Constraint Management in Manufacturing: Optimising the Supply Chain

Constraint Management in Manufacturing

This book is about making money out of the supply chain. It is impossible to improve the performance of any chain without a deep understanding of the impact of the weakest link in that chain—the constraint. Without a constraint management perspective both supply chain management and lean thinking lack focus and the real leverage that senior managers within the manufacturing industry are seeking. Attempting to achieve any major improvement in performance without recognising the impact of the constraint will inevitably lead to less performance than expected, and in many cases no improvement at all. The book has been written for both practitioner and researcher alike. It is capable of being a textbook for anyone teaching operations management and related subjects, and at the same time can act as a guide for those seeking to improve the performance of their own company. The book addresses the increasing demand to create an approach to the manufacturing process which places constraint management into an overall perspective and links it to the creative use of new technologies such as the Web. The book draws on the author’s own experiences within the UK manufacturing industry in implementing constraint management, using case studies to highlight the key issues faced in the journey to substantially enhanced bottom-line performance. It examines the role of new product development, the role of production, the role of distribution, the development of the team, and the strategic focus required to turn the supply chain, or what the author calls the ‘Revenue Chain’, into a real, practical, approach for any company. Ted Hutchin is one of Europe’s leading consultants in constraint management. As founder and managing director of I. & J.Munn Ltd he has implemented constraint management solutions throughout the manufacturing industry. As part of his work within the industry he has carried out many research assignments and developed teaching/training material based on his research and designed to transfer the knowledge he has gained to those within the industry. He is a member of APICS, the Institute of Operations Management in the UK, the Institute of Management and the Institute of Directors in the UK.

Constraint Management in Manufacturing Optimising the global supply chain

Ted Hutchin

London and New York

First published 2002 by Taylor & Francis 11 New Fetter Lane, London EC4P 4EE Simultaneously published in the USA and Canada by Taylor & Francis Inc. 29 West 35th Street, New York, NY 10001 Taylor & Francis is an imprint of the Taylor & Francis Group This edition published in the Taylor & Francis e-Library, 2005. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” © 2002 Ted Hutchin All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Every effort has been made to ensure that the advice and information in this book is true and accurate at the time of going to press. However, neither the publisher nor the authors can accept any legal responsibility or liability for any errors or omissions that may be made. In the case of drug administration, any medical procedure or the use of technical equipment mentioned within this book, you are strongly advised to consult the manufacturer’s guidelines. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication Data Hutchin, Ted. Constraint management within manufacturing: optimising the global supply chain/written by Ted Hutchin. p. cm. Includes bibliographical references. 1. Production management. 2. Theory of constraints (Management) 3. Business logistics. I. Title TS155 .H867 2002 658.5–dc21 2002074217 ISBN 0-203-30120-X Master e-book ISBN

ISBN 0-203-34552-5 (Adobe eReader Format) ISBN 0-415-28519-4 (Print Edition)

For Esme Grace, my granddaughter

Contents

List of figures

ix

Acknowledgements

xi

List of abbreviations Introduction 1

2

xiii xv

Understanding the pressure to succeed

1

Introduction to the world of manufacturing

1

Key themes in manufacturing

4

Globalisation of the supply chain

5

Supply chain/network management

6

Chain or network?

7

Lean thinking

9

An example of misplaced focus

12

Manufacturing: a constraint management perspective

13

Constraint manufacturing defined

14

The core competencies of constraint manufacturing

17

Conclusions

18

The revenue chain and the impact it has

20

Defining the chain

20

Measurements

21

The problem with problems

25

A quick snapshot of the organisation

25

The notion of the constraint

26

Typology of constraints

26

vi

3

4

The five focusing steps of TOC revisited

27

The laws of constraint management

29

Conclusions

32

The full enterprise analysis methodology

33

Three basic questions

34

Analysing problems

34

Gaining consensus on the problem

35

The starting point is the undesirable effects (UDEs)

36

The conflict a UDE creates

39

How bad can a UDE go?

41

The application of the UDE cloud

42

Constructing the composite cloud

45

Developing the core solution

50

Creating the full feature set of the solution

52

Developing the implementation plan

52

Making it happen

55

The impact of paradigm lock within constraint management

57

The impact of the paradigm lock cloud

58

Conclusions

60

Managing new product development

62

Background to new product development and project management

62

Typology of projects

63

Critical chain introduced

64

A worked example: single projects

68

Buffer management

73

Delivering the project

74

The sequence of creating a critical chain schedule

75

Project example: single project

76

Substantial delay in start?

77

vii

5

6

7

8

Multi-project and critical chain

80

Conclusions

89

Managing production

91

Typical problems in production

91

The application of DBR simulations

100

Developing the drum-buffer-rope solution

103

Direction of the solution

109

Case study 1

111

Case study 2

115

Developing the ability to implement constraint manufacturing within the production area

118

Conclusions

120

Getting the product to the customer

121

The analysis of distribution

122

Developing the solution

126

Replenishment: the solution

127

Conclusions

131

The strategic importance of managing change

133

Introduction

133

The role of change and change management

133

Managing change

134

The change agent

137

Resistance to change

141

The politics of change

142

Change/implementation models and conflict resolution examined

144

Organisational learning

145

An analysis of change control models

147

Linking the paradigm lock cloud to models of change

150

The constraint management wheel of change

152

Pulling it all together: Gaining a true enterprise focus

155

viii

Enterprise focus revisited

155

Final thoughts

156

Bibliography

158

Index

161

Figures

1.1 Typical product life cycle 1.2 Moore’s contribution 1.3 Network diagram 1.4 Core elements of constraint manufacturing 1.5 The core competencies of constraint manufacturing 2.1 A simple revenue chain 3.1 A mapped organisation 3.2 UDEs placed upon the map 3.3 The conflict cloud 3.4 A conflict cloud example 3.5 The NBR structure 3.6 An example of an NBR 3.7 The UDE cloud structure 3.8 The assumptions of the UDE cloud 3.9 The cross-connection of the UDE cloud 3.10 The construction of the composite cloud 3.11 The composite cloud from project management 3.12 The composite cloud from project management, with assumptions 3.13 The communication analysis 3.14 The core future reality tree 3.15 The core future reality tree extended 3.16 The core future reality tree of our projects 3.17 The transition tree 3.18 The extended transition tree 3.19 The paradigm lock cloud 4.1 Actual time required 4.2 Actual time plus some time for variation 4.3 Actual, variation and some time for other activities 4.4 Actual, variation, other activities and some time for interruptions 4.5 The estimation given 4.6 Moving from estimation to execution 4.7 What happens when we delay starting the activity? 4.8 The real pressure on the project 4.9 Initial project layout 4.10 Critical chain identified 4.11 Resource buffers placed

2 3 9 14 17 21 36 37 40 41 42 42 43 44 45 47 47 48 50 51 53 53 56 56 58 65 65 65 65 66 67 67 67 69 70 71

x

4.12 Complete critical chain project plan with all buffers in place 4.13 Example of a buffer 4.14 Zone three penetration 4.15 Substantial penetration 4.16 Basic project network 4.17 Critical chain determined 4.18 Buffers in place: the final project network 4.19 Project start delayed 4.20 A worsening situation 4.21 Project status after action has been taken 4.22 Multi-project release 4.23 Project loading: key resource 4.24 Staggered projects 4.25 Fully protected projects 5.1 The first cloud of production 5.2 The second cloud of production 5.3 Basic production layout 5.4 Basic plant with capacity figures 5.5 The key schedules within DBR 5.6 Placing the rope 5.7 Full DBR for our simple plant 5.8 An example of an implementation plan 5.9 The benefits and problems that DBR creates 5.10 The layout of the implementation plan 5.11 The analysis for injection 100 5.12 The analysis for injection 10 5.13 The analysis for injection 11 6.1 The basic distribution process 6.2 The core cloud 6.3 Assumptions surfaced 6.4 The complete system 7.1 Kolb learning cycle diagram 7.2 Basic control model 7.3 Single/double loop learning 7.4 First review of the change model 7.5 The change model incorporating the PLC 7.6 The wheel of change

71 73 74 74 78 78 81 81 82 82 82 84 84 87 99 100 104 105 106 107 108 112 113 114 117 118 119 122 125 126 130 146 147 148 151 152 153

Acknowledgements

I believe we are each blessed by God with gifts; mine appears to be the ability to observe, write and teach about the world of manufacturing. I wish to acknowledge the involvement of a number of people who were instrumental in the writing of this book. Manufacturing industry has figured in my life since the age of fourteen, when I first listened to John Garnett and John Longmuir talking in our house in Edinburgh. They inspired me to work within the industrial community in order to achieve improved performance and enhanced wealth creation for our nation. Others who have inspired in this fashion are Professor Jack Burbidge, a leading academic from Cranfield University, with whom I had many conversations about production control at conferences such as IMC in Ireland; Professor John Kay, also of Cranfield; and the many managers I have worked with in the manufacturing sector over the last twenty years or so. There are the leading Theory of Constraints (TOC) practitioners who have argued with me, taught me, taken my logic apart, and then helped me rebuild it, such as Oded Cohen, Eli Goldratt, Donn Novotny, Dick Peschke, Alan Leader, Kathy Austin, Henning Du Preez, Dennis Marshall, Danny Walsh, Larry Leach, David Marks and many more. Research is a difficult activity to many people, but to me finding the answers to questions, even having to formulate the question in the first place, holds great fascination. The support of those members of the TOC community, the people at the various conferences I attend, such as ICPR, IMC and APICS, people such as Professor Michael Hillery and his colleagues from Limerick and Professor Andrew Storrar from Queen’s University Belfast, is invaluable. Within industry there are many who have helped, argued against, suggested alternatives, and always given critical assessment of what I was doing, people such as Mark O’Donovan, Simon Jones, Karl Springer, John Cottrell, Mick McLoughlin and many others who have helped me to understand more clearly the world in which they live and work. Writing is a strange way to pass a day; to do so whilst working within a company is doubly strange, hence my thanks to the people within I. & J.Munn Ltd, who not only supported me, but also tested my ability to write clearly and logically about a subject for which I have a great passion. People such as Suzie Hand, Neil Butterill and my wife Audrey, who have all kept me to task, also

xii

receive grateful thanks; without them I would never have had the ability to write and to reflect. Finally, for such a book to be read it first must be published and so grateful thanks must go to the team at Taylor & Francis without whose support and investment the book would never have seen the light of day.

Abbreviations

APS BM CA CCPM CFRT CM CMTP CRT DBR DDP DE ERP FG GAAP HR I IDD IO JIT KPI MAP MIM MRP NBR NPD OE OEM

Advanced planning systems Buffer management Communication analysis Critical chain project management Core future reality tree Constraint management Constraint management thinking processes Current reality tree Drum-buffer-rope Due date performance Desirable effect Enterprise resource planning Finished goods Generally accepted accounting procedures Human resources Investment Inventory dollar days Intermediate objective Just in time Key performance indicator Manufacturing automation protocol Managing Innovative Manufacturing Materials requirement planning Negative branch reservation New product development Operating expense Original equipment manufacturer

xiv

OPT OTIF PLC PRT RCL ROI SPC SSM TA TDD TOC TOC/TP TOP TPM TPS TQM UDE WIP

Optimised production technology On time and in full Paradigm lock cloud Pre-requisite tree Real change leader Return on investment Statistical process control Soft systems methodology Throughput accounting Throughput dollar days Theory of Constraints Theory of Constraints thinking processes Technical operations protocol Total preventative maintenance Track performance system Total quality management Undesirable effect Work in progress

Introduction

This book came about in response to people asking a simple question: just how do we really manage a manufacturing company successfully in the global context of today? The people asking the question worked in the many companies throughout the UK, Europe and the USA where I had been privileged to work, both teaching and developing their people. I had spent many hours with them, trying to develop better ways of scheduling the plant, delivering products on time and in full, developing new products faster than before and solving many other problems. We examined many of the tools and techniques being promoted by consultants and researchers, we tested many of these new ideas, and started to realise that this was no simple question, and it had no simple answer. The goal of this book is to try and pull together a number of what I believe to be major contributions in trying to answer the question and I leave the reader to determine whether I have been successful or not. The key to the future for manufacturing is the recognition that this is the only true wealth-creating activity in any economy. My old friend and mentor John Garnett once told me that, sitting over dinner in my home in Edinburgh with my stepfather John Longmuir. Both men were working for what was then called the Industrial Welfare Society, now the Industrial Society, and I grew up with their discussions about manufacturing industry and with them visited many companies in Scotland. Even though I was aged fourteen at the time, the experience made a lasting impression. As I grew older, I spent many years in the REME, then time in both industry and the academic environment, until in 1991 I started to work with Dr Eli Goldratt and his team in the UK. They were developing what became the Thinking Processes of the Theory of Constraints (TOC/TP). I was immediately attracted to the conceptual approach, the rigour of the logic that underpinned everything they did, the elegance of the solutions they had developed. I became totally committed to the TOC approach and over the next ten years developed, implemented and pushed the boundaries of knowledge concerning TOC. I continue to do so, and will probably do so until I can no longer think! I have spent many years researching TOC applications, TOC techniques, and how the TOC approach can really develop manufacturing industry to attain high levels of performance. Those aspects of my work that have already been published outline some of that research, some of that

xvi

knowledge; now, in this book, I want to set out just how TOC can deliver what I call constraint management within the manufacturing industry. This is where the boy takes up the mantle of those who have gone before. Manufacturing industry fascinates me. I can think of no greater privilege than being allowed to walk around a manufacturing plant and see how the people working there try to achieve their goal. Taking raw material of various types and turning that into a product that people want to buy, to do so whilst making a profit and, at the same time, ensuring that those who work within the company are able to share in the success, is one of the great challenges in our modern world. At the same time I find myself filled with frustration at the many daft ideas that seem to gain credence simply because there are apparently no other alternatives. When the pressure is on I have found that many manufacturing managers will clutch at almost anything that comes along which suggests a better way forward. Often the new idea results in problems far worse than the original illness, but that has never stopped people from pursuing such approaches. When the new approach is entirely in line with accepted practice it is always much easier to implement. The fact that it might not actually work is not considered at all. This suggests that many people within manufacturing industry have no real process of evaluation to determine the ability of any new solution actually to deal properly with the current problem set. Having spent many years within manufacturing industry, working with managers at companies throughout Europe and the USA, I came to the conclusion that the current approaches to solving the problems were falling far short. The time was right for a new approach, one that challenged all the existing rules and policies and paradigms, one that offered a new way forward but also could withstand fierce scrutiny. From the outset of my involvement with TOC I felt that this approach would change the way manufacturing companies were managed. At the same time I was also aware that it represented a fundamental challenge to accepted norms of manufacturing management and measurement and would therefore be faced with a dramatic struggle for supremacy. That struggle is still on-going at the time of writing, but I feel that the end is in sight. Today there are three great movements coming together to address this problem. The area of quality control is now, with the development of 6 Sigma and the whole collection of quality control tools and techniques such as SPC, showing how to make products with zero defects. The area of lean manufacturing with its associated tools is showing how it is possible to first find and then eliminate waste. These two movements create the foundation, the springboard, for growth. Constraint management, with roots that lie in the Theory of Constraints, shows how to make money through developing the strength of the company. In combination these three movements deliver, to my mind, the only way to develop properly the supply chain, the true value stream of any company.

1 Understanding the pressure to succeed

Introduction to the world of manufacturing This chapter is all about pressure. Pressure to increase shareholder value, pressure to increase sales, pressure to reduce costs, pressure to increase salaries, pressure to introduce new products, indeed a whole host of pressures that all combine to make the life of the average manager difficult. It is also about some of the harsh realities of manufacturing today. Long gone are the days when you could set up the plant to make a product and leave it for days at a time. Today, when manufacturing plants must be highly flexible, capable of making a range of products, where swift changeovers are not just nice to have but a necessary condition for success, the ability to manage whatever capacity the plant has, with little or no waste, is now paramount. Today products do not have the same lifetime as they once had. In the mobile phone industry, for example, we started working with one company in 1994 when it was still possible to release a product and wait almost a year or more before the next came out. Today that timescale has been reduced to a matter of months, and the complexity of the product has increased almost exponentially since then. The range of features that must be part of every mobile phone today are beyond the belief of the designers of mobile phones eight years ago. The ‘cost of manufacture’ must now be measured in the ‘small dollar’ numbers rather than the tens of dollars of the recent past. Of course it might be observed that the traditional method of calculating the ‘cost of manufacture’ is still based on cost accounting allocation principles, something which I, and many others, have been trying to change for many years. Either way, the challenge is still to reduce the real price paid for manufacturing each and every product. As we shall see later, reducing cost is only part of the game; the real focus should be on sales. This is a central issue within this book, and also within the Theory of Constraints body of knowledge upon which this book is based. We are all familiar with the product life cycle curve (see Figure 1.1). But what this curve represents today is very different to, say, twenty years ago. The time for each stage has been reduced. Yet in some cases the time it takes to develop a new product is longer than the time it sells in the market. With current marketing

2 UNDERSTANDING THE PRESSURE TO SUCCEED

Figure 1.1 Typical product life cycle

techniques, it is not unusual for demand totally to outstrip capacity, leading to stock-outs and lost sales. Remember, these lost sales represent the highest level of possible profit and to lose them can seriously affect the long-term viability of both product and company. At the same time, due to this pressure the parties involved really do stretch across the supply chain in a more obvious and dependent manner than before. There is no time left to change from a poor supplier to a better one, no time to change from one distribution channel to another, as the window of opportunity where sales revenue can be maximised may only be a matter of months. Concurrency also plays a part in creating more pressure as there are, at any one point in time, more products being developed, more products being manufactured, being distributed, than ever before, and this demands far greater co-ordination than was the case a few years ago. The decisions that are taken at any point along the chain must contribute to the achievement of the goal of the whole chain and not just any one single point along the way. This in turn demands a process which can deliver this level of decision-making and coordination. People throughout the chain must be able to determine the impact of their decisions upon the behaviour of the whole chain and not just some local performance measurement. In such environments there can clearly be no waste, but the term waste is in need of better definition than seems to be the case today. In our research we have found that the level of friction between the various elements of the supply chain contributes to the majority of waste found in companies today. Given the example of the mobile phone industry and using Figure 1.1 as a reasonable description of the product cycle, where once the X-axis would have been measured in many months, almost years, it is now measured only in months. The same applies to the car industry. When the budget for the development of a new car is almost the same as the value of the company there can be no mistakes. The pressure is on from the moment the decision to design a new car, or indeed almost any product, is taken.

UNDERSTANDING THE PRESSURE TO SUCCEED 3

Figure 1.2 Moore’s contribution

What the figure also says is that, over time, the sales derived from any product will inevitably fall. As already noted, although the figure is still correct in most cases, the current reality is that the timescales have shortened dramatically. Yet many companies still seem to take a great deal of time to introduce new products to the market. In the work we have done within new product development the degree of urgency you might expect has still to find its way to the lab. I have come across people in research and development areas who still think that they can continue in the same old ways, and this in some of the top high-tech companies. Often the products they are developing are impossible to manufacture because they still do not involve the production people as they should. It is as if the whole field of concurrent engineering has passed them by. When working with these people it seems almost a shame to disturb their cosy environment! One way to try and manage the demand for shorter development times, and meet the ever-shortening life cycle, is to adopt new technology. But here, once more, there are problems. Figure 1.2 is probably one of the most important of recent years. Though not entirely new, Moore (1999) changed what had been a fairly normal understanding of technology take-up by adding the gap situated within the early adopters area, a gap he called the chasm. This was both new and innovative. Now it was possible to understand why some products, in particular technology-based processes and services, failed to make the inroads expected: they failed to cross the chasm. Sometimes they actually crossed the chasm, but because they did not know it they failed to capitalise on their success and they fell back. I have seen companies, post-chasm, who have recognised this fact and really moved forward, and others, pre-chasm, who have tried and tried to cross but simply could not see what was staring them in the face; they had no mechanism to cross over. They were stuck pre-chasm and that determined their performance for some considerable time. There is, within the manufacturing industry, great pressure to implement new technology, to try and take advantage of the benefits

4 UNDERSTANDING THE PRESSURE TO SUCCEED

it offers. Moore describes this kind of market, but he argues that for any technology to be truly effective it must cross the chasm into the area where the vast majority of the market lies. I have applied this model to the technology called ‘constraint management’ over the last four years. During that time I have examined the market take-up of the original product known as the Theory of Constraints (TOC) upon which constraint management is based. TOC has proven to be very attractive to the ‘techies’, the people within organisations who like anything new. They will try it out and be relatively unconcerned, but almost certainly disappointed, if it does not work. However this market is quite small. The real pay-off for any technology does not lie here; it is great for testing the market and the product itself, but to gain worldwide acceptance any technology requires the capability to cross the chasm. In the case of constraint management there has been considerable interest from many of the major companies throughout the world, such as GM, Intel, Seagate, Lucent Technologies, Philips, Security Federal Bank and many, many more. These companies have been able to derive some improvement from the application of constraint management, but there is still a great deal of work to be done. I am of the opinion that constraint management has crossed the chasm, as evidenced by the companies using the approach. However, it has only just crossed, and there is still a great deal of work to be done to reinforce the standing of constraint management and take it further into the mainstream. A research document published by the Engineering Employers’ Federation in the UK in November 2001 and entitled Manufacturing at the Crossroads highlighted the fact that the Theory of Constraints, along with lean manufacturing, was a leading factor in the ability of the USA manufacturing industry to create wealth. It is to help this process of widening the application of constraint management that this book has been written. Of course constraint management is not the only approach being used within the manufacturing industry today. Key themes in manufacturing There are many themes, tools, techniques and so on current within the manufacturing industry today. The catalogue of differing tools and techniques seems endless, from MRP (materials requirement planning) to JIT (just in time), from TQM (total quality management) to APS (advanced planning systems), from OPT (optimised production technology) to MRP II and so on. This endless stream of three letter acronyms has supported many training programmes, many consultancy projects, a great deal of investment, but has delivered only a limited degree of success. Even the techniques that gained such momentum in Japan such as JIT and TQM have, to my mind, not achieved the level of bottom-line success they might have done. Today the implementation of JIT and TQM has not prevented a great deal of the Japanese manufacturing industry from failing to maintain the improvements of the past. At the same time the onward march of technology has changed the face of manufacturing in ways we are only just

UNDERSTANDING THE PRESSURE TO SUCCEED 5

coming to recognise. The globalisation of manufacturing industry, the way in which the giant manufacturing companies span whole continents, changing the way even governments can control their activities, has created a new dimension to the global economy. Globalisation of the supply chain: consolidation and sourcing The last ten years or so have seen a dramatic increase in the number of companies who are sourcing material and components from all around the world. No longer are the suppliers just around the corner. This places a huge strain on the systems used to purchase and deliver material at the right time, to the right location, in the right volume, at the right price and all without defect. This has enormous implications for the level of technology being used, not just within the primary company, but also for all the key suppliers and distribution channels. It also has implications for the sales and marketing people: just how well are they tapping into the chosen markets? Procurement has undergone some dramatic changes over the past few years, but these changes will pale into insignificance compared to what must happen in the future. The question remains, just how ready are the people in those areas, and will the systems and measures they use assist with delivery or prevent it? The driving force for this level of globalisation that is used most often is ‘lower unit cost’. In many companies there is now a drive to develop new supply bases and manufacturing facilities in Central and Eastern Europe and parts of the Far East, usually China. The reason for this global shift is not the technological expertise resident within these countries, neither is it the excellent production facilities that already exist. In most cases substantial investment in technology transfer, in the creation of new manufacturing facilities and the education of a new workforce are the order of the day. The pressure for this global shift in sourcing both supply and production capabilities comes from the desire to reduce the ‘cost of labour’, or ‘unit cost’ or ‘cost per product’. Complex spreadsheets have been developed to show beyond all reasonable doubt that the end result of this shift will be a dramatic reduction in at least one, maybe all three, of these costs, and always to three decimal places. This must be the ultimate triumph of precision over accuracy, and all based on the erroneous assumptions of costbased allocation methods. I was recently told that an as yet to be built facility in China, with people yet to be trained, would produce mobile phones at half the price of the plant in the UK, and upon this information the UK plant was closed, with the subsequent loss of jobs and skills. At the same time as this spread in globalisation, the application of new technologies to manufacturing is developing at an enormous rate. Almost every day new technologies for communication are unveiled, and the days of MAP (manufacturing automation protocol) and TOP (technical operations protocol) seem to be almost light years ago. The application of e-commerce is now

6 UNDERSTANDING THE PRESSURE TO SUCCEED

dominant and will continue to be so. Where companies are now sourcing over wide geographical areas, this use of technology is a necessary condition for the proper level of control to be achieved. Indeed, throughout this book the relationship and importance of e-commerce to constraint manufacturing will be a continual theme. This is true for each of the key functions such as new product development and production, and on throughout the rest of the supply chain. We have been involved in recent years in the implementation of project management systems that use the web for project planning and the updating of tasks. This was a necessary condition for the company which was spread over two continents and four time zones. This level of technology will soon shift from being the exception to the norm, and it will only be those companies who understand this shift and can take advantage of it that will benefit. Supply chain/network management To my mind this is where the most changes have taken place in the minds of almost all manufacturing managers. This is also the area which requires much more attention than is currently the case. I have used the term revenue chain in other work and all the implementations I have been involved in. This is because I find the term supply chain insufficient when discussing the whole enterprise and the relationships it has with both suppliers and customers. We describe the revenue chain as starting with the client and ending with the client. This might seem rather self-evident, a statement of the obvious, yet even today many companies see supply chain management as controlling suppliers. In one case all the company did was to pick a single supplier for each component, irrespective of capability. They then argued that they had implemented ‘supply chain management’. Within the real supply chain, or revenue chain, there is an explicit recognition that it extends from client, or end user, to supplier and back to the client. As the customer places the order there is a whole chain of events triggered all the way through to delivery of the product ordered to the customer. This chain is often poorly identified in most companies; they simply do not know the various components of their revenue stream. They often think they do, but that is not the same as knowing and the steps they take to understand and improve the revenue chain soon betray their lack of understanding. This comes as no surprise to those involved in constraint management. The whole structure of the measurement system, with the constant focus on the performance at local level, actively prevents the type of global focus being described here. Of course, the development of enterprise resource planning (ERP) systems, which enable managers at all levels to see and make decisions based on the global impact, offers new hope. However, as argued strongly by Goldratt et al. (2000), because ERP systems are typically implemented with both the wrong focus and no changes to the measurement system, they fail to deliver. At the MIM (Managing Innovative Manufacturing) conference held at Aston University in 2000, one

UNDERSTANDING THE PRESSURE TO SUCCEED 7

speaker noted that some 60 per cent of all ERP implementations within the UK had failed to deliver the expected bottom-line results claimed by the sales people. But ERP, in combination with the Web, is a real advance if, and only if, we understand the nature of the revenue chain, understand the impact of the laws of constraint management, and change the way we think. Not a lot to ask is it? Chain or network? In fact what is being described is not really a chain at all but a series of connected networks. The research that we have undertaken has identified three key networks within the manufacturing industry. Material flow networks These networks are a function of the movement of material from the supply base to the end user. This is essentially a one-way movement. Material travels from the supply base all the way to the end user. This is the easiest part of the supply chain to understand. It is the one given most prominence in most of the writing that surrounds this area. It is, however, only one aspect, and it could be argued that the other two are more important, though in fact they are all part of the same system and cannot be divided. Financial flow networks These networks are a function of the money that the system generates and the assurance that what is due to the various participants of the system is received relative to their contribution. This is also essentially a one-way movement, typically flowing in the opposite direction to that of material. We have found many companies where the actual flow was very poorly understood. Often the various departments of the organisation dealing with this aspect made decisions that resulted in the opposite of what was expected. Purchasing departments slowed down the approval of purchase orders so that budgets were not compromised, even though line departments might be starved of key information or material as a result. We have also come across accounts departments that slow down payments to suppliers in order to improve cash flow, but which in reality cripple the supplier company and create a high level of frustration and animosity. This is where the norm of 30 day payments often extends to over 120 days, and the primary culprits are very large organisations playing this game with very small organisations. This kind of behaviour is hardly conducive to good supplier partnerships. There is one other aspect of financial flow networks, which is often missed, and that is the true size of the various parts of the organisation in financial terms. We have come across managers who measured the scale of their departments by the combined level of salary within the department. Sometimes a level of budget

