsson (2005) produced a similar finding and they discussed
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
138
Common architecture
Brand & product differentiation
Geometry
Perception
Common systems
Positioning
Common components
Customer segment
Engineering standards
Image
Product database
Identity
Design standards
Unique design
Figure 2. Counteracting Sets of Forces product differentiation as an important dimension in multi-branded product platforms.
Platform Dimensions Level The three brands declared that they all had extensive knowledge and experience of platform dimensions such as components, systems, interfaces and technology. However, the three brands had used definitions and principles differently in firm-related and unique ways. The sum of the different perspectives did not create a common picture of the platform. This hampered the organizational understanding and common picture of the platform. Therefore, serious problems arose in changing established structures in thinking, not only at the concept level but also in production and development. The central problem seems to be how to create a shared and common picture of the platform at an architectural level and how it can provide differentiated products.
Opposite Forces in Multi-branded Product Platform Development The analysis has showed that multi-branded platform development is an influential strategy that affects conventional ways of product and platform development quite extensively because of an expanded brand and product scope. Expanded brand and product scope entails several challenges of managerial and organizational importance, described by Bassett-Jones (2005) as a paradoxical situation caused by diversity. At an aggregated brand level, multibranded platforms entail a wider product scope of several products that need to be differentiated in relation to the product scope as a
Volume 16
Number 2
2007
whole. At an aggregated platform level, platform dimensions such as components, systems and interfaces need to be developed in relation to a new and multi-branded technological scope. This relationship implies that people from each brand need to give up their previous courses of action in a transformational manner (Allaire & Firsirotu, 1985), since multi-branded platform development seems to be related to discontinuous knowledge in platform development (Tushman & Anderson, 1986). However, not only product scope but also other dimensions are significantly different in multi-branded compared with single-branded platform development. A brand signals a kind of product position with a connected product image. It also says something about the customer segment choosing to buy products of that brand. The brand will probably also have its own protected logo and a line of design. These kinds of factors will demand extra product differentiation that will possibly counteract requests on common architecture from commonality in design, components, geometry and systems. It is now possible to identify two sets of forces of opposed characteristics that need to be handled jointly (see Figure 2). One set of forces deals with the platform from a technical perspective in terms of developing a common architecture. The other set of forces deals with brand and product differentiation between brands as a consequence of increased brand and product scope.
Common Architecture One of the fundamental ideas of multibranded product platforms is to create synergies within an extended product scope. From a technical platform perspective, such synergies originate from exploiting common elements in © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
COUNTERACTING FORCES IN MULTI-BRANDED PRODUCT PLATFORM DEVELOPMENT
several products across brands. This constitutes the major difference between singlebranded and multi-branded platforms since synergies can be realized in two ways: either from applying commonalities between brands, or from commonalities within brands. This difference seems to be remarkable and capture major challenges, since none of the brands have an existing architecture that is applicable for the desired task of platform development. From a technical perspective, multi-branded platform development is heavily dependent on the successful creation of an architecture common to the total scope of all products. However, developing a common architecture is a major challenge. Even if the brands have experience of common architectures, those are brand unique and represent architectural knowledge valuable and applicable only within the respective brand (Henderson & Clark, 1990). Therefore, to be useful within a much wider product scope, creating a common architecture must start out from all included brands. Moreover, brand-related architectures might have to be abandoned. Building a common architecture also includes the creation of a common architectural language and notions so that languages and processes support an architectural whole. In addition to the importance of an all-new platform in multi-branded platform development, there are other specific characteristics. Commonality in components and systems has, of course, significance in single-branded platforms, but for the multi-branded platforms the importance of factors related to the function and experience of using the product emerges. These may be geometry and engineering standards influencing product characteristics such as the handling of a car. A Jaguar S-type may have too many driving characteristics from a Ford, and a Skoda may have too many from a Volkswagen, even if their components are different.
Product Differentiation The other fundamental idea of multi-branded product platforms is to secure unique and distinctive product offerings in a wide product scope. This is a major difference compared to single-branded platforms since multi-branded platforms are based on an increased product scope as a consequence of including several brands. The enlargement in product scope is challenging since it captures divergent knowledge from each brand about customers and market segments. Each brand tends to have unique information about customers because of their respective history to solve customer needs from a brand-specific perspective. The © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
139
wider product scope implies a need to differentiate products between and within brands as a consequence of divergent product histories. The dilemma of product differentiation seems to be twofold. One challenge appears when the multi-branded platform scope includes products that are present in different markets. In these situations, some products from one brand will be unknown to people from other brands. In the platform development organization, this creates a risk of not having enough knowledge about all the products to be developed within the total platform scope. Another challenge appears when the multi-branded platform scope also includes products that are competing in the same market. Then confusion might characterize development efforts and raise issues on how to avoid cannibalization between products that are included in the multi-branded product scope. A significant difference between multibranded and single-branded platform development comes when the brand perception or value is related to or even built on platform architecture characteristics. A brand value factor such as safety will directly influence some systems, components and engineering standards. A user-friendly value may directly influence design, components and product database. Hence the combination of different brand perceptions and values creates additional challenges to the development of common multi-branded platforms.
Managing Counteractive Sets of Forces The fundamental challenges of managing the development of multi-branded product platforms hence is to concurrently and jointly balance two different sets of forces that go beyond the dimensions in developing singlebranded platforms (see Figure 3). The major differences between singlebranded and multi-branded product platforms might be explained in relation to Figure 3. Quadrants (1) and (2) represent what in this paper is termed single-branded product platforms, which also mirrors the majority of the published platform literature (cf., Meyer & Lehnerd, 1997; Robertson & Ulrich, 1998; Muffatto, 1999; Muffatto & Roveda, 2000; Meyer & Mugge, 2001). In this article it is argued that most platform literature is oriented towards quadrant (2) and how to move from quadrant (1) to (2), since the latter position is valuable because of its synergistic potential. Creating a common architecture is fundamental to succeed with this platform
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
140
Product architecture
Common architecture
Uncommon architecture
(2). Single-branded and synergetic platforms
(4). Multi-branded and synergetic platforms
(1). Single-branded but not synergetic platforms
(3). Multi-branded but not synergetic platforms
One brand
Multiple brands
Brand and product differentiation
Figure 3. Counteracting Forces in Multi-branded Platform Development
strategy. BMW may represent one example for quadrant (2) because of its one brand and common architecture. Ferrari might fit for quadrant (1) since products are seemingly developed with uncommon architectures within one brand. Quadrants (3) and (4) both describe multi-branded product platforms, but with a synergistic difference. Quadrant (4) is dependent on the ability to concurrently handle the counteracting forces of common architectures together with brand and product differentiation within a multi-branded scope.
Conclusions and Managerial Implications The contribution of this paper is the introduction of the concept of multi-branded product platforms, and, more concretely, the identification of counteracting forces in the development of multi-branded product platforms. Using Figure 3 as a map, it can be stated that earlier research has described quadrants (1) and (2), whereas this study has contributed with knowledge about quadrants (3) and (4). The study has identified some characteristics that distinguish multi-branded platform development from single-branded platform development. A major difference derives from the enlarged product scope, which causes two sets of forces with opposite characteristics that need to be managed jointly. One set of forces deals with developing an architecture that is common to all products from all included brands. The other set of forces is about product differentiation that must occur in relation to products within brands, but also between brands to avoid cannibalization.
Volume 16
Number 2
2007
Each set of forces has to be managed to avoid the problem that too much commonality in physical product dimensions obstructs possibilities of product differentiation, while too little commonality reduces the possibility to render desirable synergies. Therefore, it is here proposed that commonalities should be captured in processes and technologies instead of commonalities in components and systems. Finally, the balancing act between common architecture and product differentiation implies new managerial skills. Essential qualities seem to encompass handling multiple product and brand requirements combined with understanding product architecture. A need for business competence at the total scope level also seems to be almost a necessity.
References Aaker, D. (2003) The Power of the Branded Differentiator. Sloan Management Review, 45, 83–7. Abernathy, W.J. (1978) The Productivity Dilemma. The Johns Hopkins University Press, Baltimore, MD. Åhlström, P. (1997) Sequences in the Process of Adopting Lean Production. EFI, Stockholm. Allaire, Y. and Firsirotu, M. (1985) How to Implement Radical Strategies in Large Organizations. Sloan Management Review, 26, 19–34. Bassett-Jones, N. (2005) The Paradox of Diversity Management, Creativity and Innovation. Creativity and Innovation Management, 14, 169–75. Burgelman, R.A. (1983) A Process Model of Internal Corporate Venturing in the Diversified Major Firm. Administrative Science Quarterly, 28, 223–44. Chandler, A.D. (1962) Strategy and Structure: Chapters in the History of the American Industrial Enterprise. MIT Press, New York. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
COUNTERACTING FORCES IN MULTI-BRANDED PRODUCT PLATFORM DEVELOPMENT
Devlin, J. (2003) Brand Architecture in Services: The Example of Retail Financial Services. Journal of Marketing Management, 19, 1043–65. Eisenhardt, K.M. (1989) Building Theories from Case Study Research. Academy of Management Review, 14, 532–50. Henderson, R.M. and Clark, K.B. (1990) Architectural Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Established Firms. Administrative Science Quarterly, 35, 9–30. Kim, K. and Chhajed, D. (2000) Commonality in Product Design: Cost Saving, Valuation Change and Cannibalization. European Journal of Operational Research, 125, 602–21. Lawler III, E.E. (1985) Challenging Traditional Research Assumptions. In Lawler III, E.E., Mohrman, A.M. Jr, Mohrman, S.A., Ledford, G.E. Jr and Cummings, T.G. (eds.), Doing Research That Is Useful for Theory and Practice. Jossey-Bass Publishers, London. Lefton, T. (1996) MLS Seeks Ad Assist. Brandweek, 43, 8 (1/5p). Lundbäck, M. and Karlsson, C. (2003) Challenges for Inter-firm Product Platform Development. EIASM. 11th International Product Development Management Conference, 10, 683–94. Lundbäck, M. and Karlsson, C. (2005) Inter-firm Product Platform Development in the Automotive Industry. International Journal of Innovation Management, 9, 155–81. Meyer, M.H. and Lehnerd, A.P. (1997) The Power of Product Platforms: Building Value and Cost Leadership. Free Press, New York. Meyer, M.H. and Mugge, P.C. (2001) Make Platform Innovation Drive Enterprise Growth. Research Technology Management, 44, 25–39. Muffatto, M. (1999) Platform Strategies in International New Product Development. International Journal of Operations & Production Management, 19, 449–59. Muffatto, M. and Roveda, M. (2000) Developing Product Platforms: Analysis of the Development Process. Technovation, 20, 617–30. Porter, M.E. (1980) Competitive Strategy: Techniques for Analyzing Industries and Competitors. Free Press, New York.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
141
Porter, M.E. (1985) Competitive Advantage: Creating and Sustaining Superior Performance. Free Press, New York. Robertson, D. and Ulrich, K. (1998) Planning for Product Platforms. Sloan Management Review, Summer, 19–31. Sawhney, M.S. (1998) Leveraged High-Variety Strategies: From Portfolio Thinking to Platform Thinking. Journal of the Academy of Marketing Science, 26, 54–61. Schein, E.H. (1987) The Clinical Perspective in FieldWorks. Sage Publications, London. Tushman, M.L. and Anderson, P. (1986) Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, 31, 439–65. Voss, C., Tsikriktsis, N. and Frohlich, M. (2002) Case Research in Operations Management. International Journal of Operations & Production Management, 22, 195–219. Wernle, B., Weernink, W.O., Auer, G., Farhi, S. and Ciferri, L. (1999) Legends, Leaders and Trailblazers. Automotive News Europe, 4, 41–52. Wright, C. (2000) Fewer Platforms May be the Biggest Payoff from Auto Alliances. Automotive News Europe, 5, 47.
Christer Karlsson (
[email protected]) holds an MSc and PhD from Chalmers University of Technology, Gothenburg, in the area of Industrial Management. He is Professor of Innovation and Operations Management and Dean for CBS Executive at Copenhagen Business School and Professor at the European Institute for Advanced Studies in Management (EIASM) in Brussels. He is a member of several editorial boards of professional journals. Martin Sköld holds an MSc in Industrial Management from Halmstad University. He holds a position as a research associate at Stockholm School of Economics. His research is focused on strategic change processes when implementing radically new product development strategies.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
142
How Award-Winning SMEs Manage the Barriers to Innovation Povl Larsen and Alan Lewis Much attention has been focused on increasing the so-called ‘innovation quotient’ of national manufacturing economies. In particular, there has been widespread interest in revealing and examining those barriers that impede innovation, the suggestion being that the removal of such barriers constitutes a prerequisite for successful innovation. This study reports on the experiences of eight firms who had received a UK Design Council ‘millennium product’ award for ‘groundbreaking’ innovation. The implication of the award is that these firms should have overcome any barriers they faced and therefore act as exemplars of how to manage innovative new product development. However, the research shows that the firms were as likely to ignore barriers as they were to address them. Living with a barrier as an alternative to overcoming it is clearly an acceptable strategy for a number of these award winners. The study reports on how the firms managed the various barriers that they encountered.
Introduction
Barriers to Innovation
T
The barriers to innovation and NPD identified from previous research provide a departure point for the research reported in this paper and are discussed below.
he manufacturing sector of most Western economies is dominated by small- to medium-sized enterprises (SMEs). The limited scale of human and technological resources available within such companies raises particular barriers to the processes of innovation in new product development (NPD). Innovation in NPD ranges in complexity from the updating of an existing product to the successful commercial exploitation of a radically new idea. However, there is evidence that the higher the degree of innovation, the greater the financial return (Roy & Riedel, 1997). This suggests that SMEs that have been recognized by design innovation experts as deserving of an award for their ‘groundbreaking’ new product should expect to be very successful. If this were the case then the methods such SMEs employed in managing the innovation process of new products could shed light on how other SMEs might address the barriers to innovation they face. This paper reports on a study of how eight SMEs awarded ‘millennium product’ status as an accolade by the UK Design Council for their innovative products managed the barriers to innovation they encountered and discusses whether their approaches could act as ‘exemplars’ to other SMEs.
Volume 16
Number 2
doi:10.1111/j.1467-8691.2007.00428.x
2007
Financial Issues The difficulties SMEs have in accessing finance have been widely reported as barriers to survival, growth and innovation (Tidd, Bessant & Pavitt, 1997). Research by Birley and Niktari (1995) found that the majority of failures were due to: • • • • •
under capitalization short-term liquidity problems insufficient working capital insufficient start-up capital poor financial management.
To encourage investment in innovation, Freel (2000) suggested that there might be a role for government support agencies to develop mechanisms to introduce innovative SMEs to alternative sources of finance, such as venture capital and the Loan Guarantee Scheme. (The Loan Guarantee Scheme is a system whereby the government underwrites the risk of monies lent to a business.) Also, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
MANAGING THE BARRIERS TO INNOVATION
banks should be encouraged to consider the non-financial characteristics of the management team, the technology and the product market as alternatives to collateral or assets as security. However, many financiers see innovation as a high-risk venture (Hall, 1989) and this may explain why some SMEs use shortterm bank overdrafts to fund their innovation strategies.
Marketing Skills Marketing intelligence has been cited as the most critical skill required in ensuring new product success (Freel, 2000; Wren, Souder & Berkowitz, 2000). Other research (Clifford & Cavanagh, 1985; Mondiano & Ni-chionna, 1986; Tonge, Larsen & Ito, 1998) has highlighted the need for businesses to be customer focused. Foley and Green (1995) and Freel (2000) suggest that technological entrepreneurs are liable to become overly concerned with the technical aspects of their innovation at the expense of the skills necessary for successful commercial exploitation. It is important that SMEs recognize the need to be customer driven, providing customers with what they want and not what inventors think the customer needs. Foley and Green’s (1995) research also emphasized the need for faceto-face contact with customers, especially in high technology businesses where the complex nature of the products often need to be explained fully to potential customers. Developing overseas markets is particularly difficult for SMEs with their limited financial and human resources. One option is to employ overseas agents to represent the company (Foley & Green, 1995). However, agents often work for a number of businesses in the same sector and may not be motivated to sell any particular SME’s products in preference to those of another. Also with high technology and biotechnology products, the agents must be fully conversant with the product to reach the right customers and turn leads into sales.
Management and Personal Characteristics Birley and Niktari (1995) found that lack of management expertise was the second most important reason for business failure. Determination, skill, experience and good judgement can make a success of many an unlikely project, whereas poor, untrained or inexperienced management can ruin the best business (Foley & Green, 1995). Woodcock, Mosey and Wood (2000) found that owner-managers of SMEs in the UK typi© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
143
cally fail to undertake effective competitor analysis, tend not to collect adequate data with which to monitor their development performance, and engage manufacturing personnel too late in the development process. However, the most worrying factor identified was the lack of determination to bring about change, and this was attributed to the SME managers’ ‘over-optimistic view of their own performance’. While Beaver and Prince (2004) suggest that, although a stereotypical ownermanager strives for autonomy and independence, this can manifest itself in an ‘autocratic, egocentric, impulsive and often unpredictable’ managerial style.
Other Barriers Litvak (1992) argues that for technology-based SMEs the lead time for development of new products from idea conception to customer supply can be long compared to the accelerated obsolescence that technological products face in a global marketplace. Deakins et al. (1996) suggested that the management skills of small firms be reinforced with external consultants who show due empathy to the ambitions and objectives of the firm and that contact is sufficiently longitudinal to allow transfer of tacit knowledge. However, in the UK there is no formal quality mechanism in place to control consultancies, that is, anyone can set up in business as a consultant. So how do SMEs identify the best external advice? This is a particular challenge for SMEs given the fact that the larger, better known, reputable consultancies tend to be expensive and therefore beyond the reach of many SMEs (Bruce, Cooper & Vazquez, 1999). Research by Freel (2000) confirmed that SMEs themselves see the real barriers to partnerships to be associated with an inability to find suitable partners and a lack of trust. This is a view shared by Hadjimanolis (2000), who found that a low trust approach of ownermanagers tended to limit innovation.
The Design Innovation Process Clearly there are many barriers to successful design innovation facing SMEs. However, there has been significant research devoted to the processes and techniques for successful innovation and NPD, and some of the leading studies in this broad interdisciplinary field are those of Cooper and Kleinschmidt (1995), Brown and Eisenhardt (1995) and Cooper (1999). From this body of research, a number of factors that affect the success of the design innovation process can be identified.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
144
• Conduct up-front homework into competitors and suppliers, and build in the opinions of customers. • Demand sharp, early product definition of differentiated, superior products. • Build an international market-focused orientation into the design innovation process with effective internal and external communications. • Organize competent, truly cross-functional project teams guided by strong project leaders. • Ensure full senior management support with unhindered access to financial, personnel and political resources. • Plan and resource the market launch early on, and build in stages with pre-defined, tough ‘go’ or ‘kill’ critical decision points in the process.
Method To investigate the barriers to innovation facing award-winning SMEs, a recognizable population of SMEs were identified from SMEs awarded UK millennium products status (Design Council, 2001a), which was a UK Design Council initiative that identified groundbreaking new products and services created in the UK (Design Council, 2001b).
Sample Small firms dominate the manufacturing economy of Wales (and similarly the UK). The Companies Act of 1985 (www.sbs.gov.uk) states that a company is small if it satisfies at least two of the following: a turnover of under £5.6 million, a balance sheet of under £2.8 million and or employs less than 50 staff. Recent research suggests that 93 per cent of all manufacturing companies have fewer than 25 employees. In order to address this research to this dominant group of small SMEs, the research sample was limited to those manufacturing firms with a turnover of less than £2 million. Within the UK region of Wales, 29 SMEs were awarded millennium product status from a total manufacturing base of over 5,000 companies. The SMEs were contacted by telephone to enquire if they would be prepared to take part in interviews, and eight agreed.
Data Collection A semi-structured questionnaire was developed that contained open-ended questions. Before conducting the interviews, a draft version of the questionnaire was pilot tested
Volume 16
Number 2
2007
on three SMEs known to the authors. The first was a business that produced cross-stitch kits, the second business was managed by an inventor of a new type of fishing reel, and the third was a jewellery business. This resulted in minor changes, for example, instead of asking a series of questions about the business, the first question asked for the interviewee to give a brief history of their business. The main questions concentrated on the barriers to innovation the SMEs themselves had encountered and how they dealt with them. The questionnaire was administered through face-to-face interviews, conducted at the premises of the firm and took approximately one hour. All the interviewees had the same interviewer, were subjected to the same protocol, and had the same questions. The interviews were conducted during May and June 2001.
Managing the Barriers to Innovation Table 1 provides an overview of the barriers to innovation encountered by each of the firms interviewed.
Medical Supplies Ltd Medical Supplies Ltd comprised the Managing Director (MD), his wife and 20 production staff. The trigger for the millennium product was a comment from a visitor at a trade fair regarding the difficulty in keeping medicine cold. The primary barrier to innovation for Medical Supplies Ltd related to lack of finance. The MD was averse to using grants because many grants carry specific criteria on their use, such as they cannot be used for working capital. The prospect of seeking venture capital funding did not appeal because it might result in loss of control of the company. Consequently, the only option available was to use personal finance and assets underpinned by bank finance where necessary. An unexpected barrier to innovation related to the MD’s decision to locate the company at his home rather than at industrial premises in a nearby town. Medical Supplies Ltd had recently received a substantial order, so the MD applied to put up a temporary structure alongside his own house. However, after this temporary building was erected, a neighbour objected and, despite much debate on the need for employment creation in the region, this objection was upheld and the company was told to remove the offending structure. To overcome this barrier the MD dismissed all the employees except for three key personnel © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
MANAGING THE BARRIERS TO INNOVATION
145
Table 1. Overview of Barriers to Innovation Encountered Pseudonym
1st Barrier
Medical Supplies Ltd
Finance for innovation
Medical Products Ltd
Finance for innovation (inclusing spin off issues) Competitors copying products Manufacture of product
Environmental Products Co-operative Sensor Equipment Ltd Textile Equipment Ltd Marine Products Ltd Architectural Structures Partnership Textile Materials Ltd
Lack of working capital Knowledge of the NPD process Manufacture of product (including build) Manufacture of product
2nd Barrier Restrictions imposed by location Problem of global distribution
Skill shortages
4th Barrier
Research management & protection
Staff turnover
Market analysis
Finance for innovation (grant aid)
Impatience while waiting for large order
Finance for innovation (grant aid) Finance of innovation
Time
Overstretch finances (no working capital) Stress
Marketing
Skill shortages
Skill shortages and trust
Education and training
Marketing
Financing innovation
Marketing
until he could arrange to re-hire the workforce as outworkers working from their own homes.
Medical Products Ltd Medical Products Ltd was formed as an acquisition vehicle after a management buyout and employed 15 staff. The millennium product was a form of human implant. The first barrier to innovation was finding sufficient capital to fund the further research and development and eventual market launch of the millennium product. What was required was to find sufficient capital from sources that understood the operating environment of Medical Products Ltd and who were prepared to accept the risks involved. The answer lay in using venture capital. The MD and core management team accept that the business will eventually be sold in order to repay the investors, but they also have plans to start another business to develop other products – a case of serial entrepreneurship. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
3rd Barrier
The biggest barrier to innovation to date for Medical Products Ltd has been achieving global distribution. In the words of the MD: ‘The use of distributors is not ideal as they have a whole bag of products to offer customers, why should they push ours? Making a strategic alliance with one of the big companies means you lose too much control and anyway their sales teams have their own products to sell. The best option is to do-it-yourself, even though this means sending someone out to handle the process from start to finish. Oneoff visits to buyers is of no use, you have to go often, and it is very expensive’. Skill shortages have posed problems, particularly in the areas of production staff and scientific staff with a healthcare background. The production processes are unique to the company so they train individuals specifically for these posts. Finding scientists with a healthcare background has been more difficult. The company needs people with core skills that show an understanding of chemistry, biology, surgery, anatomy, physiology,
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
146
polymer science, engineering and the ability to design. This barrier was addressed by finding several people with appropriate complementary skills who can then work together as a team. To remain competitive the company needs to fund further research, which they do by sponsoring research at a university hospital. However, although this approach opens up new thinking in medical products, it creates additional barriers to innovation. The MD considers universities to be very poor at getting patent protection early on; inefficient at driving projects forward; and believes discoveries are lost through indifference, complacency or because the university publishes the results without protecting them first. Only vigilant management can overcome this barrier, but such action means that the company has to assign staff to the task from the core business.
Environmental Products Co-operative Environmental Products is a non-hierarchical co-operative employing 20 staff. The millennium product was a form of flow meter. The biggest barrier to innovation has been other companies copying the co-operative’s products. Many of the components of the co-operative’s products are purchased off the shelf and are therefore freely available to competitors. What makes the products innovative is the way in which the co-operative’s designers have used these off-the-shelf components to produce a product to fit a new application. The co-operative cannot protect the individual components through patents, only the function for which the product is created. Problems relating to others copying arise when competitors reverse engineer the co-operative’s products and produce a different design targeted for the same application. Rather than attempting to resolve this barrier, the co-operative has opted to ignore the problem and instead move towards offering a design consultancy service. Holding onto staff is a serious barrier to innovation, as competitors tend to be larger businesses that can offer better career incentives and higher salaries. Rather than tackling this barrier directly, the co-operative have accepted that once employees have gained experience they will leave to further their own careers. As the co-operative receives many unsolicited applications from people wanting to work for them, they find it easy to choose replacements. Market factors are considered to be significant barriers to innovation. Sales of the millennium product were very poor. In early 2000 the co-operative appointed a marketing
Volume 16
Number 2
2007
manager to take charge of sales forecasting and marketing. To quote the marketing manager, ‘In the past, assessing the risk of entering a new market was down to gut feel’.
Sensor Equipment Ltd Sensor Equipment Ltd’s millennium product was a low cost gas detector for use in a domestic environment. Sensor Equipment is a microcompany employing the MD and a Secretary. The first barrier to innovation Sensor Equipment Ltd faced in the development of the detector was the design and manufacture of a key functional element of the product. This was overcome through an iterative process of design–prototype–test in conjunction with a specialist manufacturer until the problem was solved. To assist with the development costs, the MD applied for an innovation grant from the regional government. However, difficulties arose relating to increasing employment as the company subcontracts all production, marketing, distribution and delivery. To address the grant criteria relating to increasing employment, the MD was able to convince the government agency dealing with the application that, although employment would not increase within Sensor Equipment Ltd, jobs would be created in the various subcontractors. Sensor Equipment Ltd sold out the marketing and sales of its millennium product to another company that expected sales to exceed a million detectors a year. But this was to prove to be a hidden barrier to innovation because the MD decided to use the fee paid for the contract to develop other products rather than consolidate the business. As the anticipated large orders failed to materialize, the company ran out of working capital. Before the business was forced to close, the MD was approached to work as a consultant to advise other SMEs on the pitfalls of innovation and was offered a lecturing post at a UK university, thus providing sufficient income to enable the business to continue.
Textile Equipment Ltd Textile Equipment Ltd comprises an MD, a secretary and four workshop staff. The company developed its millennium product, an innovative piece of textile fabrication equipment in response to a competitive threat. Lack of working capital was Textile Equipment Ltd’s first barrier to innovation and this influenced all the other barriers that the company saw as obstructing the process of innovation. The company partially resolved the lack of working capital through using design © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
MANAGING THE BARRIERS TO INNOVATION
to drive cost out of their products by reducing the number of parts required to make the equipment and also by changing some of the materials used from metal to plastic. Redesigning the products to be simpler also meant that unskilled labour could assemble the products, thereby overcoming the need to employ highly skilled and expensive production workers. Another benefit of simplification was that it assisted the company in overcoming the problem of not being able to defend its patents as the products have been simplified to the point where it is not worth other businesses copying them. The second barrier related to innovation grants from the regional government. Such grants are dependent on increasing employment, which Textile Equipment Ltd cannot guarantee. The company points out that increasing employment can only be guaranteed if an innovation results in a significant increase in sales volume. Initially, innovation can often lead to a loss in employment. Time pressures were also seen as a barrier to innovation because the MD was spending too much time dealing with the financial problems of the company. This left little time to concentrate on innovation. The only way the MD could deal with the time barrier was to adopt a ‘stop and go’ strategy, that is, when the finances ran out the innovation process stopped, but when finances enabled the creditors to be appeased he could restart the product innovation process. Stopping and starting puts the MD under enormous stress. While initially it would seem that there cannot be any let-up in the stress factor until the debt burden is lifted, the MD believes that the creation of a separate design consultancy for research and development of Textile Equipment Ltd’s product range would enable innovation to continue. Manufacture and assembly of the product range could then be subcontracted.