8 UNDERSTANDING THE PRESSURE TO SUCCEED

would be added, but still the financial level was felt to be quite low. Once the financial mapping had been accomplished, many managers saw for the first time the real scale of money passing through their area and adjusted their opinion accordingly. Information flow networks These networks are a function of all the data that are required to ensure that the product is properly delivered to the customer. This is a multi-way movement. Until recently the information systems in use were essentially local in focus and dissemination. Today, with the arrival of ERP systems, much improved server technology and the Web, it is possible to have information systems that operate globally, throughout the whole of the chain, and offering information in such a way that all managers making decisions can see the impact of that decision before it is implemented. Information flow is a multi-way process. In the past each department was a silo, each with its own well of information. These silos are very much like the medieval castles of old, each with its baron and each with a well of water to sustain the people. Whenever visitors came to the gate asking for a drink, they would be given a small cup, and never the freedom to take what they wanted. The same seems to be the case with the information held within each silo. The manager represents the baron, the people within the department those within the castle, and the visitor anyone who came calling. Only sufficient information is given out, simply to ensure the visitor moves on quickly; once more the whole well is rarely made available. Of course the only exceptions to this are those visitors from corporate! Today, given the pressures that exist, and the realisation that the chain approach is the only valid option, the notion of independent wells no longer holds water. There is only information, as simple as that. It is a common treasury for the well being of the whole chain, both internal and external members. There can be no ring-fencing, no barriers to the free movement of information. It must be able to flow, without hindrance and without amendment, to any other part of the chain. The technology to enable this to happen is already available. What still prevents it from happening is the behaviour of the people and the way they are measured, in financial terms, as if the silos were still the only way to operate and manage organisations. This is a major barrier to change in many organisations. The three types of information flow are shown simply in Figure 1.3. The key is network management, as each manufacturing company is part of a production system combining all these networks. It is essential that each network is managed effectively in order to achieve the goal of the whole system. In many companies we have found that even the notion that there might be such networks is foreign, and therefore the only way to manage the system is through the local view that each manager has. This leads to high levels of local optimisation, which often results in major problems within the whole system. As noted earlier, the

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Figure 1.3 Network diagram

introduction of ERP systems, which are capable of working in all three networks, thus allowing managers to make decisions based upon knowledge of each of the networks and how they are interacting, has changed the playing field. Yet research also shows that the expected bottom-line improvements have not been realised. As noted above, Goldratt et al. (2000) demonstrate this aspect clearly in their book Necessary but not Sufficient. It is the bringing together of all of these elements that forms the primary focus of this book. It is only when the technologies are properly harnessed that the real nature of the manufacturing organisation is recognised, that of comprising a series of networks, and that real progress can be made. But this requires, demands, a new way of thinking, which is what this book is all about. Lean thinking It is not the intention here to cover in great detail what authors such as Bicheno (2000) and Womack and Jones (1996) have already comprehensively described. Sufficient to allow setting lean thinking in context, sufficient to explore the links between constraint management and lean thinking, which is the primary aim here. Womack et al. (1990:13) defined ‘lean production’ when they proposed: ‘Lean production…is “lean” because it uses less of everything compared with

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mass production—half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half the time. Also, it requires keeping for less than half the needed inventory on site, results in many fewer defects, and produces a greater and ever growing variety of products.’ This must have seemed an amazing definition in 1990. Even today it can still be seen as revolutionary. However, as we shall see later, a constraint management perspective would argue caution in a number of respects. The primary focus of lean thinking is the eradication of waste. Ohno (in Bicheno 2000) defined seven types of waste: 1 The waste of overproduction: this is defined as making too much, making too early, a just-in-case syndrome. Many of the measures that we find within production environments lead to excess product being made, just to keep profits up according to the rules being used. Overproduction is also a function of timespan. In one company production for the day was set, and any material pulled forward from the following day’s schedule would have been termed ‘overproduction’. Overproduction can be seen in production environments when the waves of material are forcing their way through the various machines and resources. This all adds to lead time and degrades the due date performance. Of course, as we shall see later, the many efficiency measures in use within manufacturing also force overproduction. In keeping expensive machines working, in order to gain some supposed return on investment, inventory is sucked into production, not to meet orders, just to meet a rate of utilisation figure. 2 The waste of waiting: this is defined when time is not being used effectively. Note that what is highlighted is not the efficient use of time, rather the effective use of time, which is not the same thing at all. In many production environments, particularly where large batches are being used, inventory sits idle for long periods of time. David Marks, one of the UK’s leading exponents of set-up time reduction and batch environments, developed some years back a simple simulator that shows the effect of this waste very effectively indeed. In this aspect of waste, flow is interrupted, deliveries can again be late, and many times the process appears to be strangled. There is one aspect of this element that does require careful definition however. At a non-constraint resource there will always be a level of spare capacity, a period of time when work that should have been done has been done, and the next piece of work may not be due until the next day. This is not waste except in the sense that there is scope to find new products that might be sold using this spare capacity providing the capacity of the constraint resource is not affected. This will be discussed in more detail later. 3 The waste of transporting: this is defined as the excessive movement of product/inventory. This applies to both internal and external movement.

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Issues such as double-handling, large distances within the plant, which has implications for plant layout and so on, also play a role here. Again there are issues related to batch manufacture and the definition of a ‘batch’. Transfer batches are not the same as process batches, which may not be the same as release batches. In many constraint management environments the transfer batch is kept quite small in order to achieve short lead time and high due date performance (DDP). This might add to the level of transportation but is clearly not a waste. 4 The waste of inappropriate processing: this is defined as using one machine which can do many tasks rather than a group of more specialised machines. The application of a large general-purpose machine often creates a deviation in the normal flow through the plant; it creates, in many cases, a bottleneck due to the need to gain a return on the investment, coupled with the fact that in order to justify the new machine the smaller ones were removed, thus reducing flexibility. This is highlighted very clearly in The Goal (Goldratt and Cox 1984) with respect to the NCX 10 machine. This aspect of waste is also a function of the process capability of a machine: just how well does it produce parts and to what quality level? In many cases we have found that investment of this nature leads to more variation within the production facility, not less. 5 The waste of unnecessary inventory: this is defined as having far too much inventory within the system. Having large levels of inventory affects the quality performance of the company and reduces productivity. Inventory at too high a level will also extend the overall lead time and degrade the due date performance. The other aspect that is not always recognised is that the level of inventory has to be paid for, and thus costs are almost certain to be higher. This is in conflict with the notion that finished goods, and indeed work in progress, all measured at full or partial value can be seen as good by the financial measurement system. Many of the issues we have had to deal with within manufacturing companies are driven by this conflict. Issues such as obsolescence, difficulties of tracking quality problems, issues related to design flaws and many more have been identified in both this research and that of many others. 6 The waste of unnecessary motion: this is defined as the amount of movement operators have to make in the production process. It is a function of ergonomics within the workplace and is often completely overlooked. 7 The waste of defects: this is defined as the impact of defects upon the production process and the final product itself. The levels of scrap, rework, figures showing the capability of the maintenance system, the ability of the quality systems in place to discover problem areas are all part of this aspect. There are still many companies for whom the measurement of quality in terms of the product is still measured in units per hundred, where most world-class companies measure defects in parts per million. Even such

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simple tools as control charts are not commonplace in many manufacturing companies today. If we take the definition of lean production cited earlier and combine it with these seven types of waste, then many people would see this as a perfectly sensible way to improve. However, a constraint management perspective, with the focus on the impact the constraint has in any manufacturing environment, suggests caution. Too many people have gone down the path of cutting ‘waste’ only to find that the whole operation has been compromised. This is not the fault of lean thinking per se, more the fault of those who implement the words without understanding the underlying philosophy, coupled with the lack of a proper definition of the word ‘waste’. This can best be explained through the following example. The company involved is one of the big car companies, and the division was responsible for small parts manufacture. An example of misplaced focus We were involved in the implementation of the constraint management approach to production known as drum-buffer-rope (DBR) with a major car company within the UK. The company was familiar with the concepts, having already implemented the approach in other plants outside the UK. We were teaching a group of people, from shop floor supervisors to some middle/ senior managers, as part of a two-day workshop. They informed us that they were already implementing ‘lean’ and that they did not feel there was much to learn from our involvement. They did inform us that they were experiencing a number of problems with both suppliers and delivery performance. We carried out a simple analysis using the Theory of Constraints thinking processes (TOC/TP), which revealed that they were experiencing late deliveries from their suppliers and this was forcing them to reschedule the plant constantly. We enquired about what appeared to be a missing factor in their analysis, which was the level of raw material held at the plant. We were told that company policy had been to reduce substantially the level of raw material inventory held, in line with lean thinking, and that this was strictly measured. This one aspect led to regular rescheduling and the knock-on effect such changes have within the production area. When we looked at the delivery performance, it was no surprise to find that they often missed shipments to other plants. Again we asked if they were holding any finished goods inventory to protect their delivery performance. Once more they informed us that they were measured on inventory reduction and that the holding of finished goods was not allowed. The problem lay in the way in which these policies had been implemented. The senior people who had implemented them with respect to inventory reduction had failed to understand the systemic nature of their world. Reducing inventory before first gaining control over the supply chain only leads to the kinds of problems they were experiencing, similarly with delivery and finished

UNDERSTANDING THE PRESSURE TO SUCCEED 13

goods. The measures they had implemented simply reinforced the reduction of inventory. To them any inventory was bad and therefore any inventory within the system was to be rooted out. The problems of rescheduling and delivery performance were placed firmly at the door of production, but the solution lay outside, with the corporate people who had failed to understand the real impact of their policies. With respect to the suppliers, the company was continually penalising them but offering no help. With respect to delivery performance, corporate was continually penalising production, but again taking no steps to alleviate the real issues. What we tried to convince them of was that, before they start to implement such policies, they must be in control of their networks, the chains of material/financial and information that exist within, from supplier to client, and protect both the plant and the market until they are ready. If that means holding more inventory, then so be it. This is not inventory that can be described as waste, at least not yet; this inventory is a function of protective capacity. They were guilty of compromising their plant because they had failed to understand the real meaning of lean. Lean thinking is much more than just production, however, or the elimination of waste. It extends throughout the whole of the organisation; it affects the way new products are developed, how the supplier network is managed, how people are developed and so on. Manufacturing: a constraint management perspective Anyone who has ever been privileged to walk around manufacturing plants over the last forty years would quickly come to the conclusion that there might be a great deal of effort, a great deal of activity, but not always a high level of intelligence being displayed. When one considers that almost 90 per cent of companies are still in the business of stabilising their existing processes, it rapidly forces one to the inevitable conclusion that many manufacturing managers are using processes and ideas that have been around for much longer than forty years, in some cases more than a hundred years. Now I am all for the notion that if it isn’t broken there is no need to fix it, but it is equally certain that the environment in which many of the tools and techniques still used within manufacturing today were first developed has changed beyond all recognition. To keep using tools and techniques just because they are the standard way of doing things is grossly insufficient for the pressures of today, and may explain why the UK has lost a great deal of its industrial base. Of course not all companies operate this way: recent research suggests that 7– 9 per cent are engaged in optimising their processes. What this means is that they are trying to make what they have really work, challenging accepted practices and changing them when they are clearly no longer relevant to the environment in which they are being used. What is really staggering is that only 1–3 per cent are about significant restructuring. These figures were presented by the CEO of Rockwell at a conference in the USA in 2001.

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Figure 1.4 Core elements of constraint manufacturing

The history of the constraint management approach goes back to the book written by Dr Eli Goldratt entitled The Goal. Though Dr Goldratt had been involved with scheduling and related manufacturing issues before its publication, it was this book that changed the traditional view of manufacturing. A best-seller for many years, and currently selling at an enormous rate in Japan, the book is probably one of the most widely read within the industry. Since its publication in 1984 there have been more books from the same author, and many more from other authors, highlighting the various aspects of Constraint Theory and the applications that have been developed. The body of knowledge concerning the Theory of Constraints and the research carried out over the last ten years are now extensive, covering many different industries, including service industries, and are recognised as a major driving force for bottom-line improvement and change. Constraint manufacturing defined There are five distinct and important elements within the concept of constraint manufacturing: speed, reach, collaborative capacity, dealing with uncertainty and variation, and, finally, designing more for demand. Constraint manufacturing and speed Manufacturing today is all about speed—primarily in terms of speed to market with reduced cycle times, the compression of lead time, which in turns leads to value. This speed is not just in manufacturing, it is in all aspects of the company; from new product development to production, from sales to purchasing, from human resources (HR) to finance, no area of the company can avoid the challenges being set in the demand for increased speed. Today time really is money and those who have time on their side will always have the edge. Within the context of constraint management a key theme is that any

UNDERSTANDING THE PRESSURE TO SUCCEED 15

manufacturing company is really only ever selling time on the physical constraint within the plant, no more and no less. Speed is about ensuring the proper flow within the networks described earlier, finding the points of friction that prevent the smooth flow of material to the market, and the flow of money and information to facilitate the whole process. This depends upon a clear view of the whole chain, from supply to client, and the ability to align all decisions, all measures, all systems to that objective. Constraint manufacturing and reach It is all about reach—just how far do you reach? I have broken up reach into four distinct, though related aspects. The first is the obvious one of geographical reach. This is a function of where you feel your market lies in a physical sense. Many companies that we have worked with over the years have felt themselves to be dominant in their market place. One presenter told the Irish Manufacturing Conference in Dublin that his company had some 98 per cent of the market for his product range. Being surprised at this claim I asked him what he made and was told that the primary product was printed circuit boards. As I had never heard of his company I was surprised that he had such a large percentage of the world market. He then informed the conference that the 98 per cent market share represented the market within Northern Ireland. His idea of reach was rather limited. The second type of reach is market reach. I define this as the number of steps of the revenue chain affected by the company. Most companies will acknowledge that they have an effect upon their suppliers; they will also acknowledge a similar effect upon their primary customers, but what about the customers of the customers? How far into the market does the company operate, and how is it defining the market? Many times we have worked with companies who have claimed that they dominate their market, only to find that the market they are actually in is not the one they think they dominate. The kind of reach being defined here is one that recognises that serving the client base means helping the client to achieve more with its customers than any other supplier, thus locking competitors out of the revenue networks. Remember, this works not only forward towards the market but also back into the supply networks. The third kind of reach is related to process issues. This is about the adoption of the same focused decision-making process throughout the revenue chain. In the past we have been involved with major car companies in training supplier companies to use the constraint management approach simply because it makes decision-making throughout the chain coherent, focused and robust. The resulting reduction in friction and waste is a key aspect of raising revenue and controlling costs. The final reach is that of technology. This falls into two distinct categories: sustaining technologies and disruptive technologies (see Christensen 2000). Good technology reach is about pressing ahead with the sustaining technologies

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whilst at the same time creating the necessary infrastructures to examine and take advantage of new disruptive technologies. This final aspect of reach will be discussed further when we turn our attention to new product development in Chapter 4. Constraint manufacturing and collaborative capacity Manufacturing today is all about collaborative capacity—just how well do you work with your external and internal partners? When people talk about supply chain partnerships, part of the equation concerns the level of collaboration that is possible between two companies, supplier and customer. For example, within the motor industry many suppliers do not just manufacture the components, but design them as well, in full collaboration with the primary customer. This is of great importance if the supplier is able to assist with constraint operations. Equally, within the organisation it is possible for functions to examine their relationship with each other and determine how they can best meet the needs of their colleagues. Of course this assumes they know about the internal customers. In some larger companies we have found R&D people who care little for the manufacturing people, and vice versa. Often the physical size of the company prevents the day-to-day interaction that smaller companies are able to achieve. Collaborative capacity can only really come about when the supply networks are clear to all. The importance of web technology also plays a significant role here. Using systems that can link the various elements of the chain together is vital, especially when the collaborative capacity may be in a different geographical area and the importance of co-ordination and focus is increased. The application of web-enabled systems offers probably the only way forward in this environment. Constraint manufacturing and managing uncertainty and variation It is all about dealing with uncertainty and variation. This is hardly new, but then most of what I include within the term constraint manufacturing is not new. The works of Deming (1986), Shewart (1986), Juran and Gryna (1980) and many more have shown the need to manage uncertainty and variation far better than ever before. At the same time they also contributed to the development of tools and techniques to achieve just that. Even today it is surprising how many companies still do not have a clear understanding of the difference between common cause and special cause variation. The tools of Kaizen, the techniques of TQM are still far from everyday practice. Defects are still being measured in parts per hundred or maybe per thousand in many manufacturing companies, and this after years of research and publication and consultancy concerning the true impact of failing the quality test. Yes, it is true that expected standards have risen

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Figure 1.5 The core competencies of constraint manufacturing

substantially, but it appears that there is a still a great deal of work to be done in this area. Constraint manufacturing and designing for demand It is all about designing more for demand—just how quickly do you develop new products for the market? How in touch is marketing? How well has the market been segmented? How well does marketing dig out new niches which afford new opportunity? How well do they integrate with the people in new product development (NPD), both internally and externally? How quickly can they turn opportunity to financial gain? Once these questions have been considered, then there are the questions about the capability of the supporting departments, such as the drawing office and engineering, in terms of supporting the new products. The core competencies of constraint manufacturing So if we are able to define the primary components of constraint manufacturing and you recognise the importance of being able to achieve all of them, what are the core competencies required (Figure 1.5)? • Design competency—having the ability rapidly to reconfigure and deploy manufacturing capacity for new products. This is about the ability of the new product development teams to deliver, totally focused on what they have to contribute to the overall effectiveness of the system. This aspect will form the core of Chapter 4, which addresses the need for speed in new product development/project management. • Operational competency—having the ability to optimise the whole of the chain. The revenue chain is the most important element in determining both how the organisation makes money and where to focus efforts to improve that ability over time. This is covered in both Chapters 5 and 6, where the

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emphasis is on production capability and the importance of ensuring the product reaches the proper clients. It also includes the contribution of purchasing, planning and other supporting functions to delivering the product on time and in full, with zero defect. • Maintain competency—being capable of managing the whole process as a chain —effectively. Knowing where to focus requires more than just an ability to find the area of most leverage, it also demands on-going management skills, coupled with an analytical ability that appears to be lacking in many companies. What is being proposed here is a comprehensive set of tools for managing change, a genuine process of on-going improvement that is more than just a list of desirable outcomes, but a focused process that really delivers. This is also where such concepts as the creation of a learning organisation are so important. • Synchronisation competency—tight coupling of the whole chain/network. Without this feature the ability of the chain to deliver at the best level of performance will always be compromised. This applies to decision-making and problem-solving, it applies to data collection and analysis, it applies to all levels within the chain of companies and it demands systems to support this aspect. There are probably more problems associated with the lack of synchronisation and the resulting friction, which in turn leads to more waste than any other we have come across in our work throughout Europe. This is also the area of financial measurements and the key performance indicators, a set of global measures that inform anyone within the chain of the performance of the chain and where the problems lie. If these are not aligned, then the opportunity for mismatch in performance is high. To achieve these four elements there is, to my mind, only one game in town: constraint management within manufacturing, which is the primary subject of this book. Conclusions Defining the future is a fickle exercise, but already some themes are appearing on the horizon. The first is that through the wider application of technology in the form of ERP and e-commerce, to name but two, what is being created are Virtual enterprises’, defined as a temporary alliance between organisations with shared resources and competencies to give better reaction to market requests. Here costs, skills and access to markets will be shared, it is unlikely that there will be central offices, unwieldy hierarchies or vertical integration. The manufacturing enterprise of the future will comprise a temporary network of independent companies which agree to work and co-ordinate together. The number of companies using this approach already is also increasing, with many more talking about their achievements without fear. For some time companies using the constraint management approach would be careful what

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they said in public for fear of rivals using the same approach as a competitiveedge weapon. The reason given for this level of reticence was that, as it was really only common sense, they did not want to give away something so simple. They forgot the time it took them to see what they now call common sense and to realise that for many companies the real time to implement was dominated by the time taken to decide to proceed with the implementation. Results are often achieved within six to eight weeks of starting the education and training, and this in production, project management, replenishment, sales and marketing and so on. The production approach known as drum-buffer-rope often gives results on the bottom line in a very short period of time indeed. The timescale is therefore quite short if we only measure from the commencement of education. If we take the timescale from first introduction, perhaps in the form of a presentation to senior management, our experience is that we can sometimes wait for over eight months for the decision to proceed to be given. Of course the company is still suffering throughout that time, which means that the starting point for our improvement process is much weaker than if we had been able to start straightaway, and yet constraint management still delivers results.

2 The revenue chain and the impact it has

This chapter is primarily concerned with creating an understanding of the revenue chain as defined in the previous chapter. I use the term revenue chain in our teaching and implementation work rather than the more commonly used supply chain as it creates in the mind of the user the close association between the notion of the chain and the need to recognise the fundamental importance of money. Throughout the book I shall use both terms interchangeably. Defining the chain The most important piece of data at this stage is the map that shows how the system generates goal units. Remember, if the goal is not primarily about money, then the units of the goal will be different though the making of a profit might still be a necessary condition. The chain extends from the supply base right through to the market. It is not just existing clients; it is all past clients and the market where future clients are currently situated. The return loop is usually through sales and marketing back into the company, and maybe further back in certain circumstances. There are also some chains where the client is also the supplier. We carried out an implementation of the production approach with a company which made pattern books for the wallpaper industry. Their customers were the various wallpaper companies, who were also the suppliers of the most important element of raw material, the wallpaper itself. Figure 2.1 is a simple depiction of a typical revenue chain within a manufacturing company. Material flows from left to right and cash flows from right to left. The further to the right we look the larger the cash amounts, or at least they should be larger. Thus the role of our manufacturing enterprise is to ensure the smooth flow of material from the supply base to the market with the minimum of disruption and error, thus ensuring the maximum amount of money flowing back down the revenue chain. Sales and marketing, with their feet firmly planted in the market, are able to check the way the market is moving, and operate as a feedback system. In particular they are able to keep the new product development area alert to changes in product specification, product development and new products for the current or new range. This should also include not just

THE REVENUE CHAIN AND THE IMPACT IT HAS 21

Figure 2.1 A simple revenue chain

production utilising the current technology, but also areas where disruptive technology may affect the organisation. Supporting all of this activity are the functions such as purchasing, HR and finance. They each have a specific role to play and it should be noted that in all cases they are supporting roles, not leading roles. This is particularly true in constraint management companies. There are a couple of very important aspects to our chain. The first is that as a chain it comprises a series of interdependent resources and functions necessary for the proper operation of the whole chain. Thus measures must determine the operation of the whole and the contribution of each to the whole rather than the individual elements as stand-alone entities. This drives a stake right through the heart of most of the current cost allocation models in use today. Using the concept of strategic inflection point developed by Andy Grove (1996), I would argue that the current cost-based measurements have passed such a point and that they are no longer valid today for anything except reporting past performance; for decision-making and strategy development the new approach of throughput accounting is much more effective. Measurements Once the chain has been mapped, it is vital to understand the measurements that are being used. The organisation is a system, one that is capable of achieving more and more goal units, therefore the measures must determine progress towards that goal and the acquisition of the goal units. It has to measure the performance of the system as a whole, not the discreet parts, as that will only lead to potentially dangerous decisions being taken. The key measures in any constraint manufacturing environment will always focus on the progress of the chain towards the goal set for it. The focus to date within constraint management organisations has been, first, to maximise the sales potential of the organisation, then to examine the level of investment to

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meet that demand, and finally to examine the level of operating expense required to service that demand. That is the key order of focusing within any constraint management organisation. Currently within every manufacturing company there are a whole range of measures being used to determine progress. The bases for almost all these measurements, in particular those used for decision-making, are the cost accounting rules and procedures that have been around for quite a while. The problem with these measures is that the environment in which they came to prominence is no longer the environment of today. When variable costs were a substantial proportion of the total cost they had some validity. Today, when variable costs form quite a small proportion of total cost, these tools have lost their relevance. Goldratt and Cox (1984) proposed a different set of measures for determining progress within an organisation when they defined throughput (T), investment (I) and operating expense (OE) as the key measures for decisionmaking within any commercial company. Since then a number of writers have examined the application of what has become known as throughput accounting (TA) within the manufacturing industry. The first major assessment of TA came in 1995 with the publication of The Theory of Constraints and its Implications for Management Accounting by Noreen, Smith and Mackey. This book, researched by the authors, was the first real test of Goldratt’s financial measurements. It was followed by more detailed work from Smith (2000) in her work entitled The Measurement Nightmare, Corbett (1998) and his Throughput Accounting, and the work carried out by Swain and Bell (1999) in The Theory of Constraints and Throughput Accounting. This volume of published work serves to highlight the impact that TA is having in a number of major companies throughout the USA. It is not my intention here to cover once more all that has been published to date. Suffice to say that all I intend to describe should be sufficient to give the reader an understanding of why TA works in the systemic world of manufacturing today. For a deeper analysis the references cited are the best source. First some definitions: throughput (T) is usually defined as the rate at which the organisation generates money from sales taking away the truly variable costs attached to those sales. Investment (I) is defined as all the cash tied up within the organisation, and operating expense (OE) is all the money needed to turn I into T. Profit is calculated by taking global OE away from global T. Return on investment (ROI) is calculated by dividing profit by I and productivity is calculated by dividing T by OE. In the many companies in which I have implemented drum-buffer-rope, the constraint management approach to production, we have been able to calculate these measures on a weekly basis and this has enabled the top team to see what is really happening within their company. Swain and Bell (1999:14) highlight one of the key differences between throughput and traditional accounting when they state:

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TOC generally assumes a time frame for maximizing profits as a matter of weeks. The traditional measure of contribution margin assumes a time frame over several months. Consequently contribution margin measures assume direct labor costs as variable, whereas throughput margin measures assume direct labor to be a fixed cost. In considering OE, Swain and Bell argue that: ‘Operational Expense in TOC is the sum of all expenditures on production and administration activities other than expenditure on direct materials. TOC treats all costs (operational and direct materials) as period expenses’ (ibid.). One of the key aspects of the current generally accepted accounting procedures (GAAP) is the application of absorption costing, which typically requires an organisation to assign monetary values to both work in progress (WIP) and finished goods (FG) based on the level of direct labour, direct material and the overhead costs employed within the production process. Unsold FG remains as inventory. Swain and Bell (ibid.: 16) dissent from this methodology by arguing: These costs, rather than being expensed on the income statement in the period incurred, go on the balance sheet as assets. GAAP therefore rewards organisations that build inventory, even if the inventory cannot be sold. Hence when costs cannot be reduced, they can be hidden by increasing inventory. They conclude this analysis by stating: ‘Throughput P & L statements emphasize increasing throughput by maximizing the use of bottlenecked operations or remaining constraints. Emphasizing throughput in organizations also encourages decreasing inventory and increasing the rate of production’ (ibid.). Note one aspect of relevance to lean environments. With the focus on waste as a central theme in lean manufacturing environments, if the GAAP tools remain in force then there is bound to be a conflict between reducing levels of inventory, which is central to lean, and maintaining high levels of inventory, which is a theme of absorption costing. In one of our implementations of constraint management within production we reduced the levels of inventory quite substantially, improved the due date performance of the plant, reduced the overall lead time, increased the inventory turns within the plant, gave greater satisfaction to the existing client base, and yet fell foul of corporate measurements in that the reduced level of inventory made the plant appear uneconomic. The fact that it was making money for the first time was not reflected in the corporate measurement system. Noreen et al. (1995) set out to visit a number of sites that were using the TOC approach. They included European sites as well as those in the USA. This was the first independent study of TOC, and had the specific focus of financial measurement. What they found was that: ‘Companies that used TOC consistently

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generally reported impressive gains in financial results and in key operating statistics such as cycle time and due date performance’ (ibid.: xxiii). However, not all was sweetness and light. They also found sites where the results were disappointing, to say the least. They explained this by arguing: ‘At sites where top management did not view the business from a TOC perspective, there were usually—but not always—problems. The biggest problems were with managers who continued to evaluate production managers based on measures of efficiency rather than profit’ (ibid.). Noreen’s group found, as did Swain and Bell much later, that the TOC approach, as with total quality management (TQM) and just in time (JIT), is essentially ‘inconsistent with common management accounting practices such as absorption costing and standard cost variance reporting. The biggest single reason for this incompatibility is that both absorption costing and standard variance reporting create incentives to produce excess inventories’ (ibid.). What this means in practice is that when absorption costing is applied, having more inventory gives an apparent reduction in the average cost of goods sold. When production volumes are greater than sales volume the fixed costs are spread over more product units. Therefore under a standard cost variance reporting environment any department with a fixed labour workforce can improve its efficiency only by producing more product. In many companies this is translated into keeping people busy irrespective of whether the material is needed or not. We have also found this to apply to the project management environment and throughout many of our other services. TOC companies do not use absorption costing, preferring a variation of variable costing where the assumption is that only the direct material used within the final product is a variable. Noreen’s group argued that: ‘Variable costing is preferred to absorption costing under TOC for three reasons: [i]t does not create incentives to build inventories; [i]t is considered more useful in decision-making; [i]t is closer to the cash flow concept of income’ (ibid.: xxiv). Corbett (1998: 8), when considering the need for a progressive manufacturing base, argues that ‘manufacturing managers are being asked to make important decisions in spite of available cost accounting information, not because it is relevant’. The objective of management accounting should be clear. The assumption is that every organisation requires an information system which provides data to help guide and motivate everyone to move the organisation towards its goal. Therefore the goal of management accounting should be to provide managers at all levels with the information necessary to determine progress towards the goal, and to improve the level of decision-making with respect to the goal. Note that this is an holistic view, it encompasses the whole of the supply chain, both internal and external to the organisation, and places no relevance upon the performance of the individual links. Corbett (ibid.: 16) highlights what he feels to be the magnitude of the flaws in cost accounting when he states:

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Cost accounting tries to minimize product’s costs. This happens because cost accounting is based on the assumption that the lower the cost of a product, the greater the company’s profit. As the product cost results from the product’s use of the company’s resources, one way of reducing the cost of a product is by reducing its process time on a resource. Then, through the use of simple examples, Corbett demonstrates clearly the fallacy of these assumptions and concludes by saying: ‘cost accounting does not view the company as a system: that is why it does not differentiate between the company’s resources’ (ibid.: 18). The problem with problems Once the chain has been mapped and the measures determined, the next step is to verify the problems that everyone acknowledges exist, and the impact they have on the chain, as highlighted by the measures. Here we go round the various departments, suppliers and clients identified through the mapping exercise and ask questions about the level of performance they receive, and the level they give. The intention is not to talk about the last major crisis, but to discover the daily issues that have to be dealt with but rarely appear on the corporate radar system. This aspect will be more fully developed in the next chapter. A quick snapshot of the organisation Though there will almost certainly be a need to analyse fully the revenue chain, there are some quick approaches to determine, first, where the constraint lies in a rough analysis, and, second, where some short-term actions might be taken to give those in the organisation a breathing space and time to analyse what is really happening and develop a robust solution. This can be achieved using the following process. On going round any production facility, as an example, just ask a few people about their daily work and the issues they face, nothing too extreme. Quickly you will have gathered about eight or nine common issues between them all. Write these issues down and make sure the statements are clear, that they only contain one element and no causality, and could be verified by someone else going round and carrying out the same exercise. This last dimension is about repeatability. Once you have a set of issues, clearly verbalised, then, using one of the constraint management tools known as the cloud, you are able to create a simple and quick analysis of the problem set. Typically within three to four hours patterns will have appeared, deeper causality been revealed, erroneous assumptions surfaced, and possible solutions identified. The cloud technique is fully described in Chapter 3. This capability is easily taught and gives an amazing insight to any organisation within a few hours, or even minutes, when skill with the cloud technique has been developed and practised.