Marine Products Ltd The MD of Marine Products Ltd started a retail business in 1986 selling boats and marine accessories, and employs two people. The idea for the millennium product was identified from a gap in the market. Being a retail outlet Marine Products Ltd had no knowledge of NPD so to help address this barrier they built a good relationship with the local enterprise agency. Predictably, finance was a key barrier to innovation. To finance the innovative idea, Marine Products Ltd applied under the loan guarantee scheme. However, they were refused the loan because their primary market © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
147
was in exports, which disqualified their application. Next they applied for venture capital, which required the supply of a sample of the product so that it could be reviewed by a design consultant. Unfortunately, the report from the design consultant stated that the product required further investigation and more design work before it would be of interest. As a result, the company decided to cut costs and use internal investment. Using internal investment meant that the company had to be extremely careful not to overstretch themselves financially. In practical terms, this meant that they did not have the capital to invest in a number of parallel processes. For example, although they had planned to develop the product concurrently with the marketing and sales strategy, now they would have to get the product ready for launch first and then undertake the marketing and sales. In the tourist area where the company is located, few skilled engineering workers can be found, which creates a barrier to innovation, as the product requires these key skills. To overcome this barrier, product manufacturing was subcontracted to an engineering company in another region of the UK. An added benefit of this decision, according to the MD, is that subcontracting the work to other companies who have the systems and procedures already in place for employing people reduces the financial risk borne by the original innovator. Marketing also proved a barrier to innovation as a result of financial and company size constraints. Marine Products Ltd could not afford to employ marketing staff and so to overcome this barrier the company created its own website.
Architectural Structures Partnership Architectural Structures Partnership is a firm of architects involved solely in design of new structures. The millennium product was a spin-off of other work brought about by the demand for large storage and distribution centres. The biggest barrier to innovation cited by the Partnership related to finding people with the expertise to be able to manufacture the millennium product. The senior partner believed that this could be overcome by expanding the partnership business into manufacturing. But expanding the partnership to include a manufacturing capability required acquiring manufacturing expertise. The use of external consultants was rejected as the partnership did not know which consultants they could trust to do the best job. Appointing a general manufacturing manager was also
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
148
rejected, as the partnership did not know enough about manufacturing to select the best candidate. The senior partner concluded that the answer lay in improving the manufacturing knowledge of the partnership through education and training. However, this created another barrier in that the partnership could not afford to send personnel from the partnership to attend manufacturing courses and on-site courses were felt to be too disruptive. The barrier was resolved by joining an SME innovation network, which enabled the senior partner to discuss with other senior management who had been through the innovation process the pros and cons they had encountered and how they had dealt with them. According to the senior partner identifying the market for the millennium product has been ‘half the problem’. However, the partnership has been averse to using the Internet to publicise their products for fear of others copying their ideas despite the fact that they have patents. Therefore, Architectural Structures Partnership’s current approach to resolve the marketing barrier is based on generating customer contacts through word of mouth or as a result of spin-offs occurring from other projects.
Textile Materials Ltd Textile Materials Ltd employs ten staff. The millennium product is a holographic cloth and at the time of the interview had taken ten years to develop. Finding a specialist manufacturer for the millennium product became Textile Materials Ltd’s first barrier to innovation. The demands imposed by the successful creation of a hologram on cloth imposed significant constraints on the manufacturing process. The barrier was overcome more by accident then intention when a manufacturer working on another project with the firm agreed to take up the research and development. Another barrier related to finance for innovation. Textile Materials Ltd applied for funding using the loan guarantee scheme but found that the banks they approached were not interested, although the company also appeared to be reluctant to use personal collateral as security. The use of venture capital was dismissed because of the need for an investor to acquire a share in the business. Textile Materials Ltd applied for an innovation grant but failed and appeared to have decided that any further applications would be a waste of time and effort. The company did not overcome the finance barrier, instead adopting a ‘stop and go’ strategy. This meant that when there was
Volume 16
Number 2
2007
sufficient capital available, the costs associated with further development of the millennium product would get priority funding. When the finances were limited, the development process of the millennium product was put on hold. Textile Materials Ltd’s final barrier related to marketing the product. The use of a government agency to help on marketing proved to be useless, as Textile Materials Ltd did not feel that they understood the product or its purpose. They were also of the opinion that the UK Design Council’s web pages painted a very negative picture regarding the quality of the millennium product. To overcome the marketing barrier, the company analysed every end user and developed an exhaustive list of potential customers that they believed formed a plausible marketing strategy. Eventually they appointed a marketing director to take the company and its millennium product forward.
Discussion Analysis of the case studies revealed that those that ticked all or nearly all the boxes, as shown in Table 2, relating to the work of Cooper and Kleinschmidt (1995), Brown and Eisenhardt (1995) and Cooper (1999), and should therefore be seen as ‘exemplars’ of how to conduct the NPD process, were Medical Products Ltd, Medical Supplies Ltd and Architectural Structures Partnership. Medical Products Ltd was acquired through a management buyout and was well versed in the NPD process. Consequently, the management team had early on in the development process reviewed possible barriers to innovation that they might face and developed strategies to overcome them. Medical Supplies Ltd had previously developed a number of innovative products and so they too were familiar with the NPD process. Both companies’ approaches also demonstrate the importance of skill, experience and good judgement (Foley & Green, 1995) in successful NPD. However, Medical Supplies Ltd had a barrier to innovation not mentioned before, location. This barrier looked insurmountable to begin with, as the company could not afford to relocate to an industrial site and without a manufacturing base the company could not produce its products. Fortunately, the machinery for making the product could run on domestic electricity, which meant that the product could be made in the workers’ own homes. This turned out to be highly beneficial as it cut overhead costs and capital investment in buildings, thereby improving profits. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
MANAGING THE BARRIERS TO INNOVATION
149
Table 2. SMEs versus Success Factors Matrix
Medical Supplies Ltd Medical Products Ltd Environmental Products Co-op Sensor Equipment Ltd Textile Equipment Ltd Marine Products Ltd Architectural Structures Partnership Textile Materials Ltd
1
2
3
4
5
6
Outcome: Level of Sales of Product
✓ ✓
✓ ✓ ✓ ✓ ✓ ✓ ✓ ✓
✓ ✓
✓
✓ ✓
✓ ✓ ✓
Above expected Above expected Below expected Below expected As expected As expected As expected Below expected
✓ ✓ ✓ ✓
✓
✓ ✓ ✓ ✓
✓ ✓
Key: 1. Conduct up-front homework into competitors and suppliers, and build in the opinions of customers. 2. Demand sharp, early product definition of differentiated, superior products. 3. Plan and resource the market launch early on and build in stages with pre-defined tough ‘go’ or ‘kill’ decision points in the process. 4. Organize competent, truly cross-functional project teams guided by strong project leaders. 5. Build an international market-focused orientation into the design innovation process with effective internal and external communications. 6. Ensure full senior management support with unhindered access to financial, personnel and political resources.
Architectural Structures Partnership’s attitude to marketing emphasized their lack of trust (Freel, 2000; Hadjimanolis, 2000). To overcome this barrier they decided to sell through word of mouth rather than advertising or using the Internet. Their manufacturing barrier reflected the findings of Beaver and Prince (2004) relating to the need to remain independent and Freel (2000) and Hadjimanolis (2000) regarding trust. However, they resolved the barrier by joining an innovation network that comprised similar businesses facing similar difficulties where they could learn from each other. Environmental Products Co-operative’s marketing barriers related mainly to marketing intelligence: the millennium product was developed based on ‘gut feel’ clearly not supporting factor 1 in Table 2 or research by Wren et al. (2000). They also had two barriers to innovation not mentioned before in the literature: other companies copying their products and a high staff turnover. As the co-operative had the competitive edge of being first to market, they did not consider other companies copying their products as a barrier worth overcoming. Likewise, they were not concerned with the loss of tacit knowledge and information on NPD practices due to a high staff turnover as plenty of people wanted to work for them. Sensor Equipment Ltd’s barrier relating to the manufacture of their millennium product was overcome by working in conjunction © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
with a specialist manufacturer. Although the finance barrier for the company was initially overcome by winning government grant support and selling out the marketing and sales to another company, by acting impatiently and developing other products the business faced financial ruin; a characteristic identified by Beaver and Prince (2004) as detrimental to NPD success. Liquidity problems and insufficient working capital are also factors highlighted in research by Birley and Niktari (1995) as reasons for failure. Textile Equipment Ltd used grant aid to assist in the development of their millennium product. But the main financial barriers to innovation were triggered by the loss of market share caused by an aggressive competitor; having seen their sales plummet and profits turn to losses, Textile Equipment Ltd had to innovate to survive. This left the company with many of the reasons for failure identified by Birley and Niktari (1995). The company decided to use design to drive down costs, but the finance barrier was only partially resolved because to generate sufficient income required increasing sales of the millennium product and that would take time. The MD raised ‘time’ and ‘stress’ as barriers to innovation. These barriers relate to having to concentrate on business functions other than innovation in order to address the financial difficulties. One option to overcome these barriers would be to start up a design consultancy
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
150
to handle research and development and subcontract the manufacturing. Marine Products Ltd had carried out extensive market research including talking to customers and checking on the competition before embarking on developing their millennium product (factor 1 in Table 2). However, despite this, marketing was to become a barrier due to the lack of finance. Lack of finance meant that they could not afford to plan the market launch early on in the development process (factor 3 in Table 2). They had tried to get financial support through venture capital and the loan guarantee scheme, methods suggested by Freel (2000), but neither of these approaches worked and they were forced to use their own resources. The millennium product was the first time the company had ventured into NPD, but they overcame this barrier by building a good relationship with the local enterprise agency, a strategy recommended by Deakins et al. (1996). Also, they overcame the lack of manufacturing skills by subcontracting all associated processes. Textile Materials Ltd had originally employed an agency to market the product but felt the agency did not understand the product or its purpose. They also felt that the Design Councils’ website misrepresented their product. However, as in both instances it was up to the company to provide the information, it would appear that Textile Materials Ltd had failed to communicate (factor 5 in Table 2). The decision to develop an exhaustive list of potential customers after ten years of product development is clearly out of step with factor 3 in Table 2. The SME’s approach also highlights their lack of customer focus (Clifford & Cavanagh, 1985; Mondiano & Ni-chionna, 1986; Tonge, Larsen & Ito, 1998) and their obsession with the innovativeness of their idea at the expense of marketing (Foley & Green, 1995; Freel, 2000). To resolve the financial barrier a ‘stop and go’ strategy was adopted; when the finances were available they would continue with the development of their idea, when the money ran out they stopped.
Conclusion It was expected that when a SME was faced with a barrier to innovation the SME would seek methods to address the barrier, that is, recognize the barriers’ existence and identify possible scenarios and probable outcomes before deciding on a course of action to overcome the barrier. Instead, they were just as likely to ignore or live with a barrier as resolve it. In most of the SMEs it appeared that the management lurched from one crisis to an-
Volume 16
Number 2
2007
other, which, if they had been more aware of the ‘cause and effect’ of the actions taken, could have prevented some of the barriers to innovation occurring. Checking on how the case studies had performed 18 months after the initial interviews found that Medical Products Ltd and Medical Supplies Ltd had indeed succeeded in launching their millennium products into world markets. Architectural Structures Partnership had not moved into manufacturing and still used subcontractors to build their millennium product. Sensor Equipment Ltd had moved into consultancy. Environmental Products Co-operative had withdrawn their millennium product due to poor sales. Textile Materials Ltd had failed to find any businesses interested in using their millennium product, but they were still pursuing the idea. Marine Products Ltd was content with their product’s performance. Textile Equipment Ltd was still a manufacturer struggling to clear their debt.
References Beaver, G. and Prince, C. (2004) Management, Strategy and Policy in the UK Small Business Sector: A Critical Review. Journal of Small Business and Enterprise Development, 11, 34–49. Birley, S. and Niktari, N. (1995) The Failure of OwnerManaged Businesses: The Diagnosis of Accountants and Bankers. Report for the Institute of Chartered Accountants in England and Wales. Brown, S. and Eisenhardt K. (1995) Product Development: Past Research, Present Findings and Future Directions. Academy of Management Review, 20, 343–78. Bruce, M., Cooper, R. and Vazquez, D. (1999) Effective Design Management for Small Businesses. Design Studies, 20, 297–315. Clifford, D.K. and Cavanagh, C. (1985) The Winning Performance – How America’s High-Growth Midsize Companies Succeed. Sidgewick and Jackson, London. Cooper, R.G. (1999) From Experience: The Invisible Success Factors in Product Innovation. Journal of Product Innovation Management, 16, 115–33. Cooper, R.G. and Kleinschmidt, E.J. (1995) Benchmarking the Firm’s Critical Success Factors in New Product Development. Journal of Product Innovation Management, 12, 374–91. Deakins, D., Levinson, D., Paul, S. and O’Neil, E. (1996) The Use and Impact of Business Consultancy in Scotland. PERC: University of Paisley. Design Council (2001a) http://www.designcouncil. org.uk/innovationstory/story-aboutus.asp (accessed 28/03/2001). Design Council (2001b) http://www.designcouncil. org/design/content/news_story . jsp ? ContentID =09009e0d8000310b (accessed 23/10/2001). Foley, P. and Green, H. (1995) A Successful High-Technology Company: Plasma Technology (UK) Ltd. In Foley, P. and Green, H. (eds.), Small © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
MANAGING THE BARRIERS TO INNOVATION
Business Success. The Small Business Research Trust, Paul Chapman Publishing, London, pp. 72–80. Freel, M.S. (2000) Barriers to Product Innovation in Small Manufacturing Firms. International Small Business Journal, 18, 60–80. Hadjimanolis, A. (2000) A Resource-Based View of Innovativeness in Small Firms. Technology Analysis and Strategic Management, 12, 263–81. Hall, G. (1989) Lack of Finance as a Constraint on the Expansion of Innovatory Small Firms. In Barber, J., Metcalfe, J. and Porteous, M. (eds.), Barriers to Growth in Small Firms. Routledge, London. Litvak, I.A. (1992) Winning Strategies for Small Technology-Based Companies. Business Quarterly, 57, 47–51. Mondiano, P. and Ni-chionna, O. (1986) Breaking into the Big Time. Management Today, 11, 82–84. Roy, R. and Riedel, J.C.K.H. (1997) Design and Innovation in Successful Product Competition. Technovation, 17, 537–48. Tidd, J., Bessant, J. and Pavitt, K. (1997) Integrating Technological, Market and Organisational Change. John Wiley and Sons, Chichester. Tonge, R., Larsen P. and Ito, M. (1998) Strategic Leadership in Super-Growth Companies – A Reappraisal. Long Range Planning, 31, 835–44. Woodcock, D.J., Mosey, S.P., and Wood, T.B.W. (2000) New Product Development in British SMEs. European Journal of Innovation Management, 3, 212–21. Wren, B.M., Souder, Wm.E. and Berkowitz, D. (2000) Market Orientation and New Product
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
151
Development in Global Industrial Firms. Industrial Marketing Management, 29, 601–11. www.sbs.gov.uk (2006) http://www.sbs.gov. uk / sbsgov / action / layer?r . l2 = 7000000243&r.l1 =7000000229&r.s=sm&topicId=7000000237 (accessed 22/06/06.)
Povl Larsen (
[email protected]) is Senior Research Officer in design and innovation management at the National Centre for Product Design and Development Research. His research interests cover barriers to innovation, decision support systems, smart clothes and wearable technology, and design and management accounting processes in medium-sized enterprises. He has published over 40 papers in these and related areas. Alan Lewis is Director and Dean of Research and was one of the founders of the National Centre for Product Design and Development Research. He has worked with many companies in a variety of industry sectors helping them to improve their product development processes. His current research interests include product design management and international approaches to the provision of design support mechanisms. He has published over 60 papers in these and related fields.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
152
Inter-functional Integration and Industrial New Product Portfolio Decision Making: Exploring and Articulating the Linkages Helen Perks This study investigates the relationship between the nature of inter-functional integration and industrial new product/service portfolio decision making. While inter-functional integration has been widely researched, there is little understanding of its influence on resource allocation decisions within the context of a broad portfolio of development projects. The detailed activities and decisions underpinning the inter-functional management of the new product portfolio, as well as three specific new product/service projects, at a large European industrial product manufacturer are analysed. Detailed findings are provided. Two critical interfunctional dimensions – functional domination and nature of evaluation criteria – are derived and discussed. Implications for managerial action are given.
Introduction
T
his study explores the relationship between the nature of inter-functional integration and the management of the new product project portfolio. In doing this, it seeks to understand how the nature of inter-functional integration, within and across development projects, impacts upon decision making. Widespread research has articulated the benefits that high levels of inter-functional integration can accrue to new product outcomes, such as effectiveness in prototype development, R&D commercialization and product launch (Kahn, 1996; Souder, Sherman & Davies-Cooper, 1998). Yet, differing educational and professional backgrounds of diversified functions mean effective inter-functional integration is highly problematic (Lawrence & Lorsch, 1967). While research has studied and prescribed mechanisms to improve inter-functional integration at the new product project level (Kahn, 1996; Kahn & McDonough, 1997), little attention has been paid to the influence of the level and nature of inter-functional integration at the new product portfolio level. In particular, there is little understanding of how inter-functional integration affects resource allocation decision making across the new product portfolio.
Volume 16
Number 2
doi:10.1111/j.1467-8691.2007.00429.x
2007
This paper seeks to go some way towards addressing this gap by investigating and unravelling critical dimensions of the relationship between the nature of inter-functional integration and portfolio decision making in the context of industrial new product and service development. The paper firstly discusses and conceptualizes resource allocation decision making at new product portfolio and project levels and its relationship with the notion of inter-functional integration. The paper then reports on portfolio management and the development of three new product and service innovations carried out by multiple functions at a large European steel manufacturer. The research utilizes an embedded case study methodology, with resource allocation decision making as the frame for analysis. The findings derived from the case study are articulated and discussed at the end of the paper.
Making Decisions about Resource Allocation at New Product Portfolio and Project Levels Recent new product development (NPD) research has emphasized the need to manage a complex portfolio of multiple projects, © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
particularly in large companies, and attention has been drawn to the interplay of resource allocation decisions at both project and portfolio levels (Cooper, Edgett & Kleinschmidt, 1998, 2000). New product portfolio management is a dynamic decision-making process which aims to update and revise a business’s list of active new product projects. Within this process new products may be evaluated, selected and prioritized, existing projects may be terminated and resources reallocated accordingly (Cooper, Edgett & Kleinschmidt, 1999). Resource selection and allocation occurs at the levels of both the portfolio and individual projects. Indeed, resource deficiency in key areas of the NPD process has been shown to result in the omission of critical activities, poorly executed activities and lower quality final products (Cooper & Edgett, 2003). Several researchers have unravelled dominant managerial concerns in selecting portfolio methods. These include achieving the best balance of projects (Wheelwright & Clark, 1992; Cooper, Edgett & Kleinschmidt, 1997; Mikkola, 2001), maximizing the value of the portfolio (Gareis, 1989; Cooper, Edgett & Kleinschmidt, 1997), ensuring optimal allocation of resources (Hendrikis, Voeten & Kroep, 1999; Engwall & Jerbrant, 2003) and linking the portfolio to the firm’s business strategy (Wheelwright & Clark, 1992; Cooper, Edgett & Kleinschmidt, 1997; Englund & Graham, 1999). Gareis (1989) advocates the integration of single projects with a network of projects at the firm level. He suggests that this can be supported through decentralized decision making and the development of a balanced and integrated culture. Cooper, Edgett and Kleinschmidt (1999) examined the relationship between a multitude of portfolio practices and organizational performance. They concluded that the most successful firms utilize a range of portfolio methods. It has been suggested that a high level of integration between resource allocation at portfolio and project level is desirable (Cooper, Edgett & Kleinschmidt, 1999; Hendrikis, Voeten & Kroep, 1999), but this is under-investigated. Numerous researchers have explored the evaluation processes at the NPD project level. Cooper and De Brentani (1984) found that the multitude of evaluation criteria available to firms was dominated by considerations of financial potential, corporate and technological synergy, and product differential advantage. These findings were echoed in further work (Carbonell-Foulquie, Munuera-Aleman & Rodriguez-Escudero, 2003). Other research reported that the usage and relative importance of the different criteria dimensions changes as the project © 2007 The Author Journal compilation © 2007 Blackwell Publishing
153
progresses (Ronkainen, 1985; Hart et al., 2003). Further, the presence of rigorous evaluation points has been identified as one of the main drivers of new product performance (Cooper and Kleinschmidt, 1996). Research has suggested that the difficulties in portfolio decision making derive from project-level difficulties, such as imperfect or incomplete information or power struggles in the project team (Balachandra, Brockhoff & Pearson, 1996). Such difficulties mean project termination is often avoided and replaced by spending cuts, often prolonging the inevitable decision to terminate the project (Cooper and Kleinschmidt, 1988). These findings suggest that project and portfolio resource allocation decision making are intrinsically linked. In seeking to study and understand portfolio decision making, it is unwise to isolate decision making at the portfolio level from behaviours and decisions occurring at the project level. Despite emphasis on best practice in terms of adoption of prescribed and formalized methods, there is increasing recognition that new product portfolio management is difficult to implement. It is frequently an ill-defined process based on unconscious or informal decision making (Cooper, Edgett & Kleinschmidt, 1998). Cooper and Edgett (2003) identified a preoccupation with short-term profitability, overload of projects and an overemphasis on speed to market as underlying causes of failure in portfolio management. Other researchers have highlighted the problem of completing projects within the agreed time schedules (Mikkola, 2001; Engwall & Jerbrant, 2003). This is particularly pertinent in innovative high-tech industries that face short life cycles and complex technologies. Several scholars have unravelled emotive factors that affect portfolio resource allocation decision making. Early work began to highlight the relationship between human behaviour and new product selection processes (Souder & Mandakovic, 1984). Balachandra (1984) found that decision making was often based on ‘gut feel, past experiences, faith in certain individuals, hopeful guesses and wishful thinking’ (p. 93). In a later study, Payne (1995) identified peer rivalry and functional bias as underlying behavioural difficulties within portfolio management. Such studies, incorporating emotive and behavioural dimensions, have enriched the research domain, previously dominated by mathematical and quantitative techniques. This limited body of work draws attention to the nature of inter-functional relationships in portfolio management and informs this study.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
154
Inter-functional Integration and New Product Portfolio Decision Making Building on Kahn’s conceptualization (Kahn, 1996), extended by Jassawalla and Sashittal (1998), we define inter-functional integration, in this investigation, as a high intensity of cross-functional linkages, whereby multiple departments work together towards common goals. A body of research is beginning to coalesce greater understanding of the role of interfunctional integration in the context of NPD. Much research has traditionally identified the R&D/marketing interface as critical (Gupta, Raj & Wilemon, 1986; Griffin & Hauser, 1996). Other work has stressed the importance of moving beyond the dyadic level towards a multiple functional perspective in the study of functional integration (Denison, Hart & Kahn, 1996; Song, Montoya-Weiss & Schmidt, 1997). Nonetheless, high levels of coordination between marketing and technical functions appear to be significant in effective new product performance (Souder, 1988). The mechanisms which facilitate and inhibit inter-functional integration have been studied extensively, along with their impact on different outcomes (Pinto, Pinto & Prescott, 1993; Griffin & Hauser, 1996; Leenders & Wierenga, 2002). Barriers to inter-functional integration have focused on personality clashes between functions, due to different backgrounds and training (Lucas & Bush, 1988; Souder, 1988; Griffin & Hauser, 1996). In terms of success factors, particular emphasis has been placed on organizational factors as facilitators of interfunctional integration. These include decentralized decision making (Gupta, Raj & Wilemon, 1987; Jassawalla & Sashittal, 1998), unambiguous and clearly articulated rules and procedures (Gupta, Raj & Wilemon, 1986), incentives and rewards (Griffin & Hauser, 1996; Song, Montoya-Weiss & Schmidt, 1997; Leenders & Wierenga, 2002) and the degree of senior management support and involvement (Gupta, Raj & Wilemon, 1986; McDonough & Barczak, 1991; Song, Montoya-Weiss & Schmidt, 1997). In addition, cross-functional teams (Denison, Hart & Kahn, 1996) have been viewed as a means to coalesce disparate functions. Physical proximity of functions is also shown to have a positive influence on integration (Gupta, Raj & Wilemon, 1987; Pinto, Pinto & Prescott, 1993; Kahn & McDonough, 1997; Leenders & Wierenga, 2002). Such research has primarily focused at the organizational level (Song, Montoya-Weiss & Schmidt, 1997), with some, but limited, detailed exploration of project level behaviour.
Volume 16
Number 2
2007
There is a dearth of in-depth exploration of the complex inter-functional behavioural traits influencing how, in reality, firms allocate resources and select new product projects. Specifically, minimum research effort has been accorded to the relationship between the nature of inter-functional integration and resource allocation decision making at the project and portfolio levels. There is growing acknowledgement of the linkages between portfolio and project level resource allocation decision making. Further, there is recognition of the emotive and behavioural influences on such decision making. Yet, the nature of functional roles and integration in these contexts has received little attention. We suggest that the nature of inter-functional integration is likely to impact on decision making at both the project and portfolio levels and this relationship merits investigation.
Research Objectives and Methodology This research aims to explore and articulate critical dimensions of the relationship between the nature of inter-functional integration and resource allocation decision making at the new product portfolio and project levels. In order to achieve this, it seeks to address the following four research questions: 1. How and why do firms allocate resources across a portfolio of new product projects? 2. How do firms derive criteria to inform such resource allocation decisions? 3. What influence does the nature of interfunctional integration have on the criteria and resource allocation decisions at project and portfolio levels? 4. What are the critical dimensions explaining and underlying such influences? This study adopts an embedded case study methodology in attempting to address these questions. The case study method allows a holistic, rich and detailed investigation of decision making, while retaining the contextual and temporal setting. The case study research method focuses on understanding the dynamics present within single settings (Eisenhardt, 1989). It allows the richness of the detailed understanding of reality to emerge (Amaratunga & Baldry, 2001). In particular, a case study approach maintains sensitivity to the context within which the acts of management occur and to the temporal dimension through which events unfold (Bonoma, 1985). An embedded design was favoured. By adopting multiple units of analysis, within a single © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
155
Table 1. Nature of Projects Studied Name of project: Key product or service features:
Star
Protection
Advice
Enhanced shimmer paint effect
Antiseptic protection on environmental surfaces
Sharing of knowledge and expertise
complex case, opportunities for extensive analysis and insights arose. An in-depth embedded case study was conducted within Steel Division,1 a manufacturer of pre-finished steel, and a division of Steel Corp., a large European manufacturer of steel. Steel Corp. faces intense competitive pressures from foreign steel imports. The Steel Division is a profitable division of the organization and is under pressure to develop differentiated and valued added products and, more recently, services at competitive prices. Steel Division is a complex organization with multiple functions participating in the NPD process. At the time of the research, Steel Division was undertaking several projects, at various stages of development, using diverse evaluation criteria. The organizational structure within Steel Division required individuals from different levels and functional backgrounds to participate in NPD projects.
Data Collection and Analysis An in-depth analysis of decision making in and across three different new product and service projects was undertaken at Steel Division. The projects are outlined briefly in Table 1. A total of 15 in-depth semi-structured interviews were conducted across a range of functions. This evidence was supported by observational visits to the commercial, marketing and technical product development offices of the organization. Extensive secondary documentation was consulted, including project planning documents, annual plans, phase gate process blueprints, evaluation reports, minutes of meetings and copies of internal e-mails. Content analysis of the data was carried out and supported by the NUD*IST qualitative data analysis computer package. A coding system was derived, based initially on descriptive codes. These were consistently reviewed and redefined as data collection progressed. During this process, patterns emerged and interpretative and pattern 1
Company and product names have been changed to ensure anonymity.
© 2007 The Author Journal compilation © 2007 Blackwell Publishing
codes were created. These were inferential and explanatory in nature. Each of the three embedded cases was thus analysed individually and then together to draw out common patterns and explanatory factors. These were then compared and contrasted against data collected at the portfolio level, and patterns at the overall level were explored and unravelled.
Findings This section presents the findings of the study. For each project a final table provides a synthesis of the level and nature of inter-functional integration at each activity stage of the NPD process. In presenting these tables, effort was made to use common activity stages across all the projects. However, we found that there was variation in the types of NPD activities undertaken across the portfolio of projects and the activity stages are not homogeneous among the projects. This is not surprising and reflects the reality of problematic implementation of a common structured and phased NPD process within diverse projects. For each NPD activity stage of each project, the tables present key functional representation, the types of inter-functional communication and the criteria used to inform decision making. A final column indicates the level of inter-functional integration, classified as high, medium or low. The classification level was induced from the data by assessing both the extent of interaction (communication) for information exchange and the degree to which the functions collaborated for collective goals. This was informed by Kahn’s typology (1996). Second, we report on the nature of new product portfolio management at Steel Division. This is presented in terms of an overview of the process at the portfolio level, followed by a discussion of the major activities and decisions regarding resource allocation. Again, emphasis is placed on unravelling the nature of inter-functional integration throughout these activities. Thus, this part of the findings presentation addresses the first two research questions: how and why do firms allocate resources
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
156
Table 2. NPD Activities, Nature of Inter-functional Integration and Resource Allocation Criteria in Star Project NPD activity
Key functional representation in project activity
Types of inter-functional communication
Criteria for resource allocation decisions
Idea generation
Technical product manager, External pigment supplier Technical product manager Technical product manager, Senior commercial managers, Senior marketing manager Technical product manager, Manufacturing/ technical officer, External pigment and paint suppliers
Formal meetings
Technical differentiation
Low
None
Technical feasibility Formal specified criteria
None
Speed to achieve imposed time-scales
Medium
Business attractiveness Feasibility assessment
Development/ piloting
Formal meetings
Formal meetings, informal telephone conversations, e-mail
Level of inter-functional integration
Low
NPD, new product development.
across a portfolio of new product projects and how do firms derive criteria to inform such decisions? The section moves on to discuss, as posed by the third research question, the influence of the nature of inter-functional integration on the criteria and resource allocation decisions at project and portfolio levels. In doing this, the analysis draws out two critical dimensions which explain and underlie such influences (the fourth research question). The discussion shows how these provide a linkage between inter-functional integration at portfolio management level and the activities and decisions at project level. For each dimension, a succinct table exhibits its core features.
Project 1: Star Project Overview Star was an incremental development which provided greater aesthetics and colour choice for Steel Division’s lead user group: designers.
Volume 16
Number 2
2007
The project was carried out in close collaboration with the supply chain. This consisted mainly of external pigment and paint suppliers who developed a new flake to produce a desired shimmer paint effect. The project was dominated by the technically oriented product manager, acting as project leader, and the manufacturing division. It followed a phasegate process with formal regular evaluations in the early stages. During later stages, such as product line trials and manufacturing activities, less formal and ad hoc evaluations were undertaken. Table 2 presents a summary of the findings for the Star project.
Project 2: Protection Project Overview In 2001 a small team identified an opportunity, in conjunction with key supply customers, to develop a product which provided anti-septic protection on surfaces within the food industry. Multiple functions were involved in a © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
157
Table 3. NPD Activities, Nature of Inter-functional Integration and Resource Allocation Criteria in Protection Project NPD activity
Idea generation
Business attractiveness
Early market development
Development and piloting
Late market development
Key functional representation in project activity
Types of inter-functional communication
Criteria for resource allocation decisions
Level of inter-functional integration
Technical product manager, Commercial manager, Technical product manager (as project leader) Marketing senior manager, Commercial, business development manager (as project leader) UK manufacturing German manufacturing Commercial managers Business development manager, Technical product manager, Commercial manager German commercial manager
Formal meetings
Visibility and innovativeness in the marketplace
Medium
Ad hoc meetings
Previous market experience
Low
Formal meetings
Brand positioning
High
Formal meetings
Project and wider functional objectives
High
Telephone conversations, e-mails, regular review meetings
Market segmentation and targeting
High
NPD, new product development.
systematic development process, commencing with ad hoc market intelligence gathering. Table 3 presents a summary of the findings for the Protection project.
Project 3: Advice Project Overview Advice was a first attempt by Steel Division to develop a new service. It was developed as a © 2007 The Author Journal compilation © 2007 Blackwell Publishing
package of services centred on Steel Division’s knowledge and expertise of the construction industry. It included tangibles, such as complementary products and guarantees, as well as services, such as a seminar series. Rather than a formal phase-gate system, milestones were established to gauge the progress of the project. The product development manager described the process as ‘completely unstructured compared to a simple conventional product development’. He further commented
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
158
Table 4. NPD Activities, Nature of Inter-functional Integration and Resource Allocation Criteria in Advice Project NPD activity
Key functional representation in project activity
Types of inter-functional communication
Idea generation
Product development manager, Product development representative, Commercial representative, Marketing representative Product development manager, Marketing representatives, External consultants Product development manager, Product development representative Marketing manager
Formal presentations, informal meetings, informal telephone conversations
Industry practices Medium
Informal meetings, informal telephone conversations
Market requirements
High
Informal meetings, informal telephone conversations
Speedy development
Low
Informal face-to-face discussions Informal discussions, formal presentations
Brand value
Low
Wider acceptance of service concept
Medium
Market research
Tangible service development
Brand development
Internal marketing Marketing Director, Commercial manager, Marketing manager
Criteria for resource allocation decisions
Level of inter-functional integration
NPD, new product development.
that the phase-gate approach was considered but ‘we’re not actually tracking activities in that way’. Formal evaluation criteria were believed to be inappropriate: ‘It’s very difficult to gauge the success of intangible activities, such as advice and guidance’. An informal, flexible process was followed with experience and instinct playing an evaluative role. Table 4 presents a summary of the findings for the Advice project.
Volume 16
Number 2
2007
Portfolio Management Process Overview Overall new product portfolio management at Steel Division took place within the marketing division. Middle managers from four distinct areas (product development, applications development, market development and brand management) submitted budget proposals for potential new product projects. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
This range was felt to give some balance to the new product portfolio. There was no representation from commercial areas. Each area competed for resources and project selections were justified to the Marketing Director. Project feasibility was judged by estimated time to generate an expected return. Projects were divided into three areas: delivery projects, which generally had a one-year expected return, platform projects, which were given five years to generate profits to the business, and projects with longer time spans to return profits (these projects were exceptional). Decision making occurred through a number of meetings between the Marketing Director and middle managers. Some dissatisfaction was expressed with the method adopted. In particular, it failed to recognize differing degrees of project difficulty and risk (such as the development of new services as in the Advice project) and lacked formal evaluation criteria. Project decisions were communicated to the rest of the organization through an annual plan.
Resource Allocation Activities and Decisions The major mechanism for resource allocation decisions lay with the budget proposals emanating from the marketing division. A number of managers submitted high estimates on the understanding that some of the projects would be automatically eliminated through group discussion. ‘Experience has shown us that the budget proposal is twenty to thirty percent over what we’re going to get’, claimed the product development manager. Others generally received the resources requested. Judgement criteria were based on activity milestones, indicating what the projects were required to deliver and when. Such milestones helped monitor project progress but did not influence the resource allocation decisions. Such decisions were primarily informed by ‘the collective wealth of my management team, which I trust’, reported the Marketing Director. The process, according to a marketing representative, was ‘very much open forum sort of debating’. This allowed adequate consideration of the range of diverse project types, with different objectives and timescales. The Marketing Director undertook an intuitive ‘mental gap analysis’ between current projects and the areas the business ought to cover. As he confirmed, ‘as the department has matured and we’ve got a better idea of what we’re doing, we’ve felt less need to use formal evaluation criteria’. Formal strategic criteria were felt to be built into each © 2007 The Author Journal compilation © 2007 Blackwell Publishing
159
project’s phase-gate system, once under way. A key indicator of a project’s potential was the enthusiasm or commitment shown by project leaders towards the project. For example, the Star project gained support partly due to the high enthusiasm of the technically oriented project manager. Portfolio decisions were communicated through an annual plan, which was reviewed bi-annually. Monthly reviews of key project milestones and deliverables were also initiated. These provided a degree of contingency planning to account for changes in personnel or NPDs that were not anticipated. Wider representation was involved in these meetings, including the commercial division. As a result, frequent alterations to the portfolio occurred, e.g., accelerating projects or injecting more resources into ailing projects. The Star product launch was brought forward for commercial reasons. However, changes to initial decisions caused some friction and were viewed as a reaction to short-term pressures. ‘Should you really be changing in April what you believed back in September was for the long-term good?’, commented a respondent. Nonetheless, it was unusual to terminate projects that failed to perform, particularly where championed strongly and with limited functional involvement.
Discussion Dimension 1: Functional Domination In analysing the cases, the findings show how the domination of single functions, acting as functional champions, can induce bias and functional resentment, leading to the exclusion of appropriate functional involvement in resource allocation decision making, impacting the whole portfolio. This provides a linkage between inter-functional integration and portfolio decision making, which can be explained by a number of factors. First, excessive control by a single dominant function can nurture unchecked sentimental attachments to projects, as appeared to be the case in both the Star and Protection projects. Such over-enthusiasm to pet projects by dominant functions can influence decision making at the portfolio level, often masking project limitations, and can hamper meaningful functional involvement in decision making. In the Star case, for example, the project, led by the enthusiastic technical product manager, was given the official go-ahead despite concerns over commercial feasibility and resource consumption. In such cases lip service may be given to formal
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
160
feasibility assessment, but priorities are established and pushed by the dominant function. This can attract corporate resources which are then unavailable to other projects. Further, functional dominance can encourage a biased orientation in the development process. We found, particularly at the early project stages, that issues of technical or market feasibility can dominate idea generation and concept assessment and subsequent resource allocation, dependent on the background of the dominant function. In the case of Star, for example, the strong technical orientation of the product development manager encouraged technological innovation criteria to dominate evaluation decisions at the expense of market information. Second, we found that functional dominance was exacerbated where the project leader was seen to be encouraging innovation and differentiation in the new product. Such was the case in both the Star and Protection projects. Innovation attracts attention and is seen as exciting. This attracts resources to the project and the functional bias is not challenged. Additionally, we found that functional domination can affect and be affected by the nature of inter-functional communication and representation. A lack of structured and appropriate functional involvement in decision making can reinforce functional domination. This supports Kahn’s (1996) findings that collaborative efforts in the NPD process are necessary in order to achieve balanced interfunctional integration. His study found that a high order involvement encourages functions to achieve goals collectively. It improves mutual understanding and reduces conflict. However, our findings suggest that this is particularly pertinent in the early stages of new product projects, when resources are being allocated. In two of our projects (Protection and Advice), efforts to engender greater functional involvement in later stages of the projects, and to shift the project’s direction, led to conflict and misunderstandings. Key resources had already been allocated in line with the dominant functional orientation. Other studies propose a contingency approach to functional involvement in NPD (Song, Thieme & Xie, 1998). The findings of Song et al. (1998) suggest that firms enjoy greatest success by employing function-specific and stagespecific integration. They propose that activities may be performed more effectively without the involvement of all functions and that core functions should take the lead at different activity stages. Our findings develop those of Kahn (1996) and Song et al. (1998). They suggest that non-critical external functions can be involved at different stages, but in
Volume 16
Number 2
2007
an informative way, through regular updates and the sharing of information about the project. Such interactions can help buy-in from diverse functions and orientate the project towards better collaboration in the later stages. Our findings found that if functions are excluded from participative interactions in the early stages, then a need for internal marketing of the project becomes important in later stages, in order to attract wider resources. This can be a difficult and time-consuming task, as illustrated in the Advice example. In all our projects, functions were separated by physical distance. We found that this can induce feelings of physical isolation and hamper appraisal or questioning of decisions, strengthening the control by the dominant function. A high degree of dissatisfaction at not being informed at all stages of the project can occur. These findings further work examining the role of champions in inter-functional integration (McDonough, 2000). They suggest that the emergence of a ‘functional champion’ can inhibit inter-functional integration and effective resource allocation decision making at both project and portfolio levels. Table 5 synthesizes the above discussion. It exhibits the core features of the functional domination dimension and highlights how the dimension provides a linkage between interfunctional integration and portfolio decision making. The final column shows where these features are illustrated in this study.
Dimension 2: Nature of Dominant Evaluation Criteria The findings have further unravelled dominant dimensions that relate inter-functional behaviour to the nature of evaluation criteria in portfolio decision making. Like many large organizations, Steel Division has a diverse new product portfolio. Some new product projects follow an incremental trajectory, developing existing knowledge and skills. Others involve innovative departures requiring expertise and knowledge outside the traditional base. For incremental developments, the confidence of building on past experience can induce the personal judgements of dominant functions to carry weight and senior management acceptance. This can lead to an accepted disregard of contradictory information from other functions (such as customer feedback in the Star and Protection cases). This may be a suitable approach for incremental projects, where past experience can be a meaningful variable to inform resource allocation decisions. This confirms © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
161
Table 5. Functional Domination Core features of dimension
Explanation of linkage between inter-functional integration and portfolio resource allocation decision making
Manifestation
Unchecked functional sentimental attachment to project
Over-enthusiasm of dominant function can mask project limitations Preferences of dominant function can dictate resource allocation Innovativeness can attract unmonitored attention and resources to projects Nature and timing of functional involvement can dilute/reinforce functional bias Physical location of functions can strengthen/weaken influence over resource allocation by dominant function
Portfolio, Star, Protection
Project innovativeness as driver of dominant function Nature and timing of inter-functional communication and representation Physical location of functions
Adams and co-workers’ findings that higher level performance in NPD can be achieved through the integration of knowledge or information from past projects (Adams, Day & Dougherty, 1998). However, for innovative and uncertain new products (such as the new Advice service), a lack of appropriate experience and capabilities suggests the need for guidance and expertise outside the core dominant functions. Yet, poor inter-functional integration and communication can prevent this occurring. In the Advice case, for example, there was a strong belief by the core project functions that other functions did not have relevant knowledge or experience to assist or assess progress. Hence ill-founded and constrained judgements prevailed. Existing research (Cooper & De Brentani, 1984) claims that formal and efficient portfolio evaluation approaches are not widespread. We found that an accepted preference for individual perceptions and past experience at the project level, if supported by senior management, can influence resource allocation decisions. Such decisions, in terms of project support and termination, can affect the whole portfolio, regardless of the nature of the pro© 2007 The Author Journal compilation © 2007 Blackwell Publishing
Portfolio, Star, Protection,
Portfolio, Protection, Advice
Portfolio, Star
jects. Several studies have indicated the need for different organizational forms and behaviours for different types of products. Hobday (1998), for example, discusses how the characteristics of complex products and systems affect the innovation process (compared to mass produced commodity goods). The study suggests that the project, in such complex products, acts as a coordination mechanism, combining resources from a wide network of participants. It is the project which shapes and dominates resource and integration needs. These usually diverge from the usual firm routines. Our findings further develop this contingency approach to managing a portfolio of products. We suggest that firms need to adapt to the differing evaluation needs created by a diverse range of products under development. An inability to modify the experience-based approach, for example, can impede effective resource allocation decision making. Table 6 synthesizes the above discussion. It summarizes the core features of the dominant evaluation criteria dimension. It also highlights how the dimension provides a linkage between inter-functional integration and portfolio decision making. The final column shows
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
162
Table 6. Nature of Dominant Evaluation Criteria Core features of dimension
Explanation of linkage between inter-functional integration and portfolio resource allocation decision making
Manifestation
Use of standard criteria across projects Use of personal judgement and previous experience as dominant criteria
A diversity of development projects requires different types of criteria, dictated by differing levels of functional involvement Incremental projects can build on accepted past behaviours and resource priorities; previous experience and personal judgement of core functions can act as appropriate evaluation criteria Innovative developments may require broader knowledge input and diverse criteria for resource decisions; greater functional involvement may be more appropriate
Portfolio, Protection, Advice
where these features are illustrated in this study.
Conclusion This study has explored the relationship between new product portfolio management and inter-functional integration. It has shown that the nature of inter-functional integration does impact on portfolio management. It has articulated where and why this happens. Two critical dimensions which explain the relationship have been unravelled. These dimensions warrant further empirical investigation across a broader range of contexts and have implications for managerial action. First, they draw attention to the impact of excessive project control by functional champions on portfolio resource allocation decisions. In particular, they alert managers to the dangers of permitting personal bias and senti-
Volume 16
Number 2
2007
ment to dominate resource allocation decisions. This may be especially detrimental if managing a diverse range of projects. This suggests a need to ensure appropriate crossfunctional representation is in place at the project level. This appears to be particularly important in the early stages. Second, it indicates that managers should implement formal evaluation criteria which encourage multifunctional input. Such approaches are pertinent where the new product portfolio includes radical projects. Finally, the results indicate the need for systematic monitoring of the project and portfolio evaluation process by senior management.
Acknowledgements Dr Perks would like to thank and acknowledge the contribution of Angela Greenland to this study. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INTER-FUNCTIONAL INTEGRATION
References Adams, M.E., Day, G.S. and Dougherty, D. (1998) Enhancing New Product Development Performance: An Organizational Learning Perspective. Journal of Product Innovation Management, 15, 403–22. Amaratunga, D. and Baldry, D. (2001) Case Study Methodology as a Means of Theory Building Performance Measurement. Work Studies, 50, 205–15. Balachandra, R. (1984) Critical Signals for Making Go/No-go Decisions in New Product Development. Journal of Product Innovation Management, 2, 92–100. Balachandra, R., Brockhoff, K. and Pearson, A. (1996) R&D Project Termination Decisions: Processes, Communication and Personnel Changes. Journal of Product Innovation Management, 13, 245–56. Bonoma, R.V. (1985) Case Research in Marketing: Opportunities, Problems and a Process. Journal of Marketing Research, 22, 199–208. Carbonell-Foulquie, P., Munuera-Aleman, J.L. and Rodriguez-Escudero, A.I. (2003) Criteria Employed for Go/No-go Decisions when Developing Successful Highly Innovative Products. Industrial Marketing Management, 33, 307–16. Cooper, R.G. and De Brentani, U. (1984) Criteria for Screening New Industrial Products. Industrial Marketing Management, 13, 3–14. Cooper, R.G. and Edgett, S.J. (2003) The Current Crunch in New Product Development Resources. Journal of Product Innovation Management, 20, 338– 55. Cooper, R.G. and Kleinschmidt, E.J. (1988) Resource Allocation in the New Product Process. Industrial Marketing Management, 17, 249–62. Cooper, R.G. and Kleinschmidt, E.J. (1996) Winning Businesses in Product Development: The Critical Success Factors. Research and Technology Management, 39, 18–29. Cooper, R.G., Edgett, S.J. and Kleinschmidt, E.J. (1997) Portfolio Management in New Product Development: Lessons from the Leaders II. Research and Technology Management, 40, 43–52. Cooper, R.G., Edgett, S.J. and Kleinschmidt, E.J. (1998) Portfolio Management for New Products. Perseus Books, Reading, MA. Cooper, R.G., Edgett, S.J. and Kleinschmidt, E.J. (1999) New Product Portfolio Management: Practices and Performance. Journal of Product Innovation Management, 16, 333–51. Cooper, R.G., Edgett, S.J. and Kleinschmidt, E.J. (2000) New Problems, New Solutions: Making Portfolio Management More Effective. Research and Technology Management, 43, 18–33. Denison, D., Hart, S. and Kahn, K. (1996) From Chimneys to Cross-Functional Teams: Developing and Validating a Diagnostic Model. Academy of Management Journal, 39, 1005–23. Eisenhardt, K.M. (1989) Building Theories from Case Study Research. Academy of Management Review, 14, 532–50. Englund, R.L. and Graham, R.J. (1999) From Experience: Linking Projects to Strategy. Journal of Product Innovation Management, 16, 52–64. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
163
Engwall, M. and Jerbrant, A. (2003) The Resource Allocation Syndrome: The Prime Challenge of Multi-project Management? International Journal of Project Management, 21, 1–7. Gareis, R. (1989) Management by Projects: The Management Approach for the Future. Project Management, 7, 243–9. Griffin, A. and Hauser, J. (1996) Integrating R&D and Marketing: A Review and Analysis of the Literature. Journal of Product Innovation Management, 13, 191–215. Gupta, A.K., Raj, S.P. and Wilemon, D. (1986) A Model for Studying the R&D-Marketing Interface in Product Innovation Process. Journal of Marketing, 50, 7–17. Gupta, A.K., Raj, S.P. and Wilemon, D. (1987) Managing the R&D Marketing Interface. Research and Technology Management, 30, 38–43. Hart, S., Hultink, E.J., Tzokas, N. and Commandeur, H.R. (2003) Industrial Companies’ Evaluation Criteria in New Product Development Gates. Journal of Product Innovation Management, 20, 22–36. Hendrikis, M.H.A., Voeten, B. and Kroep, L. (1999) Human Resource Allocation in a Multi-project R&D Environment. International Journal of Project Management, 17, 181–8. Hobday, M. (1998) Product Complexity, Innovation and Industrial Organisation. Research Policy, 26, 689–711. Jassawalla, A. and Sashittal, H. (1998) An Examination of Collaboration in New Product Development Processes. Journal of Product Innovation Management, 15, 237–54. Kahn, K.B. (1996) Interdepartmental Integration: A Definition with Implications for Product Development Performance. Journal of Product Innovation Management, 13, 137–51. Kahn, K. and McDonough, E.F. III (1997) An Empirical Study of the Relationship among Co-location, Integration, Performance and Satisfaction. Journal of Product Innovation Management, 14, 161–78. Lawrence, P. and Lorsch, J. (1967) Differentiation and Integration in Complex Organizations. Administrative Science Quarterly, 12, 1–47. Leenders, M. and Wierenga, B. (2002) The Effectiveness of Different Mechanisms for Integrating Marketing and R&D. Journal of Product Innovation Management, 19, 305–17. Lucas, G.H. and Bush, A.J. (1988) The MarketingR&D Interface: Do Personality Factors Have an Impact? Journal of Product Innovation Management, 5, 257–68. McDonough, E.F. III (2000) Investigation of Factors Contributing to the Success of Cross-Functional Teams. Journal of Product Innovation Management, 17, 221–35. McDonough, E.F. III and Barczak, G. (1991) Speeding Up New Product Development: The Effects of Leadership Style and Source of Technology. Journal of Product Innovation Management, 8, 203–11. Mikkola, J.H. (2001) Portfolio Management of R&D Projects: Implications for Innovation Management. Technovation, 21, 423–35. Payne, J.H. (1995) Management of Multiple Simultaneous Projects: A State-of-the-Art Review. International Journal of Project Management, 13, 163–8.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
164
Pinto, M., Pinto, J. and Prescott, J. (1993) Antecedents and Consequences of Project Team CrossFunctional Cooperation. Management Science, 39, 1281–97. Ronkainen, I.A. (1985) Criteria Changes across Product Development Stages. Industrial Marketing Management, 14, 171–8. Song, M.X., Montoya-Weiss, M.M and Schmidt, J. (1997) Antecedents and Consequences of Cross-Functional Cooperation: A Comparison of R&D, Manufacturing and Marketing Perspectives. Journal of Product Innovation Management, 14, 35–47. Song, M.X., Thieme, R.J. and Xie, J. (1998) The Impact of Cross-Functional Joint Involvement across Product Development Stages: An Exploratory Study. Journal of Product Innovation Management, 15, 289–303. Souder, W.E. (1988) Managing Relations between R&D and Marketing in New Product Development Projects. Journal of Product Innovation Management, 5, 6–19. Souder, W.E. and Mandakovic, T. (1984) R&D Project Selection Models. Research Management, 29, 36–42. Souder, W.E., Sherman, J.D. and Davies-Cooper, R. (1998) Environmental Uncertainty, Organizational Integration and New Product Development Effectiveness: A Test of Contingency Theory. Journal of Product Innovation Management, 15, 520–33. Wheelwright, S.C. and Clark, K.B. (1992) Creating Project Plans to Focus Product Development. Harvard Business Review, 70, 70–82.
Volume 16
Number 2
2007
Dr Helen Perks (
[email protected]. uk) is Senior Lecturer in Marketing and Product Innovation at Manchester Business School, University of Manchester, UK. Research interests focus on behavioural aspects of co-development and networking, international product development, new service development and functional interfaces in product innovation. Her PhD, from Lancaster University, focused on resource evolution in inter-firm collaboration. She holds an MBA from Bradford University and has 12 years professional experience with European manufacturing and consulting organizations, including PA Consulting Group and Olivetti Group, Italy. Dr Perks is Academic Chair of PDMA (Product Development and Management Association) UK and Ireland and is a member of the Academic Committee of PDMA, US. She is on the editorial board of several journals including Industrial Marketing Management and International Marketing Review. Her work is published in journals such as Journal of Product Innovation Management, Industrial Marketing Management, R&D Management, Journal of Business and Industrial Marketing, International Marketing Review, International Journal of Innovation Management, European Management Journal, Journal of Services Marketing and Services Industries Journal.
© 2007 The Author Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
165
Industry Convergence and Its Implications for the Front End of Innovation: A Problem of Absorptive Capacity Stefanie Bröring and Jens Leker This paper explores industry convergence and its implications for the front end of innovation. Conventional practice of idea generation and selection seems to be difficult in times of convergence, since actors face new knowledge and competencies owned in different industries. Given these particularities of industry convergence, this paper analyses decision processes at the front end of 54 R&D projects by using a mixed-method research design. Findings indicate that there are different approaches of how firms engage in innovation in industry convergence. A central implication is the need to differentiate between the market and technological side of a firm’s absorptive capacity.
Introduction
C
onvergence is a current phenomenon of many industries such as telecommunications, computing and consumer electronics or cosmetics and pharmaceuticals (Katz, 1996; Duysters & Hagedoorn, 1997; Prahalad, 1998). It can be defined as the blurring of boundaries between industries by converging value propositions, technologies and markets (Choi & Valikangas, 2001). On the one hand, industry convergence seems to be technologydriven since a new technological development is applied across conventional industry boundaries. This sharing of technologies creates not only new technology-intense industry segments but it also increases environmental dynamics and new interfaces of formerly distinct industries (Bierly & Chakrabarti, 1999). On the other hand, convergence can also be induced by the fusion of demand structures and the combination of previously distinct product features into a hybrid product (Pennings & Puranam, 2001; Sääksjärvi, 2004). Convergence also leads to a fusion of standards and regulation which opposes additional uncertainty for innovating firms (Katz, 1996). Firms that find themselves in converging industries face new competitors producing substitute products for the same market. Thus, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
firms require many critical knowledge areas for engaging in innovation. Those necessary areas of knowledge and capabilities are traditionally owned in different industries (Bierly & Chakrabarti, 1999). These industry-specifics can be explained by the insight that competencies are cumulative and path-dependent (Dierickx & Cool, 1989). Path-dependency occurs due to the fact that competencies develop over time following specific trajectories (Leonard-Barton, 1992; Helfat, 1994; Bettis & Hitt, 1995; Teece, Pisano & Shuen, 1997). It seems that no firm – regardless of its industry affiliation – possesses all the necessary competencies for successful innovation in times of convergence. Technological or market developments critical for potential innovations for converging industries cannot be identified since a certain firm may not possess the relevant knowledge to recognize, assimilate and integrate it. Thus, a firm’s innovative capability for innovations in converging industries may be hindered by a lack of absorptive capacity (Cohen & Levinthal, 1990) to respond to trends outside its industry, which may become crucial in a context of convergence. Given the fact that firms in converging industries are confronted with new unfamiliar sources of knowledge, competencies and resources, this paper explores the front end of
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00425.x
CREATIVITY AND INNOVATION MANAGEMENT
166
innovation. The idea is to understand how firms can successfully start R&D projects which necessitate the combination of technological and market knowledge in different industries. In analysing the specific context of industry convergence, this paper follows the idea presented in the current literature to take into account different contingencies (e.g., Shenar, 2001). By addressing these deficiencies, this paper contributes to the innovation management and strategic management literature with respect to the particular phenomenon of industry convergence. The remainder of the paper is organized as follows: first, the particularities of industry convergence will be discussed in order to understand their implications for innovation management and the front end in particular. This is followed by a short illustration of the research method and sample before the major findings and implications are highlighted.