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The notion of the constraint If our analogy of the chain is valid, then so is the notion of the constraint —the weakest link in the chain. For many people a constraint is simple to understand: too few checkouts at the supermarket, road works with traffic lights, a machine with limited capacity within the production process are all forms of constraint. But within constraint management greater understanding is required, not least because there is more than one type of constraint. Typology of constraints There are basically three different types of constraint that we have identified in our research. The first is a physical constraint. This is usually defined as that machine which has less capacity than the other machines and also less than that of either the market or the supply base. There are quite a number of activities that become constraints almost by default. Heat treatment is a commonly found constraint within many production environments, simply because the normal process time of the operation is much longer than all the other processes. In many microprocessor fab plants the constraint tends to be the camera that does the photo etch process. This is usually because they have chosen that part of the process to be the constraint. The notion of choosing where you want the constraint to be sounds counter-intuitive until the logic is explored. There is also the distinction between constraint and bottleneck. A bottleneck is a specific form of constraint, where the demand placed upon the resource is greater than the available capacity in the available time frame. A constraint is simply the resource with the least capacity, though it can still meet the demand placed upon it. One final point about physical constraints: in most of the companies we have worked with over the last ten years the number of real physical constraints identified is quite small. More often than not, the physical nature of the constraint we have identified is due to the impact of a specific policy, or set of policies, within the company. Therefore the second type of constraint is a policy constraint. In our research we have found that the majority of constraints fall into this category. Many of the examples we have found centre around the rigid application of cost-based measures, which are then translated into policies that prevent performance being improved. For example, we have found companies that have implemented a ban on overtime. This might seem sound when money is tight, but consider this: what do you do when an urgent order is due to go but as a result of a problem an hour’s overtime is required, the alternative being that it waits until the next working day and is therefore late at the client? Many of the managers we worked with said that allowing overtime was simply not permitted; it was easier to annoy the client. We have come across policy limits on the number of shifts, a ban on recruitment and many other examples, all where there was a clear market and confirmed customers. We have come across purchasing policies that have turned

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off the suppliers, even though production relied almost completely upon them. In one company the group purchasing people decided to intervene in the local material control department in order to achieve a reduction in the cost per part purchased. This centralisation would also reduce overhead costs due to the redundancy of the existing people. The result was that some suppliers refused to continue working with the company, others sought as quick an exit as they could, local knowledge and quick response was lost, quality became more varied, supplier relationships destroyed, and throughout the whole exercise the group purchasing people were being heralded as proving to be most effective in driving down costs. The real impact only became apparent some time later and most of the policies had to be changed, but by then the damage had been done. What typically happens is that policies create, or exacerbate, physical constraints, often turning them into bottlenecks. The problem here is that identifying policy constraints is not that simple. The third is a paradigm constraint. A typical finding of our research is that this constraint is visible and highly effective in most organisations: effective in locking the organisation into poor performance. This constraint was fully described in my book Unconstrained Organisations (Hutchin 2001b). Many of the policies that we find in manufacturing companies are driven by the paradigms people have about how to run such companies. Now many of the paradigms people have are perfectly valid but, equally, many have lost their relevance and require to be changed. However, often these paradigms have become ingrained over many years, the people who hold them worked their way to the top using them, they are not ready to give them up just because they are no longer viable or true. The policies that we come across have been created by the paradigm of the person creating those policies. If the paradigm is no longer valid, then neither is the policy. Herein lies one of the most difficult areas of change management. The five focusing steps of TOC revisited 1 Identify the constraint—this might seem obvious but still many companies do not bother to analyse their operations in order to identify the constraint that must exist by definition within their organisation. Alternatively they argue that they have so many constraints, and they change so often, that it is of little importance to spend time doing this. This step of the five-step process applies to both physical and policy constraints. Trying to identify paradigm constraints requires great caution and care. It is very easy for the person concerned to feel threatened by this activity and therefore to build even larger and more impenetrable barriers to change than before. In most of our work within manufacturing industry we tend to focus only on physical and policy constraints and use the Socratic process to enable the person to find his or her paradigm constraint for themselves.

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2 Exploit the constraint—when applied to a physical constraint the meaning of exploit is simple: get the most you can out of the constraint without creating more problems. This means that the constraint is where all statistical process control (SPC) starts, it is where all the TQM methods are first applied, it is where the available capacity is utilised to a high level, typically greater than 80 per cent, but usually not more than 85 per cent. The constraint must still have maintenance scheduled in, it must be checked for tolerance compliance and so on. This means that there will always be a level of capacity retained to protect the constraint. The constraint schedule must reflect this in its construction and validation. When considering set-up reduction, this is the first place to focus, as any reduction of set-up at a nonconstraint will have no overall impact. In one company, which operated a single shift policy, they had some forty hours of available capacity on the constraint. Once the initial analysis had been completed we discovered that the constraint was only working for some eighteen hours. Even allowing for set-ups to take place this still meant a substantial amount of time being lost, genuine waste. Often material did not make it to the constraint on time, even though all the other machines had more than enough capacity. Often the people responsible for set-up would finish what they were doing on another machine before moving to the constraint machine. Often the constraint had to work on parts that had been damaged after completion at the constraint, thus robbing it of more time. 3 Subordinate to the constraint—this is a tough call, as will be seen throughout this book. Subordination means what it says: everything else in the organisation must become subordinate to the needs of the constraint. This includes the measurement systems, the HR policies, the top management team and the shop floor. It could be argued that the rest of this book is about the importance of subordinating to the constraint, whichever type it might be. 4 Elevate the constraint—once the first three steps have been achieved, it is possible to feel confident that control over the whole chain has been achieved. The next step is to elevate the constraint such that the whole organisation is able to improve performance substantially beyond that already achieved. Elevate is about growing the business, using the constraint as the lever; it is about taking the company forward and continually using the process to check the impact of the decisions being taken. This is where the information systems really come into their own. 5 Prevent inertia—go back to step 1—it is amazing, and frustrating, to find companies which, once they have gone through the first four steps, fail to check whether the constraint has moved. They keep on improving what has ceased to be the constraint, but feel warm and comfortable about doing so. For real improvement it is vital that the first step is carried out once more, and so on. This is what a real process of improvement is all about, a continuous process.

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The laws of constraint management The research that underpins both this book and my previous work highlighted the existence of certain laws that affected all systems being examined. These came to be known as the laws of constraint management. There are seven such laws and they apply to all systems. The first law of constraint management is that every organisation is a system comprising interdependent elements that form a revenue chain. This is hardly a new idea; systems theorists would recognise it as simply a statement of the obvious. However, in my research, focusing as it does on current manufacturing processes and measurements, the notion of a revenue chain is far from the forefront of thinking. The dominance of the cost accounting measurement system means that the interdependence between the elements is typically ignored or dismissed. Each of the key elements within the system have a degree of interdependence that many of the measurement systems in use today tend to ignore. This means that most manufacturing companies operate as if they comprised discrete elements which exhibit no dependency at all. This is a dangerous position to be in. Also much discussion is given over these days to a description of what is typically called a ‘supply chain’. This, though valid, does not capture the real importance of the chain that clearly exists, hence my use of the term revenue chain, which highlights for all to see that we are talking about money. The second law of constraint management is that the ability of the revenue chain to maximise performance is determined by the weakest link—the constraint. The notion of the limiting factor has been around in management accounting for many years, yet the obvious next step of applying that knowledge to the organisation often fails to take place. The dominance of cost accounting in the area of decision-making leads to the continued notion of independence between elements, which, though clearly not true, still determines many decisions. The constraint management approach demands a shift in thinking to one that recognises the fundamental impact of the constraint on revenue generation and the associated dangers of ignoring that reality. This means that the constraint is the most important dimension of the whole chain in terms of performance. The constraint simply determines the overall performance of the whole chain, no matter what. It is often said that you cannot buck the market: well, you cannot buck the constraint either, whether you believe in it or not.

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The third law of constraint management is that the constraint is the primary location for both focus and leverage for the improvement of the overall performance of the system. If the existence of the constraint is accepted, then the next logical step is to use that as the basis for driving an improvement process. There seems to be little point in improving any other area than the constraint unless there is good reason to do so. Such good reason only comes from a thoroughly developed analysis of the current situation using only a powerful set of logical thinking process tools, such as those within the constraint management thinking processes (CMTP). An example of addressing a non-constraint is when the buffer management system highlights a persistent buffer violator, defined as another resource that could so easily develop into a secondary constraint, which, in combination with the original constraint, creates a genuine bottleneck. The fourth law of constraint management is that improving any other link in the chain does not improve the overall performance of the chain itself. In many organisations we come across numerous improvement projects going on. These usually tie up people for considerable amounts of time in addition to their normal duties. Each project is addressing at least one current problem within the organisation as a whole. Yet in most cases there is little or no improvement in the bottom-line performance of the organisation following the completion of the project. As there is no process to identify the constraint of the organisation, there is no focusing capability to say which areas should be addressed and which can be safely left alone; hence the assumption that any improvement at a local level will translate itself into an improvement at the global level of the organisation. This is simply not true. All that has been achieved is a waste of resources, a waste of people’s time and knowledge, and high levels of frustration in those who had to comply with the project, knowing it was unlikely to make any difference. This again contravenes both lean and constraint management thinking. In many organisations we come across all kinds of improvement projects being undertaken, new machinery being purchased, levels of investment increased, but rarely is the question asked: Is this project activity on a constraint or a non-constraint resource? If it is a non-constraint, then the likely improvement on the performance of the whole chain is zero, even though the local performance of the resource has improved. In some cases we have even found people who have approved capital expenditure but have no idea whether they are improving a constraint or non-constraint area. It almost beggars belief, when companies are under such pressure to control costs and invest wisely, that so much money is thrown at non-constraint improvement.

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The fifth law of constraint management is that subordination to the constraint, in terms of the measurement system, the policies of the organisation, and the way in which the people operate, is a fundamental requirement of managing the chain. This is a tough call. Subordination is perhaps the greatest challenge facing those managers who wish to implement constraint manufacturing. In many companies we find people ready to accept the ideas and concepts of constraint thinking, ready to implement constraint management solutions, yet when the going becomes tough revert to the previous practices. Suddenly the efficiency syndrome returns, local optima returns, decisions are no longer based on global impact, only local. This can often occur when corporate pays a visit! Under the regime of subordination it is vital that everyone complies with the chosen way forward, everyone plays their part in making the constraint management solution work properly. For some this suggests a lack of flexibility, a diminution of their ability. However, the reality is that the goal is only achieved by the concerted actions of all resources within the chain, all focused on the same objectives. The sixth law of constraint management is that the management of the constraint and non-constraints is dependent upon the use of an effective decision support system. In our research we have found that many people try to manage their organisation with a poor decision-support system. This is not an argument for major investment in ERP-type software, simply a recognition that without effective support it will be difficult to make the right decisions. What is required is a system that allows for proper visibility across the whole organisation such that anyone can make decisions and still see the big picture. The information system should provide coherent data, consistent data across the whole of the chain. The technology should facilitate this. We did find one company during our research where the head office had over ten different technology platforms, most of which could not communicate with each other. The seventh law of constraint management is that variation in the system has most impact on the constraint. This might appear rather obvious, but our research suggests that many managers miss this aspect completely. Many organisations these days have implemented aspects of Kaizen, have control charts and SPC tools all around the plant, have regular meetings to discuss the TQM approach, yet for all that we still find that the role of the constraint in understanding how to use these tools is not appreciated. If variation in the form of a quality defect takes place at the constraint, then time on the constraint will have to be used once more to remedy

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the situation. This robs the constraint of capacity, which in turn robs the organisation of income, thus preventing the chain from achieving the goal. Conclusions This chapter has highlighted the need for a sea change in our measurement systems within a constraint manufacturing environment. It has revisited the five steps of focusing first described by Goldratt, and set them into the context of the laws of constraints which I first developed within my earlier work Enterprise focused Management (Hutchin 2001a). The final aspect is that without a rigorous process of analysis there is little chance of really being able to focus where we should and thus gain the leverage we desire. It is to that we now turn our attention, a process which enables us to analyse the whole of the enterprise, across the whole of the revenue chain.

3 The full enterprise analysis methodology

Every business is seeking to improve a number of key performance indicators (KPIs). These might include improving sales, increasing profit, reducing the time to market, improving productivity, increasing shareholder value, increasing market share and managing resources more effectively. At the same time senior managers are tasked with ensuring sound financial reporting, that there is a sound decision-making process and that there is a high level of visibility for all the performance measures throughout the company. Of course this assumes that they have such a set of key performance indicators linked to the business issues and that all concerned know how to interpret them. One of the key elements of most of the companies we have worked with is that people at all levels manage the business issues without reference to any other aspect than the way they are measured. This leads to the common situation where the KPIs become a source of aggravation and friction. I have become convinced over the years that without a rigorous, logical set of analytical tools improvement cannot take place. I am not the first to argue this; Deming (1986, 1994) and Goldratt (1984, 1986, 1990, 1997), amongst many others, have propounded this notion for many years. Yet I still find people who are convinced that they do not need such processes; they just implement solutions without ever thinking whether they are relevant to their problems or not. This chapter therefore introduces the full constraint management thinking processes (CMTP) as developed by the author for use in his programmes designed to analyse organisations and develop breakthrough solutions to root causes that lie deep inside the organisation. All of my work over the past ten years has been rooted in the analytical process of the Theory of Constraints thinking processes (TOC/TP) to which I was first introduced by Eli Goldratt. Eli was presenting his thinking process to a group of TOC practitioners, known as Jonahs, so called after the character in his book The Goal (Goldratt and Cox 1984) and also because Jonah was the only successful prophet in the Old Testament. I was already well versed in the systems thinking approaches of people such as Checkland (1981) and Pugh (Pugh and Hickson 1989), and had used many different diagramming techniques to analyse and understand systems. However, I was captivated by the elegance of the logic that sat at the heart of the

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TOC/TP, and still does. As a radar engineer, used to the analytical processes of the physicist, the logic and the structure made perfect sense to me. True, some of the terms were unusual, and will remain so to the person who has never been exposed to them before, but I could see that here was a very powerful tool for getting to grips with the many varied and apparently complex problems of industrial organisations. Three basic questions CMTP sets out to answer three basic questions of systems: What to change? What to change to? and How to effect the change? These three questions lie at the heart of any systemic analytical process. Note that the three questions are in an unusual sequence. Most people would expect to see only two questions, two stages in the process of dealing with such problems: define the problem, and implement the solution. Within CMTP there are three questions, and although the first may reasonably be expected, the second, determine what to change to, is not always high on the list of questions to answer. Most people assume the answer and proceed straight to the solution. This is a faulty line of thinking. It is vital that the solution is defined and properly validated before moving to implementation. Answering the question What to change to? allows those tasked with addressing the problem to have confidence that the proposed solution will not only work, not only meet the approval of the problem owners, but will also address the problem itself properly. This has the added benefit of ensuring that the problem is not defined as the absence of the chosen solution, chosen by the sponsor of the problem analysis team. Analysing problems One of the most powerful processes for addressing the problems of systems such as that described above are the five focusing steps outlined in the previous chapter. At each step of the way through that process it is vital that the analysis is properly and rigorously carried out. It is also important that the other members of the organisation are able to be a part of the process. To that end there are five distinct stages of communication within the process of analysis. The first stage is gaining consensus on the problem. This demands that anyone who examines the analysis comes to the same conclusion. Without such agreement, there are certain to be problems later if the solution fails to deliver. Failure to gain consensus at this first step only opens doors that should remain shut. So whatever analysis is carried out, it is not completed until the consensus is achieved. Remember, the driving force for this level of communication is the problem set gathered earlier which all will agree with. It is the level of causality that will be new to them. These problems have been around for a while, and have been responsible for many contentious meetings. There is one other aspect to this that is key: in the past there have been many improvement projects, but they

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have typically addressed the effects and not the causes. This time the intention is to address the causes, and remove the effects once and for all. The second stage is to gain consensus on the direction of the solution. Note that it is not essential to gain consensus on every part of the solution, which might not even be possible at this stage, or necessary. What is necessary is that all concerned agree that the direction is right, that it will properly address the problem agreed to at the first stage. The third stage is to gain consensus on the benefits of the solution to all concerned. This is all about gaining buy-in. If there is no benefit to the person, why should he or she work with you to implement the solution? Again this is not about presenting the whole solution, but sufficient to gain the level of consensus required from each individual. The fourth stage is to overcome all the reservations the members of the team will have. These will fall into two categories. The first is a reservation related to what prevents the solution being implemented, what we call obstacles. There will be many obstacles raised as to why this solution cannot be successfully implemented. It is vital to capture every obstacle, even those that do not appear to have any relevance. To the person raising them they are relevant, and though they might be found to be erroneous at a later stage, at this point they are treated with respect and included in the analysis. The second set of reservations are raised when the person sees that the solution, in combination with something that already exists within the organisational environment, will lead to an even worse situation than at present. In other words the cure is likely to be worse than the original illness. Both of these types of reservation must be captured and dealt with properly, using the appropriate tool from the CMTP set. The effect of dealing with the reservations in this way is a substantially enhanced solution, one that has every chance of being successful. The final stage is to make it happen. Once the solution to the problem has been validated, the level of agreement achieved, all reservations overcome, then the only task is to make it happen. Gaining consensus on the problem In the previous chapter I suggested a method for quickly determining the nature and impact of some of the problems facing the company. For that analysis I suggested the application of the UDE cloud procedure, which will be described later. However, often the problems within an organisation are more than a snapshot can cope with. The problems may seem to be very diverse, appearing to have no connection, with many different ideas being floated as to how to address this maze. Now the time is right to understand the full analytical process by which the revenue chain can be properly evaluated, core problems highlighted and solutions both developed and implemented.

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Figure 3.1 A mapped organisation

The starting point is the undesirable effects (UDEs) One of the interesting aspects to using the CMTP tools is that they insist on starting at the logical point of where we are right now, and with the problems we are dealing with right now. These are real problems which we are struggling with, not, it has to be emphasised, the absence of the chosen solution we would like to see in our system. It is amazing how many times, when trying to get to grips with major problems in industrial organisations, the core problem from the perspective of at least one individual is the absence of his or her pet project/ solution within the organisation. What a surprise! Once, with a group of people working within the automotive supply industry, one person on the programme who had gained his reputation from implementing Kanban systems announced that the core problem of the company we were using as a project was that it did not have a Kanban system. He was quite put out when the logic of his position was revealed as incredibly weak and he had to withdraw his analysis as fundamentally flawed. Of course what he was not expecting was the extreme rigour to which the CMTP checks the logical construction of any analysis. So what are UDEs? They are simply the visible manifestation of a deep-rooted problem. Though not easy to verbalise the first time, whenever we ask people to list UDEs the normal response is a list which covers many pages of flipchart paper. Once they have been captured, the next step is to place them on the appropriate point of the revenue map, and gain an insight to the cumulative effect they have.

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Figure 3.2 UDEs placed upon the map

So first we map the chain (see Figure 3.1). The figure shows a simple organisation that has been mapped out. There are thirteen resources and six entry points of raw material or bought-in components. The arrows show the linkages between the various operations, and the inclusion of the raw material wherever it enters the system. The final resource is number 13 and the output from here might go straight to a customer or into a warehouse. Note at this stage that I have only mapped the internal operations of the organisation and only the primary material flow networks. There are more networks that need to be mapped, the information and financial flow networks must also be mapped out in the same way, and also the wider elements of the chain, into the supply base, and on towards the end user. These have only been omitted in order to reduce the level of complexity within the book. I have omitted many of the loops that exist and would need to be made evident when mapping out the internal chain. Finally I have considered each resource as a single entity, but of course reality would be different. If each resource is seen as a department or group of machines or other such resources, then that will suffice for now. Once this map has been constructed, the next step is to enquire of each group involved what the key problems are that they have to face each and every day. Once these data have been collected, it is possible to superimpose them upon the map as shown in Figure 3.2. Note that not all areas have identified UDEs. This usually means that they consider the problems to be either transient or insufficiently important to consider at this stage. Often during a full analysis people wish to return to this step and reconsider the decision to include their UDEs. It is of interest that this late inclusion of more UDEs rarely affects the outcome of the analysis, but only further reinforces it. Note also that some UDEs

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lie across more than one area; they are affecting both to a similar extent, for example the UDEs affecting RM1 and resource 1 are listed together. Once this step has been completed, the next stage is to consider the financial and non-financial impacts that the UDEs are having. Often it is possible to state what the UDE is actually costing the organisation in monetary terms. In one case from the new product development area in a major communications company, the impact of just one UDE was measured as $5 million each year. The overall sum that was developed once all the UDEs had been analysed in this way was some $7.5 million per year. Many of them were quite small, but in combination they became very big indeed. This aspect was a revelation to the senior management group taking part in the analysis and gave them considerable food for thought. It is equally simple to state what the impact is on customer delivery, overall lead time and so on. These are measures which are not immediately linked to money though there is an obvious connection. Each person is then asked if they can quantify lost sales as a result of the problem set. Thus there are two key financial impacts highlighted: money we had but allowed to slip through our grasp, and money we should have had but also lost. Once more the full impact of this combination of UDEs throughout the chain hits people hard. In the programmes we run, the common statement from people at this stage is that they had no idea of the true level of the problem until now. This then starts to create in the mind of the people carrying out the analysis an impression of the real impact the combination of UDEs is having. Often we find that they have never thought of them in this way, if they have thought of them at all. Of course in many organisations what we find is that for every UDE there is a major project under way to address it. It is not that the UDEs are ignored; quite the contrary, they are the focus of many improvement projects throughout the whole of the organisation. It is simply that the piecemeal approach to UDE removal almost never works. True, there is some momentary relief, but unless the cause of the UDE is addressed it will return, often in a more devastating form than before. The result is that large sums of money are expended addressing UDEs with little or nothing to show for it. This lack of a logical approach to the resolution of UDEs is costing manufacturing industry its competitive edge, something that this book is trying to resolve. But there is still much to be done with what is our raw material: just how clear are the UDE statements and are they UDEs that the people can reasonably address? Any one person or group has to accept that the only UDEs they can address are those under their direct control, or where they have sufficient influence with those who do. The remainder of the UDEs must be treated for the time being as facts of life. It is important to put our own house in order before addressing the wider UDE set. So, if we now have a set of UDEs that are valid in terms of our area of responsibility, just how clear are the statements themselves? We now ask a series of questions of each UDE. The UDEs are often stated in fuzzy, almost bland language, and the first step is to gain clarity for each problem statement. For example, one often-used

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statement is ‘communication is poor’. But what does this really mean? Is it financially poor? Is it an example of destitute communication? What is meant by communication? Is it verbal, written or some other medium? The statement fails one of the reservations used within the CM logical thinking processes known as ‘clarity’. Clarity is not really a logical check at all, it is a communication check, but it is still one of the key checking points used within a TOC analysis. The whole process of checking the logic of our understanding will be discussed later. Returning to our problem statement, it requires far greater examination. Just what type of communication are we describing? What method of communication? What is the context of the communication? This activity of problem statement refinement continues until a clear, single problem statement is arrived at. Once this clear problem statement has been written down, it is possible to consider the organisational impact of this one entity. How much does it cost us on its own, and in both financial and non-financial terms? This gives us a clear understanding of each entity on its own and some indication of what the cumulative impact might be. There are many more questions to be asked of each UDE. Are they part of our current situation? Do they annoy us? Do they take up a large percentage of our time? Are they clearly negative? Are they a sign of a deeper problem? In our programme we submit each and every UDE to a fierce level of scrutiny; this is our basic raw material upon which our full analysis is going to be based; flaky thinking here destroys our confidence about the solution when we come to it. Is each statement a single entity? Is it real? Can I go and see it for myself? Is it considered to be of importance to remove it? Does it affect our capability? Is there causality in the statement? These and many more questions are asked, the UDE statement is revised many times, and the outcome is a very clear picture of the real issues facing the company right now. But UDEs have effects that go beyond their existence. The conflict a UDE creates Every UDE creates a conflict, in some cases a whole series of conflicts, between the people involved. We have often found that a great deal of time is expended in trying to deal with the conflict rather than the source of the conflict. It is also useful for the people concerned to understand fully the capacity of a UDE to generate conflicts, often highly destructive, that might have been around for quite some time. The conflict cloud: the theory The cloud concept came from Goldratt’s work (see Hutchin 2001a, b) in defining any source of conflict between two states. In this case the conflict is typically between two people, both of whom have different, and conflicting, requirements

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Figure 3.3 The conflict cloud

in order to satisfy their own needs, and at the same time deliver a shared objective. The structure of the cloud is shown in Figure 3.3. Once the statements within each of the five boxes have been filled in, the next step is to bring to the surface the assumptions that lie under each arrow, and which are the unspoken elements which keep the conflict in place. The cloud must be checked for clarity, and is read in the following manner. In order to have (the statement in box A), I must have (the statement in box B), and in order to have (Box B), I must have (Box D). However, in order to have (Box A), the other side must have (Box C), and in order to have (Box C), the other side must have (D′). Figure 3.4 shows an example of such a cloud, with the assumptions, statements which hold the logical structure in place, identified. The conflict cloud: an example from the world of project management This cloud started with a UDE from the world of project management which was: ‘often our projects fail to finish on time’. It was recognised by Mike, the project planner within the project team, that the estimates being used were inaccurate and he wanted to use estimates closer to the actual time the activity was going to take. However, John wanted to use estimates that gave proper protection to the activity. Just seeing this cloud verbalised in this manner gave a unique insight that neither man had recognised before. They could also see that failing to deal with the underlying UDE meant that such conflicts were unlikely to disappear. Note at this stage that resolving the conflict would bring relief to the two involved and allow for informed analysis of the real environment in which that conflict exists. It would not however deal with the root causes; we are still some way from that.