Industry Convergence There exist different types of industry convergence which differ with regard to their implications for the firms involved (e.g., Katz, 1996). Following Malhorta & Gupta (2001) we distinguish industry convergence into input-side and output-side related convergence. These two dimensions of industry convergence present a particular context for innovation.
Technology-Driven Input-Side Convergence Industries and their underlying key technology platforms are the result of a cumulative development. Hence, before any trends of convergence emerge, patterns of technological developments as well as technological competencies vary significantly between industries (Cantwell & Paniccia, 1998). This situation may change if new technology areas arise which are applied across industries (Bierly & Chakrabarti, 1999). In this context, input-side refers to the converging trends of technologies and technology platforms. It is often induced by the development of new technologies which in turn leads to the development of a common technology platform in previously distinct industries (Pennings & Puranam, 2001). For instance, the approach to design personalized products (pharmaceuticals or foods) based on the gene profiles of an individual leads to the blurring of nutrition and pharmaceuticals induced by the common technology ‘genomics’.
Volume 16
of different industries. It occurs if customers treat products of different industries in the same way, i.e., products which originally were not in any competition with one other start to become substitutes (Malhorta & Gupta, 2001). An example of such a market-driven convergence which was initially triggered by technological convergence can be seen in personal computers and televisions. Both products are increasing being used as substitutes. Laptop computers with a DVD-player, for instance, encompass the classical functions of a data processing computer. However, they are also becoming increasingly popular for watching DVDs or even TV programmes – product functions traditionally not served by the computer industry but by the consumer electronics sector (Rockenhäuser, 1999). Therefore, market convergence can be seen as a result of the consumer trend towards convenience and onestop-shopping, where consumers try to satisfy different needs in one transaction (Pennings & Puranam, 2001). The occurrence of both technology-driven output-side convergence and market-driven input-side convergence leads to the development of a new inter-industry segment. Due to convergence of the input and the output sides, a new value chain emerges. Here, an important question is the degree to which a new industry segment substitutes the old segments. According to Greenstein and Khanna (1997), convergence can either lead to a total phasing out of the two formerly separate industries (1 + 1 = 1) or it can also trigger the emergence of an additional industry segment which complements the two that existed previously (1 + 1 = 3). With respect to innovation management this differentiation into substitutive and complementary convergence seems necessary in order to specify how pressing trends of convergence are. In the case of total substitution of previous sectors, innovation seems to be imperative to keep up with the trends in convergence. In contrast, in complementary convergence firms may seize the opportunities of industry convergence – or just focus on the existing ‘historical’ industry sector not requiring any adaptation. In the following discussion we assume that firms seize the opportunity of convergence and conduct innovation projects aiming at an emerging industry sector resulting from complementary convergence.
Market-Driven Output-Side Convergence
Particularities of Industry Convergence for the Front End of Innovation
Output-side convergence, on the other hand, is triggered by converging demand structures
Absent competencies in either market or technological understanding may lead to consider-
Number 2
2007
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
167
Fit Regarding Market Gap Regarding Technology
Front End:
Characteristics of Industry Convergence
- Idea Generation
Convergence of Inputs (Technologies)
- Idea Evaluation &Selection
Convergence of Outputs (Market Needs) Emerging Standards (Converging Regulation)
Type of Innovation
Firm’s Competences:
Industry (A): ConsumerDriven Industry
Industry (B): ScienceDriven Industry
firm boundary
Fit Regarding Technology Gap Regarding Market
Figure 1. Particularities of the Front End of Innovation in Converging Industries
able problems in the front end activities of idea generation, evaluation and selection. These problems are due to the fact that firms with no prior experience and knowledge in either market or technology will not be able to identify relevant developments concerning technology and/or market in times of industry convergence. As illustrated in Figure 1, the science-driven firms of industry (B) face problems regarding the market side of idea generation. They cannot generate consumer marketing concepts since they have no prior experience. Likewise, it might be difficult for a marketing-driven consumer goods company of industry (A) to derive ideas from external developments by technology monitoring. This is because the consumer-driven firm is possibly not able to understand relevant technological developments, due to the lack of previous knowledge and experience. Given this lack of either technological or marketing competencies, the problem at the front end of innovation clearly is the element of awareness in the stage of idea generation. How should a low-tech consumer goods company identify emerging technological trends if it has never previously been involved with technology development? Likewise, a technology-intense company is not aware of consumer trends critical for choosing the appropriate market entry positioning. Hence, it seems that in converging industries firms generally face problems in idea generation, evaluation and selection which are due to limited familiarity with the relevant (converging) knowledge basis critical for framing and understanding ideas. This implies that the methods and process designs which are proposed by the current literature on the front end (e.g., existing customers and suppliers, well-defined stage-gate designs) may not be © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
applicable in the front end of innovation in converging industries. From a theoretical standpoint the construct of absorptive capacity – as the ability to recognize, value and acquire new information in order to apply it to commercial ends (Cohen & Levinthal, 1990) – seems to be the key hurdle for innovation in converging industries. This leads us to the following questions: (1) How do firms successfully generate and select ideas for so-called hybrid products requiring knowledge areas owned in another industry? (2) What approaches can be distinguished at the front end in order to cope with the lack of absorptive capacity? (3) How can the resource-based view (RBV) of the firm explain these?
Sample and Research Method Given the novelty of the research problem front end of innovation in converging industries, an exploratory case study design based on a mixed-method approach has been chosen. Grounded theory is used due to the paucity of prior research and in order to discover relationships from data that could be converted into hypotheses for future research (Glaser & Strauss, 1967). The emerging nutraceutical and functional food (NFF) sector serves as a basis for this study of industry convergence. The term nutraceutical describes the convergence between nutrition (food industry) and the pharmaceutical industry. Recent technological progress in life sciences has opened up new technology platforms (e.g., biotechnology, genomics) which are being applied across the traditional boundaries of the food and the
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
168
pharmaceutical industries. But it is not only technologies that are producing this effect. There is also a convergence of demand structures as consumers try to satisfy different needs in one transaction. They seek product functions like health benefits in addition to the traditional nutritive value of foodstuffs.
Data Collection and Characteristics of the Sample In order to explore the emerging NFF sector, a sampling logic using Eisenhardt’s (1989) approach of theoretical sampling has been developed. Sampling was based upon the following criteria: (1) Industry affiliation: The project must be conducted in an organization of the food or pharmaceutical/chemical industry active in the emerging NFF sector. (2) Commercialization: The project outcome must be commercialized on the emerging NFF segment either as an intermediate (B2B) or a consumer (B2C) good. (3) Accessibility: Qualitative and quantitative data must be accessible involving a semistructured questionnaire and an in-depth interview with the project owner. The unit of analysis is the particular R&D project and only one project per company has been sampled to ensure case independence. Data collection took place during autumn 2003 and was conducted in a Canadian NFF network. In total 58 members fulfilled the sampling criteria and were shortlisted, of which 54 agreed to participate in the study. This involved a personal visit to the companies’ facilities to conduct an in-depth interview and using a semi-structured questionnaire which lasted for two to four hours. The personal interview aimed at a detailed description of the case project and of the organization itself to understand how the project was linked with the organization’s specific development path. In addition, the semi-structured questionnaire fulfilled the aim of collecting data on front end decision making (e.g., most important sources of ideas and evaluation criteria). Together, this has led to a detailed qualitative and quantitative set of data per case.
Research Methodology In line with the overall aim of the paper to explore the front end in convergence and whether projects differ, data has been analysed in two sequences combined in a mixedmethod approach. Thereby the study benefits from complementarities by integrating qualita-
Volume 16
Number 2
2007
tive and quantitative data (Greene, Caracelli & Graham, 1989). Triangulation has not only been chosen for the purpose of pure exploration of emerging theoretical concepts but it also enhances internal validity of the study by comparing results of two different data sets and methods (Creswell, 1994).
Data Analysis In practical terms, triangulation was conducted as follows: first, the qualitative set of data (54 transcribed interviews, field notes and other information on the cases) was analysed with the help of the software tool MAXqda allowing for deductive (theory-derived) and inductive (emerging) codes (cf. Glaser & Strauss, 1967; Mayring, 2000). Deductive codes mainly focused on the descriptors of the projects (e.g., newness of involved technologies, market entry mode, etc.). These were derived from a literature review, building our theoretical frame. Emerging codes were attributed to individual decision making of the different organizations (e.g., influences from existing competencies). The output of this content analysis was different categories describing the cases in general and the process of front end decision making in particular. In addition, the quantitative data from the questionnaires was analysed using descriptive statistics and then compared against the qualitative data. The final output of this mixedmethod design is a set of testable hypotheses for future descriptive or causal studies. Thus, the hypotheses are an expression of emerging concepts in the new research field of the front end of innovation in converging industries.
Findings Identification of Different Project Types in Converging Industries In order to differentiate between project types to take into account project contingencies, the first goal of the analysis is to identify appropriate discriminating codes for categorizing the data (Miles & Huberman, 1994). With the help of our coding software, the code ‘route to commercialization’ with the two sub-codes B2B market and B2C market and also a project’s ‘scope of technology development’ (project uses existing technology vs. new technology development was part of the project) could be identified as appropriate discriminators. Hence, by coding the 54 projects accordingly a typology emerged from the qualitative data (see Figure 2). Group (A) comprises R&D projects which have been commercialized on the B2B market. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
B2C
II C n=6 (11%)
B n = 34 (63%)
A n = 14 (26%)
B2B
Route to Commercialization
I
III
IV
Use of existing technologies
Own technology development
Scope of Technology Development
Figure 2. Results of Categorizing the Different Projects They also include the development of new technological knowledge. These projects have been conducted by technology-driven organizations from the pharmaceutical/chemical sector. Projects in this group, for instance, focus on the development of a new ingredient (e.g., a new blood cholesterol lowering phytosterol) which traditionally is commercialized as a pharma application and now also as an ingredient for the emerging nutraceutical segment. Projects within group (B) also involve new technology development but they differ from group (A) in the chosen route to commercialization. While group (A) projects are commercialized only on B2B markets, group (B) projects are launched as finalized consumer goods on the B2C market. These projects appear most complex, as they necessitate both strong technological competencies for developing new technological knowledge as well as strong marketing competencies needed for successful commercialization on consumer markets. With regard to the emerging NFF segment, an end-consumer market, the B2C commercialization activities seem new to most of the innovating organizations in group (B). To give an example, a specialty chemicals company has developed a new whey protein. Due to a lack of access to the B2C market, the company has entered into a strategic marketing partnership with a manufacturer of sports nutrition. The evolving inter-industry segment allows B2B firms to move down the valuechain in order to commercialize consumer products (e.g., certain supplements). To cope with competence gaps that arise, these projects are conducted mainly in inter-industry © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
169
partnerships of technology-intense chemical/ pharmaceutical and marketing-skilled food companies. The third type of projects, constituting group (C), commercializes consumer products which are based on existing technologies. This group’s projects focus on the fast development of new consumer products (functional foods and supplements). The ingredient technology already existed. These projects are conducted in the low-tech but marketing-intense food industry. Innovations are based typically on an existing ingredient, such as antioxidants, which are used to fortify different foodstuffs in order to issue a claim as, for instance, ‘boosts your immune system’. Food companies, generally, do not have the competence for own ingredients development and therefore have to outsource them. These three groups allow for the assumption that even though industries converge, innovation systems do not start to blur, but remain distinct. However, a majority of 34 cases from group (B) is leaving the traditional industry-specific approach to innovation. Thus, it seems that the nature of a project is not always determined by its industry affiliation and the industry-specific resource profile: most projects in group (B) stem from technology-intense firms which traditionally commercialize their products on B2B markets. These primary observations require a more detailed analysis on the level of decision making at the front end of innovation in order to understand the influence of a firm’s industry-specific resources and competencies.
Qualitative Analysis: Major Influences in R&D Front End Decision Making The qualitative analysis of front end decision making, as displayed in extracts in Table 1, shows that the three project groups differ with respect to idea generation and idea selection. Table 1 shows the dominant codes (the coding with the highest frequency in each group) of both idea generation and selection, and gives an example of the corresponding codes. The content analysis indicates that idea generation in group (A) was based mainly on the existing technology development programme. Hence, for projects in group (A) existing R&D competencies have been dominant not only for idea generation, but also for idea selection. The companies would only start projects for the emerging NFF segments if they are in line with their overall R&D programme. In contrast, group (B), which develops technology-intense consumer goods and, thus, necessitates different sources of knowledge, does not stress existing competencies but
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
170
Table 1. Group Differences and Selected Quotes on Idea Generation and Selection Group (A) New technology development commercialized on B2B markets
Group (B) New technology development commercialized on B2C markets
Group (C) Use of existing technology commercialized on B2C markets
Idea generation (selected quotes)
‘Existing expertise is a very important driver; you try to build on the existing, since new technology development is very complex.’ ‘The idea really came from the existing research programme.’
‘External partnerships have not been important for generating the idea to build the ingredient. But after the proof of concept they have been very important for the market part of the idea in order to find the right application in the end-consumer market of supplements. Our food partner has marketing experience and knows best.’
Dominant coding (I-TECH; I-STRP; I-MK)
I-TECH: Ideas derived from existing technological expertise and history ‘We explore new areas and there I really follow my research interest. But there is a self-selection, because the interest is quite the same. Sometimes it involves further competencies we do not possess yet, but in general activities are somehow linked to technologies of previous projects.’
I-STRP: External partners involved in idea generation ‘You have to learn about the market segment during the beginning of the innovation process. Here, we had the great advantage of having an industrial partner who knew the market very well, so we could use his knowledge together in developing the product; he knew exactly what would work and what would not. But this was not a formalized process but more an exchange of ideas and knowledge in order to find the best solution.’ E-PART: Partners play an important role during evaluation
‘We want to extend our breakfast juice product line with a functional food product. The move into the health segment with juices offers a good opportunity to benefit from our existing brand.’ ‘Our partner explores ingredients which allow a claim “rich in fiber and good source of calcium” then tests them to see if they are stable in the beverage.’ I-MK: Idea derived from existing market resources and history ‘We stress the budget and the market opportunities and trends. If this looks feasible and the project fits to the market positioning and brands of the existing products we buy in the needed technological systems.’
Idea selection (selected quotes)
Dominant coding (E-TECH; E-PART; E-MK)
Volume 16
Number 2
2007
E-TECH: Fit with existing technology development projects
E-MK: Fit with existing market positioning and marketing
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
171
External Trends * Experiences in Technology Development Experiences in Marketing * Strategic Partners * Group (A) Group (B) Group (C) *
p < 0.05
1 2 (not at all important)
3
4
5 (very important)
Figure 3. Median Comparison of Different Influence Factors to Front End Decisions
relies on inter-industry partnerships. These partnerships seem to be important for idea generation as well as for idea evaluation to understand whether a certain ingredient technology will not only technically function but also meet customer needs. Front end decision making in marketing-driven group (C) was influenced by internal marketing competencies as new ideas are not only derived from existing activities (e.g., line extension) but are evaluated on the basis of ‘how does the idea fit with our existing marketing programme?’. Here, external consumer market developments (e.g., trend of healthy eating) together with the degree of internal fit with marketing competencies play a dominant role. Hence, the fit with existing marketing resources and competencies determines the project selection. This seems important, since an innovation with a functional health benefit is easier to introduce if it can benefit from existing strong brands.
Quantitative Analysis: Major Influences in R&D Front End Decision Making As described above, the qualitative analysis is complemented by a semi-structured questionnaire. Figure 3 illustrates a selection of overall criteria which influence front end decision making. While group (B) and (C) respondents rank ‘external trends’ as important, group (A) seems not to attribute much importance to this factor. At the same time ‘experience in technology development’ has been ranked as an important influence by group (A). This supports the findings of the qualitative part of this study indicating that the technology-focused group (A) is mainly internally-driven in the steps of idea generation and selection, which allows the following hypothesis: H1: The more a R&D project in converging industries focuses on technology development, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
the more dominant are existing experiences and competencies in R&D during idea generation and selection. In contrast to group (A), group (B) shows the significant influence of ‘strategic partners’ already at the front end. This further supports the qualitative analysis in proposing that very complex R&D projects, which can only be started by combining competencies from two different industries, require strategic partnerships to close competence gaps right from the front end of innovation. Hence, projects in group (B) do not overstress the fit with existing resources and competencies but leave existing trajectories to engage in hybrid innovation requiring knowledge from different industries. Therefore, we hypothesize: H2: The more a R&D project leaves the existing market and technological trajectories, the more important are inter-industry partnerships to close competence gaps during idea generation and selection. Moreover, results with respect to group (C) are in line with results of the qualitative analysis of idea generation and evaluation, as the median comparison indicates that group (C) is influenced mainly by existing marketing activities and experiences. In comparison with groups (A) and (B), the item ‘experience in marketing’ is most important for group (C). This means that R&D projects conducted in marketing-intense organizations that want to enter a segment arising from industry convergence will seek to maximize synergies with existing products. As the qualitative data has shown, the motivation to do so can be seen clearly in the intent to use existing marketing resources (e.g., brand names, distribution channels) for new products. There seems to be a self-selection of those ideas which are close to the existing marketing competencies. This leads to the following hypothesis:
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
172
H3: The greater the B2C market focus of a R&D project in converging industries, the more important are existing market experiences and competencies in idea generation and selection.
Discussion of Implications and Future Research Having identified emerging theoretical concepts from our case study research, the next step (cf. Eisenhardt’s (1989) roadmap guiding case study research) is to validate these by comparing them against the existing literature. The domain of the RBV (e.g., Penrose, 1959; Wernerfelt, 1984) helps in understanding the group differences from a theoretical point of view as follows. The hypotheses shown above relate the R&D project type to the existing expertise and competencies of an organization. This indicates that even though the R&D project is the unit of analysis, the project type seems to depend on the organizational surroundings and the history of the project context. These findings can be complemented by recent insights in project management arguing that projects ought to be linked to history and context (Shenar, 2001; Engwall, 2003). Findings also complement recent discussions about competences and their effect on organizing new product development (see Christiansen et al., 2005). Our study demonstrates that the organization of the front end as well as the overall R&D project is dependent on the competence fit an organization has with the emerging new industry sector. Hypothesis H1 states that the R&D project type is influenced by cumulative technology development expertise leading to specific competencies (i.e., group (A)). Regarding this hypothesis, the RBV literature offers various studies arguing that technology development is path-dependent (e.g., Helfat, 1994). Existing studies commonly conclude that once a certain technological path has been chosen and established by previous R&D, it facilitates subsequent technological activity in the chosen area (Helfat, 1994; Rosenberg, 1994; Vega-Redondo, 1994; Rycroft & Kash, 2002). This relates to the cumulative development of technological competencies following certain technological trajectories. Thus, comparison with the existing literature shows that group (A) can be characterized as a project type, which focuses on its existing technological competencies being employed in their traditional way. These existing cumulative competencies and experiences in certain technological fields seem to dominate this project type. Hence, group (A) engages in path-dependent innovation by a ‘stretch of existing competencies’ (Hamel &
Volume 16
Number 2
2007
Prahalad, 1993) to the opportunities which arise from industry convergence. There is no resource reconfiguration (Capron, Dussauge & Mitchell, 1998) as the existing technological competencies get extended and applied to the convergent NFF sector. This means that additional returns can be generated by offering technology platforms to the emerging NFF segment. Those platforms are traditionally developed to be offered to the chemical or pharmaceutical sectors. Thus, industry convergence regarding group (A) does not challenge any competencies. In this group the value creation system is the same and the industry players can benefit from a new application of newly developed technologies which do not require any adaptation of downstream competencies. This differs in the case of science-driven companies commercializing consumer goods (group (B)) where downstream competencies regarding marketing do not suffice. The core competence approach may explain the R&D project type of group (A). However, it does not have much explanatory power regarding group (B). Interestingly, group (B), also science-intense having strong technological competencies, does not show the same type of innovation projects. Even though some of these projects are characterized by equally specialized technology development competencies, this group manages to identify the increasing B2C market opportunities of the emerging NFF segment. It leaves its traditional path of commercializing industrial goods and strives to commercialize technology-intense consumer goods. Hence, while group (A) shows path-dependent innovations, group (B) enters in ‘path-breaking innovations’.1 As stated in Hypothesis H2, the more the project departs from existing technological and market trajectories, the more this leads to competence gaps which get filled in by collaborations. Given these findings, comparison with the literature reveals that more dynamic approaches of the RBV, such as dynamic capabilities as the ‘ability to integrate, build, and reconfigure internal and external competencies to address rapidly changing environments’ (Teece, Pisano & Shuen, 1997, p. 516), seem to explain this R&D type, while the focus 1
It is important to note that ‘path-breaking’ should not be confused with ‘breakthrough’ innovation. The term ‘path-breaking’ refers to the degree of leaving the cumulative path along which firms habitually innovate; it may be a breakthrough innovation, but does not have to be. Hence, in terms of the degree of innovativeness, a ‘path-breaking’ innovation is new to the innovating firm; it does not necessarily have to be new to the world. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
on core competencies (Prahalad & Hamel, 1990) has less relevance. As expressed in Hypothesis H3, pathdependency cannot be attributed only to technological competencies but also to marketing competencies. Similar to group (A), the R&D project type constituting group (C) seems to be determined by its cumulative competencies in B2C marketing. The findings reveal that there seems to be a distinct market-related pathdependency. However, existing studies, when referring to path-dependency, implicitly refer to technological path-dependency (cf. Dosi, 1982; David, 1985; Vega-Redondo, 1994; Helfat, 1994; Rycroft & Kash, 2002). The importance of previous technology-related activities for future ones may be easier to observe and the lock-in effect may be more obvious. But isn’t there also a market-related path-dependency? If competence building is a cumulative activity determined by the past, doesn’t it also entail path-dependencies regarding market-related competencies? This has been less distinctly addressed in the existing literature.2 In particular, the extant literature does not link existing market-related trajectories and their influence on decision making at the front end of innovation. The link can be seen in the fact that market-related trajectories, similar to technological trajectories, do have an influence on idea generation as well as on idea evaluation and selection. As previous experience with the target market has been shown to be important in group (C), it can be concluded that there is a lock-in effect of existing marketing competencies as well. This may be determined by existing relations with certain retailers, or the brand image and loyalty. Similar to group (A), group (C) projects also do not require any resource reconfiguration, as existing technologies are used. To conclude, the discussion of the different R&D project types constituting groups (A), (B) 2
For instance, in their seminal contribution on ‘core competencies’, Prahalad and Hamel (1990, p. 82) define these as ‘the collective learning in the organization, especially of how to coordinate diverse production skills and integrate multiple streams of technology’. This definition clearly stresses cumulativeness regarding technological competencies evolving in a path-dependent manner. In addition, Leonard-Barton’s (1992, p. 118) discussion on ‘core rigidities’ focuses on rigidities regarding the technical systems dimension, but does not address distinctly the problem of core (path-dependent) marketing capabilities which may also decrease a firm’s ability to adapt to environmental change. A more balanced approach can be found in Dierickx and Cool (1989, p. 1506) arguing that market-related assets like brand loyalty have to be accumulated over time. This implies that the building of marketrelated assets is path-dependent.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
173
and (C) reveals that the differences regarding technology development scope and route to commercialization can be explained only partly by differences in resources and competencies of the organizations conducting the projects. Thus, industry-specific resource accumulation (Mitchell, 1989) cannot necessarily explain the nature of projects in converging industries. Rather, the differences can be explained by the degree to which existing market or technological trajectories are followed or whether they are abandoned in order to engage in path-breaking innovation. Therefore, findings have been reflected against the approaches of dynamic capabilities. This more dynamic extension of the RBV allows understanding of the project differences. On a theoretical level, the three initial project types boil down to two different types of R&D projects in converging industries: path-depending innovation and path-breaking innovation. While the former type does not face any resource misfits and, thus, operates only in familiar territory by stretching its competencies, the latter type faces a lack of absorptive capacity owing to really entering the core of convergence. Furthermore, the theoretical abstraction of the findings entails different implications for the RBV. Path-dependent innovation seems to be possible by a stretch of core competencies (Hamel & Prahalad, 1993) to related areas of the emerging industry segment. It has to be stressed that the extent to which such a ‘stretch’ is possible is limited. This may be due to the low fungibility of specialized resources, i.e., resource adaptability (see Anand & Singh, 1997), restricting the redeployment of resources in converging industries. In contrast, innovation in a path-breaking approach offers a wide range of opportunities in converging industries. But it necessitates external knowledge. Hence, dynamic capabilities for integrating external knowledge and competencies are of highest relevance for pathbreaking innovation. Regarding further research, this study has revealed that current research on the front end of innovation can benefit by linking R&D projects to their organizational context to understand the influence of existing competencies. Furthermore, it seems promising to differentiate between technological and market path-dependency. This allows for understanding the influences of the cumulative existing experiences in market and technology which themselves determine an organization’s absorptive capacity. Future studies could use the hypotheses of this research to further investigate the interdependencies of existing competencies, absorptive capacity and front end decision making.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
174
Managerial Implications First, innovation managers need to evaluate carefully whether the industry they are operating in may be affected by trends of convergence which calls for an effective monitoring of external developments not only inside their industry but also across industry boundaries, as critical knowledge may be developed in other fields. Companies that may be affected by trends of convergence then need to identify whether convergence is of substitutive (1 + 1 = 1) or complementary (1 + 1 = 3) nature. In the case of substitutive convergence, innovation aimed at the converging areas seems to be imperative for the survival of the company since this type of convergence will lead to a phasing out of the two formerly discrete operating industries. In the case of complementary convergence, however, the company has the choice whether it wants to pursue an active role in the emerging segment or rather to concentrate on the existing ‘old’ industry. As this study of complementary convergence has illustrated, different companies take different approaches to innovation. This means that initially the innovation manager has to decide whether he just wants to ‘stretch’ existing competencies into the newly emerging segment or whether he wants to encounter innovations which are not only using the opportunities from the input side of technology convergence but also from the market side. These companies need to be aware of competence gaps which increase the more the organization leaves its existing value-chain position. Hence, the innovation manager has to be aware of competence gaps both on the technological and on the market side. It has to be stressed that it is necessary to identify the external partners needed to close these gaps even at the stage of idea generation in order to account for missing absorptive capacity. To conclude, innovation managers who are engaging in path-breaking innovation need to find a partner from the other of the two converging industries. In particular, the market-related gaps, which are often underestimated, need to get closed early so that front end decision making with regard to idea generation and selection improves, and the competence bundle gets renewed to be ready for a changing competitive environment.
Acknowledgements The authors thank the participants of the IPDMC 2005 Conference in Copenhagen, the journal editors as well as two anonymous
Volume 16
Number 2
2007
reviewers for comments and suggestions on earlier drafts of this paper.