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Figure 3.4 A conflict cloud example

How bad can a UDE go? If left alone UDEs fester and grow ever more destructive. One way to check the real devastation a UDE can cause is through the use of the negative branch reservation (NBR). NBR: the theory The basic idea behind an NBR is straightforward. Given the starting position of just one UDE, just how bad can things get? Using other entities that already exist, can the logic of the argument show that if left alone the UDE will always lead to something far worse (see Figure 3.5)? Figure 3.6 illustrates an actual NBR developed during one of our programmes within the rail industry and first described in Enterprise focused Management (Hutchin 2001a). This NBR was taken from an analysis carried out before the Hatfield rail crash. The simple logical structure shows that the likelihood of a major incident could have been recognised long before that actual accident happened. This process of analysis helps to create a deeper understanding of the true impact of failing to deal with the cause of the UDE set. Dealing with a UDE on its own will inevitably lead to the re-emergence of the UDE and the almost certain arrival of the really negative entity in reality.

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Figure 3.5 THE NBR structure

The application of the UDE cloud Once the UDEs have been subjected to scrutiny, the next step is to analyse each one and find out why they continue to exist. The constraint management tool for this activity is known as the UDE cloud. Using the same basic structure as the conflict cloud described earlier, the intention is to capture the true nature of the conflict, this time between the current state, the UDE and the desired state, the desirable effect or DE. The questions asked of each box are as shown in Figure 3.7. This analysis is intended to reveal key core drivers in a problematic environment and we must be sure of our ground. The solution will be built on the foundation of our problem analysis and we should bear in mind one of the key platforms of chaos theory, namely sensitive dependence on initial condition. Simply put, if we fail to determine properly the root of our problem, the solution will be well wide of the mark. Once the cloud has been constructed, it can then be checked by reading the cloud in the same manner as the conflict cloud, using the logic of necessity statements: In order to have (A)…we must have (B). In order to have (B) we must comply with (D) and so on. It may be necessary to change the wording slightly in order for it to flow but this rarely changes the meaning and context of the cloud. This is followed by the next step, that of raising assumptions (Figure 3.8). The level of rigour applied at this stage is vital if the cloud is to reveal the true nature of the conflict that exists. This starts with the nature of D

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Figure 3.6 An example of an NBR

and D′. In order to ensure clarity of conflict, the entries in the boxes must be a clear and precise statement of the entities. They should be written in the present tense and be obviously in conflict. If the conflict is only apparent through the surfacing of assumptions between D and D′, then the verbalisation requires further attention. Once all the boxes have been filled, the strength of the cloud should be considered. This is checked by determining the impact of the cross-connection, that of D on C and that of D′ on B. If D significantly, and negatively, impacts C, if D places C at risk, then that cross-connection is a powerful one. If the same applies to D′ on B, then the cloud is a particularly strong one. One such crossconnection is sufficient to give a cloud of some substance. Where both crossconnections are strong, then the cloud is extremely powerful. The cross-connection demonstrates the power of the hold the UDE cloud possesses (Figure 3.9). Whatever is written in the B box is never in conflict with what is written in the C box. Indeed, both are recognised as necessary conditions for the achievement of the goal, the objective that is written in the A box. This is what both the logic of the cloud structure and the intuition of the individual speak about so vividly. However, whatever is written in the D box clearly violates the existence of the C box and similarly what is written in the D′ box clearly violates what is written in the B box. Thus the cloud is held in place. D is in conflict with D′, the present problem at odds with the desired future, and there

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Figure 3.7 The UDE cloud structure

is no obvious way to remove D, which prevents C being achieved, whilst at the same time protecting B from the impact of D′. There is one final check to determine the strength of the cloud: the nature of what is written in the B box. The ability to check clouds comes with practice, the robustness of the UDEs, the power of the cross-connection, and the way in which the B box has been verbalised. One of the primary reasons why the UDE remains is also a function of the apparent conflict contained within the B box between the construct of the organisation and the construct of the individual. It is this unresolved conflict of constructs that ensures the continued existence of the UDE over the desirable effect, the DE. Whenever a UDE cloud is examined, often what is an assumption under the arrow from A to B or from B to D appears as the entry in the B box. The real content of the B box in a UDE cloud is always in itself a cloud. Each individual has a construct about their work, their relationships, their role and indeed themselves. Equally, through rules, procedures and measurements, organisational constructs also exist. It is the conflict between these two constructs that forms the entry to the B box in the UDE cloud. For more examples of the application of the UDE cloud process there is a full description with respect to project management in Enterprise Focused Management (Hutchin 2001a) and with respect to managing change in Unconstrained Organisations (Hutchin 2001 b). For further descriptions of the cloud process, see Cox and Spencer (1998), McMullen (1998), and Scheinkopf (1999).

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Figure 3.8 The assumptions of the UDE cloud

Figure 3.9 The cross-connection of the UDE cloud

Constructing the composite cloud The process of building the composite cloud starts with collecting a reasonably large number of clouds from each member of the team involved. First, the UDE clouds are constructed and checked. The next step starts by examining the chosen

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clouds for a common thread. The process of selection starts with comparing two or three clouds at random to see if there is any pattern to the statements contained within the boxes. The first box chosen is the D box, then D′ and then on around the clouds in the sequence C—A—B. This sequence is important as it is the B box which almost always proves to be the most demanding when the generic cloud is being constructed and validated. The ability to determine a pattern is rooted in the ability of the person doing the compilation. The first assumption that determines this approach is the skill and knowledge of the person carrying out the analysis. Without previous experience of both building and analysing clouds this would be a difficult activity. The second assumption is that it is a task best done first by one person, whose work is then scrutinised by at least one other equally skilled practitioner. The third assumption is that such a person has the skill to determine patterns from a wide range of initial conditions, problem areas and environments. Therefore it is unlikely that people without knowledge and experience of the problem areas, such as production or project management, would be able to determine the patterns that may or may not exist in clouds drawn from those problem areas. Therefore the construction of the composite cloud is accomplished by searching for a statement, which can be written in each box of the composite cloud, that encapsulates the equivalent entries in the individual UDE clouds. This is shown in Figure 3.10. This process is iterative and demands clear thinking. Once the cloud has been completed, the logic is checked once more, and then the assumptions surfaced. Once the composite cloud is validated, it can then be used to check with other UDEs to determine whether the composite cloud still applies. If this is the case then the composite cloud can be considered to be a generic cloud for the situation or situations being examined. Once this has been achieved, the next step is to turn the analysis into a form that can be readily communicated to the rest of the team. For this we use the communication analysis, another of the tools of constraint management. What follows is an example drawn from new product development within the high-tech communication industry. The team had already worked their way through a number of UDE clouds and had finished with the composite cloud shown in Figure 3.11. This became their generic cloud. Once the cloud had been constructed, it required checking by the whole group. Did it capture the real sense of the conflict? Did the cloud fall into line with the intuition of the team? Did each member of the team have first-hand experience of the conflict and the problems in trying to deal with it? How real was the analysis? It did not take long for full agreement that the cloud did capture the conflicts, did fall into line with their intuition, and they all had stories which demonstrated the on-going struggle to resolve the conflict, that this was all too real. Once this level of agreement had been achieved, the next step was to bring to the surface the assumptions that lay behind each of the arrows. Each person did this on their own, sometimes returning to the original set of clouds each had to see if any assumptions from there also fitted here. They each represented a

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Figure 3.10 The construction of the composite cloud

Figure 3.11 The composite cloud from project management

different location, in a different country, and this ability to verify that the same problems were common to all three locations gave enormous confidence that they probably operated in the other locations as well. Ensuring that the other locations had the opportunity to validate the logic analyses was central to their gaining buy-in in the other sites (Figure 3.12). The surfacing of the assumptions was a revealing exercise for the group. They really had to come to terms with some of them, and in some cases realise that they were part of the problem. They also started to realise the systemic nature of the issues, a realisation that is very much in line with the observation of Deming (1986, 1994) that most problems are systems driven, not people driven, though it has to be said that people were certainly responsible for maintaining some of the problem issues in the way they were managing the project environment. They then checked and rechecked the logic of the cloud and the assumptions in preparation for the next step.

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Figure 3.12 The composite cloud from project management, with assumptions

The composite cloud once validated allows for the construction of the communication analysis (CA), which is shown in Figure 3.13. This analysis is read using the if…then statements as it is an example of the logic of sufficiency. The ellipses represent the ‘logical and’ function; for example, if we read the analysis from the bottom: ‘If we want to be able to manage effectively to meet commitments, and if budget and staffing requirements have to be met, then there must be a stable development plan and team.’ The rest of the analysis is read in the same way. The validation of the analysis comes from the raising of reservations. There is a specific set of reservations allowed; this is done to prevent spurious reservations, or perhaps just spiteful ones. The list is shown below: • Clarity reservation—this is raised when the meaning of the statement is not clear, the content of the box appears to be confusing, or some similar reaction.

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•

•

•

•

•

The response is to think of a better way to communicate the message, one that properly captures the issue being described. Entity reservation—this is raised when the entity is not recognised by the reader; the question here is ‘I do not think this entity exists’. Now the final say here is that of the person raising the entity; this ensures that it cannot just be removed because someone else would prefer not to have the statement made public. Causality reservation—this is raised when the arrows connecting entities are not recognised; the question is focusing on the supposed causality between two entities. The response here is that more work needs to be done to ensure that the causal relationship is both clear and understood by all. Insufficiency reservation—this is raised when the arrow connecting two entities is felt to be insufficient; in other words, to support the logic there should be a logical and. Very often the person raising this reservation will already know what the missing element is and should offer it. If they cannot offer the missing logic then the reservation fails. Additionality reservation—this is raised when there is felt to be a different cause for the same effect; it is the logical or function. Again the person raising the reservation must also offer the missing logic. There is also the question of weight. The primary arrows of causality can always be reinforced by secondary arrows conforming to ‘logical or’ status. However, in order to prevent over-complication, the weight of the additional arrow must be of similar weight to that of the original analysis. Tautology reservation—this is where the danger of circular logic is present.

Following the validation exercise, this analysis then formed the basis for communicating the work done to others within the company, in both their own sites, and those other sites not included in this team. It was at this point that the team felt that they had gained a true understanding of the real causality within their organisation, and how it was driving the many UDEs they experienced day after day. Once this whole analysis had been validated in the class, the next step was to check the analysis with others in the field. This aspect took a few days and gave full confirmation that each step of the analysis was sound and that the core driver for the UDE set was as indicated. At this point it was agreed that consensus on the problem had been achieved. Developing the solution was the next step. This involves the construction of, first, the core future reality tree (CFRT), which shows both the direction of the solution and the expected benefits, and then the full implementation plan where the reservations of the team are also incorporated into the solution. Developing the core solution This element of the analysis is called the ‘core future reality tree’ or more commonly abbreviated to CFRT. The intention here is to check that the solution properly addresses the core problem identified earlier. This is a key feature of the

Figure 3.13 The communication analysis

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Figure 3.14 The core future reality tree

analysis. This is where the notion of sensitive dependence on initial condition has most impact. Miss the target here and by the time the full solution is implemented the only thing that can be guaranteed is that the solution will fail. The initial starting point is an injection, which is derived from the core cloud and determined through the invalidation of an assumption. It is the assumptions that hold the conflict depicted within the cloud in place. There will always be valid assumptions and true assumptions. What we are seeking are erroneous assumptions, assumptions that can be invalidated by implementing a change. Such a change is termed injection, and for any solution there will be a number of injections comprising the full feature set. An injection is a statement of actions completed and is always written in the present tense as if completed. The structure is shown in Figure 3.14. When checking the analysis it might be necessary to add further features/ injections to the original in order to secure the solution. This might mean the logical structure ends up looking more like Figure 3.15. If we take the worked example, then the construction of the core future reality tree might look something like Figure 3.16. Note that there are entities that also existed in the CA represented once more. That is simply because they were valid then and are still valid today—that is, in the future. The DEs are derived from the UDE clouds and also from other UDEs not used in this initial analysis. Once this has been done, it is possible to communicate the solution and gain the consensus of the people to the direction of the solution. The third stage is gaining consensus on the benefits of the solution. This involves checking the impact of achieving each and every DE in both financial and non-financial terms. This gives real clarity to the organisational pay-off in implementing the solution and also works at the individual and

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departmental level. It should also give real clarity, focus and leverage to the revenue chain of the enterprise. As with the initial analysis this is not an area for superficial analysis and rigour. The solution must deliver the DEs and therefore the robustness of the construction and the validity of the logic are paramount. Once more the logical reservations are used to determine our confidence level in the solution. Creating the full feature set of the solution The full solution still has to be developed. It is vital that each element is properly constructed and validated. The starting point of this part of the analysis is the list of UDEs we began with. For each UDE there is a corresponding desirable effect or DE. These have to carefully worded to ensure there are no problems with communicating the effect to all concerned. Once the list of DEs has been created, it can then be validated against the UDE list. Once that has been completed, the list of DEs can be placed along side the CFRT and the logic examined. The first question centres on whether the CFRT is sufficient to create the DEs. The usual answer is that additional injections are required to support or create the DEs. These then have to be placed into the logical structure that will become the full future reality tree. Once completed this must be checked once more, this time by the whole team. This is a key dimension of achieving consensus within the whole team about both the direction and benefits that will be derived from the solution. At this stage measures to determine the successful implementation must be developed. This can be in the form of either the acquisition of the DEs or the removal of the UDEs, or in some cases both. Developing the implementation plan Once the overall solution in the form of the CFRT has been validated, it is then ready for transfer to an implementable plan. This starts with taking every injection that has been developed and refined from the validation process and listing them. There are then two key questions that must be asked of each injection. There is no specific sequence of asking these questions; I usually place them up on a screen and invite the team to question them using either of the two valid reservations. The first is the use of the NBR to ask whether the implementation of any one injection will lead to a situation even worse than the present. We first came across the NBR tool earlier (see Figure 3.5); the difference here is that, whilst then the driver for the NBR was a UDE, this time it is the injection. Here the group is encouraged to question the injection from every possible angle. The intuition of the group is typically very strong and they will soon be able to determine the NBRs that demand analysis and those that do not. Once these NBRs have been identified and constructed, the injection, which breaks them, is added to the feature set of the solution. In this way the solution is

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Figure 3.15 The core future reality tree extended

substantially improved, and the likelihood of problems of this nature are avoided. The second area is where people can readily see that the injection will be prevented from implementation by an obstacle, or set of obstacles. Again, each person is invited to write up his or her obstacle for further examination. The list of obstacles can be quite long, but none is ever turned down. The obstacle’s existence is driven by the intuition of the individual. If they think it is an obstacle then that is it, the obstacle is deemed to exist and must be overcome. Once the list of obstacles has been validated, the key check is that the obstacle must prevent the injection from being implemented. There must be a clear link between the obstacle and the injection. The next step is to determine what must be implemented in order to overcome the obstacle, what is called the intermediate objective (IO). The source of the IO comes from the person who suggested the

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Figure 3.16 The core future reality tree of our projects

obstacle in the first place. Their intuition about the obstacle gives them an insight into the likely IO to overcome it. Once more the whole analysis is subjected to scrutiny. It may appear that there is a great deal of rigour in this process, and that would be a correct assessment. I have found that where rigour is reduced the ability of the solution to deliver is compromised. Once the full list of injections and IOs has been identified, it is then possible to construct the pre-requisite tree (PRT), which is the logical sequence of events necessary to achieve the future reality tree. Now the latter is given a sound foundation, it is placed into context and made ready. The injections are sequenced in both logic and time dependency, thus creating a logical implementation plan, which survives scrutiny. The IOs are placed according to the position of the injections. Now we have a real plan which is capable of implementation. Well, that might be true but there could still be problems. Often the IOs are still quite difficult to achieve. It’s not that there are more obstacles, it’s just that there are many elements to successfully implementing the IO and there is often a problem with sequencing these actions. The final technique that addresses this issue is the transition tree, the transition from the current state to the desired state (Figure 3.17). The logic of this tree is quite interesting. The sequence of actions is placed up the left-hand spine as shown. If the sequence of actions is known, then the structure of tree used will be as shown. The central spine shows the starting point

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at the bottom and then, as each action is completed successfully, the next stage is achieved, the outcome of the action. This stage then sets the starting point for the next action and so on. If the outcome of an action has not been achieved, then it is not possible to proceed to the next action as the starting condition has not been achieved. This is the logic of sufficiency. The right-hand column is where the reasons for taking the action are placed. This is a logical statement explaining why the action is both necessary and sufficient for the outcome to be achieved. In any implementation of a transition tree the central and right-hand spines are not negotiable, but the left one is. If an action does not achieve the expected outcome, then the person tasked with implementing the tree can, without reference to any other authority, change the action being taken. The only rule is that the logic of the overall tree is not affected; in other words the outcome of each stage is still achieved and the overall outcome is also achieved. This is a powerful example of real delegation. Now the actions being taken are less important than the outcomes of the actions and the logic behind them. Measures can be put in place which ensure compliance with the central spine, but the actual actions being taken do not need to be checked, only the logic of those actions. But what if the sequence of actions is not known or clear? It would then be impossible to write the logic, hence the need for an additional step. The next variation of the transition tree takes note of this requirement and adds another step, the logic of why the sequence is how it is. Once more the logical structure can be examined and scrutinised before implementation and any further amendments are carried out. This is shown in Figure 3.18. The main difference here is that the logical sequence of actions needs to be determined before anything can start, hence the insertion of the logical analysis of why the next step is where it is. In most implementations I have found this additional element to be of use only a few times. In most cases the simplified form is good enough. Others within the TOC community have further developed the transition tree and it is now recognised as the most powerful tool after the cloud. Making it happen Well, all that has to happen now is for the plan to be implemented in full. Just take each transition tree and work through them until completion, implement every PRT, and the results will be yours. This is usually what happens but every so often there are still problems. I considered earlier the three types of constraint that exist: physical, policy and paradigm. The indicator that there is a paradigm constraint usually makes itself known at this stage. With all the work done to determine the problem and the effects it is having, in other words having gained consensus on the problem, then to have taken the time and energy to fully develop the solution and the plan to implement it, gaining consensus on the direction and benefits of the solution, and overcoming all the reservations; if nothing still happens, then there is another obstacle to overcome, one that lies

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Figure 3.17 The transition tree

very deep within the individual. Analysing this phenomenon lay at the heart of my research at Cranfield from 1994–7 and resulted in my book Unconstrained Organisations (Hutchin 2001 b). The notion of the paradigm constraint, which is encapsulated in the term ‘paradigm lock’, is a cloud of immense power and one that affects almost all organisations.

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Figure 3.18 The extended transition tree

The impact of paradigm lock within constraint management The basic conflict is internal to the individual. Each person has a set of beliefs, a set of paradigms, that determine who they are and how they operate. These paradigms will dominate their thinking across the whole spectrum of life. Many will have been taught through education at all levels, many will have been learned through the customs and practices of their organisation, many will be an expression of who they are and what they represent. However, there are also times when a challenge presents itself to a particular paradigm, a challenge so fundamental that, even though the individual might really want to implement the new paradigm, it is still quite beyond him or her. This is the nub of the paradigm lock. The individual is locked into a cloud of such power that they are trapped. They are locked into a dominant paradigm which prevents them from breaking free and which in turn stops the improvement dead in its tracks.

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Figure 3.19 The paradigm lock cloud

The paradigm lock cloud described The impact of the paradigm lock cloud The research upon which this cloud is based examined a number of people, about 300, from around fifteen companies, drawn from the UK, Europe and the USA. I examined over 400 UDE clouds developed with each of the people and over the period of the research searched for a common theme, which is where the paradigm lock cloud came from. Others have also tested this within the TOC community, notably Oded Cohen, who at the time was the CEO of the Goldratt Institute in the UK. Each person has been able to replicate my work and confirm not just the existence of the cloud, but also the impact it has. It simply stops change dead in its tracks. I have found no stronger force for maintaining the status quo in any organisation.

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The injections to overcome the paradigm lock cloud The cloud can be overcome, as can all clouds of this nature. It might not be easy, but there are three injections which I have found to be necessary in the process of removing the impact of paradigm lock: 1 Taking responsibility and being accountable for the results of my actions. This injection is both straightforward and difficult at the same time. It should be easy for people to take responsibility for the results of their actions. Reality is different, however. In many organisations the blame culture is endemic. Often the measurement system and subsequent penalty ensure that most people are able to push the blame somewhere else, indeed anywhere else except on themselves or their department, work group or team. This enshrines the ability to avoid taking responsibility, to avoid standing up and being counted; far better to stay low and let someone else take the blame. Of course there are times when taking the blame is unavoidable, in which case the finger usually points to the client, the supplier, the system, anything that might conceivably be able to stand in the firing line. This injection demands that such behaviour be condemned and changed. It is vital if change is to take place that people feel able to take responsibility for what they do. Of course this also means that they will not suffer sanction if they do so. 2 Giving and responding to leadership. This is also a difficult area to develop. People like to lead; they are less inclined to respond to leadership, especially when the leadership comes from subordinates. It is often the case that managers are expected to lead, though in my experience they simply manage, not lead. To manage is about maintaining the status quo, and many managers are very good at maintaining the status quo; leadership is about change, and here many managers start to feel uncomfortable. Leadership is not about the top team either; it can come from any level in the organisation. The really great leaders of our industry knew that, knew they had to listen to the shopfloor, the customers, the suppliers, indeed to anyone who had an involvement in the organisation, in the supply chain. Too few managers lead, all too many manage, and what is needed is a combination of both. To overcome the paradigm lock it is essential that all managers are able to understand and respond to leadership, whether they give it or whether it comes from another source. 3 Subordination to the goal, and therefore the constraint. This is the really tricky bit. The Theory of Constraints argues throughout the five focusing steps the importance of both the goal and the constraint. It is vital for all within the organisation to understand the importance of knowing the goal, and the units of measurement that respond to the goal. Equally it is vital to understand the impact of the constraint, as shown in the laws of constraint management, and operate accordingly. However, many people, from top team to shop floor, fail properly to subordinate to either the goal or the constraint, when both are necessary conditions for success. They prefer subordinating to the measurement system, to their past training and education, even though time has moved on and the content

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of their training/ education is probably long out of date. All too often the real constraint within the organisation is not physical, or even policies per se, but the lack of imagination driven by the fear of change. Hence the policies in place support the paradigm, even though they cripple the organisation. This in turn generates physical constraints that many people within the organisation are trying to resolve, but the driving force lies not in the physical nature of the constraint but in the thinking that led to its creation. Conclusions This brief overview of the thinking process of constraint management offers an insight into the logic and rigour of the process. Competitive manufacturing will not be achieved without such a process. The CMTP is about teaching people to think in a new and vibrant manner. Competitive manufacturing, and constraint management, are about applying that approach to the challenges of the manufacturing sector today. The following chapters will apply this process to four distinct areas; first, new product development (NPD). It would have been just as feasible to start elsewhere, but for the companies we have worked with over the last ten years it has been the area of NPD that has determined the success or otherwise of the whole operation. The reason is relatively simple: most of the organisations we have been involved with have been in markets where the life expectancy of the product has been dropping to ever-smaller timescales. In one case they dropped from about 18 months to around 6 months. Though manufacturing and distribution could keep up, though the people were more than capable, the key issue for this particular company was how quickly it could develop a new design and enter the market successfully. The focus of the whole company became NPD, and hence I have chosen to start there. NPD is also one of the best conduits for feedback from the market. Within the motor sport industry the same is the case with what they call high-performance engineering. In this market there is great pressure to meet exacting standards, and failing to deliver is seen on the race track as well as the bottom line. Those tasked with creating tomorrow’s products have to keep in touch with what is happening out in the various markets. There are many examples of companies which, once strong, have been brought low because they did not focus as much as they should have done on changes in the market. But being able to produce new products ready for a chosen market is of no value if production cannot make them and distribution cannot ensure availability at the point of sale. Above all, if the people upon whom the whole venture depends are not able to resolve the many problems and issues, make decisions in a coherent manner, then failure is almost certainly going to happen sooner rather than later. Here, constraint management starts to make a difference, starts to impose new and exciting changes on the current structure, the current procedures for NPD. It is also here that the challenge moves to the other functions within the organisation.

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Thus the second area is production, where there is a simple goal: to deliver on time and in full every time. It must also do so with an ever-shortening lead time, without ever missing 100 per cent due date performance. Zero defect is of course a necessary condition in this task and is a given, or at least it should be. This is an easy objective to state, but much more difficult to achieve in practice. The third area is distribution: it makes no sense to develop new products, manufacture the new products, and then fail to ensure that people can buy them. It is also of interest to note that this still happens many times. It is as if people were surprised that the time and effort they put into developing a product which they feel will capture the world actually does so. The fourth area is that of developing the people. All the systems in the world are of no value if the people do not sign up to them, if they do not have the confidence to address the issues that have to be dealt with, have no involvement in the process they are being asked to manage. The fifth area concerns the ability to manage the change process and to create a learning organisation; followed by the sixth and final area, that of bringing it all together. In each of these chapters the logical approach of the constraint management thinking processes lies at the heart of the analysis and of the developed solution.

4 Managing new product development

The initial pressure on our system tends to come from, first, the market, then possibly marketing and, finally, many times from research and development. The combination of all three places a great deal of pressure on the ability of those within new product development (NPD) to actually deliver. This is where the approach known as ‘critical chain’ enters the argument. The approach was first described by Goldratt in his book Critical Chain (1997). It is not the intention to repeat here what I have already written or writings by other authors such as Larry Leach (2000) and Rob Newbold (1998). The technical detail of critical chain has been covered in great detail by them and needs no great introduction here. This chapter sets out to give sufficient understanding of the basic concepts of critical chain such that the reader can see what it is trying to achieve, and set the approach into the context of an enterprise focus for projects, project management and NPD in general. The approach came about because people who recognised the elegance and simplicity of the constraint management solution for the manufacturing environment and production scheduling saw that it could be transferred to the world of projects. The same importance attached to the notion of the constraint; the same importance of safety and the right place to put it: these and other aspects of the production solution were transported to project management. For a more detailed analysis of this approach as applied to the world of project management see my work entitled Enterprise Focused Management (Hutchin 2001a). Background to new product development and project management Every project is supposed to have an objective. Some are fairly obvious, such as the completion of a road, bypass, sewage works and so on. In construction, if the intention is to build a new airport or a new stadium, then whether the project is completed on time or not is clear for all to see. The same pressure to deliver also applies to high-performance engineering within the motor sport industry. But projects often have more than one objective. The companies involved expect to make money out of the project; the client intends to gain revenue from the newly developed product; the contractor expects to make money from his or her labour

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and so on. The downside of non-compliance with the demand of the project is that penalties may well be applied, and these financial penalties come out of the profit. Equally, any work not completed by the due date will still have to be completed, and in many design, build and finance projects the contractor carries out the remedial work at own expense. This further drains the profit pot. Within the high-tech industry the intention of the project is typically to bring to market as early as possible products that substantially improve the bottom line of the organisation. The penalty here for being late is that someone else will take the market, often completely. One important distinction between the two sectors, construction and NPD, involves profit margin. Within the construction industry many of the projects examined had a small margin for profit for the contractors, often 2–3 per cent. Even in some of the larger projects the margin was still relatively small: 8–9 per cent. In the high-tech market the picture was very different. First, the scale of the projects in budgetary terms was often higher, and the corresponding margin also higher, sometimes as high as 25–30 per cent. This difference had a profound effect on investment decisions. The paradigm within most civil engineering is that the individual project, rather than the organisational centre, finances innovation projects, such as the implementation of critical chain. With such small margins this does not leave a great deal of flexibility for real investment. Within high-tech the environment allows for investment in such innovation either spread across a number of projects, or funded through the centre, thus lifting the pressure from any one project or group of projects. Typology of projects But are all projects the same? Within the work undertaken over the last five years within the CM community, three distinct types of projects have been developed. These are single project, multiple single project and multi-project environments. Single project environments are perhaps the simplest to work in. They are easily defined within an organisation as stand-alone projects. The people working on them only work on that one project. The equipment is allocated to that single project and remains with the project until completion, or at least the completion of their involvement. Single projects can still be quite complex, with many activities to be completed both consecutively and concurrently. The scheduling exercises still have to be done. The work breakdown structure must still be completed. Indeed all of the usual activities of project management apply. Risk analysis, cost breakdown, procurement and so on are part of the dependent events that form the chain of activities leading to a successful conclusion. Multiple single projects is simply the environment where the organisation is structured to deliver more than one project at the same time but has no, or a very limited, overlap of resources. Each project is still stand-alone with resources

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usually being allocated only to that project and to no other. Many construction companies are structured in this way. Where there are resources allocated across projects they are rarely key resources, rarely scarce resources; and where there is a demand for a specific set of resources, they usually fall into the category of HQ staff people, support people and so on. For each single project all of the usual activities described earlier still apply. Multi-project environments are where there is considerable overlap between projects in terms of resources. This is very much the scenario for most hightech and high-performance engineering companies. Resources are allocated to a number of current projects, under teams perhaps even still working on projects that require some form of remedial activity, and possibly preparing for new projects as well. Even within a single project they will be working on a number of concurrent activities. The pressure here is usually immense. Clients, and their representatives, are continually seeking earlier and earlier delivery dates. Often management seeks to launch new projects before existing projects have been cleared out of the project department. The ability to prioritise within these environments is usually based on who shouted the loudest last! At times there are many people all shouting at the same time and at the same volume level: more a succession of monologues than a dialogue. Success in a multi-project environment, however, is incredibly lucrative. If a set of projects can hit the market early then the financial implications far outweigh any local expenditure constraint. It was for these types of projects that the critical chain approach was developed and implemented. It has worked in all three environments. Critical chain introduced The critical chain approach to project management was first introduced by Goldratt in his book Critical Chain in 1997, although the approach had been used within the CM environment for some eight or nine years prior to this. Subsequently, others, notably Newbold (1998) and Leach (2000), have written excellent books on the subject. I do not intend here to reproduce their work, but I think it necessary to give some overview of the approach, and if the reader wishes to understand more then the work of these other two, in particular Leach, is highly recommended. Creating a network of activities to form a project plan is the starting point of network creation. This of course assumes that the goal of the project has already been determined. Most projects have more than one activity; that being the case, it is important to build the network of activities, keeping the logical structure intact. By this I mean the events that are dependent on each other and this should be reflected in the plan. Once all the activities are known and the dependencies known, it is possible to construct the plan using either PERT networks or Gantt charts. The starting point is the same in both cases: how long each activity is going to take—in other words an estimate of the timescale for each activity.

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Figure 4.1 Actual time required

Figure 4.2 Actual time plus some time for variation

Figure 4.3 Actual, variation and some time for other activities

Figure 4.4 Actual, variation, other activities plus some time for interruptions

Usually the people who are going to do the task are invited to give such estimates. Therefore for any one task the estimate looks like Figure 4.1. The bar represents a period of time equal to the estimation. This is usually based on all things going well, but how often do things go wrong? There can be substantial variation during execution. The task might prove to be more difficult than previously thought. The technology might not work. The specification might be changed. There might be rework necessary before handover, and there are many more examples of variation within the task. This means that there is a level of uncertainty in the estimation, which has not yet been included. Therefore, in order to accommodate the possibility of such variation the bar changes to that shown in Figure 4.2. Though the overall time has been increased, the potential for variation has been covered. But what if I have to do other things in the same time frame? What about all the other projects I am involved with? What about the various meetings I have to attend? What about the other responsibilities I have to discharge in the course of a normal day? I had better include all of these in my estimation. At this point I know that if I do not take account of all the possible interruptions I know will occur in the lifetime of this task, then I will be in danger of not completing it on time. This results in a further extension to the original estimation (Figure 4.3). But how often in the working day am I interrupted? There are always additional interruptions to those already included taking place, and all of the time it seems. The telephone calls, e-mails to catch up on, the dreaded knock on the door, a whole plethora of small events that somehow add up to most of the working day. Every time it happens I lose time on all the other activities I am supposed to complete; therefore I had better include an element for that as well (Figure 4.4). Now I have an estimate to be proud of! I have included the time to complete the task itself; I have included time for the possibility of variation within that task; I have included time for all the other tasks I am responsible for at the same

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Figure 4.5 The estimation given

time; and finally, I have covered myself from the variation that occurs as a result of interruptions. This leaves the estimation looking like Figure 4.5. The next question is related to the time we are prepared to commit to. Once we move to execution, it is likely that most times we shall finish as shown in Figure 4.6. Note that the statistics show that we hit the actual time we said, in other words we appear to finish early compared to the estimation given (elapsed). Note also that there are times when the activity did not finish around the actual estimation but way beyond it. In other words we needed some, and at times all, of the protection we felt was necessary. There will even be times when the time required was even further to the right than t4. In the cases where we were clearly late there are of course many explanations that we can quote. The result is the same however: we were late and that conditions the next estimation. Giving a commitment in terms of an estimation is a different exercise to where we think the activity might finish. Experience has taught us that if we give a commitment and fail to meet that commitment, there is the likelihood of being taken to task about our non-performance. It is always preferable to err on the side of caution: better to be applauded for completion on time, with a reasonably large estimation, than be penalised for finishing late with a small estimation. In many companies, in many project environments, the usual reaction to such events is to work with the largest estimation allowed and then work carefully to it. If management cuts the estimation there is still sufficient protection to allow some degree of comfort. There is a danger, however, with such estimations; I call them elapsed estimations, rather than the actual estimations. We feel that there is plenty of time, so often the start of the activity is delayed (Figure 4.7). We complete other tasks, we allow interruptions, we attend to other activities and so on, without necessarily starting the task we were supposed to, at the time we thought we might. This leads to what is called the ‘student syndrome’ or ‘last minute syndrome’. Putting off the time to start, knowing there is plenty of time to complete. At least according to the elapsed estimation there is. The reality is different however. In Figure 4.7 the task has been delayed for other events to take place. I now start the activity with much less time left within the estimation to give the level of protection I felt was essential when first the estimation was given. But I have done nothing to reduce the possibility of further interruptions or variation within the task itself. Now the task starts later, and I have done nothing to change the content of the task so the possibility of variation has not changed. Now there is every chance

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Figure 4.6 Moving from estimation to execution

Figure 4.7 What happens when we delay starting the activity?

that the completion date will be put in jeopardy. Though the actual time to complete may not differ much, the time at which the activity is completed has been shifted along the x axis by a considerable margin and the likelihood of missing the due date is now very high. Equally all subsequent tasks also run the risk of starting late as a result (see Figure 4.8). In the construction of the critical chain schedule the key aspect is to work with the original estimations, the actual estimations rather than the elapsed estimations, and account for the possibility of variation at a different location,

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Figure 4.8 The real pressure on the project

and work the project differently to remove the possibility of negative impact from other project activities and interruptions. A description of critical chain starts with the recognition that the constraint of any project is the longest chain of dependent events by resource measured in time. This is what dictates the overall lead time of the project and is therefore de facto the constraint. Remember, the constraint is defined as anything that prevents the system from achieving the goal set for it. The goal of a project is to deliver a product or service by a certain time, the due date. The faster the due date can be achieved the faster the system achieves the goal. This is why time, measured from the start of the project to full completion, with no degradation of specification and full compliance with the budget, is the constraint of any project. This is of course dependent on the ability of the team to produce the network of activities properly and completely for the lifetime of the project. It also means that management has the necessary tools to identify the critical chain. Certainly within our experience we have identified the critical chain without the need for specialist software, though having that facility does help. Within multi-project environments, however, the use of appropriate software is essential. Assuming we have the necessary tools, at this point we should have the constraint of the project clearly identified. A worked example: single projects Consider the following project network. This is a simple project and has been produced using the rules and procedures of critical chain. Estimations have been used that reflect the actual time to complete each task rather than the elapsed

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Figure 4.9 Initial project layout

time. The logical structure has been validated, in other words the activities have been checked in terms of both preceding and successive activities. Each type of shading represents a single resource, each different from any other. The key project people, the project leader, the team leaders and the client, have approved the network. Remember, as the estimated times are actual and not elapsed there is little if any protective time, or float, in any of them. Though the overall time to completion may seem short, there is currently no protection for variation of either special cause or common cause. Also note that the project activities have no start and finish times, only durations. Neither are there any milestones. Often these fixed times act as an additional constraint and measurement for the project. However, constraint management argues that the success of the project is not determined by any internal milestone or dates fixed in the calendar by the software, but by the overall completion of the project. Hence the importance of task durations during the estimation phase (Figure 4.9). The next step is to identify the critical chain, the constraint of the project. This is defined as the longest path of dependent events, by resource. As a matter of interest, the critical path is from M1 through G2, M3, B4, B5 and Y4 to completion. The critical chain, however, is different and is shown in Figure 4.10 with activities shown shadowed. Therefore the critical chain activities are R1, Y2, Gr3, G4, G5 and Y4. All the other activities are feeding that chain. However, the time to completion is not the sum of the critical chain activities: there is still the question of protection. The normal protection contained within every activity is not present, therefore protection in the form of buffers must be included. This involves both sizing and placement. The first buffer to work on is that concerning the resources. It is vital that the key people are available on or slightly ahead of the time they are due to work on the project. If they are late then the likelihood of the project running late is high—they are after all working on the critical chain, and therefore the constraint of the project. Any delay on one critical chain activity places a delay on the whole project. Resource buffers are used to give an early warning to the resources, and the resource managers, to allow them time to prepare for the work they have to do.

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Figure 4.10 Critical chain identified

Equally, if the preceding activity finishes early, then we want to take advantage of such an early finish and move quickly to the next activity; if the resource is waiting for the original start time, or continues to work to a computer-generated start-date or policy-determined milestone, then we have lost both the opportunity to move the project forward and the opportunity possibly to finish the whole project early. Thus the resource buffer is an important aspect of the critical chain approach (see Figure 4.11). One final aspect of the resource buffer concerns the ownership of the resource. There are two key managers in this project, the project manager and the resource manager. The commencement of the resource buffer heralds the shift of control of the resource from the resource manager to the project manager, where it remains until the task is fully completed. Once the resource buffer has been sized and placed, the next step is to protect the project from variation within the tasks themselves. Thus the critical chain and the feeding chains require protection. These buffers are called the project buffer and the feeding buffer respectively. They are situated at the end of the chain they are protecting and sized according to the level of risk within that chain. This level of risk takes note of all the usual sources of paranoia in the minds of the people doing the tasks and of those managing them. Now we have the final project structure with the buffers in place (see Figure 4.12). Each resource buffer is in place to protect the start of the critical chain activity for its respective resource, and the feeding buffers and project buffer are also ready to do their job. It is often noted that there are activities

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Figure 4.11 Resource buffers placed

which begin prior to the critical chain activities; this leads to the suggestion that the critical chain has moved. The critical chain is defined prior to buffer insertion. Just because M1 starts before the first activity of the critical chain R1 does not make the constraint of the project shift to that arm of the project network. The longest set of dependent activities is still from R1 through to Y4. In order to ensure that the chain from M1 to B5 does not impact the constraint, the feeding buffer is inserted and the size of the buffer reflects the level of paranoia the people have about that set of activities. What we have now is a project plan with all activities utilising actual times, not elapsed, with the buffers all in place and the due date checked. If the overall time envelope of the project plan, including buffers, exceeds the overall time allotted to the project, it is necessary to elevate the constraint. This might mean checking the logic linkages between activities, adding more resources, subcontracting some activities so that they can be completed in parallel with other tasks and so on. At the end of all this activity the project plan can be approved and implemented. We are ready for the transition from estimation to execution. In execution the key question to ask is: What is the remaining duration of the current tasks? This gives much more information than simply asking how much has been done. Time is the critical factor, not work done, and knowing how much time is left gives a clear indication about the robustness of the plan, and about the implementation. Also we are seeking early finishes being handed on,

Figure 4.12 Complete critical chain project plan with all buffers in place

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Figure 4.13 Example of a buffer

so there is an expectation that the initial buffer size will increase as activities finish early, and decrease when they finish late. The buffer time is therefore dynamic once we are in execution. Using the zone management approach to the buffers gives us a clear indication as to whether any penetration is due to special or common cause variation. The level of penetration determines the actions necessary to address the scale of the problem. All focus is now on the completion of the project on or ahead of time, not reacting without reason to the delays that might occur to any one task or set of tasks. Buffer management Let us examine the use of buffers, in this case a project buffer. A buffer in almost all constraint management applications is comprised only of time. Let us assume a buffer length of three months for a project whose critical chain is nine months. Once into execution the project updates simply consist of determining the remaining durations of all live tasks and entering the data into the decisionsupport system. There will be variation here, with some tasks finishing on time, some early and some late. The level of penetration of the buffer and the nature of the buffer violator determine the level of concern about the status of the project. Buffers comprise three zones, usually but not necessarily equal. In our example each zone is one month long, as shown in Figure 4.13. The buffer is in place and the reports will show, if all tasks are finishing early, that the buffer has actually grown in size, moving the left-hand end further left, the due date never changing. The reports produced will usually show all three variables, on-time, early and late, this giving a clear picture of project status. In this example, as we are only examining the critical chain, in which case the buffer being penetrated is the project buffer, Figure 4.14 shows that some tasks have indeed finished late and the result is that the first zone, zone three, shows the level of penetration. Now I have to ask some questions about this penetration. What I am not going to do is react to the penetration and start to take remedial action, which usually involves adding to cost and knock-on effects on other parts of the project. First, where is the buffer violator and what is the nature of that violation? This line of questioning is trying to determine whether the problem is due to special or common cause variation. Effectively all I am going to do at this stage is watch what happens; if the violation is quite large and the location of the buffer violator early in the project, then I shall take great care to keep an eye on the next few days and the progress of the current task set. But what happens if the problem persists, or another problem hits the critical chain? Then the buffer reports will show further penetration of the buffer,

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Figure 4.14 Zone three penetration

Figure 4.15 Substantial penetration

perhaps just into zone two or possibly close to zone one. The level of paranoia is now quite high. Planning will take place to determine the best course of action in order to bring the project back under control and give the remaining tasks sufficient protection. Figure 4.15 shows that the buffer has been penetrated to the start of zone 1. Now the plan developed whilst the penetration was only in zone 2 is put into action. All the time the focus remains on the due date, the remaining duration of the tasks, with the specification still being maintained as at the start, zero defect as a given. Delivering the project The final element in the implementation is to ensure that all the people involved work according to the new rules of managing projects. This is the dimension of subordination referred to in the five steps of focusing. Once the decision has been taken to implement critical chain, then there is no further debate. Subordination is the order of the day. Early finishes are passed on correctly, the work being undertaken is done in such a way that the problems that might have been common in the past are no longer there. There is little or no multi-tasking, people do not wait to start activities, and if an activity has been released to them they start without delay and work through to completion properly. Early finish is not a concern that might result in estimations in the future being reduced. Early finishes just reflect statistical fluctuation and nothing more. This leads us to consider the behaviours that exist in a critical chain environment. The intention is to have an open and honest culture where people are encouraged to work together as a team, often across functions and levels. There is no blame culture in such an environment. In terms of network planning the actual estimations are freely given; network validation and resource definition are exercises to assist the project to completion, not to protect oneself from attack. Tasks are only carried out in line with the plan and the relay-runner ethic dominates. This means that people run as fast as they can and hand over in a clean and effective manner. They are only focusing on the tasks in hand and no other tasks, thus reducing the level of multitasking; they report duration to

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completion; they report early finishes; and if there are problems they report them as early as possible. As already noted, buffer management is the key to the successful operation of the plan, and the buffer reports go to the key people within the project, to the key line managers within the organisation, and also to those key people outside the immediate project area. This might include the client, the suppliers and always includes the senior management levels. The expected effects on the projects are on-time or early completion, no reduction in specification, good budget control over the lifetime of the project, better safety statistics, reduced firefighting, higher morale and significantly increased margins. In terms of the organisation the expectation is that the company is more competitive; it is able to attract higher market share; it can achieve higher levels of turnover; it can choose which projects to take on board; it can achieve the profit target set; and it is in the position of ensuring that the client is satisfied and that repeat business becomes the order of the day. If we can do all that, then we have achieved the goal set out in Chapter 1 and the necessary conditions that must be met. The sequence of creating a critical chain schedule ready for implementation Any ERP type application such as critical chain, which uses the CM process of analysis and solution development, contains a series of features. These features refer to both software and the management methodology. It is important that all the features contained within the solution, both the initial generic solution and the final specific solution, are properly understood, validated and implemented. Therefore in order to deliver the critical chain solution, there are a number of features that must be achieved. These features fall into two distinct categories: the first refers to the generic elements that are common to all critical chain project implementations; the second to those aspects which are specific to the environment in which the solution is being implemented. The feature set of creating and implementing a critical chain schedule therefore follows the path outlined below: 1 Construct the network of activities using the estimated actual times, not elapsed, and with all proper logical connections made with specific reference to resources and the links between them. 2 Ensure that the project team have the opportunity to consider the activities in terms of where the inputs are coming from, who is providing the inputs, the precise nature of the tasks, the expected outputs of the task, where the outputs have to go, the equipment required, and so on. 3 Submit the network to critical chain software to identify the critical chain itself and to check for problems: first, those of logical connection, and then of resource conflict. Allow the software to provide the initial schedule.

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4 Having determined that the critical chain identified meets the needs of the client, insert the appropriate buffers: project buffer, feeding buffers and resource buffers. 5 Once more ensure that the overall project plan still complies with the requirement of the client and the organisation. 6 Communicate the plan to all involved parties for review and comment to ensure that they can sign up to the plan and their commitment to it. 7 Ensure that the changes to the measurement systems have been agreed and implemented especially with respect to resource effectiveness versus efficiency. 8 Ensure that all parties to the project are able to work without interruption whilst performing their tasks and to complete the task as soon as possible and then pass it on; that is, report completion as soon as it is finished. 9 Ensure all suppliers work to the same rules and procedures and delivery measures. 10 Ensure that buffer management principles are properly understood, with agreement as to roles and responsibilities should problems arise. This set of features forms the basis of critical chain implementation. Once the project has been launched, the focus moves from estimation to execution. The reporting of tasks now forms an integral part of the whole process. It is important that remaining task durations are supplied so that the project plan can be upgraded and buffer penetration determined. Now the estimations are of no value, it is simply sufficient to focus on the sequence, and move the tasks through as fast as possible, keeping to quality on all other contractual requirements. Project example: single project Figure 4.16 shows a simple project network: I have taken a few liberties with the names allocated to the various tasks, but that is not the primary concern here. What I have produced is a simple project network, constructed in PERT and then translated into the more familiar Gantt chart. The resources have been allocated and all task times are based on the actual time to complete and not the elapsed time. Had I used elapsed time estimates, then the project would have taken much longer to complete. Once this network has been constructed, it is verified by the team responsible for the critical chain implementation and the various people involved in the tasks. It is vital that all members of the project team are able to validate the project network The next step is to determine the critical chain of this network. For this example I have used the critical chain software available from Prochain Inc. in the USA. This uses MS Project as the data entry mechanism, and then a series of menus to implement the critical chain procedures. The first step is to validate the

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network once more and then to determine the critical chain itself. This is shown in Figure 4.17. Note that the critical chain crosses individual paths, something that does not happen under critical path. The critical chain is highlighted by means of closely spaced diagonals. Once the critical chain has been determined, the next step is to size and place the buffers. For this exercise I have used a size which is 30 per cent of the chain being protected as the buffer size. This is a judgement call, a management decision. It is linked to the level of paranoia that I have about the level of variation, both common and special cause, that might affect the critical chain and the feeding chains. For the resource buffers I have used a standard of five days but that could be changed depending on the nature and reliability of the supplier. Once sized, the next step is to place the buffers, and this is shown in Figure 4.18. So let’s examine the final layout with all buffers in place. The grey box is our project buffer, the dotted boxes are the feeding buffers and the boxes shaded with widely spaced diagonals are the resource buffers. Note that as a result of the insertion of feeding buffers some of the feeding chains start before the critical chain. This does not make them the critical chain. The critical chain is defined before the buffers are inserted. Though inserting the feeding buffers may take the start of a feeding chain earlier in time, it does not change the critical chain, the constraint of the project. Some people also point out that the original plan, that in Figure 4.16, has an earlier finish date than the final plan with the buffers in place. Whilst that is true it ignores the fact that the estimates being used are actual time estimates, not elapsed, and if we were to use elapsed estimates the timescales would be much closer. What we have now is a critical chain project network with the protection where it is of most value, at the end of the chain rather than spread thinly across all activities. The next step is to ensure that the overall project profile still fits into the timescales demanded by the customer. If it does not then the logical connections must be re-examined, the resource levels must be re-examined, and the timescales checked with the customer. There are other areas to examine but these are the most common. If the project refers to new project development and launch, marketing will be involved to ensure that they are also ready with their side of the launch; the same applies to production and distribution. Once the project has been signed off, it is then launched into the system. Reporting now follows a simple path: only provide the remaining durations of the tasks being undertaken, ensure zero defect in all activities, and signal completion of tasks straightaway, thus allowing swift handover to the next resource and the start of the next task in the chain. Substantial delay in start? Not all projects start on time; there are delays for a variety of reasons, so how does this show up in the information system being used within critical chain (see

Figure 4.16 Basic project network

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Figure 4.17 Critical chain determined

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Fig. 4.19)? What this figure shows is that nothing has happened to the project, no activities have started whatsoever. The delay is some eight weeks and therefore

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there is penetration of a number of buffers, both feeding and project. The status of the project is clear and the reasons can be examined. Now the situation, illustrated in Figure 4.20, seems bleak, the project buffer has been substantially penetrated. It is at this point that discussions will centre on how to bring the project back under control. The options discussed before will be examined, the impact of any decisions taken using the what-if facility of the software, and the areas where the work has to be carried out informed and involved in the discussion. Once agreement has been reached, the only thing left to do is implement the plan and measure the results (Figure 4.21). Action has been taken, tasks have been addressed and brought under control. Note that the project buffer has now been brought back to the initial condition. Remember that buffers are dynamic: they can be used, and they can be repaired. Time can be gained under critical chain management; the focus on remaining duration, the focus on handing over as soon as the task is completed, the focus on what is happening within the buffer, and the level of penetration, are central to the critical chain project management approach. This project will now continue through to a successful completion. The remaining tasks are well protected by the remaining buffers, and it is likely that the project will in fact finish ahead of the due date, which is at the end of the project buffer. Multi-project and critical chain What has been described so far applies in the main to single project environments, but what about multi-project environments, where most NPD is carried out? The research that has taken place over the past three or four years has highlighted that the real power of critical chain project management is released in this environment. Though not recognised in 1997 when the book by Goldratt first came out, the bulk of the implementations of critical chain lie in this area. Managing critical chain within multi-project environments Thus the real test of managing critical chain comes from this area. The lessons drawn here are from a number of implementations with which we have been involved over the last four to five years. In each case the company was a major player in its chosen market, with tremendous pressures to stay in that position. They each saw critical chain as a means to achieving that end, but with varying results. The traditional approach to managing multi-project environments is simply to release projects in line with the demands from customers, or the needs of cash flow, or both. Rarely do the considerations of the resources come into the equation. This often leads to the situation where key resources are scheduled across a number of projects within the same time period. The technique is usually called ‘fractional head count’ and has usually contributed to substantial delays in project completion for all projects where the resource is being employed, to added cost overrun, to added resource ineffectiveness and to high levels of stress for all concerned.

Figure 4.18 Buffers in place: the final project network

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Figure 4.19 Project start delayed

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For the key resources the normal procedure would be to schedule their work in line with the demands of the project and resource managers. In the example in

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Figure 4.22 they could start project 1 without difficulty, but once project 2 has been released and the time for their involvement arrives, they are immediately under pressure to stop working on project 1 and switch to project 2. This means that no work can continue on project 1 until the resource has completed the work on project 2. But then project 3 starts and once more there is pressure to move to that project; now there are three projects under way, all demanding time from the key resource. This typically translates into the work profile shown in Figure 4.23. What is happening is that the elapsed time for each activity is now considerably greater than the estimated, though the actual time spent is probably close to that original estimation. For project 1 the real time of completion is much later than before, which means that all subsequent tasks are also late, which typically means that the overall project is now very late. The same is true for the other two projects. Note that project 2 has suffered in that projects 1 and 3 have been able to capture the key resource for quite some time. This usually means that the priorities for projects are subject to considerable interpretation. Note also that the resource is very efficient, which means that both the resource and the resource manager are unlikely to attract any undue, and probably painful, attention. The project manager for project 2 has a very different view, having been hauled over the coals for non-performance in his, or her, project. What is required is a very powerful variation of resource levelling. It is not enough just to shift the resource activity in time: all that happens then is that the resource is not overloaded. The essential importance of that resource must now be recognised. Once the key resource has been identified, it should be recognised as a second constraint within the project environment. The first constraint for each project remains the critical chain of each project. But now we have a new and more powerful constraint in that it affects all the projects the key resource is involved in. The starting point is to stagger the projects closely as shown in Figure 4.24. What we have done here is to stagger the projects in such a way that the key resource is no longer having to switch between projects but can complete one before moving to the next. The resource must finish each activity before moving to the next project. What has now developed is a fully protected project environment (Figure 4.25) where the strategic resource is able to function properly. Using the buffer management described as part of the single project solution, let us now examine what happens when we move from estimation to execution. The key to managing this system now is the linkage between the projects. The gap in terms of time that now exists between the activities of the key resource in project 1 and subsequent projects is to decouple the projects such that a delay in project 1 does not violate the project buffer of project 2 and possibly that of project 3. The gap of time, called the strategic resource buffer, simply acts as a period of time, which is used only if tasks in project 1 start to slip, slippage which is covered in the project buffer of project 1, without violating the protection of project 2. Let us assume that project 1 does indeed go late, but by a

Figure 4.20 A worsening situation

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Figure 4.21 Project status after action has been taken

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Figure 4.22 Multi-project release

Figure 4.23 Project loading: key resource

Figure 4.24 Staggered projects

time less than that set aside for the strategic resource buffer. The project buffer of project 1 will be violated and the normal procedures of buffer management will start to function for that project. Project 2 is still not affected by what is happening in project 1 and is therefore still OK. Once the key resource is able to complete the project 1 tasks, it moves to project 2 and starts the project 2 tasks. Any remaining time in the strategic resource buffer is therefore effectively added to the project buffer of project 2. At the same time project 3 is still robust simply because all subsequent tasks move earlier in time. Should the tasks in project 1 finish on time, then there is no need for the strategic resource buffer to be used at all. The resource can move straightaway to the tasks of project 2, thus pulling project 2 activities earlier in time, with a similar effect for project 3 and any other projects which have already been

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Figure 4.25 Fully protected projects

released. Of course, if the tasks of project 1 are finished earlier than scheduled, then the tasks of all subsequent projects for the key resource are also pulled earlier, with the considerable advantage that the revenue stream is now arriving ahead of the scheduled time. Today we see companies taking advantage of web-enabled project management software to link sites across wide geographical areas and time zones. The software is not a replacement for sound project management but enables managers to keep control, and ensures a level of co-ordinated decisionmaking that was rarely possible even five years ago. The buffer reports, which are all senior managers need, are now available almost immediately, and only show up when there are violators affecting project performance. A case study from the multi-project environment: high-tech industry This company is active in the development of disc drives for the computer industry. It has long recognised that only by a ruthless focus on new product development can it maintain and grow its market position. There are always nimbler competitors around. Currently with 23 per cent of the disc drive market and 30 per cent of the tape-drive market, the company has had to fight hard to maintain position. The target set by the company was to introduce new products in half the time usually taken, and it is now well on the way to achieving that goal. Not only is Seagate now producing products faster, it is also doing that with the same resources as before, and indeed producing more products than before. The Executive Director of Process Leadership argued that: Although cost always remains king, flexibility and time to market dominate our priorities today. We must be able to create and introduce new products faster. Generally, the first supplier to enter the OEM quality cycle enjoys preferred status. It’s the part that gets designed in. Our studies showed

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that a delay of even one day in product launch costs one $500,000 in lost revenues and $300,000 in bottom-line profits. (Unpublished case study) This is not a unique feature of just this company. The same results are coming from more and more companies adopting this approach. The Executive Director and his team-mates created a vision for their development. To them NPD was a strategic planning business unit, interfaced tightly with the customer. Product portfolio management was aligned closely with technology and resource availability. To increase decision-making bandwidth and velocity the senior team flattened out the organisation by introducing core teams. A team was defined as a small number of people with complementary skills who were committed to a common purpose, performance goals and an approach for which they held themselves mutually accountable. Utilising the new structured development process, they were empowered to run each programme as a business unit. The company also realised that having a process was not enough. It needed enterprise software support to manage the complexity of product development. Furthermore, given the unique nature of product development, with high levels of uncertainty, traditional project management and reporting software would not do the trick. They needed software that complied with the critical chain methodology. The key team determined that complete functionality in the chosen new product development (NPD) software had to have three aspects: technology portfolio management, pipeline management and programme/project management. At the same time the company was clear that enterprise software was not just about database reporting and process automation. To deliver true value, the software had to break the fundamental barrier to NPD performance: time collaboration. They realised early on that the key reason collaboration was breaking down was not lack of communication. Many people were actually overloaded with information. The real problem was how to maintain consistent priorities across the organisation when everything was in constant flux and there was competition for shared resources. It was going to take more than process automation or communication to solve this problem. This required having intelligence in the engine that could give signals on time: collaboration. An extensive search ended with Speed to Market, a young company that did not have a complete product suite at the time, but had a breakthrough solution for project execution, based around the critical chain model. It was not an easy decision, but the company went ahead with the Concerto route. The results were dramatic in a short time. They chose a strategically important programme to first implement the critical chain Concerto system. The programme was already late, and over $500 million was riding on this project. The new system was put in place to recover some of the delays. One senior team member noted that:

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Not only were we able to recover delays, we were able to bring the new product out five weeks earlier than our original plan. This was the first 15, 000 rpm disc drive to hit the market. All competitors dropped out, either due to the technical challenge or because they were late to the market. We were quickly qualified by our top two customers and began shipping within 30 days. Those five weeks produced an extra $11M in revenues and $5M in gross profits. (Unpublished case study) The results are not just on the bottom line. For one, critical chain Concerto has simplified the life of the company’s knowledge workers. They no longer have to be burdened with meaningless reports and sit in long, contentious meetings fighting for resources. They have simple, actionable signals. There is complete consensus on priorities. The result is a dramatic boost in collaboration and trust. Another big impact has been the reduced need for data. No longer do managers have to worry about all the details. One senior executive summed up the implementation by stating that critical chain Concerto puts the core team member at the centre of the action. The software reduces the number of critical items on which managers must focus. Since not everything is critical for programme velocity, Concerto filters out the noise and centres on only what is relevant. Further, it uses buffer management to proactively manage likely trouble spots. Managers receive intelligent forward looking signals on where the delays are likely to be, and information necessary for them to take action to avoid them. A strong what-if capability enables team members to quickly understand the impact of their decisions on the overall goals of the company. Once this impact is understood, they make the right decisions themselves. (Unpublished case study) Conclusions The role of critical chain project management within the revenue chain is to shorten dramatically the time to market of all products through the early/on time completion of all projects and to ensure the proper level of co-ordination throughout the organisation. Of course it is of little value being able to cut the time to prepare new products for the market if production are not ready to play their part. This means that the same level of co-ordination, the same level of focus and leverage developed within NPD, the ability to achieve consistent and coherent decision-making, must now be implemented within the production area. This includes purchasing, planning, the adoption of many of the current key themes within manufacturing industry such as TPM, TQM, SPC, and all with a

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constraint management perspective. It is to that aspect that we now turn our attention.