References Anand, J. and Singh, H. (1997) Asset Redeployment, Acquisitions and Corporate Strategy in Declining Industries. Strategic Management Journal, 18, 99–118. Bierly, P. and Chakrabarti, A.K. (1999) Managing Through Industry Fusion. In Brockhoff, K. (ed.), The Dynamics of Innovation: Strategic and Managerial Implications. Springer, Berlin, pp. 7–26. Bettis, R.A. and Hitt, M.A. (1995) The New Competitive Landscape. Strategic Management Journal, 16, 7–19. Cantwell, J. and Paniccia, I. (1998) Technological Change and Vertical Integration: Analysis of International Vertical Integration in Multinational Companies. In Colombo, M.G. (ed.), The Changing Boundaries of the Firm: Explaining Evolving Interfirm Relations. Routledge, New York, pp. 158–84. Capron, L., Dussauge, P. and Mitchell, W. (1998) Resource Redeployment Following Horizontal Acquisitions in Europe and North America, 1988– 1992. Strategic Management Journal, 17, 631–61. Choi, D. and Valikangas, L. (2001) Patterns of Strategy Innovation. European Management Journal, 19, 424–9. Christiansen, J.K., Hansen, A., Varnes, C. and Mikkola, J.H. (2005) Competence Strategies in Organizing Product Development. Creativity and Innovation Management, 14, 384–92. Cohen, W.M. and Levinthal, D.A. (1990) Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 5, 128–52. Creswell, J. (1994) Research Design: Qualitative and Quantitative Approaches. Sage, Thousand Oaks, CA. David, D.A. (1985) Putting the Past into the Future of Economics. Technical Report No. 533, Institute for Mathematical Studies in the Social Sciences, Stanford University. Dierickx, I. and Cool, K. (1989) Asset Stock Accumulation and Sustainability of Competitive Advantage. Management Science, 35, 1504–11. Dosi, G. (1982) Technological Paradigms and Technological Trajectories – A Suggested Interpretation of the Determinants and Directions of Technical Change. Research Policy, 11, 147–62. Duysters, G. and Hagedoorn, J. (1997) Technological Convergence in the IT Industry: The Role of Strategic Technology Alliances and Technological Competencies. International Journal of the Economics of Business, 5, 355–68. Eisenhardt, K.M. (1989) Building Theories from Case Study Research. Academy of Management Review, 14, 532–50. Engwall, M. (2003) No Project Is an Island: Linking Projects to History and Context. Research Policy, 32, 789–808. Glaser, B.G. and Strauss, A.L. (1967) The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine, Chicago. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
INDUSTRY CONVERGENCE AND INNOVATION
Greene, J.C., Caracelli, V.J. and Graham, W.F. (1989) Toward a Conceptual Framework for MixedMethod Evaluation Designs. Educational Evaluation and Policy Analysis, 11, 255–74. Greenstein, S. and T. Khanna (1997) What Does Industry Convergence Mean? In Yoffie, D. (ed.), Competing in the Age of Digital Convergence. Harvard University Press, Boston, pp. 201–26. Hamel, G. and Prahalad, C.K. (1993) Strategy as Stretch and Leverage. Harvard Business Review, 71, 75–84. Helfat, C.E. (1994) Evolutionary Trajectories in Petroleum Firm R&D. Management Science, 40, 1720–47. Katz, M.L. (1996) Remarks on the Economic Implications of Convergence. Industrial and Corporate Change, 5, 1079–95. Leonard-Barton, D. (1992) Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development. Strategic Management Journal, 13, 111–25. Malhorta, A. and Gupta, A.K. (2001) An Investigation of Firm’s Strategic Response to Industry Convergence. Academy of Management Proceedings, Best Paper Series. Mayring, P. (2000) Qualitative Inhaltsanalyse: Grundlagen und Techniken. Deutscher Studien Verlag, Weinheim. Miles, M.B. and Huberman, M.A. (1994) Qualitative Data Analysis. Sage, Thousand Oaks, CA. Mitchell, W. (1989) Whether and When? Probability and Timing of Incumbents’ Entry into Emerging Industrial Subfields. Administrative Science Quarterly, 34, 208–30. Pennings, J.M. and Puranam, P. (2001) Market Convergence and Firm Strategy: New Directions for Theory and Research. Paper presented at the ECIS Conference, The Future of Innovation Studies. Eindhoven, 20–23 September 2001. Penrose, E.T. (1959) The Theory of the Growth of the Firm. Basil Blackwell, Oxford. Prahalad, C.K. (1998) Managing Discontinuities: The Emerging Challenges. Research Technology Management, 41, 14–22. Prahalad, C.K. and Hamel, G. (1990) The Core Competence of the Corporation. Harvard Business Review, 68, 79–91. Rockenhäuser, J. (1999) Digitale Konvergenz und Kompetenzmanagement. Deutscher UniversitätsVerlag, Wiesbaden. Rosenberg, N. (1994) Exploring the Black Box: Technology, Economics and History. Cambridge University Press, Cambridge.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
175
Rycroft, R.W. and Kash, D.E. (2002) Path Dependence in Innovation of Complex Technologies. Technology Analysis and Strategic Management, 14, 21–35. Sääksjärvi, M. (2004) Consumer Evaluations of Hybrid Innovations. Publication of the Swedish School of Economics and Business Administration No.122, Helsingfors. Shenar, A. (2001) One Size Does not Fit all Projects: Exploring Classical Contingency Domains. Management Science, 47, 394–414. Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18, 509–33. Vega-Redondo, F. (1994) Technological Change and Path Dependence: A Co-evolutionary Model of a Directed Graph. Journal of Evolutionary Economics, 4, 59–80. Wernerfelt, B. (1984) A Resource-Based View of the Firm. Strategic Management Journal, 5, 171– 80.
Stefanie Bröring (broring@uni-muenster. de) holds an MSc and a PhD in Business Administration from the University of Münster. Her graduation involved a research stay at the Department of Management of Technology at the University of Quebec in Montreal as well as a semester at the Rotterdam School of Management. She has published academic articles on the front end of innovation, industry convergence and the organization of new business development. Currently she is conducting research on path dependencies in new business development processes. Jens Leker is Professor of Business Administration in the Faculty of Chemistry and Pharmaceutical Sciences at the University of Münster. He obtained his PhD in Business Management from the University of Kiel. His institute’s interdisciplinary approach combines business management research with natural sciences in order to get a deeper understanding of R&D processes. His research interests involve innovation management, strategic management and company analysis, especially in the chemical and pharmaceutical industries.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
176
The Learning Organization as Facilitator of Complex NPD Projects Jongbae Kim and David Wilemon With rapid technological and market changes, new product development (NPD) complexity is a significant issue that organizations continually face in their development projects. The inability to recognize and/or manage complexity can cause the best-intentioned projects to fail. By creating a learning organization attuned to complexity and its management, however, companies are more likely to have the knowledge and skills essential to respond competently to the complexity frequently encountered in NPD projects. In this paper, we first define complexity in NPD and then examine organizational learning as it can assist in dealing with development complexity. Next, we report findings from an exploratory research study on organizational learning and its relationship to product development complexity. The study is based on 32 field interviews with NPD participants regarding their learning experiences in dealing with complexity; the transfer of project learning to other projects; and the factors that minimize/block the transfer of learning among projects. Based on our research, we advance several suggestions for implementing a learning organization designed specifically to capitalize on the experiences of development firms’ efforts in dealing with complexity and its consequences.
Introduction
W
e live in a time of unprecedented technological, market and environmental change (e.g., Nonaka, 1991; Iansiti, 1998; Cooper, 2000 ). Such changes are closely related to the complexity issues frequently faced in development projects. For example, technological innovations are generally complex undertakings, possessing attributes with which developers are often unfamiliar, thus they involve high degrees of learning (Robertson & Gatignon, 1986). Both internal and external forces can result in complex development projects: integration of technologies, developing and marketing multi-functional products (e.g., digital convergence), advance of new product development (NPD) practices, market forces affecting NPD (Iansiti, 1998, p. ix), accelerated product development, and communication (Griffin, 1997, p. 33). Regarding accelerated product development, for example, parallel processing, which can result in the compression of development time, requires more activities to occur in a specific period of time. However, concurrent development is more complex and thus more challenging than most sequential development approaches (Cooper, 1990).
Volume 16
Number 2
doi:10.1111/j.1467-8691.2007.00427.x
2007
Simple development projects face lesser design challenges, fewer difficulties in production, and less market uncertainty than do complex development projects (Clift & Vandenbosch, 1999). In order to deal with the challenges encountered, NPD teams need to understand and be prepared for the complexity of a proposed project. Those organizations that can accurately identify, assess and manage the complexity inherent in projects are likely to gain important competitive advantages in speed, product quality and market performance. Although NPD teams are often involved in developing complex projects, many organizations struggle to learn how to manage them successfully. The rate of learning and the ability to adapt quickly is closely related to the major performance outcomes of NPD projects. Stata (1989), for example, argues that the rate at which individuals and organizations learn may become the only sustainable competitive advantage, especially in knowledge-intensive industries. In managing complexity, organizational learning is especially important, since, as noted, there are numerous factors which cause development projects to become increasingly costly and complex. Furthermore, Chapman and © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
Hyland’s research (2004) indicates that highcomplexity firms used a greater variety of levers than low-complexity firms, and in most instances they used levers more frequently than low-complexity firms. These authors note that levers are specific actions, tools or techniques available to management in developing and consolidating relevant organizational (learning) behaviours. Examples of appropriate levers include: product family strategies; innovation process definition; and project planning and control tools. They also emphasize the necessity of high-complexity firms to continually encourage learning behaviours. Compared with other attributes inherent in a project such as risk which is likely to be influenced by external, often uncontrollable forces, the challenges encountered in dealing with complex issues are likely to be influenced by an organization’s learning ability (Kim & Wilemon, 2003a). Thus, it is important for organizations to capture, store and use their learning in dealing with complex NPD issues to increase the effectiveness and efficiency of their development programmes. Unfortunately, one of the least studied areas in NPD is how to deal with the complexities that occur in virtually all major NPD projects. The inability to manage complexity can have serious consequences for product developers. Examples include higher development costs, slower cycle times, strained customer relations and even project failure ( Smith & Reinertsen, 1992; Murmann, 1994; Meyer & Utterback, 1995; Griffin, 1997; Tatikonda & Rosenthal, 2000; Kim & Wilemon, 2003b). These consequences are exacerbated when little emphasis is placed on learning to manage complex development challenges. Through in-depth interviews with 32 NPD participants, this study explores their experiences of organizational learning in NPD projects. Based upon our research, we advance several suggestions for implementing a learning organization designed to capitalize on the experiences of development firms’ efforts in dealing with complexity and its consequences. Our purpose is to help product development participants identify and manage the complexities they face through understanding the nature of complexity in NPD and offering guidelines in creating a learning organization to manage complexity.
Defining Complexity in NPD and Examining Organizational Learning The concept of complexity has been studied in several areas, such as diffusion (e.g., Rogers & Shoemaker, 1971), purchasing and © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
177
selling tasks (e.g., Fisher, 1970; Johnston & Bonoma, 1981; Gatignon & Robertson, 1989; McQuiston, 1989), and product development projects. Several definitions of complexity in product development are summarized in Table 1. Based on prior research studies, complexity in product development is often faced when development tasks are not easy to understand or difficult to manage. As seen in Table 1, complexity is often related to project size as represented by the number of technologies, number of components, number of organizational interfaces or number of functions designed into the product (Larson & Gobeli, 1989; Murmann, 1994; Meyer & Utterback, 1995; Griffin, 1997; Novak & Eppinger, 2001). Moreover, complexity can be related to the nature of the work effort posed by a project, for example, degree of interdependency (Tushman & Nadler, 1980; Allen & Hauptman, 1987; Von Hippel, 1990; Iansiti, 1998; Tatikonda & Rosenthal, 2000), intricacy (Larson & Gobeli, 1989; Tatikonda & Rosenthal, 2000), or newness (Clift & Vandenbosch, 1999; Tatikonda & Rosenthal, 2000; Novak & Eppinger, 2001). Compared with the early definitions of complexity in product development, recent studies as seen in Table 1 are inclined to include various aspects of complexity in NPD process (e.g., Tatikonda & Rosenthal, 2000; Chapman & Hyland, 2004). In this respect, project complexity is more relevant for studying this field than product or market complexity. In this study, we broadly define complexity in product development as the difficulties and uncertainties encountered in NPD caused by various sources of complexity. We used this definition of complexity in interviewing our respondents in order to help capture and understand how our interviewees experienced complexity in their NPD assignments. It is also important to note that competition has become increasingly knowledge-based (Ruggles, 1998; Amesse & Cohendet, 2001). Continuous learning becomes crucial in achieving competitive advantage, particularly in technology-based organizations. The essence of innovation management lies in its ability to continually enhance an organization’s knowledge base to help create new products, processes and methods. In a similar vein, to effectively handle complexity inherent in projects, organizations need to enhance their organizational learning capabilities. As Meyer and Utterback (1995, p. 298) note, ‘development of novel technologies for unfamiliar markets and latent markets requires a great degree of experimentation and learning to reduce uncertainty’. Organizational learning has been described as the capacity or processes within an organi-
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
178
Table 1. Definitions of Complexity in Product Development Author(s)
Volume 16
Construct
Definitions
Larson & Gobeli (1989)
Project complexity
Murmann (1994)
Product complexity
Meyer & Utterback (1995)
Integration complexity
Griffin (1997)
Product complexity
Iansiti (1998) Von Hippel (1990) Allen & Hauptman (1987) Tushman & Nadler (1980) Clift & Vandenbosch (1999)
R&D/Innovation management complexity
Sbragia (2000)
Project complexity
Tatikonda & Rosenthal (2000)
Project complexity
Number 2
2007
Project complexity
The number of different disciplines or departments involved in the project as well as the intricacy of the design itself The number of parts in the product The number of different core technologies embodied in a product and their diversity as they affect synthesis The number of functions designed into the product High level of interdependency among domains Reengineering projects and minor modification to existing projects are classified as simple projects, whereas major modifications and projects leading to new-to-the-world products are classified as complex projects The number of functional areas involved in a project; intensity of the interaction between the different functional areas in a project; and difficulty of achieving co-operation between the functional areas involved in a project The nature, quantity, and magnitude of organizational subtasks and subtask interactions posed by the project. The key determinants of complexity are: • technology interdependence • novelty • project difficulty
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
179
Table 1. continued Author(s)
Construct
Definitions
Novak & Eppinger (2001)
Product complexity
Boer et al. (2001)
Product and market complexity
Chapman & Hyland (2004)
Product, process, technological and customer interface complexity
Three main elements are: • the number of product components to specify and produce • the extent of interactions required to manage components and their integration (parts coupling) • the degree of product novelty • High internal complexity due to size, dimension, lead-time and life expectancy of the systems developed by different partners and (sub)contractors, and the integration required • High external complexity, due to different goals of partners, which are related, amongst others, to political constraints • The number of distinct components, production steps and core technologies • The extent of interrelations and complex linkages • The difficulty in interpreting customers’ requirements
Adapted from Kim & Wilemon (2003a).
zation to maintain or improve performance based on experience (Nevis, DiBella & Gould, 1995). Learning capability can be defined as the ability of organizational members to learn individually as well as collectively. Individuals involved in NPD projects are engaged in a constant process of learning. These individuals transmit their learning to others and the cumulative knowledge acquired from projects can be embodied in the organization (Ayas, 1999). Comparing organizational learning to individual learning, Stata (1989) observes that organizational learning occurs through shared © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
insights, knowledge and mental models. As a desired end, a learning organization is one that encourages and accelerates individual, team and overall organizational learning, and assists in continuously transforming their mission and actions (Bierema, 1999). Nonaka and Takeuchi (1995) suggest several characteristics of knowledge-creating companies: expressing the inexpressible by using metaphor and analogy; disseminating knowledge by sharing an individual’s personal knowledge with others; and acquiring new knowledge in the midst of ambiguity and
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
180
redundancy. Garvin (1993) also notes that learning organizations are skilled in the following activities: systematic problem solving, experimentation with new approaches, learning from experience and past history, learning from the best practices and experiences of others, and transferring knowledge quickly and efficiently throughout the organization. As seen in these previous studies, disseminating knowledge by sharing an individual’s personal knowledge with others or transferring knowledge quickly and efficiently throughout the organization is consistently emphasized as a major characteristic of the learning organization. Recently, research in product innovation has evolved from learning in single NPD projects, to inter-project learning in NPD, to learning in the wider product innovation processes (Boer et al., 2001; Gieskes & Hyland, 2003). Thus, we include in the study the issue of transferring the benefits of learning as well as barriers to transferring learning since it is necessary to gain insights into those factors that hinder learning. There have been several studies on barriers to transferring learning (Szulanski, 1996; Gieskes & Hyland, 2003; Szulanski, Cappetta & Jensen, 2004; Szulanski & Jensen, 2004). For example, Gieskes & Hyland (2003) reported on learning barriers identified by product managers in over 70 companies. Lack of resources, unsupportive culture and poor communication (including a lack of cross-functional interactions) were found to be major factors that discourage learning behaviour. On the other hand, Szulanski, Cappetta & Jensen (2004) reported that the extent to which the perceived trustworthiness of the source contributes to the effectiveness of intra-firm knowledge transfer is moderated by the causal ambiguity of the knowledge. Specifically, as causal ambiguity increases, the effect of the perceived trustworthiness of the source on the accuracy of the transfer weakens progressively and then becomes negative. In addition, Szulanski & Jensen (2004) investigated the effect of the template (i.e., a working example) on stickiness and found that use of a template in a replication effort reduces stickiness and that replicating a composite of routines that is not combined into a single working example increases stickiness.
An Exploratory Survey Research Focus The purpose of our study is to gain first-hand knowledge of how organizational learning can result from handling complex development
Volume 16
Number 2
2007
issues and how the associated learning is or is not transferred to subsequent projects. The specific questions asked of our NPD team participants were: 1. When a complex NPD issue has been satisfactorily resolved (or when it has not been resolved), is your organization likely to learn from the experiences of dealing with a complex project issue/problem? What issues, if any, develop when dealing with a complex NPD issue? Does learning occur? If so, how? If not, why not? Examples of follow-up probes: – Give an example of an important complex project issue which was resolved satisfactorily. How was it resolved? Did learning occur? What, if anything, was done with the learning? – What approaches, if any, are used to capture learning? Who, if anyone, is responsible for capturing the learning? – Has more or less emphasis been placed on learning, its value and its use in this organization? 2. If there are benefits from learning about managing complexity, are these benefits transferred to subsequent projects? If so, how? Examples of follow-up probes: – What would be an example where learning from a project experience was transferred to other projects? – Do project team members appear aware of the potential value of learning from projects? – Is learning part of a project’s documentation in your organization? – What role do individual team members play in capturing and transferring project learning if it occurs? 3. What hampers/blocks the transfer of learning between projects? Examples of follow-up probes: – Based on your personal experiences, what are the major blocks to the transfer of learning in your organization? – How accepting and open are project teams to the learning derived from other projects? If not open, what appears to be the major reasons for the lack of openness? – Does senior management encourage intra-project learning? If so, does this encouragement facilitate the transfer of learning? While our major research questions were few in number, each of these broad questions were followed up with several probing ques© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
Development of Project ‘A’
The knowledge set derived from developing Project ‘A’
181
Development of Project ‘B’
The knowledge set derived from developing Project ‘B’
The knowledge set transferred from developing Project ‘A’
A specific learning through solving a complexity problem for ‘A’ development project
A specific learning through solving a complexity problem for ‘B’ development project
TIME
Figure 1. Relationship Between Projects from the Perspective of a Learning Organization tions as noted above. This interview process proved especially useful in understanding how our interviewees viewed and experienced complexity and how they might learn from it in their NPD assignments. Figure 1 illustrates how learning can result from developing each project and how learning from one project can impact other projects. The arrows in Figure 1 show the focus of our study. For example, the shadowed arrow is related to the first research question about occurrence of learning. On the other hand, the striped arrow indicates that projects are connected by learning which is related to the second and third research questions.
The Sample Our research results are derived from in-depth field interviews with 32 NPD participants employed by technology-based corporations located in upstate New York and Connecticut. Particular firms and individuals were chosen due to their accessibility and their willingness to participate in our study. Though our sample is not random but rather a convenience sample of respondents and firms, the criteria for selecting our sample are whether they are technology-based firms and also have active NPD programmes. In addition, even though small in number, the individuals interviewed are experienced and have been active participants in several NPD projects. The companies are involved in such businesses as electronic components for cable and broadcast applications, various HVAC products, compressors, complex casting projects, photographic base paper and various medical devices. In-depth interviews using a structured protocol were conducted by four interviewers. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
Each interviewer was thoroughly briefed on our study’s objectives and received training in field interviewing. Each of our interviewers had prior experience in NPD. All interviews were tape-recorded and transcribed. The interviews ranged in length from one hour to over two hours, and were conducted over a fourmonth period. All the responses to our questions are based on the respondent’s NPD experiences with their organization’s most important NPD projects during the preceding two years. Content analysis procedures were used to organize and analyse the results of our interviews since it transforms communication content into data that can be summarized and compared. For each question, we identified the major themes from the qualitative data and coded the data and put an ‘N’ for the number of times the theme was mentioned and a percentage of the total themes for a specific question mentioned. For the responses to most questions, we were able to categorize the major themes into 4–6 per categories or groupings by carefully combining issues/themes. Given the open-ended nature of our questions, respondent answers often fell into more than one category for a particular question. As noted, to elicit further insights about complexity in NPD, the interviewees were asked additional probing questions after the initial question was asked. About 56 per cent of respondents were from R&D and engineering while the remaining 44 per cent were from other functional areas such as marketing, quality assurance and manufacturing. Approximately half of our respondents answered the questions from the standpoint of project leaders or a functional manager directly involved in NPD, whereas the other half responded as NPD team members. About
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
182
Methods to Transfer
12.5% (4) Not Aware if Learning Occurs
Transfer of Learning
Yes – Organizational Learning Occurs
Occurrence of Learning
87.5% (28 a )
68.7% (22) The Benefits of Learning are Transferred
- Using the same individuals: 47% (7) - Documentation: 40% (6) - Meetings/Forums: 13% (2)
18.8% (6) Not Transferred 12.5% (4) Don’t Know
Barriers to Transferring Learning b - Lack of Communication: 50% (16) - Discontinuities: 34% (11) - Inadequate Documentation: 25% (8) - Time Constraints: 19% (6) - Others: 13% (4)
Figure 2. Occurrence of Learning and the Transfer of Learning Benefits (Note: a Number of Responses. b Percentages total more than 100 due to multiple responses from respondents.)
44 per cent of respondents had participated in 2–4 NPD projects over the preceding two years. However, 25 per cent had participated in more than eight projects. More than 80 per cent of respondents noted that the length of a typical NPD project was about a year or more. Finally, with regard to the type of project organization generally used for development projects, about 25 per cent and 34 per cent were matrix and dedicated teams, respectively, while 38 per cent developed their projects via a functional organizational approach.
Findings Occurrence of Learning Whether ‘learning’ occurs when dealing with complex NPD issues was our first research question, since we were interested in determining if and how learning occurs during NPD projects. ‘Occurrence of Learning’ in Figure 2 reveals that most respondents stated that learning does occur when dealing with complex NPD issues. Only 12.5 per cent indicated that they were not aware if learning occurred. When learning did not occur or when it was not used, similar mistakes were likely to be repeated in other projects as noted by two interviewees:
Volume 16
Number 2
2007
No . . . truth is often ignored on glossy management slides that claim great success . . . if problems are acknowledged, it is usually blamed on inadequate technical skills of our engineering organization even if the root cause is something else. Lessons learned from previous projects are often quickly ignored if short term, aggressive schedules or budgetary constraints are mandated. However, as seen in Figure 2, most respondents noted that they learned when dealing with complex NPD issues. As one project team member noted, ‘All the development programmes in our organization can be a learning experience’. If organizations learn something from their previous projects and apply it to future projects, then ‘repeat’ occurrences are less likely since the organization is better prepared to manage complex projects: The more complex an issue, the more difficult it is for us to resolve. With each iteration of the process, an engineer can ‘learn’ to deal with specific complexities. On an overall basis, an engineer also learns to manage these types of problems when they see them developing. While most respondents agree that learning occurs, there were clear differences whether © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
or not the learning was shared with others. Of the 28 respondents saying ‘yes,’ seven (21.9 per cent) mentioned that only individual learning occurs. They noted that while there is often learning by individuals, this does not necessarily imply group learning and that most of the learning is informal and personal, not captured in the organization’s memory. They did not think that they did a good job cross-pollinating their learning about complexity to other individuals (and projects) in the company who could use the information. As one project team member noted: ‘It takes the organization considerable time before everyone benefits from the knowledge we gain from our projects’. Of course, there are outcomes associated with individual and organizational learning efforts which benefit individuals as well as organizations (Preskill & Torres, 1999). However, organizational learning is more than the sum of learning by individual members of the organization (Stata, 1989). Individual learning is necessary but insufficient to produce organizational learning. Individual learning becomes ‘organizational learning’ when others can access and share the knowledge (McKee, 1992). To maximize learning outcomes, organizations need to develop and maintain a supportive infrastructure and culture for learning to occur throughout the organization (Preskill & Torres, 1999).
Transferring the Benefits of Learning to Future Projects While our first research question focused on the actual learning experienced while developing NPD projects, our second research question relates to transferring the learning between projects. It can be desirable when the benefits of learning can be transferred to subsequent projects thereby helping the organization manage complexities more efficiently. Many innovation scholars note that focusing on single projects is not enough to stay competitive and that success depends even more on exploiting synergy between and among projects (Wheelwright & Clark, 1992; Meyer & Utterback, 1993; Bartezzaghi, Corso & Verganti, 1997). Boer et al. (2001) noted that mastering the sharing and transfer of knowledge can become a powerful competitive weapon. Thus, if there were no effective means for transferring the benefits of learning to other projects and programmes, learning would be of limited value. The learning will be maximized when transferred to other projects and project support functions. ‘Transfer of Learning’ in Figure 2 reveals that about 69 per cent of respondents noted © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
183
that the benefits of learning about managing complexity are transferred to subsequent projects and that lessons learned are often applied to similar development programmes. Note the following comments: Solutions from yesterday’s projects are applied to tomorrow’s projects. Gating principles and parameters are used as baselines for new products with similar characteristics. This reduces the amount of iterations needed to produce a quality product. Usually problems are visible enough that project leaders will be prepared to look for similar problems on their own new projects. On the other hand, about 19 per cent of our respondents stated that learning did not occur and the same or similar mistakes were apt to be repeated on future projects. Thus, the benefits of learning from NPD are likely to be limited in these companies. Sometimes, learning is not transferred due to project characteristics that organizations pursue rather than their knowledge sharing system or culture. As one project team member noted, ‘The information learned from one project is attempted to be used in our other projects, but is difficult since each project is unique’. While many of our respondents agreed that the benefits of project learning were often transferred, the responses differed in terms of how these benefits were migrated to subsequent projects. Of the 22 respondents saying ‘the benefits of learning are transferred,’ 15 mentioned the three major modes for conveying learning as noted in ‘Methods to Transfer’ in Figure 2. About 47 per cent of respondents mentioned that learning was transferred by keeping some of the same project personnel involved in subsequent projects and by establishing a system that would help guide project personnel in migrating NPD project learning. Thus, when the same individuals are transferred to new projects they are often able to bring their experiences with them. Iansiti (1993) noted that when it comes to transcending product generation gaps, transferring knowledge efficiently and quickly is essential. But without fundamental changes to the entire R&D process, such as the use of integration teams to facilitate organizational learning, R&D is likely to be inefficient in undertaking product generation changes. Involving engineers in the integration of several product generations is necessary to allow them to transfer and use the knowledge they have gained (Iansiti, 1993). We found similar results in our research. Consider these comments from our interviewees:
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
184
Transfer of learning, if it does occur, is usually through the individual experiences of various team members and team managers. Learning is usually transferred to new projects when the same parties work on these new projects. We don’t, however, have a good system for making sure that information and learning is passed along to our newer team members. However, a respondent warned about the dependency of relying too extensively on one individual’s experiences adding, ‘We rely way too much on someone’s memory when problems crop up in manufacturing after a new product is transferred to us’. However, for knowledge which cannot be easily transferred, for example tacit knowledge, using the same individual may be the best and in some cases the only alternative. As noted, documentation was considered another useful way to transfer the benefits of learning (40 per cent) to other and future projects. Documentation is gathered during the development process for use during subsequent NPD efforts. Listed below are some typical comments from our study regarding the important role that documentation can play: Documentation of mandatory project management processes and tools in new product development processes is one thing we do here to ensure that our learning gets used. I also see team members learning from their experiences and taking it forward to the new projects they are working on. Meetings are another method for conveying prior project learning to other projects/people (about 13 per cent). A project leader made this comment: I think that a vehicle that helps our project team are the meetings we have the first Thursday of every month where people volunteer to share their experiences or some technical know-how that they have experienced on other projects. So, we provide a forum where you can share experiences and there’s a Lotus Notes Database, I think it’s called Tool Box or Tool Kit, which contains everyone’s presentations with a table of contents. They set them up initially for people who are leading project teams. There’s a lot of good information there. People sign up to give their ideas and we keep all that information and learning in the Lotus Notes Database. To sum up, organizations can benefit from the learning associated with dealing with com-
Volume 16
Number 2
2007
plexity problems for specific development projects as well as build a transfer system to benefit and learn from their previous experiences. As one project team member noted: ‘The experience plus the context of that experience fundamentally determines the benefits derived from project learning’. Regarding the transfer of learning, Boer et al. (2001) proposed a model to describe and explain how companies can gain a substantive competitive advantage by extending their innovation efforts to other phases of the product life cycle and by facilitating knowledge transfer and learning both within the company and with other partner organizations. In their model, product and process complexity is a contingency factor influencing the choice of levers that fosters behaviours underpinning continuous innovation and learning within product innovation.
Barriers to Transferring Learning In the previous section, about 69 per cent of respondents agreed that the benefits of learning were transferred to subsequent projects. However, this does not necessarily imply that their learning transfer process was without flaws. Therefore, we further explored what hampers/blocks the transfer of learning from one project to the next (‘Barriers to Transferring Learning’ in Figure 2). First, half of the respondents noted that a lack of communication, both written and oral often blocked the transfer of learning. As one project team member noted: ‘Without good communication about what’s happened in the past you can’t learn from it’. Some of the major reasons for lack of effective communication can be grouped as follows: 1) the characteristics of the information transferred; and 2) the attitudes of the ‘information owners’ and ‘information receivers’. Regarding the characteristics of NPD information, it can be highly complex, arcane or tacit, making it difficult to transfer. As one project team member noted: ‘Lessons learned are hard to transport to someone else. You almost have to live them (the lessons learned) to understand them. You have to feel the pain’. Another interviewee stated: ‘If we don’t cross fertilize and get the opportunity to work with the different team members, I don’t think that the real learning comes to life’. Explicit knowledge is formal and systematic and thus usually easier to communicate and share. On the other hand, tacit knowledge is highly personal and deeply rooted in action and in an individual’s commitment to a specific context and thus is not so easily expressible and more difficult to formalize (Nonaka, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
1991). Using the notions of tacit knowledge and distributed cognition as a basis, Madhavan and Grover (1998) proposed a model that links team members’ and leaders’ cognitive attributes and the team’s process attributes to the efficiency and effectiveness with which potential knowledge, residing within a team, is realized in a new product. There are other reasons why learning is difficult to transfer. Many of our respondents noted that dealing with the personal relationships within their teams and with other support groups was more challenging than the technological challenges. In some cases, there is simply a reluctance to share information with other individuals and groups in the development process. This reluctance may be caused by not willing to give up ‘secrets’ to another group, jealousy, interpersonal conflicts or simply wanting to be the ‘star’ and solve a high visibility problem for the recognition which may follow. In other cases, there can simply be a reluctance to adopt information or knowledge originating from others. Some comments from our study give examples of the range of issues regarding why people are reluctant to share information during development projects: The most noticeable thing is the natural tendency to revert back to ‘the way we have always done things’, even when confronted with the success achieved on previous projects using new methods. Because we are all in different groups, we are isolated. We call them silos, so one silo might learn something but not transfer its learning to another silo. But, our group is different because we deal with all the groups so we try to learn from each of them and try to break down the silo structures. Dedicated teams are great, but when people spend too much time on just one type of project, like we have right now on the XYZ project. They know a heck of a lot about XYZ products, but they don’t know much about ABC products. If we don’t crossfertilize and get the opportunity to work with different teams we lose something. Second, about 34 per cent of our respondents noted that organizational discontinuities, disruptions or a lack of coordination between development teams can block the transfer of learning. The high workload associated with new projects, sometimes coupled with ineffective vehicles for transfer, may block or dampen key lessons learned. Consider these comments from our interviews: I am the one that knows things in detail so I can transfer that knowledge or try to get © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
185
some of the previous team members to help transfer that knowledge to a new team. So although cross-using resources is a good idea, I advocate keeping people on common projects if you can. I think around here we respect our SBUs and make sure that we try to keep as many core team members together as feasible. However, if there is a real need for someone in some other SBU then we release that person. There is never enough sharing of knowledge, however, between our SBUs due to the lack of resources, people and time. Changing personnel and responsibilities constantly depletes the pool of experienced team members . . . despite our claims in the project plan that project follow-ups will be used to capture the learning, it never really happens here. Third, about 25 per cent of respondents stated inadequate documentation of learning was an important blocking factor. Without good documentation, it is difficult to go back and really learn what went wrong and why it happened. Learning may occur, but if it is not documented in a way that allows an organization to use this learning, then it will probably lose its usefulness in facilitating other projects. However, many organizations lack written procedures and have no useable system to record and recall their past challenges, problems and learning. Adequate documentation or written procedures that help define what was learned from the last project is often absent in our projects. In our gate system there is a section where you are supposed to write down what you’ve learned so that you’ll avoid these mistakes and use the learning. But, no one ever looks at those things again. They just get filed and we seem to make the same mistakes over and over. We’ve learned that we should put an iteration cycle into the project schedule to allow for corrections. But when someone wants to include this iteration and review cycle, someone will then say ‘No, the project has to be done by this date, otherwise it is not cost effective blah, blah, blah’. And so they will leave it out and we will experience the same problems again. Fourth, budget and schedule constraints (about 19 per cent) can be blocking factors since they may cause the lack of a sufficient, thorough review process. Thus, NPD team participants are often too busy to keep records and to communicate their learning, thus insufficient reviews/post-mortems occur within a time frame in which products have to be ready.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
186
There is not a lot of communication during the execution stage of our projects. In order to meet product launch dates in as short a time frame as possible, people get very focused on achieving those goals and there is not a lot of time or incentive to have crosslearning between groups. So, people really don’t take the time or don’t see the need to capture our learning. Basically at Gate Six or Gate Seven in our product development process we document what we learned about our project to help us next time. All that information is written and stored in a database but I’ve never known anybody to look at it again. Finally, geographical and cultural distances (about 13 per cent) were important barriers to learning as noted by the comments from the two team members below: Transfer of our learning across the globe to our sister facility is inhibited by language barriers and by the few opportunities to meet with them. Remember when your team is working with several different cultures in Asia and in Europe, each has its own way of working, so capturing the learning that occurs is very difficult. We are working on this challenge. In order to foster the transfer of learning and to minimize (or eliminate) barriers to learning transfers, we need to understand what is happening with the learning process and to develop better approaches for transferring learning. Boer et al. (2001) proposed a methodology, based on a behavioural model, to help companies facilitate knowledge transfer and foster learning in the process of continuous product innovation. Their model explains relationships between learning behaviours and outcomes, capacities enabling these behaviours, levers that managers can use to change existing or promote new behaviours, and contingencies affecting this set of relationships. For example, a joint diagnosis with a company’s managers outlined how weaknesses in one group’s behaviour were responsible for rework and design changes during the production phase and other problems that were not sufficiently considered by the R&D department. Our findings can be useful in understanding how organizational learning relates to managing complexity in NPD projects. We suggest the following relationships summarized in Figure 2. Several implications can be derived from these findings and can be used in creating a learning organization.
Volume 16
Number 2
2007
Suggestions for Implementing a Learning Organization Among the major benefits of continuous learning for innovative organizations are: gaining higher performance from development projects; selecting development projects which fit the firm’s strategies and capabilities; learning from the similar complexity experiences (capturing, storing and comparing learning systematically); and retrieving learning for future projects. Based on our findings, NPD teams need to learn from their experiences about managing complexity in development projects and they need to share learning with other team members as well as with subsequent project teams. They also need to develop better approaches for transferring learning as well as minimizing or eliminating the barriers to learning transfers. Based on our findings, we advance several suggestions for implementing an effective learning organization.
(a) Require Communication and Co-operation Misunderstandings can develop since the degree of project complexity may not be fully understood due to poor communication and a lack of understanding. Thus, effective communication and co-operation are critical in minimizing these undesirable outcomes. However, as seen in Figure 2, lack of communication is a major barrier to transferring project learning. It is also a barrier from individual learning to team or organizational learning. Thus, effective communication and co-operation are required to manage complexity inherent in a project. Gieskes and Hyland (2003, p. 867) noted the following: In increasingly complex product innovation processes the key to learning and encouraging and supporting learning behaviors is communication. Knowledge needs to be spread throughout the organization, what works and (importantly) what does not work must be shared; better to make a mistake once than repeat it endlessly. However, complexity can create significant challenges regarding the co-operation and communication between functional groups, which can affect the efficiency and effectiveness of NPD processes and performance. The increase in the number of technologies, functions or components in a development project leads to more individuals and functional groups being involved, which can result in a proliferation in the number of people and processes. This can lead to lengthy interactions © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
with various groups in a development project (see, e.g., Levinson, 1981). Human cognitive capabilities can limit our ability to understand what occurs in complex organizations (Stata, 1989). Organizational structures, geographical distances and cultural norms are other factors that can contribute to communication and co-operation difficulties. In industrial purchasing situations, complexity of the purchase process is positively related to the number of participants involved as well as the frequency of conflict between them (Kirsch & Kutschker, 1982). Thus, complexity can place considerable strain on those responsible for developing and marketing new products. In addition, since gaining support for a new product can be influenced by its complexity, it is important to consider internal users’ perceptions, needs and capabilities. In studying the diffusion of innovations, Rogers (1995) notes that innovations that are perceived as being more complex will be adopted less rapidly than other innovations. To sum up, co-operation and communication are needed to understand and manage the degree of project complexity and are also needed for the transfer of learning. However, complexity inherent in a project is likely to create communication and co-operation difficulties.
(b) Construct a System to Share Individual and Team ‘Learning’ When ‘learning’ is shared within a team or with other project teams, such learning can be the basis for organizational learning. However, individual learning may not be easily shared with others for several previously noted reasons. Rewards and recognition can also encourage the information sharing process. Applying new IT systems/processes or creating a documentation system or forming/ creating new organizational structures can also foster the sharing of learning (see also Figure 2). Furthermore, our sample profile reveals that about 44 per cent of our respondents had participated in 2–4 NPD projects during the preceding two years, but 25 per cent had participated in more than eight. Learning may increase with the number of projects people are able to participate in, which can facilitate project efficiency and effectiveness. However, pressures from participating in several projects can foster the transfer of learning as well as hamper learning transfers. For example, if a key team member is burdened by multiple project responsibilities, transferring of learning from one project to another may become a low priority for that team member. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
187
(c) Identify those Factors that Influence and Shape the Capture and Transfer of NPD Team Learning To effectively handle complexity, organizations need to understand both the development process in which complexity issues occur and the process by which learning is captured, stored and retrieved (Kim & Wilemon, 2004). Based upon the understanding of both systems, we can then develop an effective learning system which can facilitate development projects. Figure 3 depicts our framework. This model can be helpful to a company to understand how organizational learning can be captured and used during its NPD processes. Steps 1 to 3 depict how specific learning about complex issues can occur in NPD. On the other hand, Steps 4 to 6 show how the learning which does occur is captured, stored and retrieved. Step 1: Encountering and identifying complex development issues: The potential for learning is triggered when an NPD team encounters a complex issue/problem. The frequency and contents of complexity issues experienced during development projects are likely to be influenced by such factors as the NPD phase, the type of new product, the people/groups responsible for a specific development task, and the experience of the personnel involved. Step 2: Seeking methods to solve the identified complexity issue: When faced with a complex issue, an NPD team needs to refer first to the existing knowledge assets of the team and the organization’s ‘learning database’ depicted in Figure 3. It is an important role of the most knowledgeable individuals to determine if the complexity issue is new and unfamiliar to the organization or the industry and if there are prior experiences (learning) in dealing with the identified issue. The degree/ intensity of searching for solutions to complexity issues is likely to be influenced by such factors as available time, people in charge, a project’s priority, and the competencies/ experiences of those engaged in searching for solutions. Step 3: Solving the identified complexity issue: This step involves applying an appropriate method to the identified complexity issue. The outcomes are likely to be influenced by these factors: • application of the ‘right’ methodology and organizational approach (e.g., Griffin, 1997; Clift & Vandenbosch, 1999) • assignment of priority, resources and organizational attention to the complexity issue • persistent, focused effort until the complexity issue is resolved.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
188
Key factors
Development of Project ‘A’ Step 1: Encountering and identifying a complex development issue
Step 2: Seeking methods to solve the identified complexity issue
-
Phase of NPD Type of new product Sources of complexity People in charge
-
Ability of internal/external search efforts Available time People responsible Competence
-
Step 3: Solving the complexity issue and evaluating the results
-
Matching the method with the project Competencies Effort expended Priority
Outcomes of Project ‘A’
Development Process Interrelated
Learning Process Organizational Learning System & Assets Steps 4 and 5: Capturing the learning and storing the learning
Learning Database (Knowledge Asset)
Step 6: Retrieving learning for future projects
Figure 3. Learning from Development Projects: A Process Model
Steps 4 and 5: Capturing and storing the learning, and Step 6 Retrieving learning for future projects: Organizational learning includes the development of insights, associations and conclusions about the effectiveness of past activities and behaviours and their potential influence on future actions (Fiol & Lyles, 1985). By managing the complexities in developing a new product, a development team has the potential to learn. However, without capturing, storing and retrieving learning (from a learning database) for future projects, any learning produced is likely to have limited value. As for the learning system des-
Volume 16
Number 2
2007
cribed in Figure 3, there are several learning subsystems, such as ‘knowledge creating/capturing systems,’ ‘knowledge accumulating/storing systems,’ and ‘knowledge transferring systems’. Thus, when all these subsystems perform well, organizational learning is likely to be maximized. It is important to note that Steps 4 and 5 do not always occur after Steps 1–3. Steps 4 and 5 are also likely to occur at the same time as the issues noted in Steps 1–3 occur since the development process and the learning process can be experienced simultaneously. This is desirable when both systems are highly interrelated. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
Suggestions for Future Research Complexity increases the information processing required within an organization. Organizations are clearly in a position to make more effective decisions on complex issues when they have access to quality information. What learning is acquired can affect NPD outcomes more than the ‘quantity of learning’ obtained. Furthermore, the more projects that are developed, the greater is the potential for useful learning accumulation. Moreover, the more challenging the projects undertaken, the more valuable the learning is likely to be, particularly if similar projects are developed in the future. Several questions warrant additional research: • What types of organizational designs and mechanisms are most conducive to transferring NPD learning? • Are the current efforts to identify, accumulate and use learning useful? • What cultural factors facilitate NPD teams and organizations to share and use information? • What kinds of information need to be shared/transferred among functional groups to achieve high NPD performance? • When are the best times in a project’s life to share information? • What impact does the length of the technology development cycle have on successfully capturing and transferring learning? Some of the above questions have been addressed by other academic researchers (e.g., Szulanski, 1996; Gieskes & Hyland, 2003), yet more needs to be done in order to expand our knowledge of this important area. Such research has the potential to dramatically increase the proficiency of NPD programmes.
Conclusions Our research focuses on how NPD teams learn from dealing with various sources of complexity during the development process. We found that most of our study participants did believe that learning occurred when they dealt with complex issues during the development process. However, there were important differences among the participants whether learning was shared with other individuals and other teams. Similarly, many of our interviewees indicated that their company’s methods for cross-pollinating project learning were often non-existent or not effective. The most important vehicles for transferring learning were individual team members and project documentation. We also found that the most impor© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
189
tant barriers for transferring learning were lack of documentation, discontinuities and poor documentation. Finally, we proposed several suggestions for developing and implementing an organizational learning system to facilitate the effective management of complexity. Our research helps extend the small yet growing body of knowledge on organizational learning, NPD complexity and how these concepts are interrelated. In particular, our work supports the earlier work of Meyers and Wilemon which focused on how teams managing complex projects learn, how learning is transferred, and what factors tend to block learning (Meyers & Wilemon, 1989). Our work also supports Boer’s work which helps explain how companies can facilitate learning and knowledge transfer via various vehicles both within organizations and with external organizations, such as partners and alliances (Boer et al., 2001). Our research further complements the important research of Gieskes and Hyland on barriers which can retard learning in product development groups. Gieskes and Hyland (2003) found that learning is often blocked by the defensive routines of those involved in NPD, the lack of resources which can affect information availability, and a lack of personal responsibility for learning.
Acknowledgements The authors appreciate the support of the Earl V. Snyder Innovation Management Research Center, Whitman School of Management, Syracuse University, Syracuse, New York for its support of our programme on Complexity in Product Development Projects.
References Allen, T.J. and Hauptman, O. (1987) The Influence of Communication Technologies on Organizational Structure. Communication Research, 14, 575–8. Amesse, F. and Cohendet, P. (2001) Technology Transfer Revisited from the Perspective of the Knowledge-Based Economy. Research Policy, 30, 1459–78. Ayas, K. (1999), Project Design for Learning and Innovation: Lessons Learned from Action Research in an Aircraft Manufacturing Company. In Easterby-Smith, M., Burgoyne, J. and Araujo, L. (eds.), Organizational Learning and the Learning Organization. Sage Publications, London, pp. 176–93. Bartezzaghi, E., Corso, M. and Verganti, R. (1997) Continuous Improvement and Inter-project Learning in New Product Development. International Journal of Technology Management, 14, 116–38. Bierema, L.L. (1999) The Process of the Learning Organization: Making Sense of Change. NASSP Bulletin, February, 46–56.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
190
Boer, H., Caffyn, S., Corso, M., Coughlan, P., Gieskes, J., Magnusson, M., Pavesi, S. and Ronchi, S. (2001) Knowledge and Continuous Innovation: The CIMA Methodology. International Journal of Operations and Production Management, 21, 490– 503. Chapman, R. and Hyland, P. (2004) Complexity and Learning Behaviors in Product Innovation. Technovation, 24, 553–61. Clift, T.B. and Vandenbosch, M.B. (1999) Project Complexity and Efforts to Reduce Product Development Cycle Time. Journal of Business Research, 45, 187–98. Cooper, R.G. (1990) Stage-Gate Systems: A New Tool for Managing New Products. Business Horizons, 33, 44–54. Cooper, R.G. (2000) Strategic Marketing Planning for Radically New Products. Journal of Marketing, 64, 1–16. Fiol, C.M. and Lyles, M.A. (1985) Organizational Learning. Academy of Management Review, 10, 803–13. Fisher, L. (1970) Industrial Marketing: An Analytical Approach to Planning and Execution. Brandon/ Systems Press, Inc. Garvin, D.A. (1993) Building a Learning Organization. Harvard Business Review, 71, 78–91. Gatignon, H. and Robertson, T.S. (1989) Technology Diffusion: An Empirical Test of Competitive Effects. Journal of Marketing, 53, 35–49. Gieskes, J.F.B. and Hyland, P.W. (2003) Learning Barriers in Continuous Product Innovation. International Journal of Technology Management, 26, 857–70. Griffin, A. (1997) The Effect of Project and Process Characteristics on Product Development Cycle Time. Journal of Marketing Research, 34, 24–35. Iansiti, M. (1993) Real-World R&D: Jumping the Product Generation Gap. Harvard Business Review, 71, 138–47. Iansiti, M. (1998) Technology Integration: Making Critical Choices in a Dynamic World. Harvard Business School Press, Boston, MA. Johnston, W.J. and Bonoma, T.V. (1981) The Buying Center: Structure and Interaction Patterns. Journal of Marketing, 45, 143–56. Kim, J. and Wilemon, D. (2003a) Sources and Assessment of Complexity in NPD Projects. R&D Management, 33, 15–30. Kim, J. and Wilemon, D. (2003b) An Exploratory Study of Complexity in New Product Development Management. Proceedings of the 12th International Conference on Management of Technology, Nancy, France. Kim, J. and Wilemon, D. (2004) Complexity as a Factor in NPD Projects: Implications for Organizational Learning. In Khalil, T., Lefebvre, L. and Mason, R. (eds.), Internet Economy: Opportunities and Challenges for Developed and Developing Regions of the World. Elsevier Science Ltd., Amsterdam, pp. 281–99. Kirsch, W. and Kutschker, M. (1982) Marketing and Buying Decisions in Industrial Markets. In Irle, M. (ed.), Studies in DecisionMaking. Walter de Gruyter, New York, pp. 443– 88.
Volume 16
Number 2
2007
Larson, E.W. and Gobeli, D.H. (1989) Significance of Project Management Structure on Development Success. IEEE Transactions on Engineering Management, 36, 119–25. Levinson, H. (1981) When Executives Burn Out. Harvard Business Review, 59, 73–81. Madhavan, R. and Grover, R. (1998) From Embedded Knowledge to Embodied Knowledge: New Product Development as Knowledge Management. Journal of Marketing, 62, 1–12. McKee, D. (1992) An Organizational Learning Approach to Product Innovation. Journal of Product Innovation Management, 9, 232–45. McQuiston, D.H. (1989) Novelty, Complexity, and Importance as Causal Determinants of Industrial Buyer Behavior. Journal of Marketing, 53, 66–79. Meyer, M.H. and Utterback, J.M. (1993) The Product Family and the Dynamics of Core Capability. Sloan Management Review, 34, 29–47. Meyer, M.H. and Utterback, J.M. (1995) Product Development Cycle Time and Commercial Success. IEEE Transactions on Engineering Management, 42, 297–304. Meyers, P. and Wilemon, D. (1989) Learning in New Technology Development Teams. Journal of Product Innovation Management, 6, 79–88. Murmann, P.A. (1994) Expected Development Time Reductions in the German Mechanical Engineering Industry. Journal of Product Innovation Management, 11, 236–52. Nevis, E.C., DiBella, A.J. and Gould, J.M. (1995) Understanding Organizations as Learning Systems. Sloan Management Review, 36, 73–85. Nonaka, I. (1991) The Knowledge-Creating Company. Harvard Business Review, 69, 96–104. Nonaka, I. and Takeuchi, H. (1995) The KnowledgeCreating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, New York. Novak, S. and Eppinger, S.D. (2001) Sourcing by Design: Product Complexity and the Supply Chain. Management Science, 47, 189–204. Preskill, H. and Torres, R.T. (1999) The Role of Evaluative Enquiry in Creative Learning Organizations. In Easterby-Smith, M., Burgoyne, J. and Araujo, L. (eds.), Organizational Learning and the Learning Organization. Sage Publications, London, pp. 92–114. Robertson, T.S. and Gatignon, H. (1986) Competitive Effects on Technology Diffusion. Journal of Marketing, 50, 1–12. Rogers, E.M. (1995) Diffusion of Innovations, 4th edn. Free Press, New York. Rogers, E.M. and Shoemaker, F.F. (1971) Communication of Innovations: A Cross-Cultural Approach. Free Press, New York. Ruggles, R. (1998) The State of the Notion: Knowledge Management in Practice. California Management Review, 40, 80–9. Sbragia, R. (2000) The Interface between Project Managers and Functional Managers in Matrix Organized Product Development Projects. Proceedings of the 9th International Conference on Management of Technology, Miami, Florida. Smith, P.G. and Reinertsen, D.G. (1992) Shortening the Product Development Cycle. Research and Technology Management, 35, 44–9. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing
THE LEARNING ORGANIZATION AS FACILITATOR OF NPD PROJECTS
Stata, R. (1989) Organizational Learning – The Key to Management Innovation. Sloan Management Review, 30, 63–74. Szulanski, G. (1996) Exploring Internal Stickiness: Impediments to the Transfer of Best Practice within the Firm. Strategic Management Journal, 17, 27–43. Szulanski, G. and Jensen, R.J. (2004) Overcoming Stickiness: An Empirical Investigation of the Role of the Template in the Replication of Organizational Routines. Managerial and Decision Economics, 25, 347–63. Szulanski, G., Cappetta, R. and Jensen, R.J. (2004) When and How Trustworthiness Matters: Knowledge Transfer and the Moderating Effect of Causal Ambiguity. Organization Science, 15, 600– 13. Tatikonda, M.V. and Rosenthal, S.R. (2000) Technology Novelty, Project Complexity, and Product Development Project Execution Success: A Deeper Look at Task Uncertainty in Product Innovation. IEEE Transactions on Engineering Management, 47, 74–87. Tushman, M.L. and Nadler, D. (1980) Communication and Technical Roles in R&D Laboratories: An Information Processing Approach. Management Science, 26, 91–112. Von Hippel, E. (1990) Task Partitioning: An Innovation Process Variable. Research Policy, 19, 407–18. Wheelwright, S.C. and Clark, K.B. (1992) Creating Plan to Focus Product Development. Harvard Business Review, 70, 70–92.
© 2007 The Authors Journal compilation © 2007 Blackwell Publishing
191
Dr Jongbae Kim (
[email protected]) is Professor of Marketing at the School of Management at Dankook University, Korea. His teaching focuses on marketing management, marketing research, new product management, and management of creativity and innovation. He has contributed articles to many scholarly publications such as R&D Management, European Journal of Innovation Management, International Journal of Technology and Marketing, International Journal of Revenue Management, and Creativity and Innovation Management. Dr David Wilemon (
[email protected]. edu) is the Snyder Professor of Innovation Management in the Whitman School of Management at Syracuse University, USA. He is an active researcher in the areas of corporate ventures, product development, project management and high-performing teamwork. His research appears in the Academy of Management Journal, Journal of Marketing, California Management Review, Sloan Management Review, Columbia Journal of World Business, Transactions on Engineering Management, Journal of Product Innovation Management, Technology & Engineering Management, Creativity and Innovation Management, and R&D Management.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
192
Open Innovation – The Dutch Treat: Challenges in Thinking in Business Models Han van der Meer This article covers the subject of the practical application of the principles of open innovation in Dutch industry. Open innovation is considered to be the third stage in evolving systems for innovation management. The results of the study showed that innovative Dutch companies have successfully adopted the principles of open innovation regarding open innovation culture and importing mechanisms. Some challenges are found in the use of exporting mechanisms; but the biggest challenges for innovative Dutch companies lie in the flexible and open way of handling their business models.
Introduction
M
anagement of innovation is in essence the process of bringing monetary value to technological knowledge and creativity, and in recent years a particular model of doing so has been popularized: open innovation. The essence of open innovation lies in several key elements. One is the notion that it takes a lot of effort to bring monetary value to technological knowledge, because the knowledge itself has little value in itself. A second is that innovation seems to pay better if a company’s own knowledge is combined with that of others. Yet the reality of open innovation seems to be that it is easier said than done. Over 80 per cent of all patents generated by Dutch universities are left unused (Dekker & van der Meer, 2005). And even when knowledge is commercialized, its actual applications are often quite different from those originally envisioned by its inventors. Peters and Waterman demonstrated this effect in their 1982 book, and more recent studies (Tidd, Bessant & Pavitt, 2001; Stefik & Stefik, 2004) do not lead to any different conclusions. And it is not just open innovation practice that is lagging behind its promises. Looking at outcomes of international benchmark studies (Lucking, 2004), Dutch companies as a whole innovate considerable less than those in other countries. These studies show that the pace of innovation in Holland is slower in terms of
Volume 16
Number 2
doi:10.1111/j.1467-8691.2007.00433.x
2007
measured outcomes, such as new products, new business ventures and fast growing technology-based firms, than elsewhere in the world. This raises some questions: why does innovation in Dutch companies lag behind, and to what extent does open innovation play a role? This article presents the first set of results of a survey on open innovation practices in Dutch companies. The survey consisted of a written questionnaire (n = 814) followed by in-depth interviewing within 28 highly innovative companies. Before presenting these results we will first deal with the theoretical background on how to innovate and the origins of open innovation, the understanding of which is important to the interpretation of the survey.
Defining Innovation To be unambiguous about our interpretation of innovation, we have chosen the following out of the several hundreds of different definitions of innovation in the literature: Innovation is the total set of activities leading to the introduction of something new, resulting in strengthening the defendable competitive advantage of a company. (van der Meer, 1996) This broad definition includes all types of innovation, such as new products, new © 2007 The Author Journal compilation © 2007 Blackwell Publishing
OPEN INNOVATION – THE DUTCH TREAT
193
Table 1. Several Factors Important to an Innovative Climate Negative short kept out punished formal kept out analyses means closed autocratic internal vague
Factor ← ← ← ← ← ← ← ← ← ← ←
horizon maverick failures communication uncertainty planning planning external co-operation decision-making orientation strategy
markets, new technologies and new organizational forms, ‘new’ meaning new to a particular company.
Positive → → → → → → → → → → →
long accepted tolerated informal accepted action opportunities open participative customer clear
nothing more to innovation than an innovative climate. However, there are also advocates for the structural approach.
Structural Approach
Approaching Innovation Much evidence can be found indicating that innovation is a fruitful way for firms to live long lives and prosper (Collins & Porras, 1994; Christensen, 1997; De Geus, 1997; Cobbenhagen, 2000; Tidd, Bessant & Pavitt, 2001). Therefore, the question is not why to innovate, but how to innovate. In answer to this question, there are basically two ways to stimulate innovation in a company (Arthur D. Little Inc., 1985; van der Meer, 1996): 1. Culturally: creation of an innovative climate. 2. Structurally: systematic use of innovation mechanisms. We will now provide a short overview of these two approaches. By discussing how management should pursue these approaches to enable innovation within a company, several paradoxes and ways of coping with these paradoxes will become apparent.