5 Managing production

The greatest honour I have in my work is the ability to see many different companies and how they manufacture their product. Being able to walk around many different types of plant, steel works, computer chip manufacture, printing, chemical plants, pharmaceutical plants, automotive suppliers and many more, is a privilege few people are able to share. Typical problems in production Whenever I go round a manufacturing plant it is strange how easy it is to see much the same problems in all of them. Each manager taking you round is convinced that his or her problems are unique to not only that industry, but also that company. Whilst there are times when such local issues take centre stage, they are few and far between. What is also interesting is that the financial aspects of the production area are not high on the list of many production managers: they are focusing closely on problems related to due date compliance, lead time extension, quality in all its various forms, suppliers failing to deliver, customers with unreasonable requests When the issues lie within manufacturing the response is typically to consider the approach known as drum-buffer-rope, first described by Goldratt and Cox (1984) and then by Goldratt and Fox (1986) and Goldratt (1990). It has also been described in many other books, some of which are listed in the bibliography at the end of the book. What I am going to do here is to introduce the conceptual solution, and then discuss some of the key features of the implementation that I have learned over the past ten years. I shall also explain the role of the simulations we use as part of the education as this forms a crucial element of any implementation. The problems that exist within production are hardly new. As I visit many production facilities I find, as do many others, that the problems are by and large generic. Consider the following list: 1 Due dates are often missed: what this means is that the product, or service, was delivered late to the client. Many companies pride themselves on being able to achieve due date performance (DDP) greater than 90 per cent, yet

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even this achievement acknowledges that there is still much to do. However, many companies are still operating at DDP levels of 70 per cent or less. This leads to pushing back launch dates for new products, marketing having to rejig their forecasts, sales becoming convinced of the need to outsource the production area to more consistent and reliable sources of product. It means that the customer service area is continually trying to placate customers seeking knowledge of the whereabouts of their order, and almost certainly changing priorities as a result. 2 It is difficult to respond to urgent customer demand: so that whenever a client rings and asks for an order to be pushed through it is either accepted in spite of the almost certain knowledge that it will be late, or some other orders will be pushed late to accommodate this rush job. Either way there is always a certainty of outcome: something will have to give. Of course it may be possible to put more resources on to the orders by using subcontractors or hiring temporary staff, but this has cost implications. 3 There is too much expediting: I need hardly say what this means; just watch the people tasked with expediting work themselves into the deck. Always chasing, always trying to resolve issues, always changing priorities, always falling foul of other managers, and, if truth be told, rarely succeeding in their overall task. In one company we were told that it was far quicker to release a new, replacement, order than to find part-finished or even finished product that appeared to be missing. 4 Inventory levels are too high: one of the more interesting aspects of the work I do is that when we are successful people see parts of the plant they have never seen before, at least not for many years. As the levels of inventory are reduced, space becomes apparent once more. It is also important to remember the cost implications of this high level of inventory: it must have been purchased, it must have used up some of the financial reserves of the organisation, but it may wait many months, if not years in some cases, to be sold. At the same time, this high level of inventory also hides the real performance of the resources: busy they might be, but productive? 5 There are frequent material/parts shortages: this has always puzzled me, why do we have too much inventory at the same time as too little? The answer lies in the type of inventory we are describing. That of which we have too much is not required right now, whereas that of which we do not have enough is exactly what we need right now. We may have it, but it is not where I need it; we may have had it, but have used it to satisfy a batch requirement; we may have failed to purchase it, in trying to control costs of purchase production has been starved. 6 Production lead times are too long: this is interesting because, whenever we start to work with clients, this is where they want us to start. They always seem to say that product is taking too long to reach the market and therefore they are about to purchase some expensive piece of machinery to speed up the whole process. In my experience nothing is further from the truth. Rarely

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does the purchase of a faster, better, more efficient resource lead to overall improvement, typically quite the reverse. When we carry out an audit of the production facility, what we usually find is that the overall lead time may be measured in weeks, and the sum of the process times for any product measured in hours, or maybe a day or two depending on the nature of the production process. What we have found is that the balance between actual time on a machine to time in the production area is about 1 per cent being worked on and 99 per cent hanging around waiting for something to happen. It might be sitting in front of a machine waiting to be worked on, it might be waiting after a machine for the rest to join it on the pallet. It might be waiting for inspection to appear. Whatever the cause, in most production environments material spends more time waiting than being worked on. At the same time much investment is being spent speeding up the 1 per cent and little is done about the 99 per cent. No wonder most investments in technology fail to deliver other than a highly localised improvement, which is no improvement at all. 7 Priorities are constantly shuffled: this can hardly come as a surprise after what has been discussed so far. With all that expediting, all those urgent orders, all those shortages, it is a wonder that anything actually leaves the plant at all! Yet this is still a key area to understand. In one implementation of drum —buffer—rope one of the problems with implementing the system was the fact that the operations director could not stop tinkering with the priorities, trying to improve matters by constantly changing things around. The hard lesson for him was that he was actually causing many of the problems himself. The impact of all this change plays havoc with the schedule, plays havoc with the ability to deliver, affects the overall lead time, affects the due date performance and leads to reduced financial performance. These are just a few of the problems that we find in almost all production environments, both around Europe and within the USA. From Finland to France, from Germany to England, we have come across these problems and the impact they have. What we also find is that many companies have numerous projects, which are on-going, to address these issues one by one. However, the constraint management approach argues, as we know, for the identification of the core problem rather than those that are clearly visible. This is not to say that the core problem is not visible, simply that the real impact it has, the linkages between the core problem and the many other problems that exist, are hidden from view. What we must do is to surface those links, using the bonds of cause and effect logic, and then test the analysis to ensure we have not been seduced by the magnificence of our logical understanding.

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The dominance of material release and local efficiency The outcome of the many analyses we have carried out within the manufacturing sector leads to the following description. There is a major driving force within almost all manufacturing industry which is the absolute need to have managers run their plants by the optimisation of local resources, in other words local optima is how they are measured and therefore how they will function. This is the dominant paradigm in almost all of the manufacturing sector around the world and not just in the UK or Europe. Where this is the case, notions such as the importance of cost per part dominate thinking. This in turn leads to the desire to have large batches in order to save set-up costs and thus gain low cost per part manufacture. This ensures that the levels of material released allow for these large batches to be worked on. At the same time as this is happening, most managers agree that it is the local measurement of performance which is important to them. The ability to maintain high efficiencies for each resource under their control is how corporate measures their performance and readiness for promotion. Hence within many production areas, resources, both people and machinery, are kept busy. As one manager put it, ‘long live the protestant work ethic’. This means that the timing of the release of material is governed not only by the need to maintain the batch policy, but also by the efficiency policies as well. With this constant pressure to keep people busy we often find that the shop floor supervisors and foremen are taking material out of stores, hiding the occasional excess, for the time when there is nothing formal to do and they can then keep their people working: getting ahead, as they put it! So now there are three forces with respect to material release: the need to keep the batches at the right level for cost saving set-up reduction; the need to keep resource efficiencies high; and finally, the need to keep people busy when the formal system is not releasing material for people to work on. This leads to the inevitable conclusion that material release, in terms of both volume and timing, is related to these three forces. The laws of constraint management I have argued elsewhere (Hutchin 2001a) and earlier in this book for the importance of seeing the organisation as a chain, a series of connected, dependent resources that combine to make the whole. The laws of constraint management, which were developed as a result of my own research within manufacturing industry and the many implementations of TOC applications, are clear-cut and apply in all production environments. In Chapter 2 I discussed the laws in some detail, but they bear further examination with respect to production. The first law of constraint management is that every organisation is a system comprising interdependent elements that form a revenue chain. Most production organisations have more than one resource, which must interact with other resources, linking either material or information or both. The intention is that the

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focused management of these links will take the overall organisation to the desired goal, in other words that only by synchronising the efforts of all the links in the chain can the goal of the organisation be achieved. In many production environments the dominant measurement is still individual resource performance measured in efficiency terms. If the system is one of interdependence, then such measures are highly counterproductive. Given the chain analogy, the notion of the weakest link is straightforward. However, when the discussion turns to improvement projects it is amazing just how many such projects have little or no impact on the constraint, usually because those carrying out the improvement projects have no idea of the location, or indeed the existence, of the constraint. Hence the third law of constraint management, which argues that the constraint is the primary location for both focus and leverage for the improvement of the overall performance of the system. This also points the way to the five focusing steps as developed by Goldratt, the first of which is ‘identify the constraint’. We need to know where the constraint is if we are to have any chance of gaining the level of focus and leverage we seek. This also assumes that we know the type of constraint we are dealing with. We usually think of constraints as being physical, perhaps even bottlenecks, a specific form of constraint, defined as any resource whose capacity is less than the demand placed upon it. But there can also be policy constraints and paradigm constraints. This debate was covered in more detail in Chapter 3. The fourth law of constraint management is that improving any other link in the chain does not improve the overall performance of the chain itself. This might seem self-evident or, as some of my colleagues put it, a ‘statement of the bleeding obvious’. Yet in many companies we see many projects designed to improve the performance of non-constraints. This might be acceptable, but only just, when the constraint is not known, but it also happens when the constraint is known. This ridiculous level of waste might seem odd in what are supposed to be ‘lean’ companies, but it is usually due to the continuation of the existing local measurement system as much as anything else. What is not in dispute is that any such activity does nothing for the overall performance of the revenue chain. What we are alluding to here is the second of the five steps of focusing, ‘exploit the constraint’, which means: rather than try to improve non-constraint areas, exploit the one area that makes a difference—the constraint itself. This applies only to physical constraints; it is not possible to exploit either policy or paradigm constraints: they must be first subordinated to, and then eliminated altogether. Which leads us to the next law. The fifth law of constraint management is that subordination to the constraint in terms of the measurement system, the policies of the organisation and the way in which the people operate is a fundamental requirement of managing the chain. This is a tough call and is the third of the five steps of focusing, namely ‘subordinate to the constraint’. It is common throughout organisations for people to focus all over the place, which usually results in no focus at all. This is driven by the local requirement of the measurement system. People will try to maximise

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any number of the current measurement set and forget that there are only a few measures that really count. This taking the eye off the ball is common, and is highly destructive. When it comes to an implementation of constraint management, the role of subordination becomes ever more critical. The sixth law of constraint management is that the management of the constraint and non-constraints is dependent upon the use of an effective decision support system. This is not the same as a computer system with expensive software. Typically, within constraint management we are talking about buffer management. This is true of the three major applications: production, project management and distribution. There will be times when the use of computers will assist. I have scheduled hose plants with spreadsheets; indeed, we started in one such plant using flip chart paper for the constraint schedule and the release schedule. We have used spreadsheets in other types of plants, and it is not until the level of activity has been substantially increased that more advanced systems are necessary. They become important once the system is under control and increasing in volume. They will be part of the next level of improvement, but not always the first level. There is only one area where we have found it necessary to use software from the outset and that is in the area of multi-projects, which was covered in the previous chapter. The seventh law of constraint management is that variation in the system has most impact on the constraint. The variation we are talking about here is special cause variation rather than common cause. This last law also argues that variation at a non-constraint is therefore far less important. This leads to the necessary conditions of both a sound management methodology and a decision support system, which ensures that actions, as a result of such variation, are undertaken only when the management system says so. This is primarily when either the goal, or at least one necessary condition to achieve the goal, is being violated. There is also a dimension here about the difference between special and common cause variation where the buffer management has been found to be highly effective in determining the difference. The impact of WIP on lead time These laws, I have found, dominate all the various manufacturing projects I have been involved with in all the companies. So, if we return to our analysis of what is currently happening within the production area, what we find is that the timing and volume of material being released is governed by the need to make each resource efficient, producing at its maximum capability. This, in combination with the fourth law, concerning the improvement of non-constraints or making them work harder than the constraint, will lead to material or parts being released earlier than required, which means that the level of work in progress (WIP) has just gone up. Now if WIP is too high, and there is pressure to keep everyone busy, then the inevitable outcome is that finished goods (FG) will also be too high. You may remember when we discussed the role of inventory in the

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traditional accounting systems that this is not seen as in any way negative, though we might take a different view now. At the same time as this is happening, material is purchased according to the expected levels of demand. Often there are common parts, and therefore when parts are released too early, and they are also common parts and the ordering system only purchases in line with the forecasted demand, it is highly likely that there will be material shortages being laid at the door of purchasing, who in order to avoid negative responses from senior management will increase the level of material and parts being purchased, which in turn leads to ever higher levels of inventory. So not only do we have production consuming more inventory than it needs, thus creating more WIP and FG inventory, purchasing are also adding to the pile of inventory by bringing in more raw material/parts. Now if the level of WIP is high, then there is plenty of material for people to work on, which means that often there will be times when material that needs to be worked on arrives at a work station that is already busy on something else, which leads to material being stuck in queues at certain resources and on a regular basis. As lead time is directly proportional to WIP, then the inevitable outcome is that production lead times are too long. If this is the case, and if there are urgent customer orders also going through the same resources, then these orders will demand expediting, which, due to the level of work already in the system, makes responding properly to those demands almost impossible. Now, if we take account of the first law of constraint management, the importance of recognising that the goal of the organisation can only be achieved through the synchronisation of all the links, we can see that if we make a change in one link it will have an effect on the others. What this means in production is that if we change something in one department, there will be a knock-on effect. If at the same time there is the pressure to keep busy, and there will be times when instructions cannot be carried out, then existing priorities will be changed. Thus due to the combination of changing priorities and the changes taking place, there is an almost constant shuffling of priorities throughout the plant. This shuffling of parts usually demands that parts not initially required at this time are now critical. But it is equally certain that these parts will not be immediately available, because they were purchased against the original plan, not the new one; therefore we have the outcome that some parts/material are classed as a shortage. Also, as priorities are shuffled and there are often many common parts within the production facility, we now find that some parts are being diverted from one order to another: what one production manager called on one of our programmes ‘strategic re-allocation of resources’, or as it is called on the shop floor ‘stealing’. This in turn adds to the level of shortages experienced throughout the production area. If, as is likely, the level of FG does not include the necessary products to meet this current demand, and there is no chance of production being able to facilitate the quick transfer from raw material to finished product in the available timescale, then the shipment is missed and the delivery is late. This is particularly true when small amounts of the products are required, because this will

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be in contravention of the batch policy so that any small batch is placed at the end of the queue and will almost certainly miss any near-future due date given to the end customer. The inherent conflicts within the production area This is not a new picture, and the response of many companies is to expedite even more, recruit more progress chasers, all to meet the twin demands of accommodating urgent customer demand and of meeting the existing customer due dates. This leads to ever more expediting, more changing of priorities, and so on round the loop once more. Sound familiar? When we use the CMTP tools to examine this analysis, what we find at the core of the discussion are two very powerful conflicts, which can be described using the cloud technique. The cloud shown in Figure 5.1 highlights the conflict that exists between focusing the plant on meeting the needs of the client versus meeting the needs of the corporate measurement system, and the high level of importance attached to efficiencies. Note that there is a deeper conflict at the heart of this cloud. If we commit the plant to meeting the needs of the client, then we have already found that the need to maintain all resources at optimum, if not maximum, efficiency is compromised. Equally if we focus on individual resource performance, then we have also found that we will severely compromise on time and in full (OTIF). This powerful cross-connection within the cloud usually ends up with managers bouncing between the two positions, as described in the D and D′ boxes, depending on who is looking at the time. If the client is breathing down your neck, then efficiencies go out of the window. If corporate are visiting—coming in to help is the usual term —then just watch how efficiencies go up and, out of sight for the moment, the delivery performance collapses. The way to escape from this apparent stranglehold is to examine the assumptions that hold the conflict in place. Remember, it is the power of the assumptions that keep the cloud alive and maintain its destructive power. We know that for constraint management to be effective we have to break the logic of the cloud, and the place we want to break the cloud is also clear: we must remove the logic of the arrows from A—C—D′ as the other side has the customer, from whom all money flows. By examining the assumptions we can discover a window of opportunity. We can challenge the assumption that argues for the use of all resources all of the time, highest possible efficiencies, as being a necessary condition for achieving the goal. Equally we can also demonstrate that in any chain system the sum of the local optima is another erroneous assumption. If we shift our thinking by recognising the erroneous position of local optima summation, and then develop alternative measures that determine progress to the goal, we can keep the logic of the arrows from A—B—D, and replace C and D′ with two new elements. A set of measures that truly determine progress towards the goal, throughput (T), investment (I) and operating expense (OE), and at the

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Figure 5.1 The first cloud of production

same time focus our management efforts on the performance of the whole chain, from supplier to client, using DDP and overall lead time, and OTIF as the arbiter of successful performance. But this is not the only cloud to be driven by our analysis. There is a second cloud, which needs to be understood before we can move forward. This is shown in Figure 5.2 and demonstrates the conflict between allowing or not allowing non-productive time. This means the deliberate stopping of machines when they are not required to fill a customer order. This cloud is a fundamental challenge to concepts such as high machine rate utilisation. When a new machine is installed, the common practice is to run it constantly in order to gain a return on the investment, due to the process of cost allocation. What this usually means is that the organisation now has more inventory than before, which increases the carrying cost, delays other material from flowing freely through the plant, and results in precisely the opposite of that intended. Real supply chain management contains a fundamental challenge to this dominant paradigm of efficiencies, cost allocations and product costing. This is perhaps why so many companies have found that managing the supply chain without at the same time changing the measurement systems has limited improvement capability. Before that, one of the key aspects of any implementation is the level of education that takes place just to ensure that the conceptual solution has been properly understood. For this we use a number of simulations, both computer and

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Figure 5.2 The second cloud of production

actual. For example, one of my colleagues, David Marks, developed a simple and very practical exercise using four boxes each of which has a timer, some plastic cubes and some simple wooden pallets. Using this simulation exercise we are able to demonstrate the impact of cutting the batch size from ten to five on lead time, we can replicate KanBan, and of course drum-buffer-rope in a simplified manner. We have found these practical exercises to be of immense value in gaining an understanding of some of the simple rules that need to be implemented if success is to be achieved. The application of DBR simulations: an example of gaining consensus on the problem When we are working with companies in the implementation of DBR, we make good use of simple computer simulations. Using a simulated plant, which is able to replicate to a reasonable degree the actual operations within a production facility, allows both the student and the teacher to explore many assumptions about managing such a facility. The plant comprises eight resources, including an

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assembly area. It has three main products, the market demand is known and there are four raw material suppliers. There is one common part used in two different products. We typically start by asking the class what the usual problems of production are: those problems that always seem to be making the life of the production manager extremely difficult. A list is then produced which closely resembles the one given below: 1 There are many quality problems. 2 Absenteeism is a major problem. 3 Our suppliers are very unreliable. 4 The customer is always changing his mind. 5 Breakdowns are a common occurrence. 6 The schedules are always wrong. 7 Senior management interferes with the schedule. 8 There is not enough time to meet the demand. I then invite the class to work through this list and consider whether or not each is real, quantifiable, has a damaging impact on delivery performance and so on. I then inform them that I am going to ask them to run a simulated plant where there are no quality problems, a perfect workforce attending for eight hours every day for five days, suppliers who always deliver when there is cash to pay for the desired items, the market is fixed with no changing of minds, there are no breakdowns because the equipment is totally reliable. The class, in their teams, are responsible for the schedules, so that aspect is down to them; they are the senior management; and the whole of the demand from the market can be supplied by the simulated plant in the time given. In other words, I remove most of the suggested problems from this new environment; this should mean that they have no trouble in meeting the expected level of performance. I then ask them to meet a target of only £1,500 profit in the week, which means that there is no constraint operating within the plant. Actually this means that there is no physical constraint within the plant, but there might be a policy constraint, or set of policy constraints, in operation. They are then given five minutes to prepare and are allowed to proceed. The results are typically depressing. Out of five groups, each comprising two or three people, at least one and often two go bankrupt; others will have posted a loss; and maybe only one will have made a small profit, typically less than £300. In the review that follows we find that those who did well have usually imposed a policy of not purchasing material, thus ensuring that they do not go bankrupt, but of course also instituting a policy of not setting out to meet the market demand, even though there are no physical constraints within the plant. Those who have gone bankrupt have tried to meet the demand by purchasing sufficient material, but find they cannot get it through the plant within the timescale demanded. All in all there is now a universal recognition that the levels of performance are way below expectation and that something has to be done. They usually complain

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that the time allocated for preparation was insufficient and that given more time they would perform better. I now give them fifteen minutes to prepare. Once more they are given the plant to run and the results are checked at the end of the week. Once more the results are dismal. There is clearly something else preventing the expected level of performance, and not the list of problems suggested at the start. Sure, the problem set will exacerbate the problems, but they are not the causes of poor performance within the production environment; there are other forces at play. This is when the power of the five steps of focusing enters the equation. What we have been doing is to use a Socratic approach to allow them to discover for themselves that they do not know how to manage this simple plant, which probably means they don’t know how to manage their own plant either. The five steps of focusing: a reminder from Chapter 2 First developed by Goldratt, the five steps of focusing offer a powerful approach to understanding and analysing any system. Here we are going to concentrate on the production area, but, as already described in a previous chapter, the steps have been used in other areas such as project management and distribution: 1 Identify the constraint: constraints come in three distinct types: physical, policy and paradigm. Physical constraints define themselves; it might be a machine, a building, the number of people within the organisation, or some other aspect of the physical world. Policy constraints are those defined by the rules and procedures of the organisation. Examples include overtime bans, restrictions on travel, restrictions on recruitment and many more. Typically most policy constraints are related to some form of cost control designed to improve the financial performance, though most often resulting in precisely the opposite. The final constraint set is that of paradigm, the mind set of the people running the business. This is the most difficult to deal with, and the most difficult for managers to accept. 2 Exploit the constraint: this only applies to physical constraints. This is an aspect of improvement most often missed: make the most of the capacity you have before you invest in more capacity. There are many times when we visit plants to find that they identify the constraint and then jump to step four, elevate. They implement a new solution before they have both maximised the performance of the system as it is and ensured that they have gained proper control through subordination of all other aspects of the business to the constraint area. We can typically obtain 15–20 per cent more capacity and, if the market is able to take that additional product, additional profit just by exploiting the constraint, with no additional investment in machines or other technological services. Exploit only applies to physical constraints, however: it is not possible to exploit a policy or paradigm constraint, they must be removed altogether.