Cultural Approach The cultural approach towards enabling innovation entails creating an innovative climate. An innovative climate is the set of attitudes and values that are favourable to innovation (Ekvall, 1996; Isaksen & Tidd, 2006). Several factors important to an innovative climate are summarized in Table 1. While cultural factors are clearly important in enabling innovation (Kanter, 1983), some authors would have us believe that there is © 2007 The Author Journal compilation © 2007 Blackwell Publishing
The structural approach towards enabling innovation concerns the organized use of enabling innovation mechanisms. Innovation mechanisms are organizational entities designed to promote the development and management of new ideas, projects and business (Arthur D. Little Inc., 1985). Well known examples of innovation mechanisms include champions, task forces, venture teams, skunk works, spin-offs, enabling acquisitions, spinins, venture capital, licensing, innovative budgets, partnering, listening posts, among many more (van der Meer, 1996). After this short introduction to the cultural and structural approaches to enabling innovation, we will now discuss how management should handle them.
Three Stages, Three Tasks for Management To discuss which approach management should use to enable innovation, we suggest breaking the innovation process down into three basic stages: 1. The concept stage in which new ideas are found; the stage of ‘invention’ and free creativity. 2. The development stage in which ideas are transformed into projects. 3. The business stage in which projects are turned into new business. As it turns out, the task for management to enable innovation is different in each stage.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
194
CONCEPT
strategy
means
stimulation search process
CLIMATE
BUSINESS
DEVELOPMENT
planning
competences projects
MECHANISMS
action control
ORGANIZATION
Figure 1. The Three Stages in the Innovation Process
Figure 1 shows the three stages in the innovation process and which management task suits them. As shown in Figure 1, the task of management during the three different stages in the innovation process can be described follows (van der Meer, 1996): • In the concept stage, the task of management is to create a climate favourable to innovation through the use of the cultural approach. • In the development stage, management should establish the correct enabling mechanism to nurture the projects. • In the business stage, management should follow a classical approach: planning, action and control. From this list it becomes apparent that managing innovation really is managing paradoxes. The complete innovation process requires all three tasks of management, even when these tasks will be in mutual conflict. For example, even when a decent amount of accepted uncertainty may be beneficial to an innovative climate, it surely is incompatible with the planning required during the business stage or with any partnering mechanisms during the development stage. The ways in which management has seemed to cope with these paradoxes show us evolving systems within companies, which finally lead to the open innovation model that is central to this article.
Evolving Systems for Innovation Management Looking at the normal evolution of innovation systems in companies, we found the following stages: Stage 1: natural innovation Stage 2: systematic innovation with a closed system
Volume 16
Number 2
2007
Stage 3: systematic innovation with an open system. A modern innovation approach combines a good innovation climate (stage 1) with a stagegate methodology (stage 2) in an open system approach (stage 3) (Chesbrough, 2003). We will now discuss these three stages in further detail.
Stage 1: Natural Innovation In the natural innovation stage, innovation in a company flows naturally and ideas are generated in a climate favourable to innovation. A clear and shared vision of a company’s strategic position is of special importance to this stage, so that innovation contributes to a company’s business (Parker, 1990; Nanus, 1992). The major way to develop during the natural innovation stage is by dynamic champions on each project, and it has been shown that a top manager is often the champion of several innovation projects (Howell & Boies, 2004). Combined with the fact that it is the management’s responsibility to develop and embed a clear strategic vision, it becomes clear that top management plays a dominant role in the natural innovation stage. The natural innovation stage can be very fruitful, but is limited in the way innovation can be controlled. Most innovation starts and finishes with top management and when the company grows we see a need for a more structural approach. It can then be concluded that the extent of this stage is limited by the size and complexity of a company.
Stage 2: Systematic Innovation with a Closed System In the second stage, control over the innovation system is found by installing a more formal innovation pipeline, also named a funnel. Here we find elements of what Saren (1984) describes as activity- and decision-based inno© 2007 The Author Journal compilation © 2007 Blackwell Publishing
concept
195
development
Gate 2
ideas
Gate 1
OPEN INNOVATION – THE DUTCH TREAT
business
Success is: New product/ technology/ market for our company
Figure 2. Closed System Stage-Gate Model for Innovation
vation models, which describe and decompose the innovation process. These formalized models finally lead to the introduction of stage-gate models (Cooper, 1992; Tidd et al., 2001). Figure 2 illustrates a simple format of such a funnelling model. In this second stage of evolving systems, the success of the system is narrowly defined as ‘a new P(roduct)/T(echnology)/M(arket) combination for our company’. As can be seen from their definition, these systems are inward looking and hence characterized as closed. These systems feature a pipeline of stages in the innovation process, in between which are gates that try to filter out potential losers. The criteria here are based on three overall clusters for successful innovation (Cooper, 1992; Besemer, 2000; Byttebier, 2002): • novelty • feasibility • effectiveness. As ideas, projects and business flow through the pipeline, their number drops dramatically from one stage to another. A steep mortality curve of 3,000 ideas to 60 small projects, seven market introductions and one market success is accepted as a natural phenomenon of innovation and can be influenced only slightly by the way the process is managed (Stevens & Burley, 1997). This systematic and closed approach has several major advantages, including a clear overview of projects in progress and use of active portfolio management. However, the criteria gauged at the gates cause it to be a double-edged sword. The feasibility criterion leads to a conservative portfolio, and the effectiveness criterion causes any potential innovations outside the dominant business model to be left unused. Similarly, the idea/project/ © 2007 The Author Journal compilation © 2007 Blackwell Publishing
business inflow is closed in nature, and ‘out of the box’ thinkers are repressed in human resources potential (Kirton, 1994). In the most extreme of cases, the funnel vision ultimately leads to tunnel vision.
Stage 3: Systematic Innovation with an Open System In modern innovation management, open models for systematic innovation have been designed to overcome the limitations of closed systems. Open models differ from closed systems in their definition of success. In open models success not only entails the successful implementation of ideas in the original business domain of a company, but also the successful implementation outside that domain (Chesbrough, 2003). Figure 3 gives a simple format of such an open system. The open system model has several major advantages over the closed system. First, it allows money to be made in every stage: not only by selling, but now also by licensing out or spinning out at earlier stages. Second, it allows for the full use of human resource potential since it also allows ‘out of the box’ thinking. One of the leading scholars on open innovation is Chesbrough who popularized open innovation in his 2003 book Open Innovation. He decomposes open innovation into three elements: culture, structure and business model. To provide a better understanding of open innovation, we will briefly introduce these elements in more detail.
Open Innovation Culture Innovating in an open system requires a different way of thinking. The set of norms, beliefs
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
196
Spin in
Ideas
License out
Acquire
Success is: - new P/T/M - full use Human Resources - revenue of portfolio selling/ buying
Gate 2
Gate 1
License in
Spin out
Divest
Figure 3. Open System Stage-Gate Model for Innovation Table 2. The Culture of Open Innovation (Chesbrough, 2003) Contrasting Principles of Closed and Open Innovation Closed Innovation Principles The smart people in our field work for us
To profit from R&D, we must discover it, develop it, and ship it ourselves If we discover it ourselves, we will get it to market first The company that gets an innovation to market first will win. If we create the most and the best ideas in the industry, we will win We should control our innovation process, so that our competitors don’t profit from our ideas
and values that work well in the open innovation system (or open innovation culture) is illustrated in Table 2, taken from Chesbrough (2003).
Open Innovation Principles Not all the smart people work for us. We need to work with smart people inside and outside our company. External R&D can create significant value; internal R&D is needed to claim some portion of that value We don’t have to originate the research to profit from it. Building a better business model is better than getting to market first If we make the best use of internal and external ideas, we will win We should profit from others’ use of our innovation project, and we should buy others’ IP whenever it advances our own business model.
process that enable in- or outflow. Some examples for such mechanisms are listed in Table 3.
Business Model: Terra Incognita Open Innovation Structure Inspecting the open innovation model closer, we can see mechanisms for importing and exporting knowledge, ideas and projects. Such mechanisms include methods, structures and systems in every stage of the innovation
Volume 16
Number 2
2007
In Chesbrough’s (2003) description of open innovation, he adds an important and dominant element: the flexible use of several business models. This idea is of special importance to open innovation, because it circumvents the ‘Not Sold Here’ syndrome that is present with closed system innovation companies. By the © 2007 The Author Journal compilation © 2007 Blackwell Publishing
OPEN INNOVATION – THE DUTCH TREAT
197
Table 3. Some Mechanisms of Open Innovation Stage Concept
Development
Business
Importing
Exporting
• Creative sessions networking with universities and scientific institutes • Knowledge clusters ‘Open Day’ • Conferences • Fairs • Suppliers and end-users • Licensing in • Patent search • Partnering • Spinning in • Venturing in
development and adoption of additional business models when new opportunities arise, companies open themselves up to a greater range of money-making activities. The business model is described as a ‘cognitive device to convert technical aspects of a product or service into economic value’ and revolves around the central question of what it takes to transform technology or specific knowhow into (commercial) success. The industry of copier machines flourished because someone figured out you should not sell high-priced machines, but instead you make your money out of paper and toner. The business model links the technical domain (what do we deliver?) with the social domain (how much value does this give to the user and how are we paid for it?). Thinking in business models is the pivot in the open innovation paradigm. Goretex (‘breathing’ waterproof clothing) resulted from a Dupont employee’s idea to use the properties of Teflon technology in quite another way, and it resulted in a world-leading company. The cell phone experienced a major breakthrough on the market when somebody invented the prepaid concept. Google provides services for free and makes money out of advertising. All these are examples of how business models link technical domains to social domains. In hindsight it is always easy to analyse clearly the essential success factors in a business model. Drawing one up from scratch is quite another story and is not easily or logically deductible from activities at hand. Most companies stick to their existing business model and by doing so miss a lot of opportunities (Christensen, 1997; Cooper, 2005). A business model should provide in two respects: • It should create value for the end user (and the following parties in the value chain). © 2007 The Author Journal compilation © 2007 Blackwell Publishing
• • • •
Cluster projects Industry groups Public–private co-operation Licensing out
• Patent brokers • Spinning out • Venturing out
• It should guarantee that the innovator (or creator or other key players) gets a fair share of the value added. Most companies find it very difficult to define their present business model, let alone handle more than one business model at the same time or develop a new innovative business model (Gerards, 1979; Collins & Porras, 1994). Yet this is exactly where opportunities arise to create value for the company because a business model is by definition based on a company’s unique core competencies, experience and innovative potential. Companies with an open innovation approach are fully aware of their dominant business model and can develop new ones if needed. They can value new innovative models proposed by outsiders and adopt them if they wish. But for most companies thinking in alternative business models is still a long way from home, as our research will show.
The Research Having discussed the characteristics of open innovation, we will now introduce our research and discuss our findings. Our research on innovation was focused on the Netherlands and the open systems model. Research questions were the following: • Which factors are hampering innovation in Dutch companies? • To what extent do Dutch companies plead to open behaviour? • To what extent do Dutch companies exhibit open behaviour?
Data Collected We collected the research data by using a questionnaire called the (Dutch) National Innova-
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
198
Table 4. Distribution of Number of Cases in Case Analysis Size in number of employees 50–99
100–199
200–499
500–999
>1,000
Total
4 5 9
5 3 8
2 1 3
3 2 5
2 1 3
16 12 28
Industry Service Total
40
13
35 30
1
6 2
4
25 20
12 11
5
3
8
15 10
9
14
10
7
5 0
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
Enterprise's innovation potential (e.g. R&D, design, etc.) too small Lack of skilled personnel Lack of information on technologies Lack of information on markets Innovation costs hard to control Resistance to change in the enterprise Deficiencies in the availability of external technical services Lack of opportunities for co-operation with other firms and technological institutions Lack of technological opportunities No need to innovate due to earlier innovations Innovation too easy to copy Legislation, norms, regulations, standards, taxation Lack of customer responsiveness to new products and processes Uncertainty in timing of innovation
Figure 4. Factors Hampering Innovation in Dutch Companies
tion Survey (Nationale Innovatie Enquête, 2003). In spring 2004, 5,000 such questionnaires were sent to companies in all sectors of industry and services with more than 50 employees. There were 814 responses and an additional in-depth interview and case analysis of 28 companies that rated themselves in this questionnaire as forerunners in innovation were carried out. Table 4 shows the distribution of the cases analysed. From these cases we charted factors that were found to hamper innovation. These hampering factors are illustrated in Figure 4. Finally, we performed 28 case studies of Dutch companies that had scored themselves as forerunners in innovation by conducting
Volume 16
Number 2
2007
in-depth interviews with them to gauge whether these companies showed characteristics of open innovation. The in-depth interviews covered the items innovation culture, innovation mechanisms and the use of one or more business models. When 80 per cent of the characteristics of an open innovation culture were found (see Table 2) we ranked the company as ‘showing the characteristics of open innovation culture’. When two or more importing or exporting mechanisms were found (see Table 3) we ranked the company as ‘showing the characteristics of open innovation structure’. For each case study, an 8–10 page case report was produced giving the specific examples of the culture, the structures © 2007 The Author Journal compilation © 2007 Blackwell Publishing
OPEN INNOVATION – THE DUTCH TREAT
199
Table 5. Percentage of the Dutch Companies Showing the Characteristics of Open Innovation (n = 28 self-declared ‘highly innovative’ companies with more than 50 employees) Culture
68%
Structure
More than one business model
Importing
Exporting
74%
54%
used and the use of one or more business models. Table 5 shows our findings, subdivided into cultural, structural and business model elements.
7%
do not have a direct link to open innovation practices but rather pertain to innovation in general.
Few Business Models Internal Factors Hampering Innovation Our research shows that the factors hampering innovation in Dutch companies are very similar to those found globally. Research by Resources Global Professionals (2004) shows that three-quarters of innovation projects are partly successful or not successful at all. Managers of the researched companies gave the following reasons: • • • •
Too little commitment Too little time available Too few resources Wrong innovation strategy
37% 37% 21% 31%
The same type of internal causes is mentioned in the (Dutch) National Innovation Survey. According to this research, economic reasons also play an important role. Some notable results are that 44 per cent of the companies report ‘long payback period’, 40 per cent ‘high innovation costs’, 30 per cent ‘legislation, standards etc.’ as important factors hampering innovation in their companies. These results are included in Figure 4. Beautiful excuses may not be far from the truth, yet somehow they seem to miss the point: management waste scarce time and motivation available for innovation. A lot of effort is put into wrong projects and innovation teams neglect knowledge already available elsewhere. Companies co-operate too little with other companies and research institutes. New technology gets far more (management) attention than non-technological aspects of innovation. In short, management of innovation in Dutch companies shows much room for improvement. Yet these causes are internally focused and, important as they may be, they © 2007 The Author Journal compilation © 2007 Blackwell Publishing
Open innovation practices become clearer in Table 5. As becomes apparent from the percentages, the dominance of the existing business model is the main challenge to open innovation in Dutch companies. In most of the cases this business model is not explicitly specified at all. Instead it lives implicitly and under the surface of the daily routine. Hardly any company in our sample was able to show flexibility in choosing appropriate different business models. The three cases where we did find this flexibility were diversified conglomerates with a high autonomy at business unit level, where its headquarters showed the ability to implement and use multiple business models, while we found the same rigidity as in the rest of our sample of 28 companies at business unit level. Although we found that a lot of larger companies are charmed by the perceived benefits of exporting (obsolete) knowledge, our research shows that most companies find it difficult to install and maintain exporting structures that really pay.
Status Quo in Holland There are some good examples of larger companies active in the field of exporting systems like Twentse Kabelfabrieken, Philips and DSM. The top management of these large companies already claim to use the principles of open innovation. Others, such as Heineken and Shell, now adopt strategic co-operations such as the highly successful joint development of Senseo coffeemakers by Philips and Sarah Lee. Philips recently started the High Tech Campus in Eindhoven where research capacity and laboratory capacity is provided to
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
200
companies that spun off Philips but also to other high-tech start-ups. According to DSM, open innovation has brought dynamics to their total operation. DSM made the transition from a classical mass chemical production plant to sophisticated consumer products like Dyneema strong fibres and food additives. This transition was made possible only by using strategic alliances with other companies and research institutes. DSM even went into revolutionary pre-competitive co-operation with their major competitors. These cooperative research projects were realized in an independent joint research institute, the Dutch Polymer Institute. DSM also puts sincere effort into corporate venturing by scanning literally hundreds of small high potential knowledgebased firms. Out of these hundreds, two or three are candidates for further financial investment for which DSM will provide venture capital. An especially interesting example of a cultural invention within DSM itself is the Innovation Award 2004 granted to the researcher who proposed stopping DSM’s own research and license outside technology instead. But these are exceptions. The reality in Dutch companies seems less ideal. Researchers and managers at business unit level within larger companies have a hard time finding balance between open and closed behaviour. When things really matter they demonstrate an overwhelming tendency towards the closed innovation principles, even when they are not the largest players in their market. Licensing out technology when it has been sitting unused on the company’s shelves for years is easily acceptable for a company like Philips. It is the same game with different rules at Proctor & Gamble with their ‘use-it-or-lose-it’ policy. Here developments may be sold to direct competitors after not having been used for three years. But most Dutch companies do not warmly embrace this type of open behaviour. Our first survey on open innovation in Dutch industry shows large companies primarily focusing on bringing their own obsolete ideas and knowledge outside by selling it to others. The use of patent information licensing, new business start-ups stimulating spin-offs and corporate venture capital departments are examples of exporting structures. Both academic researchers and R&D managers see opportunities to generate short-term cash. Top and business unit level management recognize interesting playgrounds in these exporting structures to obtain rich experience without direct threats to their existing business. Almost all cases are in a knowledge domain outside the direct interest of the company itself.
Volume 16
Number 2
2007
As a start-up for an open innovation system, opportunistic approaches can be useful in the short term. Companies are forced to identify their key competences or crown jewels and the crucial knowledge domain they want to keep and protect. But it is only a first step on a long journey to establish an open innovation system based on long lasting, deep co-operation with a larger number of partners in alternating coalitions. Research based on the results of the Community Innovation Surveys (CIS) has shown that such behaviour is only displayed with ‘high-level’ innovations that are more radical, complex or new markets so that companies may acquire higher certainty by pursuing market information or share the resources necessary for market introduction (Tether, 2002; Miotti & Sachwald, 2003; Belderbos, Carree & Lokshin, 2004). For small and medium sized enterprises (SMEs), the situation is somewhat more complex. Examples of smaller companies, such as Eastside Tanner who licensed their newly developed system for wastewater recovery to a large engineering company, are very rare in Holland. Yet a lot of entrepreneurs recognize their normal way of thinking in open innovation principles. Most SMEs do not own huge R&D capacity and so borrowing, hitchhiking and combining all types of external knowledge is their normal pattern of behaviour (Brown & Hagel, 2006). And so a more open attitude by large companies and research institutes could provide SMEs with even more opportunities. Co-operation, sharing of knowledge and joint exploitation in several stages of the innovation process seems necessary out of opportunistic motives or perceived or real lack of capacity to deliver. Since both large and small companies benefit from consortium-like co-operation, the power distance between these partners is (perceived) smaller. Even the smallest player in such a consortium can make the difference between success and failure. Therefore, the basic assumption of open innovation is equality of partners regardless of their size. Naivety, second fiddle or unreliable behaviour is punished even harder than usual in a business surrounding operating under the closed innovation paradigm. A lot of SMEs and their partners still have to experience this practice.
On Collaboration As is apparent, we have found evidence that there is a difference in collaboration between innovative larger companies and innovative SMEs. Innovative larger companies have a © 2007 The Author Journal compilation © 2007 Blackwell Publishing
OPEN INNOVATION – THE DUTCH TREAT
tendency to display closed behaviour when things really start to matter, while innovative SMEs are more naturally suited to engage in open innovation. Yet comparable research based on data from the CIS shows that firm size is no predictor of the amount of collaboration or success thereof (Faems, van Looy & Debackere, 2005). The key to explain this apparent contradiction is the specific focus on companies that are innovative. As Faems, van Looy and Debackere (2005) state, the CIS data did not include characteristics of organizational structure. We then hypothesize that by grouping all types of companies, high innovators and low innovators and anything in between, that there will be no statistically significant relationship between firm size and amount or success of collaboration. Indeed, the smaller amount of highly innovating larger companies may be offset by a greater amount of highly innovating SMEs, and vice versa. Therefore, we believe that the research based on the CIS data actually supports our work rather than contradicting it. Collaboration is indeed one of the ingredients of open innovation and as figures from CIS research suggest, it can surely and positively influence the success of innovation projects. Our contribution to this element is that larger companies face a greater challenge than SMEs in this respect, with some significant examples leading the way.
Open Challenges It has been shown that open innovation is not just about the hype, with a number of major examples leading the way. It does, however, need a deep involvement to really pay off, and in this respect Dutch companies find it hard to find a good fit. The value added by the open innovation paradigm is thinking in business models, but handling them in an open way. This is the real challenge for Dutch industry.
Acknowledgement The author would like to thank Roderick van Domburg for his contribution in revising and structuring the materials.
References Arthur D. Little Inc. (1985) Management of Innovation. Arthur D. Little Inc., New York. Belderbos, R., Carree, M. and Lokshin, B. (2004) Cooperative R&D and Firm Performance. Universiteit Maastricht, Maastricht. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
201
Besemer, S.P. (2000) Creative Product Analysis to Foster Innovation. Design Management Journal, Fall, 59–64. Brown, J.S. and Hagel, J. (2006) Creation Nets: Getting the Most from Open Innovation. The McKinsey Quarterly, 2, 41–51. Byttebier, I. (2002) Creativiteit Hoe? Zo! Lannoo, Tielt, p. 170. Chesbrough, H.W. (2003) Open Innovation. Harvard Business School Press, Boston, MA. Christensen, C. (1997) The Innovator’s Dilemma. Harvard Business School Press, Boston, MA. Cobbenhagen, J. (2000) Successful Innovation: Towards a New Theory for the Management of Small and Medium-Sized Enterprises. Edward Elgar Publishing, Cheltenham, Glos. Collins, J. and Porras, J.I. (1994) Built to Last: Successful Habits of Visionary Companies. Harper Business, New York, pp. 90–212. Cooper, R.G. (1992) The NewProd System: The Industry Experience. Journal of Product Innovation Management, 9, 113–27. Cooper, R.G. (2005) Your NPD Portfolio May be Harmful to Your Business’s Health. PDMA Visions, 29, 22–6. Dekker, D. and van der Meer, J.D. (2005) De weerbarstigheid van open innovatie. Management en Consulting, 3. Ekvall, G. (1996) Organizational Climate for Creativity and Innovation. European Journal of Work and Organizational Psychology, 5, 105–23. Faems, D., van Looy, B. and Debackere, K. (2005) Interorganizational Collaboration and Innovation: Toward a Portfolio Approach. Journal of Product Innovation Management, 22, 238–50. Gerards, H.M.A.M (1979) Gedragsmodel voor middelgrote ondernemingen. PhD thesis, University Twente. Geus, A. de (1997) The Living Company: Habits for Survival in a Turbulent Business Environment. Harvard Business School Press, Boston, MA, pp. 61–93. Howell, J.M. and Boies, K. (2004) Champions of Technological Innovation: The Influence of Contextual Knowledge, Role Orientation, Idea Generation and Idea Promotion on Champion Emergence. Leadership Quarterly, 15, 123–43. Isaksen, S. and Tidd, J. (2006) Meeting the Innovation Challenge: Leadership for Transformation and Growth. John Wiley & Sons, Chichester, pp. 98–115. Kanter, R.M. (1983) The Change Masters. Simon & Schuster, New York, pp. 23–58. Kirton, M.J. (1994) Adaptors and Innovators: Styles of Creativity and Problem Solving. Routledge, London. Lucking, B. (2004) International Comparisons of the Third Community Innovation Survey. Department of Trade and Industry, London. van der Meer, J.D. (1996) Profile of an Innovative Organisation. In Prokopenko, J. and North, K. (eds.), Productivity and Quality Management: A Modular Programme. ILO, Geneva. Miotti, L. and Sachwald, F. (2003) Co-operative R&D: Why and With Whom? An Integrative Framework of Analysis. Research Policy, 32, 1481–99. Nanus, B. (1992) Visionary Leadership: Creating a Compelling Sense of Direction for Your Organisation. Jossey-Bass, San Francisco, pp. 10–21.
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
202
Nationale Innovatie Enquête (2003) Vakgroep Technologie en Organisatie van de Universiteit Twente. Parker, M. (1990) Creating Shared Vision, Dialog International, Clarendon Hills. Peters, T.J. and Waterman, R.H. (1982) In Search of Excellence. Harper and Row, New York. Resources Global Professionals (2004) Deelonderzoek Innovatie, uitgevoerd door Interview NSS Maarssen, April. Saren, M.A. (1984) A Classification and Review of Models of the Intrafirm Innovation Process. R&D Management, 14, 11–24. Stefik, M. and Stefik B. (2004) Stories and Strategies of Radical Innovation Breakthrough. MIT Press, Cambridge, MA. Stevens, G. and Burley J. (1997) 3000 Raw Ideas = 1 Commercial Success. Research – Techology Management, 40, 16–27.
Volume 16
Number 2
2007
Tether, B.S. (2002) Who Co-operates for Innovation, and Why? An Empirical Analysis. Research Policy, 31, 947–67. Tidd, J., Bessant J. and Pavitt, K. (2001) Managing Innovation, Integrating Technological, Market and Organisational Change, 2nd edn. John Wiley & Sons Ltd, Chichester.
Han van der Meer (
[email protected]) is ABN-AMRO chair innovative entrepreneurship at Saxion Universities and assistant professor at University Twente and Technical University Delft, the Netherlands. He is founder and partner of van der Meer & van Tilburg, consultants for innovation and growth since 1979.
© 2007 The Author Journal compilation © 2007 Blackwell Publishing
INNOVATION LEADERS SHOULD BE CONTROLLED SCHIZOPHRENICS
203
Innovation Leaders Should be Controlled Schizophrenics Jan Buijs Innovating is a multi-faceted process. In this paper, four different, yet intertwined aspects of this process are distinguished. The first aspect concerns the content of the innovation; a new product, a new technology or a new market. The second aspect concerns the group dynamics of the innovation team. The third aspect concerns seeing the innovation process as a creative process. And the fourth aspect has to do with leadership. Since these four aspects are simultaneously working together during the innovation process, the leaders of this process are working in a very difficult situation, as all four aspects need to be dealt with in different ways. Nearly all of them are, in one way or another, in conflict with one another. They may conflict in real actions, in time horizons (past, present or future) or in effect (positive reactions during market introduction do not garantee ultimate market success). This means that innovation leaders need to show a special kind of leadership. This leadership must be balanced, peoplefocused and must include a high tolerance for ambiguity and paradoxes. They have to be nice and nasty at the same time. In short: innovation leaders should be some kind of controlled schizophrenics.
Introduction
M
ore than 20 years ago, J.B. Quin wrote an article in Harvard Business Review with the title ‘Managing Innovation: Controlled Chaos’ (Quin, 1985). He introduced an intriguing paradox between the necessary risk taking which occurs during innovation, and the risk avoiding momentum of the normal management process of daily routine business. To summarize his message: yes, we love innovation, but only if we can control it in such a way that nothing is going to change! There is a lot of evidence that innovation is different from daily business. Normal business is routine and experience based. It is about repetition, risk avoidance and the (successful) past. Innovation, on the other hand, demands out-of-the-box thinking, breaking the rules, risk taking and challeging the future (Burns & Stalker, 1961; Kanter, 1984; March, 1991; Smulders, 2006). Very little has been said about the consequences of the differences between exploitation (= routine) and exploration (= innovation). The issues of staffing the innovation team and selecting the people who are going to lead the innovation process have hardly been discussed in the innovation litera© 2007 The Author Journal compilation © 2007 Blackwell Publishing
ture. In this paper, we will break the silence surrounding these issues and expose the implications of Quin’s message. We will introduce yet another paradox: innovation leaders should be controlled schizophrenics. We will argue that in order to managing innovation (processes) the responsible leaders (managers and/or consultants) have to behave and act in different and conflicting roles and take on different attitudes at the same time. They must do this without losing contact and rapport with their innovation team members. They need to have a great tolerance for dealing with the different conflicting and competing aspects of innovation within the innovation team. Like the leader, the innovation team is also struggling with the same conflicting aspects but with a different time scale, different interest levels and with differences in knowledge and experience. The innovation team members expect their leader(s) to be in charge and to be in control. Yet, they also want support, enthusiasm and trust. They do not want to hear that their leader sometimes has doubts about the direction to be taken, the sequence of the process and about the success of the project. If the innovation leader shows his doubts too strongly, then he ruins the game.