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3 Subordinate to the constraint: this is a tough call. In my research from 1993– 6 I examined why many change programmes failed to deliver results. The most common cause was a failure to subordinate to the proposed change. What is required is that once the constraint has been properly identified, then nothing else matters within the revenue chain. Everything must subordinate to ensuring that the chain functions as well as it can because this determines the performance of the whole chain. 4 Elevate the constraint: this happens when additional capacity is applied to a physical constraint or the policy is removed/replaced or the paradigm is changed. 5 Prevent inertia—go back to step 1: this typically means that once you have addressed the first constraint, there is another waiting to be identified, and that means you have to go round the loop once more, and continue to do so as performance is enhanced and new and more interesting constraints are surfaced. An amendment to the five steps The five steps have been around for some time now and many writers have described them in detail. There is one aspect that is often overlooked: setting out to design the constraint in from the outset and then driving the company accordingly. This often feels strange and both counter-productive and counterintuitive; but those companies that have understood the principle have gained substantially from it. The essence is that if you allow the constraint to move around your organisation, every time it does so adds to cost, and not just a marginal cost either: it can be substantial. It is far better to analyse the revenue chain of the organisation and then make a strategic decision about the best location for the constraint and use that as the basis for the whole of the manufacturing strategy. Developing the drum-buffer-rope solution The usual starting point for any work with drum-buffer-rope (DBR) is the ability to map the chain of events from raw material release to the shipping dock. In Figure 5.3 I show a simple plant: only two entry points for raw material, and eight resources, including an assembly point at resource 6. I give no information about the nature of the product range but it might be simply one product or a number of products that all go through the same overall process. For now let us assume only one product. Therefore, the diagram shows a very simple plant. Material arrives from the supply base and enters the company at two locations, resources 1 and 4. It is then processed by the other processes, with an assembly at resource 6, and leaves the plant to enter the market at resource 8. Very simple, and yet in many of the production workshops I have run over the last ten years, even plants as simple as

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Figure 5.3 Basic production layout

this have proved to be too difficult for many production specialists. The first step is to determine the constraint, the first of the five focusing steps of improvement. Well, to answer that question we have to ask some questions. What are the individual capacities of each resource? What can each produce in the course of a day, say a shift of eight hours? Where do we find such information? Who owns this information? One of the earliest lessons I had from my father was to walk around the plant and see what I could see. Now this might seem very obvious, but that is clearly not the case. I was on assignment in Portugal with one of the UTC Group companies at that time and I gave a task to a group of internal audit people to determine what was happening on the shop floor so that we could map the production process prior to determining the constraint. After the first day it became clear that they did not possess the eyes capable of seeing what was in front of them; they did not check the reality presented to them, but just accepted the words of the production manager. I took them round and showed them how to ask questions, how to watch what was happening and ask the question why. Indeed, I had to ask this question many times before I had an answer that matched the reality I was looking at. Looking at the labels on each batch; watching the flow of material; watching where it stopped flowing, asking why; watching where there seemed to be a build up of material, and asking why; watching some products leaving the line and being worked on elsewhere, and asking why. In fact this whole process of evaluation took some three to four hours until I was satisfied that I had a good enough picture of what was happening on the shop floor. Anyway, back to the simple plant. To make life easier let us assume that we have done the homework and the figures are as shown in Figure 5.4. So it is possible to agree that the constraint is clearly defined—resource 3. Most people attending one of my workshops will put their hands up and agree, yet they are

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Figure 5.4 Basic plant with capacity figures

not yet right: there is still insufficient data to confirm that resource 3 is the constraint. I ask them about the size of the market, I ask them about the capability of the supply base. Many companies today do not have internal constraints, they have enough capacity to meet the current demand from the market; their constraint lies either in the market or in the connection to the market, but not inside production. Equally there are many companies today which are struggling because their supply base is unable to meet the demand placed upon it: once more the constraint does not lie inside production. However, for the purposes of this exercise let us assume that there is no problem with either the supply base or the market, in which case the constraint as it currently appears from the data given is resource 3. This is the starting point for exploiting the constraint. In our simple plant there is only one product so the question of product mix does not yet apply. All I am trying to achieve at this time is the best schedule for the constraint that maximises the time I have in terms of the market I am trying to serve. If the data suggest that the constraint is capable of 200 units per day then this schedule should achieve close to that. I may want to include time for maintenance, quality checks and so on. These will take productive time away, but will also reduce down time and so will provide me with greater security of production (see Figure 5.5). There are three basic types of capacity: productive, protective and spare. I never use the term ‘excess’ as this implies that that level of capacity can be cut from the organisation without penalty. Productive capacity is simply that: the level of capacity necessary to deliver to the market product on time and in full, with zero defect. Protective capacity is that level of capacity required to protect the plant and the customer from variation within the overall process. I will discuss this in more detail later. Finally there is spare capacity: that level of capacity left over which in turn offers an opportunity either to make more product in the same time

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Figure 5.5 The key schedules within DBR

frame, or to reduce the production lead time in order to obtain an edge on the market. I will return to this question later. Now we have both the drum and the rope (see Figure 5.6); all that remains is to set the buffers. This is a simple exercise, though often not carried out correctly. The buffer, say the constraint buffer, operates between the gating operation, resource 1, and the constraint operation, resource 3. The length of the rope is measured in time and that is what constitutes the buffer. Sizing the buffer can be done in a number of ways but the simplest is to ask how long material usually takes to arrive at the constraint following release at the gating operation, and to use that. This lead time usually covers most of the common cause variation that occurs in production, and possibly some of the special cause as well. This is because most people cannot differentiate between the two. So for the sake of argument let us assume that the lead time between release and the constraint is six hours, then the constraint buffer should be set initially at six hours. The expectation now is that material released for consumption by the constraint in six hours time will be available. But ensuring that material reaches the constraint on time is insufficient for achieving OTIF. We must also ensure that all of the activities that follow the constraint are also completed without fail. There should be no problem as these resources are not the constraint; they have ample capacity to meet the target. But our paranoia has no boundary as yet and so we use a shipping buffer just to keep our focus in the right place. Again the size of the buffer can be determined using the lead time from the constraint to the market. Take care here, however: in one company they carefully set the shipping buffer from the constraint to the shipping dock and were soon measuring 100 per cent DDP. This was fine, except that they still received many complaints from customers citing late delivery as the cause. The people within the company could

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Figure 5.6 Placing the rope

not see how this was happening as every item on the schedule was leaving the shipping dock on time. The answer was simple, as they usually are: the company was measuring time at the shipping dock and simply forgot that many products still had many hours of travel before they arrived at the customer’s site. OTIF was not measured at the departure point within the company but at the arrival point of the customer. Once this was highlighted they were able to modify their shipping buffer accordingly and achieve 100 per cent DDP once more. Have we finished? Well no, there is still one remaining area of concern. There is a line within our company that has no constraint and yet could still cause problems. Resources 4 and 5 are not the constraint, they have plenty of capacity, but if they ran late, if they experienced problems, they could delay the assembly operation and that could then impact the material from the constraint operation. Having taken all the care to ensure that the constraint is working properly, we lose any benefit due to the non-constraints. The answer is simple: we place an assembly buffer between the gating operation of the non-constraint path and the assembly point, sizing as before. Once all three buffers are in place we are ready to deliver. All we have to do is make it work: drum—buffer—rope is in place (Figure 5.7). So that seems easy enough. Now the real problems begin: making it work. This is where the role of subordination enters the equation. The key driver for subordination is the measurement system of the company. This is where the ongoing conflict between the application of either cost accounting or throughput accounting for decision-making and on-going improvement measurement enters the equation. This whole area has been given some considerable prominence by writers such as Smith (2000) and Corbett (1998). I do not intend to replicate their

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Figure 5.7 Full DBR for our simple plant

work here but it is necessary to understand the intrinsic differences between the two approaches in order to understand why I advocate the use of throughput accounting (TA) rather than cost accounting (CA) for decision-making within organisations. Once the solution has been understood, I then return to the computer simulations, and over the remaining sessions of day 1 and all of day 2 the class implements the DBR solution, gaining the maximum profit and developing the ability to understand the different types of plant layout that exist, known as V, A, and T plants. V plants have a basic structure where raw material is processed into a wide variety of end products such as hose used within the automotive industry, or a steel rolling mill, or a textile plant. They typically have this feature of a low number of raw material elements which then, through a series of processes including many split points, become this wide range of finished products. All the products are essentially manufactured in the same way. The equipment in such plants tends to be highly specialised and therefore capital intensive. This in turn leads to operational measurements, which require large batch production. Some typical problems of V plants are the fact that in many, although there may be finished goods in the warehouse, it is still quicker to release raw material and manufacture from scratch than it is to find what is supposed to be available. There are also high levels of misallocation throughout the plant. There is a real danger that at each split point material designated for one path will actually travel up another, usually to keep efficiencies at each work-station at the right level. In one hose plant we came across a measure concerning batch size. For every order

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the minimum batch size was 1,000 m of hose. If the order was for 1,200 m then two batches each of 1,000 m was released and the 800 m not required was put into the finished goods warehouse. We found some hose that had been in the store for over ten years. A plants build only a few distinct products composed of many different components, for example generators. Here assembly takes place using these different components and processed raw material into the small number of finished products. The components are unique to the specific products and the routings for the components are also different. The plant uses general purpose machines rather than the specialised machines of the V plant. The final category is the T plant, which is similar to the A plant. Here once again there are common components and sub-assemblies going forward to final assembly into the finished product. The components are common to many different products and the routings have no divergent points or assembly processes. The production routings for the components are quite different in T plants. For more information about the types of plants see Umble and Srikanth (1990). During the education we also cover the impact of batch sizing, the impact of chasing high levels of efficiency throughout the simulated plant, what happens when we rapidly increase sales once DBR has been implemented, and a few other surprises. The intention is that once the training has been completed, we shall be in a position to construct the implementation plan for their specific company. Direction of the solution So what is the feature set of any implementation of drum-buffer-rope? The essential injections are as follows, and in no particular order: 1 Each department is judged according to its impact on the overall performance of the revenue chain. What this means is that departmental performance is only of interest in terms of the contribution it makes to the smooth running of the chain. If the department is a nonconstraint, then all it has to do is move material/information through as fast as possible, ensure that no delays are incurred within the department, and be ready to support the constraint area as and when required by the buffer management system 2 The constraint is identified. Remember that constraints can fall into one of three different categories: physical, policy and paradigm. As noted earlier, very few manufacturing companies have real physical constraints under their control. The most common form of constraint is seen to be policy constraints. My own research suggests that in almost all organisations the most dominant constraint is that of the paradigms by which the people are managing the company. Here we tend to assume that the constraint lies

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within either physical or policy, and leave the people within the organisation to recognise paradigm constraints for themselves. 3 Management overcomes the traditional inertia and deals with the important activities first, such as satisfying the needs of the market. This might seem rather obvious but it is surprising just how many managers in the companies in which we have implemented DBR still try to do two things at the same time. Yes, they accept the importance of the market and the chain nature of their business, but they then try to continue with the efficiency models or cost allocation models they have always used and thus put the implementation at risk. This is often where they find the existence of paradigm constraints—their own. 4 The schedule of the constraint is constructed according to the available capacity and the quantities and due dates of the market demand. This is straightforward and requires only a simple IT solution, typically a spreadsheet initially. Once up and running, and when control has been gained, it may be necessary to use more sophisticated tools, but not at the start. It is important that the information required such as due dates, volume and internal capacity are known. Often this information has to be found before any progress can be made. (For more information see Goldratt (1990) and Stein (1996).) 5 Management takes the necessary decisions that remove any potential conflict. Conflict can come from a variety of sources, such as corporate when they see efficiencies drop, purchasing when they are told to buy when they might normally not do so. There is also the question of the shop floor and the way they operate. There may have to be changes to work practices, breaks and so on, and these must all be handled carefully. 6 Management determines the size of the appropriate buffers and plans release of material to be in line with that timing. This really is a management decision area. If the buffer is too large, then there will be long lead times and a great deal of inventory; if too small then, although the lead time is much better, there is greater risk of missing deliveries. This in itself is a cloud and one that management must deal with. This is also a key part of any implementation process. 7 Management understands the importance of buffer management. Buffer management is the real key to successful implementation, and then the bottom-line impact. Buffers tell us about how we are doing, they tell us about any buffer violators, resources that are likely to give the constraint, or if the shipping area is a problem. If the only aspect of DBR that is really understood is buffer management, then there will always be a measure of success. Don’t forget that within DBR the buffer is not measured in volume of inventory but in TIME. This is often misunderstood but is central to the DBR approach. 8 The rate and magnitude of sales is kept to a level which enables the buffer management to continue to protect the whole system from any resulting

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problems. This is not so important at the start but rapidly becomes vital once the spare capacity has been revealed. Often when some 15–20 per cent additional capacity has been uncovered, the excitement leads immediately to going to the market and selling that capacity straightaway. Nothing could be more dangerous, as the result is that we allow a wall of inventory to be released, which seriously affects the performance of all resources, not just the constraint. We know of companies who have done just this and almost lost the company as a result. 9 Teams are set up to deal with other issues such as set-up reduction, quality, maintenance, and buffer violators. We have said that when a non-constraint is not required to work on an order, it must stop working. But the people can still be kept occupied. There is maintenance to be completed; there are quality issues to be addressed; there is the constraint area and maybe people from the non-constraint area can help out there. If the non-constraint area is a regular buffer violator, then analysis can take place to determine just why this is so. 10 Education regarding the negative impact of local optimisation is given to all employees and other parties to the chain where appropriate. In the many implementations we have done, this is the real starting point as it is vital that all the people understand just what is expected of them. This includes purchasing, sales, marketing, finance, planning, senior management and production people. 11 Management educates employees on the need to work as fast as possible when work is waiting to be done, otherwise not to consume any material. This is part of the overall educational package that accompanies any implementation. This feature set has formed the basis for all our drum-buffer-rope implementations over the past ten years. There are times when the companies involved have added features which are specific to their environment, but this set has always been the foundation. One company produced the implementation plan shown in Figure 5.8. The implementation starts at the bottom and works its way to the top. The logic is that of necessity, which means that each element is a necessary condition for the achievement of the statement at the top, which is the successful implementation of DBR. The next step is to determine how each of the statements will be implemented. Here we use the technique called a prerequisite tree, which is one of the CMTP tools described in Chapter 3. Once each statement has been analysed using this tool, the expectation is that they will do it. What follows are some case studies to highlight the implementation issues. Case Study 1 One company that we were involved with made fluid pumps for the European market, though they had clients further afield. They came to the

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Figure 5.8 An example of an implementation plan

DBR programme as they recognised that they were falling behind against almost all the key manufacturing measures: their delivery performance was poor, they had a long lead time compared with the major competitors, their quality was not as good; they were not yet losing money but it was on the cards that before long financial pressure would force one or two issues. The senior manager within the plant had read the book The Goal (Goldratt and Cox 1984) and approached us for help. We started by ensuring that almost all of his top team read The Goal and considered how it might work in their environment. They were surprised that we did not immediately come in and start to change things. Once they had read the book, ten of their people attended a programme which used the simulations to introduce the conceptual approach, and after it had been completed, over two days, they spent a further three days constructing the implementation plan for their site.

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Figure 5.9 The benefits and problems that DBR creates

We started with putting up the objective: ‘DBR and buffer management have been successfully implemented within our company’ (Figure 5.9), and asked the team first to put up on the white board all the positives they could see with the implementation. Once they had spent some time doing this, we asked them to list their concerns: what they felt might be negative outcomes of implementing DBR, what might stop the implementation, what their concerns were. We did not at this stage try to put them into the CMTP terminology of NBRs and PRTs, but just to come up with a list of issues they knew had to be dealt with; the separation could take place after they had brain-dumped their concerns and then we could take it from there. Some of these would not survive the transfer to the CMTP tools, but at this stage it is important to ensure that all concerns are listed and considered. An issue such as ‘People distrust change’ is probably true of all possible change, not just this one. Yet what we are seeking here are specific problems related directly to the change itself, not generic problems. The next stage is to lay out the

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Figure 5.10 The layout of the implementation plan

various features of the solution, known as injections, as shown in Figure 5.10. Note that although each has a number this is used primarily for communication purposes. This map is known as the injection map and is based on the logic of necessity. It reads this way, from the top: in order to have successfully implemented DBR and BM within the company we must have implemented the four elements feeding this statement. This process continues down the page until all the connections have been read, and then validated. This map is the implementation map for the whole process of DBR within this company. Note that they are not sure where the real physical constraint might be within the production area so they are using the shipping buffer approach at the start and then the BM system will tell them where the primary buffer violators are and through proper analysis any internal constraint will be identified. The next step is to take each injection and to build the individual implementation plans for each. This is done through the use of the pre-requisite tree technique within the TOC/TP.

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Case Study 2 This case study is from the high-tech industry. A small company in Leicestershire approached me to work with them to improve their production facility. They had attended a three-hour presentation that had been developed to entice people to consider the TOC approach to production, DBR, and to move forward in their implementation. The company was a small manufacturer of microelectronic components and microchip wafers. They had an excellent record of innovation but had not been able to ensure the levels of delivery performance expected in the market. They decided to implement the drum-buffer-rope approach and started in the usual manner with some fifteen people attending the two-day conceptual approach, followed by a further three days constructing the implementation plan. The team consisted of people from sales and marketing, planning, purchasing as well as production. The IT manager also attended as it would be his role to provide a scheduling system, which he did using a spreadsheet. In the development of their implementation plan it soon became obvious that they had to work hard to understand their current workflow. They also had to work with the sales people as they had a tendency to take orders which production could not meet before the work with DBR. Using the simple spreadsheet they soon produced a schedule that was good enough for their plant. They set up a buffer system, and to begin with they adopted the shipping buffer approach. They had an idea where the constraint was within their production facility, but they also knew that the buffer management system should confirm this diagnosis or show that the constraint was actually elsewhere. Once under way they initiated a series of lunchtime meetings at which the whole team with the addition of the managing director, and occasionally the finance director, would go through their success to date; using the TOC/TP tools they had learned, in particular the cloud and NBR, they addressed many of the issues that had to be resolved as time went by. They also invited me to attend some of these meetings. They still had a major problem with accepting orders that were working with a lead time less than the overall time through the plant. The assumption was that if they did not do this they would lose the orders. The production people, however, knew that taking the order meant that it was certainly going to be late. They knew that they had to ensure that all orders went through the plant at the proper time. The policy of accepting orders that violated the buffer system had to be addressed: it was rightly seen as a lack of subordination, one of the most difficult aspects of the five steps to accomplish properly all the time. It took some days before the issue was resolved and involved the active participation of sales, marketing and some of the clients who were placing these orders. The outcome was that the clients accepted the importance of maintaining the buffer system, of ensuring that orders were dealt with properly, and that they stood a far greater chance of on time, in full delivery if they worked with the production team and

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the DBR rules, rather than fight them, and so it proved. Within a short period of time due date performance increased, cycle time reduced, there was increased visibility throughout the factory. There was also a new problem on the horizon. Whenever DBR is implemented spare capacity is revealed. This spare capacity must be used properly. Some of it remains as protective capacity, but what is left over should be sold in the form of more orders, more product through the plant. Remember that this increase in volume through the plant goes straight to the bottom line as there is no increase in investment to achieve this new level of production. It is simply a result of better focus throughout the plant and the application of buffer management. By the time the company was achieving far higher levels of volume through the plant, the information system was starting to become a temporary constraint and steps were being taken to ensure that this aspect of the operation did not become a genuine constraint. What follows are three of the analyses the team produced as part of the implementation process. This was a highly successful implementation: the lead time was substantially reduced; the due date performance was better than 97 per cent; the level of inventory within the plant was reduced; the flow of material was enhanced; problem areas were highlighted far quicker than before and properly addressed, this through the application of buffer management. Figure 5.11 is the map for the achievement of the injection reference, the measurement system. They understood the need for the changes that were necessary for the DBR to really deliver, and used the analysis to engage in a debate within the company, and then to drive the new measurement systems through to completion. This involved a substantial degree of challenge to accepted practices, many of which were abandoned. Once the PRT had been completed and agreed, people were tasked with the various intermediate objectives and teams set up to assist them. The same process was used for all the PRTs created. For the buffer management system the map shown in Figure 5.12 was prepared. This was one of the most successful injections. Even four years after the project was completed this team still met and still managed the buffers. All investment decisions had to go through this group, and only evidence of buffer violations or possible shift in the constraint would be used as the basis for such decisions. They do have problems with buffer violations, they still find that they cannot afford to take their eyes off the ball, but the buffer management system they created and continue to manage is a powerful tool for the long-term development of this company. The next analysis (Figure 5.13) is about the need for subordination as outlined in injection 11. Once more they were able to develop another successful injection with a major analysis of how to ensure proper subordination throughout the company. The team within the company set about the implementation, with the full support of the senior management team and the directors, and delivered. They addressed all the problems they had started with, they were able to improve the financial performance of the company, and they now had a platform which would enable them to build for the future.

Figure 5.11 The analysis for injection 100

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Figure 5.12 The analysis for injection 10

Lessons learned from the case studies These and many more case studies formed the basis for my continuing development of the TOC and what it is possible to achieve within the manufacturing industry. DBR on its own did not save all the companies that I have been associated with. It might have made substantial improvement to the due date performance, to the overall lead time, to the ability of production to take more product through the plant in a shorter time than ever before, but that was still insufficient in many cases. This is still only one part of the revenue chain, and though it is possible to demonstrate the power of the TOC approach, it does not mean that the company is able to take real advantage of what has been achieved.

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Figure 5.13 The analysis for injection 11

Developing the ability to implement constraint manufacturing within the production area That the constraint management approach to production can deliver can hardly be in doubt. Apart from my own case studies there exists within the Goldratt Conferences a wealth of case study material in the form of videos from all kinds of companies which have derived great benefit from this approach. But moving to constraint manufacturing takes more than just DBR with a few bells attached. Production is still only one link in the chain of networks comprising the

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enterprise. There are still areas that must be examined. However, from both my own experience and that of other TOC practitioners, without implementing the DBR approach, and in particular buffer management, there is little chance of success in implementing constraint manufacturing. Conclusions So, in our journey to world class levels of performance we have addressed issues in NPD and production and the associated support functions, but we still have to deliver the product to the end user. It is of little value to deliver the finished goods to the shipping dock or the plant warehouse if we then fail to deliver it on to the next stage or the client. Remember the example of the small company in Leicestershire which also produces microelectronic components complimented themselves on the success of their DBR implementation. Imagine their surprise when customers still complained of late deliveries. The degree of lateness was not as bad as it had been, but they were late nevertheless and certainly not good enough for their clients. They checked their data which showed 100 per cent DDP, but this was to the shipping area, not the client. They were measuring the delivery performance only as far as the loading area and the trucks that took finished product away to the client’s address. They had simply failed to check the real delivery performance, namely to the client. It might seem a rather silly oversight, and it was easily accommodated into their new systems, but it is an oversight that is more common than one might imagine. It is therefore essential that the distribution channels are also included in our analysis and that is the subject of the next chapter.

6 Getting the product to the customer

As noted at the end of the previous chapter, having spent all this time designing and manufacturing the product, it would appear obvious that the next step is to place the aforementioned product into the hands of those who will sell, and then buy, the product. However, this also appears to be a difficult step for many companies. The number of times a potential purchaser visits a retail outlet to buy, only to find the required item is not in stock, the waiting list is huge, and sitting there is another product, just as good, from a competitor, and just waiting to be bought. This aspect of the global supply chain is not just about mainstream manufacturing: health care is part of this environment, as is education, services and so on. Indeed any organisation that requires equipment, consumables, medicines, reams of paper and other supplies will know of the impact of slow delivery and the consequent effect of high levels of inventory just to protect against such poor levels of service. The approach known as distribution, or as I, and others within the CM community, prefer, replenishment, is not new, but it is equally not common either. Figure 6.1 gives a diagram of a typical distribution process, showing the links between the supplier base, through the plant and the plant warehouse, on through the regional warehouses to the clients who exist within the market. As with most models it represents a typical environment, one where the demand from the client/customer base is not constant but subject to quite large swings of variation in most cases. We should start by understanding what is happening with the client, the retail outlet, the car showroom or some other example. People come to the outlet to buy. However, often when people come seeking to buy a particular product they fail to find it. It is currently out of stock. In order to meet the needs of the customer a transfer shipment often takes place: one client ships to another the required product, and in trying to manage demand, there is added cost. The plant traditionally pushes product further away from itself in order to comply with the way such transactions are measured, as a sale, even though it has not yet found a buyer. The result is that either the customer buys a competitor’s product or decides not to buy at all. That customer will tell everyone he or she meets, and the tail of this stock out in terms of lost sales increases. Perhaps we should really understand the causality that exists in this part of the supply chain.

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Figure 6.1 The basic distribution process

The analysis of distribution So now is the time to consider just how this system functions and the kinds of problems it creates. There is a certain logic that applies to the problems existing in this area. This analysis applies to almost any supply chain. The starting point is the commonly accepted objective that we would all like our managers to be successful in managing their supply chain. This works at all levels of management, from the retail outlet to the boardroom. Also it is essential that sales are made on a regular basis. A retail outlet that does not sell does not continue for long: sales are a necessary condition for the success of the enterprise. Therefore it is important that the managers are able to protect their sales all of the time. If, as is likely, they lose sales if stock is not readily available on the shelves, then it follows that there is pressure to hold more inventory in order to protect against a stock out. However, protecting sales is not the only

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important task of most managers, they must also recognise that allowing waste adds significantly to cost and therefore it is vital they control costs, often very strictly. Coupled with this is the recognition that excess inventory adds to wasted cost in the form of returns, obsolescence and added carrying cost so there is also pressure to reduce the level of inventory held. In fact we have come across many companies where the reduction in inventory is a requirement placed upon many managers around assessment time. Now the manager is held in a powerful conflict: he knows that sales are the lifeblood of the company and the industry. In a field of strong competition and often no real brand loyalty, it is imperative to ensure that all retail outlets have sufficient product to sell as and when required. The financial tail of a stock out is far longer than the individual lost sale. Equally, the importance of not contravening the rules and measures of head office dictate what he or she is going to do. Sales might pay the salary, but head office determines whether there is a job at the end of the week or not. Now it is imperative to comply with the rules of cost control and inventory levels, and the question of whether sales are lost or not pales into insignificance. Our manager needs help. Help comes in the form of the usual method of balancing this real and damaging conflict: through the use of forecasting tools to try and determine the right level of inventory to hold. Now managers try to use the forecast to resolve their inventory-driven conflict. However, as with all forecasts there are two inevitable outcomes; on the one side there is the time when the forecast is higher than reality and thus the level of inventory of finished products is too high; and of course there is the obverse, the forecast is lower than reality and the manager does not have sufficient inventory. At this point he can point the finger of blame at the forecasting system and not his own judgement, or even that of his superiors. But this is only the tip of the problem. Often in the world of fast-moving consumer goods, and indeed many other types of products, the transportation lead times are far longer than the level of tolerance held by the client. This is often the case in the furniture industry where prospective purchasers are told that they will have to wait until the next production run of their desired chair or settee before they can expect delivery, and this can often be many months away. By the time the production facility has got around to making the desired product, the prospective client is already sitting in a new chair bought from a competitor. Driven by this, many managers will hold inventory close to the customers, which leads to a need for regional warehouses in which to store this level of product. However, they still have to determine just how much to keep at the warehouse, and once more they are faced with the same problem as at the outlet itself. They are trying to use the forecast to determine the correct level of inventory to hold, knowing that such forecasts are still an educated guess, and this in turn leads to managers trying to hold enough inventory in the regional warehouses to cover the forecasted demand profile. In determining this level at the regional warehouse the manager has to take note of two important dimensions. The first is that the lead time for delivery to

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the warehouse is still longer than the client is prepared to wait, and that the production lead times are also longer than the time the client is prepared to wait. As a result the manager tries to hold regional levels of inventory at higher quantities above the forecasted demand during the period equal to the combined transportation and production lead times. This leads to two inevitable outcomes; the first is that in the near term the market demand is expected to be met by the regional warehouse inventory levels; and second, at the same time, regional warehouse orders are sent back and loaded on to the production facility for a more remote period of time, typically mediumterm demand. Now there are typically two results at this stage. In the first, the forecast is lower than real demand and yet the regional warehouse is still expected to meet that demand; consequently the warehouse does not have sufficient stock to meet the current level of demand. Equally, when the forecast is higher than real demand and the warehouse is placing orders on the plant in line with the medium-term forecast, the warehouse now holds excess inventory. What this usually means is that, across the product range, within the warehouses there is both excess of some products and stock out of others. Equally, across the warehouses, some will have excess stock while there is excess demand elsewhere and vice versa. This whole process thus adds to the level of missed sales to clients, often to levels that are unacceptable to head office. Given that the regional managers care about customer satisfaction they now place urgent orders with the production facility to try and meet the demand for out of stock products. At the same time the plant managers, who also care about the customer and the level of satisfaction the company is able to offer, respond to the demand by allowing the demand to come into the production arena as a rush job. Now whilst production has to respond to urgent orders on a frequent basis there is also the on-going issue of excess stock in some places and stock outs in others. As a result of this mismatch, one that can be readily seen within the company, it is not surprising that very quickly production people exhibit a lack of trust in the distribution people. At the same time within the production facility there is almost constant rescheduling taking place in order to try and meet the ever-changing demand from distribution. This in turn leads to production often failing to meet the original promises it made to the distribution people and also to the sales people. Now both distribution and sales exhibit a lack of trust in production. There is still one final analysis in this environment. There are key problems with any form of forecast. First, the sum of many forecasts is much less accurate than the aggregate forecast for the same demand. Second, the only thing accurate about almost all forecasts is that they are going to be wrong to some degree. As a result the more forecasts used in any system, the less accurate the total is likely to be. Given that the warehouses are using forecasts based on medium-term periods of time, the inevitable outcome is that all too often the orders placed on the plant have little or no relevance to actual market demand. As the plant does not have infinite capacity, then frequently it does not have sufficient capacity to

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Figure 6.2 The core cloud

satisfy the client demands. Equally if we only consider the levels of inaccuracy in the forecast, plant capacity is all too often wasted on manufacturing the wrong products. If the orders placed upon the plant do not reflect real market needs and if plant capacity is being wasted, then it follows that all too often the plant does not have sufficient finished goods inventory to satisfy the next orders in the chain. The end result is that there are far too many missed shipments to the regional warehouses. This is not an isolated picture but one created by many examinations of this particular environment. This set of problems gives rise to an examination, which results in the cloud in Figure 6.2. This conflict demonstrates clearly the issues that managers are trying to resolve day by day. There is little disagreement about the content of the A box. It is vital for the overall success of the enterprise that the right product must always be in the right place at the right time. The necessary conditions for achieving that goal are written in the B and C boxes. They are, in the B box, the importance of ensuring that excess inventory is not being held throughout the system. The impact of this would mean that costs are higher than necessary and thus reduce profit capability. Equally it is important to ensure that product is always available as and when required by the market. This is true for both urgent customer demand and when normal fluctuations occur within the market place. The logical conclusion from trying to ensure reliable delivery is that the level of inventory held throughout the distribution system is higher than might be expected. However, to limit the damage of excess inventory the level held is kept low. The assumption that is being challenged (Figure 6.3) is that the primary reason for holding more inventory is a function of time between the raw state of the product and delivery to the point of sale, whatever that might be. The crossconnection of this cloud is particularly powerful. The pressure to hold less inventory inevitably challenges having the right product in the right place.