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00431.x
CREATIVITY AND INNOVATION MANAGEMENT
204
Innovation is about coming up with and implementing something new. It is about searching for ideas, exploring ideas, developing ideas, implementing ideas and successfully introducing the ideas (products) into the marketplace. Innovation leadership is about bridging the gap between dreams and reality, past and future, certainty and risk, concrete and abstract, us (‘we love innovation’) and them (‘they don’t want to change at all’) and success and failure. And all of these dualities are present at the same time. Innovation leaders are already aware of the natural conflict between the day-to-day routine processes in the firm (exploitation which is necessary in order to earn money in the present) and the innovation processes (exploration which is intended to find new ways to earn money in the future). Yet they should also be aware of the inherently conflicting and paradoxical aspects inside the innovation process itself. Handling these paradoxes requires a one-person multi-manager or, in other words, a form of controlled schizophrenic innovation leader. This paper will address the issue of leadership only. The issue of selecting the team members will not be discussed in this paper.
The Innovation Process as a Multi-process Process There is not just one innovation process; it is a set of different, parallel, competing and conflicting processes which all occur at the same time. The first question to be answered concerns the content of the innovation process. Are we searching for new products, new manufacturing processes, new ways of organizing, or new ways of dealing with people? This content is usually structured by the wellknown stage-gate models of the innovation process (Cooper, 1984). This is familiar territory for innovation practitioners. The second aspect to be looked at is the psychological process of the innovation team. Not only do the forming-storming-normingperforming and adjouring stages come into play, but also the search for a shared understanding, the level of comfort with ambiguity and the degree of trust between team members during the innovation journey play a role. These are the relatively ‘normal’ group dynamic aspects of the game. This should be familiar territory for organizational development consultants and human resources managers (Schein, 1969, 1987; French & Bell, 1978). The third important aspect of innovation is the creative process of the team. This is the idea-producing process. It involves handling
Volume 16
Number 2
2007
the sequences of divergent and convergent thinking, dealing with the different iterations and loops in the process, working with metaphors and analogies in the search for new ideas, encouraging wild ideas and stimulating out-of-the box thinking. It also requires evaluating and judging of the new ideas during the convergent stages. This should all be familiar to creativity facilitators (Rickards, 1974; Leonard & Swap, 1999). Finally, we must remember the process of leading and playing. Leading is a way of making a voyage of discovery, finding a path through unknown territory and dealing with unfamiliar circumstances. It is playful in the sense of playing with rules (and isn’t innovation about breaking the rules?), having fun and being challenged by some ridiculous dreams and extremely high ambitions. This leading and playing can be handled best by a special form of leadership: the continuous alternation of the generative and the focusing mode of leadership (Hohn, 2000). This is new territory for most of us. The innovation leader must master all of these four processes simultaneously and in a way that makes the team feel secure. While the leader is already thinking about the next uncertain step to be taken, the team has to be encouraged to execute the present step comfortably. If the leader shows his or her uncertainty about the next step to the group, then the innovation process will be stunted, the energy will dissipate and the present step of the process will be left unfinished. This attitude of being certain about uncertainties and offering comfort in the present moment, while also taking future steps into consideration, calls for a high level of tolerance for dealing with different states of minds and different personal feelings. This means having multiple personalities at the same time, and that is the classical definition of schizophrenia!
The Innovation Process Usually, the innovation process is described as a series of stages through which an idea is processed. During each stage, certain activities are executed in order to improve the quality of the idea and to let the idea grow. Each stage ends with a gate, in which the idea is checked and evaluated. It is then decided if the idea can be carried over into the next stage, if the idea needs to be further developed in the current stage, or if the idea needs to be abandoned altogether. The type of idea is not important; it could be an idea for a new market, a new technology or a new product. It can be a very vague first idea © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INNOVATION LEADERS SHOULD BE CONTROLLED SCHIZOPHRENICS
205
Figure 1. The Delft Innovation Model (Buijs & Valkenburg, 2005)
that is developed into a well tested and proven new successful product on the market (in the case of a product innovation) or a new way of producing or solving a problem (in the case of a new technology). Many academic authors have produced some lengthy and monotonous discussions about the number of stages and the names of the activities inside those stages (e.g., Cooper, 1984; Roozenburg & Eekels, 1995). Yet, in general, all these stage-gate models look more or less the same. The older models started with the primary idea. How this initial idea was created was not shown in the model. Newer models include information about the starting activities that are used to generate the primary idea. These starting activities have become known as the fuzzy front end of innovation (FFE) (Koen et al., 2001). We will describe one of those stage-gate models in the form of an illustration (see Figure 1). Five stages are described in this model: 1. Strategy formulation; 2. Design brief formulation; 3. Product development; © 2007 The Author Journal compilation © 2007 Blackwell Publishing
4. Market introduction; and 5. Product in use. The names of the five stages are not mentioned in Figure 1, because this figure is just one step further on. All activities (circles) and results (squares) of all stages are being shown here, otherwise the five stages would be shown as five black boxes only. From the company’s point of view, the first stage is the formulation of a new strategy. Based on the changing competitive position of the company, the management must decide if there is a need for new product/market/ technology combinations. From a more societal perspective, the starting stage should be the ‘Product in use’ stage. In this stage, the present products are being bought, used and evaluated by the users in relation to the offerings of the competition, including substitutes and/or replacing services. This usage will change the users’ behaviour (i.e., switching over to other competing products) and that will eventually lead to changes in the competitive position of the company. If the company
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
206
discovers these changes, then they have to start at stage 1 ‘Strategy formulation’. In Figure 1, the ‘Product in use’ stage is at the top in the one o’clock position, the ‘Strategy formulation’ stage is on the right at the three o’clock position, the ‘Design brief formulation’ is at the six o’clock position, the ‘Product development’ stage at eight o’clock, and ‘Market introduction’ at eleven o’clock. This circular form shows that the success of a first innovation process implies the need for a succeeding second innovation process. In the model shown, each stage is described (and visualized) in the same way. Each stage starts with the result of a preceding stage (visualized as a square) and is followed by three parallel processes (= activities) in which this result is altered and changed (the content of the idea is growing). The three parallel processes (visualized as circles) influence each other during processing. This interactive processing ends in a next in-between result which, after positive evaluation, acts as the starting point for the next step or stage. The evaluations are the gates in this model. Although stage-gate models are describing the process an idea is going through, the evaluation steps are useful not only for evaluating the quality of the ideas, but also for checking and evaluating the process itself. What went well? What can be improved? And what has been learned? Reflection occurs during evaluation and learning occurs during reflection. After all, every innovation process is an organizational learning process (Buijs, 1987). Something that is not shown in the model is the possible result of an idea failing to be accepted during evaluation. When this occurs, an iteration may begin or the idea may be killed. Innovation processes without loops do not exist. Yet, not one of the existing models clearly shows these loops. Another element that is not shown in this kind of stage-gate model is how all of the activities in the innovation process are related to each other and are interlinked. This means that, for example, executing an activity in stage 2 ‘Design brief formulation’ will influence not only other activities in stage 2, but will also influence activities in stages 3 ‘Product development’ and 4 ‘Market introduction’ (downstream, which is logical). It may even influence activities in stage 1 ‘Strategy formulation’ (upstream, which seems illogical). For example, the results of a detailed market study in stage 2 (in the model’s terminology: external needs assessment) can lead to questioning previous results of the description of the strategic position of the company (step 1 of stage 1). For an innovation leader, this implies that every step can have consequences both
Volume 16
Number 2
2007
upstream and downstream. The leader should be aware of this very complicated interplay while helping the team with the execution of the innovation activity at hand. Therefore, the leader acts in the present, while keeping the past and the possible future(s) in mind. The best way to describe this phenomenon is to imagine this circular innovation process model as a kind of inflatable lifebelt (a swimming aid). If you squeeze on one area, then it will influence the pressure in all other areas. And if the belt has some weak spots, then it will show bulges in these areas.
The Group Process Innovations are seldom the result of one individual creative genius. Usually, they are the result of a huge team effort over a long period of time (van de Ven et al., 1999). Innovation teams not only form the engine and heart of the innovation process, they are also essential for encouraging the organization to accept the innovation result. Innovation team members come from many different relevant departments or functions within the company. Good innovation teams are limited not just to R&D or marketing people. They also include members from departments such as manufacturing, purchasing, legal affairs or customer service. As members of the innovation team they are responsible primarily for the contribution of a specific type of content in the innovation process (related to their functional/ departmental background). They also act as a ‘postillion d’amour’ between the innovation team and home base (which is their department). In this way, the organizational acceptance finding is built into the composition of the innovation team. This gives the forming of the innovation team an even greater importance than just the composition of an ordinary project team. It is not only about cross-functional diversity or cross-cultural diversity, but also about gender, age, experience (within or outside the company) and personality styles (Mostert, 2007). During team formation, the normal group dynamic process that is so typical of all team building begins. Following the formation stage come the storming and norming phases, after which the team is finally ready to perform their activities. Every change of team membership forces the team to fall back into the storming phase and prevents the team from performing at the highest possible level. The last phase is called the adjouring phase. This is the period for celebrating the success and for learning from failures, for saying goodbye to all the team members, for thanking them for their contributions and for preparing © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INNOVATION LEADERS SHOULD BE CONTROLLED SCHIZOPHRENICS
207
Figure 2. The Nonsequential Nature of the Creative Process (Couger, 1995)
them for their return to their departments. This so-called re-entry is often neglected, yet it is of major importance for the acceptance finding and the reflection and learning of the team members (and the company). The selection of the innovation team leader (usually by the top management of the company) should be the starting point of the forming stage. In the ideal situation, the newly appointed innovation leader can pick out his or her own volunteers. The leader should at least have the power to veto unwanted team members. Innovation is about having the right people in your team. The social abilities of the leader are much more important than his or her content knowledge about the innovation (Wheelwright & Clark, 1992).
The Creative Process The third way of looking at the innovation process is to see it as a creative process: a process that leads to new ideas. Traditionally, the creative process is also described as a sequential step-by-step process, like the stagegate innovation models. This strict and formal sequence has been challenged (Isaksen & Dorval, 1994). The content of the steps are more or less the same but the logical sequence has been dismissed. Depending on the team’s judgement of the task at hand, they start with one of the steps. After reflecting on the completed task (or during execution of the task), they select what they believe to be the next appropriate step. This does not have to be the next logical step of the rational ordered model. The appropriateness of this next step depends on what stage of evolution the idea has reached, the quality of the team, the © 2007 The Author Journal compilation © 2007 Blackwell Publishing
quality of the facilitator and the type, number and qualities of the interventions this leader is applying. The personal viewpoints or moods of the team members can also influence this appropriateness. A summarizing picture of this nonsequential creative process is shown in Figure 2. Two sub-steps are distinguished within all (five) stages of the creative process (in the logical order: (1) Problem definition; (2) Compiling relevant information; (3) Generating ideas; (4) Evaluating and prioritizing ideas; and (5) Developing implementation plan). First, a divergent sub-step occurs. It is then followed by a convergent sub-step. ‘Divergence’ refers to searching for as many ideas/opportunities as possible, without any judgement. ‘Convergence’ refers to the validation of the ideas generated in the light of the original problem statement or problem situation. Recently, an additional step in between divergence and convergence has been introduced: a cleaning-up or clustering step (Van der Meer, 2006; Tassoul & Buijs, 2007). The clustering step acts as a process break (= people-related) as well as a content break (= idea-related). The process break has to do with the different rules which apply to each sub-step (i.e., divergence needs no judgement, while convergence is more or less pure judgement). As a result, the innovation team members have to behave differently. The content break has to do with the organizing of all the ideas generated. If you start converging while all of the ideas are randomly organized, then the convergence process will be difficult. Therefore, the experienced leader cleans up the piles of ideas into a small number of clusters of ideas with shared common char-
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
208
use when). At the same time, he or she is fully aware of all the other factors of the team behaviour and the challenges of the objectives of the innovation journey.
The Leadership Process
Figure 3. Divergence and Convergence with the In-between Clustering or Cleaning-up Step
acteristics, and attaches a label or stimulating metaphoric name to distinguish the different clusters (see Figure 3). If the innovation team is in a divergent substep, yet the desired flow of ideas is not being produced, then the innovation leader can use all different creativity techniques in order to stimulate divergent thinking. The same is true for the clustering and convergent stages. Once again, the need for schizophrenic behaviour from the team leader becomes clear. In a situation where the innovation team is not producing enough ideas, the leader can help by introducing idea-generating techniques. At the same time he or she should already be thinking about the next convergent sub-step in which all of those ideas have to be evaluated and judged. While working hard to get the team generating in sub-step 1 (divergence), he or she is already thinking about what to do in sub-step 2 (convergence) without losing contact with the team during the execution of task 1. The opposite is also true. If the results of task 2 (converging = judging the ideas) are not satisfactory (no ideas left), then task 1 (divergence) must be repeated. A starting point for this next iteration can be found in the labels (or metaphoric names) the group has given to the previously formed idea clusters from the cleaning-up stage, in order to find better or newer ideas. In this case the innovation leader is concerned both with the content of the process (the quality and number of ideas) and the relevant methods and tools (which technique to
Volume 16
Number 2
2007
The schizophrenic behaviour of the innovation leader is most prominent in the leadership process itself. If the team is feeling down, then the leader should be optimistic; if the team is overly enthusiatic, then the leader should be cool. If the team has fallen in love with an extremly funny idea, then the leader should point out which were the original objectives of the innovative task. If the team rejects all of the ideas and they focus too much on feasibility, then the leader should provoke them to dream and to let at least some of the wild ideas be considered. The leader is constantly switching between two different leadership styles. In her empirical research, Helga Hohn (2000) discovered that leaders of teams with an innovative task use both a generative mode of leadership and a focusing mode of leadership. She used the yin/yang symbol to illustrate that the one mode is already present within the other mode and vice versa. The characteristics of the two opposing modes are summarized in Table 1. Another important finding by Hohn is that innovation has a lot to do with playing and fun. Playing is not only a legitimation of dreaming, it also helps the team members to step outside their box of conventional thinking. Hohn also discovered that leaders play with both the content of the innovation and with the bureaucratic rules of the organization. ‘Organizational cheating’ is very helpful for achieving and creating the mental space the team needs for performing their innovative task. When introduced into an organization, most new ideas and innovations are met by a firm ‘no’. Innovation leaders should not react to this response. They should simply continue and find ways to circumvent that organizational ‘no’. They can do this by playing with the budget, playing with the traditions, having fun with the organizational heroes, challenging the organizational myths and legends. In this way, they can create their own new story, discover new heroes, build a new organization (the formation of the innovation team) and enjoy the innovation journey.
Conclusions and Management Implications By taking apart the four different processes that simultaneously play a role in the © 2007 The Author Journal compilation © 2007 Blackwell Publishing
INNOVATION LEADERS SHOULD BE CONTROLLED SCHIZOPHRENICS
209
Table 1. The Two Modes of Leadership (Hohn, 2000) Generative mode Vision development Play/fun metaphors Development oriented Have we created new ideas? Pace given by the creative process Challenge and risk taking Exploration of conflicts Finding freedom Chaotic Intrinsic motivation Autonomy and challenging conditions
innovation process, it becomes clear that the innovation process is, indeed, very complex. It is also clear that it is a process that is quite different from the normal way of ‘getting things done’. Talking about innovation as a single process is misleading. Innovation is a multi-faceted process that is full of contradictions. It is simultaneously hard and soft, nice and nasty, fun and serious. Innovation involves technology and people, marketing thinking about manufacturing and manufacturing thinking about marketing. Innovation is about the present and the future. It is never conforming, but always confronting. There is never a dull moment! As stated earlier, the innovation process model is like an inflatable lifebelt. It is useful for top management to check the quality of the lifebelt regularly. If there are punctures in the lifebelt, it cannot do its job properly. Of course, you can add more compartments to your lifebelt (each of the five stages form their own compartment and the gates act as pressure valves between the compartments). As a result, a puncture remains contained within one compartment. But too much control, in other words too many compartments (all stages and gates and also all activities plus ‘mini-gates’ within a stage), will make the lifebelt too heavy and impossible to use. Safety checks are no guarantee of survival, but at least they make sure that your equipment is fit for purpose. Since Henry Chesbrough (2003) introduced the Open Innovation concept, this already very complex innovation process is no longer being executed within the relative safety of the familiar environment of their own company, it is being played out in an open situation. Nowadays companies must co-operate with competitors, with start-ups, with universities and other partner organizations. What once were propri© 2007 The Author Journal compilation © 2007 Blackwell Publishing
Focusing mode Goal management Fight/power metaphors Business oriented Have we solved the problem? Pace given by planning and monitoring Defining action Crisis and conflict management Acting with constraints Ordered Extrinsic motivation Material and immaterial rewards
etary rights, meant to protect the company’s interests, are now seen as a shared ground for joint innovations. The difficulties in the company’s own innovation process, as described earlier, are now complicated by the necessary co-operation with a portfolio of external partners. All of the external partners have their own objectives, history, management styles and ideas about success and failure. Dealing with all of these multiple aspects of innovation at the same time and harmonizing the different perspectives, views and time horizons of the different team members and partner organizations calls for a very special kind of leadership. This leadership demands a great tolerance of ambiguity and paradoxes. It calls for choosing people over rules without losing track of the innovation journey. It also calls for passion and fun. It is like driving a four-wheel drive car as fast as possible on a muddy track, with the challenge of not letting the car get dirty. CEOs who ask for innovation should be aware that this kind of leadership is rare. It is advisable to search for people who are able to handle this controlled schizophrenia, stimulate them, protect them, believe in them and then let them guide the innovation process. HIPO no longer stands for high potential, but for a Highly Innovative Person On its way! An image that might come to mind after describing these four interrelated processes, and the way in which they are kept under control by the innovation leader, is that of a juggler. Jugglers talk about their game as ‘the art of letting go’. That is schizophrenia in optima forma: you want to be in control by letting it go! However stimulating and elegant this metaphor may be, it is a misleading image. The juggler is playing with a set of cones, yet the cones themselves are passive. We now
Volume 16
Number 2
2007
CREATIVITY AND INNOVATION MANAGEMENT
210
know that the four innovation sub-processes (analogous to the cones) do interact with one another during the innovation journey. Therefore, a better image would be of a juggler starts out playing with four equal cones and then the cones suddenly change in size, colour and weight. In doing so, the cones can also change their paths through the air. One of the cones could change into a ball and, before realizing this, the juggler may drop the ball. Unwillingly, he or she now has to play with two or three different types of cones and one or two different types of balls. These changes may continue throughout the juggling. We also must not forget that this juggler is riding on a unicycle during his act. If you can imagine such a juggling act, then you have a clear impression of the task of an innovation leader. Finally, it is important to remember that no juggling act has ever been developed without sometimes dropping the cones during practice and sometimes throwing the cones away in the corner. The same is true for innovation processes: there is no innovation process without failures and mistakes. Organizations need to learn from them as quickly as possible. If the organization out-learns its competitors, they then take the lead. And taking the lead is what innovation is all about!
References Buijs, J.A. (1987) Innovation Can be Taught. Research Policy, 16, 303–14. Buijs, J.A. and Valkenburg, R. (2005) Integrale Productontwikkeling, 3rd edn, Lemma, Utrecht. Burns, T. and Stalker, G.M. (1961) The Management of Innovation. Tavistock Publications, London. Chesbrough, H. (2003) Open Innovation. HBS Press, Boston, MA. Cooper, R. (1984) The New Product Process: A Decision Guide for Management. Journal of Marketing Management, 3, 238–55. Couger, J.D. (1995) Creative Problem Solving and Opportunity Finding. Boy & Fraser Publishing Company, Ferncroft Village. French, W.L. and Bell, C.H. (1978) Organizational Development. Prentice-Hall, Englewood Cliffs, NJ. Hohn, H. (2000) Playing, Leadership and Team Development in Innovation Teams. Eburon, Delft. Isaksen, S.G. and Dorval, K.B. (1994) Expanding Views on CPS: A Synergy Methodology. In Geschka, H., Moger, S. and Rickards, T. (eds.), Creativity and Innovation: The Power of Synergy. Geschka Publications, Darmstadt. Kanter, R.M. (1984) The Change Masters. Irwin, London. Koen, P. et al. (2001) Providing Clarity and a Common Language to the Fuzzy Front End. Industrial Research Institute, Washington.
Volume 16
Number 2
2007
Leonard, D. and Swap, W. (1999) When Sparks Fly. HBS Press, Boston, MA. March, J.G. (1991) Exploration and Exploitation in Organizational Learning. Organization Science, 2, 71–87. Mostert, N. (2007) Diversity of the Mind as the Key to Successful Creativity at Unilever. Creativity and Innovation Management, 16, 93–100. Quin, J.B. (1985) Managing Innovation: Controlled Chaos. Harvard Business Review, 63, 73–84. Rickards, T. (1974) Problem Solving Through Creative Analysis. Gower Press, Aldershot. Roozenburg, N.F.M. and Eekels, J. (1995) Product Design: Fundamentals and Methods. Wiley, Chichester. Schein, E.H. (1969) Process Consultation, Its Role in Organization Development. Addison Wesley, Reading, MA. Schein, E.H. (1987) Process Consultation, Volume 2. Lessons for Managers and Consultants. Addison Wesley, Reading, MA. Smulders, F.E.H.M. (2006) Get Synchronized! PhD thesis, Delft University of Technology. Tassoul, M. and Buijs, J. (2007) Clustering: An Essential Step from Diverging to Converging. Creativity and Innovation Management, 16, 16– 26. Van de Ven, A.H., Polley, D.E., Garud, R. and Venkataraman, S. (1999) The Innovation Journey. Oxford University Press, New York. Van der Meer, H. (2006) Conference Report, Impressions of the 9th European Conference on Creativity and Innovation, ECCI 9. Creativity and Innovation Management, 15, 120–2. Wheelwright, S.C. and Clark, K.B. (1992) Revolutionising Product Development. Free Press, New York.
Jan Buijs (
[email protected]) is a professor in Product Innovation and Creativity at the Faculty of Industrial Design Engineering at the Delft University of Technology. He has been active for more than 30 years as a teacher, researcher and consultant. He has worked with many different organizations: from low-tech SMEs to high-tech multinationals, from hospitals to insurance companies, from consulting firms to universities. His work has ranged from helping startups to closing down mature industries. His current research interests include multidisciplinary innovation teams and the relationship between branding and NPD. He is chairman of the European Association for Creativity and Innovation (EACI), a not-forprofit organization which is bridging the gap between academics and professionals in the field of innovation and creativity (http://www.EACI.net).
© 2007 The Author Journal compilation © 2007 Blackwell Publishing
BOOK REVIEW
211
Book Review Hoving, H. and Plantinga, R. (2006) The 7 Laws of Innovation – The Human Side of Innovation in Organizations, Panta Rheyn, Rotterdam, The Netherlands. 70 pp, Paperback: ISBN-10: 90-809526-2-1; ISBN-13: 978-90-809526-2-1.
Seven is one of the ‘sacred numbers’ in the social sciences. Many theorists and professionals summarize their knowledge and prescriptions in a list of seven principles, or statements, or ‘laws’. Actually, one of the best-known bestsellers of management literature has the title The Seven Habits of Highly Effective People. The author of that best-seller, Stephen Covey, could not find a publisher, so the Covey family decided to publish the book themselves. To date, the book has sold more than 15 million copies, and Dr Covey is a rich man. Apparently, publishing one’s own books can be a profitable business. This should be a comforting thought to Herman Hoving and Rik Plantinga. Their book The 7 Laws of Innovation is published by Panta Rheyn, Mr Hoving’s own consultancy firm. First, I will summarize the content of the book, before discussing the pros and cons. According to the authors, there are seven basic rules (the ‘laws’) of successful innovation processes. These laws are described in chapters 2–8, after the introductory chapter. The first law is to navigate on your gut feelings, i.e., based on gut feelings and on analysis of the situation, one should formulate a Profile of Desires and Demands. The second, third and fourth laws form the FVC model of forces, values and chances. The second law (forces) states that you should use your personal powers. According to the third law, innovators should be aware of emotions. The link with values is that significant values have corresponding emotions that act as ‘drivers’. The fourth law (chances) is the focus on opportunities. Then, by combining forces, values and chances, innovators should develop their own vision (fifth law). The final two laws focus on the implementation of the vision. The sixth law, ‘Put yourself in the shoes of the other’, describes and prescribes an empathic stage to get support for your vision and to organize your allies. The seventh law, ‘Experiment as much as you can’, gives recommendations for the launch stage. Following these seven guidelines guarantees a humanistic way to promote innovation. © 2007 The Author Journal compilation © 2007 Blackwell Publishing
The seven laws can be summarized in just one simple sentence, or in the words of the authors: ‘The human way of innovation is intuitive, powerful, value-driven, plausible, visionary, empathic, and experimental’ (p. 7). From the description of the seven laws it is already clear that there is a more or less (chrono)logical order. The authors pay attention to this ‘steps model’ of a series of consecutive innovation stages in their final chapter on the ‘Innovation flow’. At first sight, their figure 9 might give the impression that the innovation process is linear, but in the text it is quite clear that in most cases innovation is characterized by a cyclical process. So far, I have summarized the content of the book. That was the easy part of writing the review. Now my evaluation. That is a far less easy job. The evaluation depends on the criteria that are chosen. From a scientific point of view, the book does not offer new and surprising innovative insights. Also, the authors do not offer much support for their ideas and for their sometimes sweeping statements. To be sure, there is an index, but there is no list of references. Moreover, the index is, in fact, a combination of author and subject index. The ‘author’ part of the index is a peculiar set of names, i.e., many well-known innovation experts are missing, but the late controversial Dutch politician Pim Fortuyn is mentioned three times, and the mythological Greek god Kairos scores two citations. And these are just two examples. The authors also have problems sometimes in building a logically consistent, coherent structure for their ideas. To give only one example: the authors illustrate their conclusion that norms are at the bottom of the pyramid of societal stability with a figure (figure 2, p. 28) in which these same norms are placed in the middle layer of the pyramid! Such inconsistencies clearly damage the value of the text, and not only for scientists, but also for the general readership. I happen to know that the first author, Mr Hoving, is very strong in the divergent, exploratory phase of creativity and innovation projects. Writing a book on
Volume 16
Number 2
2007
doi:10.1111/j.1467-8691.2007.00430.x
CREATIVITY AND INNOVATION MANAGEMENT
212
innovation is a creative effort. A little bit more attention to the convergent phase of evaluation and selection of options would probably have resulted in a logically more solid book. Many management books belong to the so-called ‘Heathrow Literature’: you buy the book at the airport, you read it during the flight, and you throw it away after you have landed. The present book has too much value to share the sad fate of Heathrow books. The authors are enthusiastic innovation experts, and it is clear that they love their profession. They have pleasure in teaching. Moreover, their language is easy to read, it is clear, and often convincing (although the inconsistencies that I noticed spoil the effect somewhat). They are not rigid believers, in that they are fully aware of the fact that their ‘laws’ are not to be interpreted as scientific laws and/or as strict rules, but more
Volume 16
Number 2
2007
as mere guidelines to enhance the chances to successfully complete innovative activities. Real experts will not find new insights in this text, but the seven ‘laws’ certainly make sense, and summarize a sizeable portion of the existing knowledge of innovation processes. Therefore, this book certainly has value as a text for seminars and courses in innovation management. It is an introductory text written in such a way that every layman with an interest in the topic can understand the basics of the innovation process in just a few hours. To satisfy a real scientific curiosity, however, you will need to study other texts. Herman Steensma Department of Social and Organizational Psychology Leiden University
© 2007 The Author Journal compilation © 2007 Blackwell Publishing