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Figure 6.3 Assumptions surfaced

Shortages and long lead times are the norm. Equally if we allow more inventory, then there is substantial damage to our cost controls. The odd fact is that often in this environment there is too little product which is wanted and too much which is not. Developing the solution The key feature set that the solution contains comprises two distinct elements. The first is that sufficient finished product inventory is held at each of the regional warehouses in order to satisfy client demand during the time it takes the plant to replenish each regional warehouse. The second element is that enough finished product inventory is held at the plant always to be able to replenish what each regional warehouse is shipping to the market. The intention is that if these two elements of the solution are implemented with the appropriate management systems, namely buffer management, a set of highly desirable effects will replace the problems that currently exist. These desirable effects comprise the following: 1 Finished goods inventory at the regional warehouses will only be what is required to meet client/customer demands. 2 There will be few or no product returns. 3 Client/customer orders are shipped on time and in full. 4 There are no missed sales to the market.

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5 The regional warehouses only order finished product when replenishing the buffers mandates such an action. 6 There are finished product buffers at the plant for each product in order to guarantee product availability to the regional warehouses. 7 The plant has enough capacity to satisfy demands. There are also two key measurements introduced to help focus the minds of management on what is really important here. The first measurement is called ‘Throughput Dollar Days (TDD)’ first described, along with the second, in Goldratt and Fox (1987). This measure is a function of delivery performance. It deals with quantifying the scale of the variance from promised delivery to actual. It is calculated by assigning to every missed order a value equal to the selling price multiplied by the number of days the shipment is late. A summation of all orders will give a very quick indication of the performance of the chain. Indeed, the same measure can be used at all stages within the chain including departmental performance. This measurement forces any plant to concentrate on those orders with the highest TDD figure, which may not be the most delayed. In conjunction with buffer management, this measure gives real focus to delivery performance. The second measure checks out what should not have been done, but was done anyway. This is called ‘Inventory Dollar Days (IDD)’. This is a measurement used to minimise those activities that occur before they are scheduled. It is calculated by the summation of the value of all products, multiplied by the number of days each stays in the warehouse. The intention is to keep this measurement as low as possible. Replenishment: the solution The first injection of the solution feature set is: ‘There is a finished product buffer at each plant’. This means that there will be a level of inventory at each plant for the specific purpose of ensuring that stock outs are avoided. The driver for this injection comes from the realisation that whenever a product is not immediately available from the plant’s finished product buffer, it may take up to a full cycle time through the full range of products for the warehouse to replenish the regional warehouses. The combination of these two elements means that the buffer at the plant must be sized in order to guarantee that the cycle time at the plant will never deplete the buffer. One basic assumption of this analysis is that the plant has enough capacity to satisfy the demands of the clients, which is why drum—buffer—rope is a necessary condition for this aspect of meeting the demand from the supply chain. Given that there will be a product buffer for each product at the plant, the second injection is to ensure that the size of each finished product buffer is equal to the paranoia consumption of the regional warehouse during a time interval equal to one and a half times the plant’s cycle time. This should mean that,

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provided the level of paranoia is reasonable, the product buffers should not be depleted even when the capacity of the plant is finite. Equally if the level of paranoia leads to more than is necessary being held in the buffer, this will be reduced the next time around. Of course having a buffer in place means that it must be properly monitored, which is the next injection. This will enable those managing the process to keep the level of inventory in line with consumption and for any problems to be identified before the buffer is fully consumed. The final injection at this stage is to implement a different measurement system and give education to all members of staff to guarantee that the proper buffer levels are maintained and that the buffers are protected in line with demand. Given these four injections, we now have finished product buffers at the plant for each product, which guarantees product availability to the regional warehouses. The same four injections are then repeated for the regional warehouses. Each warehouse now has a buffer, properly sized this time in line with a paranoia level driven by the consumption and the reliable shipments to the warehouse from the plant, including the shipping time. Once more education and measures are implemented that give proper focus and the buffer is monitored properly. The intention here is to ensure that the buffer guarantees product availability to the clients. But what is the impact of this approach upon the plant? We have already considered the importance of DBR within the plant, but is that sufficient? Well, the key aspect of the plant is to implement proper measurements and education throughout the plant to guarantee that proper buffer levels are maintained and that protecting the plant’s finished product buffers is given the highest priority. As a result of this the plant’s schedule and mode of operation will be to produce product only when replenishing the finished product buffer. Hence the content of the finished product buffer will only be what is needed to protect throughput. At the same time, it ought to be recognised that saving set-ups is necessary only when capacity is a constraint. Hence the plant must utilise the available capacity to produce product only when replenishing buffers. Now the saving of set-ups is done only when mandated by the need to replenish a depleted buffer. This in turns leads to the recognition that large production runs will only be carried out to overcome set-up induced capacity limitations. Hence the plant frequently has enough capacity to satisfy client demand. Given the existence of the buffers, coupled with proper education and measurements, the environment has now changed substantially. With finished product buffers at the plant, the regional warehouses now have product delivered as and when required, and always on time. Clients’ orders are now shipped on time. There is less inventory actually sitting in the system, which means less obsolescence and fewer quality problems, especially with shelf-life issues. If the clients receive their shipments on time there are fewer stock outs, which means that the level of lost sales has been reduced considerably, if there are any at all. Equally, fewer products are returned.

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Implementing this approach means that the clients must learn how to manage in this new environment. They cannot continue to order as they have in the past; they must gain confidence that the new systems will deliver what they need. If we do not address the operational methods of the client, then there will be no real improvement as they will order on the basis of past experience and not according to the new rules. Hence it is important that the client holds enough finished product inventory to be always able to satisfy the market’s demands during the time it takes to be replenished from the regional warehouse. Therefore we implement the same four injections once more, this time with the client. A buffer is created, sized according to the shipping time of replenishment and the rate of replenishment, managed in line with the principles of buffer management, and the measures and procedures are changed to reflect the new working practices. The expectation now is that clients will only order to replenish their buffers, in line with consumption. The level of product at the regional warehouse means that the order will be filled on time and complete. Now the product that is being shipped closely matches the actual demand of the market, which in turn means that the short-term needs of the clients are always met and little or no product is returned. At the same time the level of missed sales will be reduced almost to zero. But this assumes that the suppliers to the plant are reliable, and they may not be. Hence there is a need to hold enough raw material inventory at the plant to be always able to produce product when the replenishment of the finished product buffer demands such action. Yet again the same four injections, education and measurements, buffer placement and size and buffer management, all play their role with the raw material supply. This ensures that the plant is always able to meet the demand placed upon it. Buffer management will then control the level over time and allow reduction as and when the system shows both capability and consistency. So what are the outcomes of implementing this solution? End users expect immediate availability of the products they want to purchase. At the same time the level of performance of the other suppliers, our competitors, is poor in comparison to what we are now able to achieve. Hence the inevitable outcome is that the demand for our products from both new and existing clients will increase. As the overall plant capacity is limited, all decisions with regard to accepting substantial increases in demand are evaluated through the use of buffer management. In this way increases in demand will be accepted based upon their impact on the overall performance of the plant. With all process improvement now focused through the use of buffer management and with large production runs only being allowed to overcome set-up induced capacity limitations, the plant is almost always in the position of having enough capacity to satisfy customer demand. The finished system is shown in Figure 6.4. The injection with reference to the finished product buffer needs further discussion. Many plants will currently have finished goods stock sitting in the warehouse. With this injection we declare the plant warehouse to be the main

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Figure 6.4 The complete system

buffer designed to accommodate all fluctuations within the system. Therefore this is usually a fairly big buffer. The biggest obstacles to the implementation of this injection are the policies and measurements of the plant; for example when a product is shipped to the regional warehouse it is recorded as a sale for the plant. This causes the plant to ship as soon as possible and rush products down the chain. This practice must be stopped. Monitoring the buffer, the buffer management system, also requires further discussion. The environment of today is not that of tomorrow. Therefore it is essential to monitor the buffers to see whether they are sized correctly. Of course they are monitored continuously for

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penetrations into region one and immediate action taken when this occurs. But also the buffer level at the end of the cycle-time for a product gives good information; it identifies the extremes: the products with buffer levels in the top of region three and in the lower region two. How is this done in reality? Most distribution companies carry many thousands of products, therefore an information system will be necessary, but not a complex one. Another question surrounds the level of education required. In our experience the primary obstacle to the implementation comes from the current behaviours within the organisation, especially that behaviour which is reinforced by the measurement system and issues such as batch size, efficiencies and so on. We use similar simulations to those described in Chapter 5 on production to start a debate about the replenishment model and why it works. This acts as a powerful tool to encourage the change process. There is still a real problem with the clients. Even when they fully understand the new process they will still continue to purchase in line with experience. No longer does the customer have to buffer against erratic behaviour of the chain; no more forecast paranoia. At the beginning of the new system they will, however, still order too much, but fairly quickly they will shift as they gain confidence in the system’s ability to deliver. As this happens the relative size of the buffer will also decrease. Conclusions In summation, inventory should not be held as close as possible to the market, which is the prevailing paradigm. It should be held at specific locations according to the impact upon the system when seen as a whole chain. Thus it is possible to switch from push to pull. It is best done by starting with a single family of products rather than the whole range of families. For example, this is what GM did with the Enterprise scheme and the Cadillac range before widening the scope. Once results have been achieved, typically within four to six months, it is possible to roll out the solution to the remainder of the product range of the company. As with CCPM and DBR it will also be necessary to change the operational measurements across the whole product range. The combination of the production approach, DBR and the distribution approach, replenishment, offers a real breakthrough solution for any company that must ensure that products are always available at the point of sale. Replenishment has been used with great success in the supermarket industry and the car industry in the USA, indeed in any environment where stock outs violate the necessary conditions of achieving the goal. When the supply chain comprises a number of aligned companies the key decisions about replenishment are driven by the company nearest the market. They will have the best information and intuition about what the market is likely to pay for the products. Then, rather than having a series of intermediate prices, each company may now take an agreed percentage of sales, with an agreed

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minimum sales price. The same can be done with internal supply chains, each party to the chain having its contribution properly recognised. These two approaches deliver the core of supply chain management within the constraint manufacturing area. The application of buffer management ensures proper focus, and the use of web technologies has allowed companies in widely dispersed areas to manage and control effectively.

7 The strategic importance of managing change

Introduction Now that we have come this far it seems a pity not to ensure that the process of change is able to undertake the tasks that lie ahead. Research over the years has shown without any doubt that if the whole area of change management is ignored, there can only be one result—disaster (see Hutchin 2001b). There are a number of fundamental changes that must take place within any organisation seeking to adopt and gain benefit from a constraint management focus. There is the shift to the critical chain approach for project management. There is the shift to drum—buffer-rope for production and replenishment for distribution. There is the need to adopt a sound management methodology such as that contained within the constraint management thinking processes and taught through enterprise analysis methodology. There is the need to change many of the measures used in support of decision-making such that there is proper alignment between decisions and overall direction. Above all there is the need to change the behaviour of many people within the organisation. This last aspect is no easy task and should never be underestimated. The role of change and change management This book has followed a simple model: that all improvement projects are designed to deal with a core problem. The starting point is the recognition that a problem exists. This leads to a careful analysis of the problem and from that to development of a solution. Once the solution has been determined, it is important to implement it properly. This usually involves change, from a small minor adjustment to considerable upheaval throughout the whole organisation. To be successful this change must be properly managed. This cycle of problemsolution-implementation is also linked to the ability of the organisation to learn, from both failure and success.

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Managing change Brooks (1980) derives five major areas which management must take into account if it is to aid rather than hinder organisational change. Brooks considers that: The model provides a conceptual framework which focuses on the key variables influencing the success or otherwise of management change initiatives’ (1980:74). These five are the aims and objectives of management, the technology being applied, the people involved, the current structure, and the range of control in the environment. When considering the forces that act on an organisation, the structure of that organisation has important connotations for the way in which it responds. It is implied that if the organisation and the environment in which it exists are about to change, then it is equally likely to require a change within itself in terms of structure and culture if it is to remain responsive and adaptive. There have been many studies which show that there are many effective organisations operating in stable environments or with stable technologies that are characterised by rigid structures with power concentrated at the top and clearly defined roles at lower levels. It is equally true to say that where the environment is rapidly changing, then the effective organisation is characterised by less reliance on formality and greater reliance on interdependence of unit operation. This is coupled with greater emphasis on joint planning and problem-solving, with greater responsibility and authority placed at lower levels (Burns and Stalker 1966; Emery and Trist 1965; Lawrence and Lorsch 1967; Pettigrew and Whipp 1991). Thus if an organisation is in the process of change, fixed rules and procedures will rapidly become outdated and severely hinder the process. As change often involves the unexpected, with unforeseen influences, a joint participative approach is to be preferred, as is the case with the CMTP methodology. Of course some organisations still feel that change will not affect them. This view is dismissed by Hersey and Blanchard (1972), who take the view that such is the nature of a dynamic society that the question of change has shifted from whether it will happen to one of when. They state: how do managers cope with the inevitable barrage of changes, which confront them daily in attempting to keep their organisations viable and current? While change is a fact of life, effective managers…can no longer be content to let change occur as it will, they must be able to develop strategies to plan, direct and control change. (Hersey and Blanchard 1972: 6) The risks associated with change The fact that change has become commonplace involves the organisation in risktaking. Moore and Gergen (1985: 72) place risk-taking as ‘a crucial element in change, transition and entrepreneurship. In turn, fear of risks is a key factor in

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resistance to change both for managers who need to decide whether or not to initiate change and for employees required to adapt for change’. Thus risk has two primary elements, the risk to the organisation and the risk to the individual. Both of these are recognised by Moore and Gergen, who then outline four key structural/cultural factors that influence risk-taking. These can be summarised as: 1 organisational expectations where the managers need to clarify what changes need to occur, why they are necessary and what is expected as a result of those changes; 2 reward systems, whether formal or informal; 3 support systems, which apply to the entire workforce; 4 available resources to allow the risk taker to discover a working system. In order to achieve change Moore and Gergen consider that organisations need moderately high-risk takers and it is this risk that requires careful consideration. They conclude by saying: ‘asking people to change is asking them to innovate: to try new tasks, skills and work methods at all levels to make the change work well for themselves and the organisation’ (ibid.: 76). Within the CMTP tool set the application of the negative branch reservation is of most value at this point. This tool is the primary tool for determining the level of risk that any change might involve whilst at the same time creating the capability to implement new injections to ensure that the risk is properly contained or taken out of the equation altogether. The challenges of change Risk is not the only challenge facing managers when change is required. Leonard-Barton and Kraus (1985) identify a number of key challenges which include: the dual role within the company of those involved with the task of change; the variety of internal markets to be served; legitimate resistance to change; the right degree of promotion; the choice of the implementation site, where appropriate; and the need for one person to take responsibility. In consideration of the dual role they note that: Those who manage technological change must often serve as both technical developers and implementers. As a rule, one organisation develops the technology and then hands it off to users, who are less technically skilled but quite knowledgeable about their own areas of application. (Ibid.: 102) Though their focus is on technological change, what they argue here is also true of almost any change process and certainly true of the CMTP change process. This imposes a responsibility for the implementer to design the changeover in such a

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way that it is almost invisible. When the people are transferring the CMTP knowledge contained within the CCPM approach into their own environment, it is vital to ensure that the others within the organisation are ready to accept the new approach without question. For Leonard-Barton and Kraus (1985:103) the way forward is through a marketing approach. They argue: Adoption of a marketing perspective encourages implementation managers to seek to use involvement in the: (1) early identification and enhancement of the fit between a product and user needs, (2) preparation of the user organisation to receive the innovation and (3) shifting of ‘ownership’ of the innovation to users. The time given to achieving the buy-in of the other members of the organisation is felt to be a prime factor in the success, or otherwise, of the process. Managing the introduction of change Wooldridge (1982: 40) notes the concerns of managers facing the introduction of change by saying: the prospect of introducing technological change has brought about increasing despair amongst line managers. They cannot believe it when faced with outright opposition to change from employees and their unions, even when that change is blatantly vital to the survival of their organisation. One of the major problems facing anyone concerned with this is that the reality of the situation is both complex and subtle. Again Leonard-Barton and Kraus (1985: 103), who argue that the marketing approach will assist in the change process, have found that many implementations fail because ‘someone underestimated the scope of importance of such preparation’. The idea that the technical superiority of the innovation will guarantee acceptance and that pouring abundant resources into the purchase and development of the technology at the expense of the implementation process will provide success is scorned by Leonard-Barton and Kraus. They propose ‘not only heavy investment by developers early in the project but also a sustained level of investment in the resources of user organisations’ (ibid.: 103). Without proper implementation there is no improvement process and if the involvement of all the people concerned is not achieved, then the likely outcome is not what might be expected. The whole point of the third question, ‘How to effect the change?’, in the three questions of CMTP is to prepare the people fully for the change and indeed to involve them in that process. This is done through surfacing the obstacles that stand in the way of success and raising reservations, which refer to the possible negative outcomes of implementing the proposed

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solution. The notion of the marketing approach also implies that there are multiple markets within the organisation which require to be addressed. At each level of the company there needs to be a planned strategy applicable at that level. Managers on one level will require a different response from managers or users at a different level. Leonard-Barton and Kraus (1985:104) believe that: Top management and ultimate users have to buy into the innovation to make it succeed but marketing an idea to these two groups requires very different approaches… We believe this executive must view the new technology from the perspective of each group and plan an approach accordingly. This buying-in to the proposed innovation leads to the concept of ‘ownership’ of the proposed change. Though the exact meaning will vary depending on the size and nature of the change project, the term implies the full involvement of all interested parties. This is where we have found the five stages of communicating the change to be of immense value. The gaining of consensus on the problem, then the direction of the solution, and then the benefits of the solution create an involvement which is fundamental to any change process. Then through the overcoming of all the reservations of the team their full ownership is achieved. Any change of a fundamental nature often involves a transfer from one technology platform to another. Therefore the identification of those who will influence the workforce is paramount. The opinion leaders within the organisation play a vital role at this stage. Equally important is the realisation that the opinion leaders may not be the actual managers within the departments, but others who, though they do not have the functional leadership, may have de facto leadership. These people are all part of the team who will raise reservations. The change agent Whoever is responsible for the change, they all share one thing in common: they are agents for change. Atkinson (1985:14) notes the importance of the change agent when he notes: ‘The key to change is recognising that a need to take action is an important aspect of the change process, and that a “change agent” or “catalyst” is imperative to the successful implementation of new technologies.’ It is the nature of this person that is crucial to the success or otherwise of the implementation. Atkinson suggests the following description of the person who can deliver such change: The individual, the catalyst who makes things happen, is central to effective implementation strategies. Whoever occupies this role must possess the requisite attitudes, skills, knowledge and experience to develop an objective overview of the problem, and create decisions, which work in the long term. This ‘facilitator’ must also be able to harmonise enthusiasm,

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grasp opportunities, explore the sources of resistance and change attitudes in order to promote a healthy and effective organisation …change cannot create itself. It must be welcomed as an opportunity for those who work in the organisation to take some responsibility, and help prepare for, and create their own future. Hersey and Blanchard (1988) picked up the theme of motivation and leadership, two key aspects of a successful change agent, when they described what makes a good leader. Through the development of situational leadership they sought to provide a ‘common language to help solve performance problems’ (p. 2). They go on to suggest that their approach can be used to ‘diagnose leadership problems, adapt behaviour to solve these problems and to communicate solutions’ (ibid.). In their analysis of what they call a ‘real change leader’ (RCL), Katzenbach and his team (1995:6) consider the key elements or attributes of a successful change manager. They define such major changes as: those situations in which corporate performance requires most people throughout the organisation to learn new behaviours and skills. These new skills must add up to a competitive advantage for the enterprise, allowing it to ‘produce better and better performance in shorter and shorter time frames. They also describe the common characteristics of the RCL as: 1 Commitment to a better way. 2 Courage to challenge existing power bases and norms. 3 Personal initiative to go beyond defined boundaries. 4 Motivation of themselves and others. 5 Caring about how people are treated and enabled to perform. 6 Staying undercover. 7 A sense of humor about themselves and their situations. (Ibid.: 13) This leads to their definition of the term ‘real change leader’ as: ‘Individuals who lead initiatives that influence dozens to hundreds of others to perform differently—and better—by applying multiple leadership and change approaches’ (ibid.: 16). Throughout his study Katzenbach uses cases to describe what kind of effect RCLs can have: in particular they go after ‘specific performance improvements based on building new skills and attitudes, and getting commitment from all hands’ (ibid.: 34). The close relationship between what Katzenbach calls an RCL and a CMTP practitioner is not surprising. Both have a focus rooted in the market, both are working to a vision of what can be, and setting out to achieve it. Words that are part of the language of a CM enterprise analyst, often known as a Jonah after the

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character in the book The Goal (Goldratt and Cox 1984), such as enthusiasm, commitment and trust, are also part of the RCL vocabulary. Katzenbach recognises the importance of vision in the process of change. He writes: You have to start out with a vision that isn’t well articulated. You have to sense that it can be grey, it can be murky, but it should have at least the attributes of things you want. Then I think it is helpful to talk long and hard to a lot of people. (Katzenbach 1995:93) The next stage in the process is to determine whether the agent of change should come from inside the organisation or outside. Atkinson (1985:14) considers both: clearly there are many advantages associated with using personnel within the structure to bring about change. Organisational knowledge, relating to structure, organisational culture, departmental and work groups, managerial responsibility etc., is an important asset, which the internal change agent possesses. Unfortunately there are disadvantages regarding subjectivity, bias and dependence for future career and promotion prospects. These negative factors all tend to suggest that the internal agent for change is not sufficiently detached from the situation to perform his function with discretion. When considering the position when the agent is external, Atkinson argues that their advantages lie in areas such as: skill attainment, experience of change programmes in different cultures and structures, objectivity etc. All this helps the external practitioner to take a detached and professional view. Unfortunately, external consultants take a great deal of time to become acquainted with organisational philosophy, policy and practice. (Ibid.: 15) Caruth (1974:10), in his examination of the systems analyst as a change agent, noted that there are: four areas of major concern to the systems analyst: (1) basic human motivation, (2) why people tend to resist change, (3) the ways in which people resist change in the workplace, and (4) how to overcome resistance to change. Caruth considers that the first is a key area on which to focus. It is necessary for long-term improvement and change to reinforce the motivation of the workforce

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and the ‘greatest opportunities for motivation lie in the areas of egotistic and selffulfilment needs’ (ibid.: 11). It is often due to the lack of opportunities most employees have to use the creative side of their personality in their work and to a lack of recognition and appreciation that they become stagnant in their approach. Again Caruth makes the point that: There are areas in which management must concentrate its motivational efforts. These are the areas which the systems analyst should utilise in his efforts to bring about change with a minimum of disruption and resistance. (Ibid.: 11) In our own research we have found that the shop floor is one of the greatest sources of new and innovative ideas, but over the years it has been excluded from this process. Equally the measures in force in many companies do not encourage people to improve, but only ensure they do not fall foul of the measurement system. Atkinson (1985:15) considers that the best approach centres on what he calls the team approach. This he describes as the coming together and grouping of external specialists who possess expertise, skill and experience, coupled with the organisational strengths of the internal practitioner, helps bind the partners of change. The team approach develops a ‘synergistic’ learning climate where the experience, knowledge and creation of ideas can be maximised. Leonard-Barton and Kraus (1985:107) also considered the formation of the implementation team and argued that it should include: (1) a sponsor, usually a fairly high-level person who makes sure that the project receives financial and manpower resources and who is wise about the politics of the organisation; (2) a champion, who is a salesperson, diplomat and problem-solver for the innovation; (3) a project manager, who overseas administrative details; and (4) an integrator who manages conflicting priorities and moulds the group through communication skills. Within most of the CM implementations we have been involved with over the last ten years or so, this approach has proved to be the most successful. Then through the use of both the Belbin team dynamics methodology and the prerequisite tree implementation plans are constructed which are both robust and feasible.

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Resistance to change For resisting change itself, Caruth (1974) puts forward the suggestion that there are a number of key factors. The first is that change, in any form, is perceived as a threat: ‘It is seen as a source of frustration, an obstacle which prevents an individual from satisfying a basic need’ (ibid.: 12). It is not so much that the need is not satisfied, rather it is threatened. Caruth continues to detail what he considers are more specific reasons, the first being economic security, where the change is seen as threatening the source of income. Depersonalisation is a further cause for resistance to change; as Caruth puts it: ‘if he feels that the change will carry with it the notion of powerlessness, loss of autonomy, or a loss of identity with the products of one’s efforts’ (ibid.: 12). Job status is a further causal factor where change could imply that some of the trappings associated with the present position might be swept away or reduced in status after the proposed change. Change is also seen as introducing levels of uncertainty about competence and the re-skilling, or worse, deskilling, which may result. All this produces a situation where change is seen as disruptive and also possibly a destructive force to the social group within the workplace, and hence people tend to resist such change. The methods used in such resistance can vary widely from the merely outspoken response to the quiet yet positive sabotage of the implementation. Caruth examines a number of possible methods of opposition, ranging from open aggression to the spreading of spurious rumours about the new implementation and the effect it will have on staff. Some will just withdraw and lend no support to the new changes, which in turn leads to the situation where there is no sense of involvement or responsibility shown towards the new system. Others will be totally negative, expressing the opinion that the new system will never work and should never have been introduced in the first place. Finally comes the point when the person withdraws totally, and this will often lead either to the person being transferred to another department or even leaving the company altogether. Any implementation process that results in the kind of negative outcomes as described by Caruth is already a failure as it has resulted in lose-lose rather than win-win. This situation is full of potential danger for the change agent as he or she has an interest in the success of the implementation. It is important therefore to overcome the barriers to change. Top of the list, according to Caruth, is communicating with the interested parties. If the people who are going to be affected by the change are directly involved with the change from the outset, then they have a stake in the development of the system. The people in the organisation are important sources of information, often knowing the underlying methods of operation that exist in the company. It is important that this participation is honest. As Caruth (1974:13) explains: If participation is used simply to placate employees they will very quickly see through the ruse and resistance, perhaps more fiercely than ever, will soon develop.’ Hence when such

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change is being considered the management should consult with employees from the earliest point, which reinforces our application of the five steps of communication. Again Caruth states: ‘Management should carefully explain the reasons for the change, how it will be implemented, what requirements the new system will impose, the benefits to employees etc.’ (ibid.: 13). Caruth also emphasises that the negative as well as the positive aspects should be explained. This is where we advocate the application of the NBR, which is the perfect tool for communicating the possible negatives, but which also acts as a mechanism for the creation of additional features to the solution. In conclusion he writes: People can be conditioned to accept change as a normal occurrence if rewards for acceptance are positive. People will seek out opportunities for change if the right climate has been created by management…the majority of people will come to accept change if they are allowed to participate in developing the change, if management communicates openly with them concerning change, and if they are taught to accept change as a way of life. (Ibid.: 13) Leonard-Barton and Kraus (1985) also accept that resistance to change is a major factor and argue that there are two main types of resistance. These they define as, first, overt resistance, which is a function of mistakes or issues that have been overlooked within the implementation plan; and second, tacit resistance, which is a function of underground feelings, and develops into action against the implementation. The politics of change The issue of power, the use of power in organisational contexts, and the problems that surround it have been researched and discussed by writers such as Handy (1985), Drucker (1980), Kakabadse and Parker (1984), Pfeffer (1981 and 1992), Lee and Lawrence (1985) and Morgan (1986). What is central to all of these commentators is the fundamental importance of recognising the political dimension associated with organisations and in particular that of change management. The individual who is tasked with managing the change process must recognise the power dimension of what he or she is doing and the likely impact it will have on themselves and others within the organisation. The person tasked with change has to be aware of whatever power he or she has and be able to determine how this power might be properly used. LeonardBarton and Kraus (1985) call this person the product champion, who will nurture and attempt to anticipate opposition from the person they call the assassin, who will equally try to destroy innovation. This the assassin can sometimes do with one careful shot, which means that the champions have to marshall their forces carefully. The most common reasons for this opposition are the fear of de-

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skilling, loss of power or lack of personal benefit. Leonard-Barton and Kraus (ibid.: 108) feel that a good implementation plan should ‘try to identify where a loss of power may occur so that managers can anticipate and possibly avert any problems arising from that loss’. Thus any innovation must offer an obvious advantage over the old system or there will be little incentive to use it. The implementers have considerable power at their fingertips, which can be seen in two primary aspects: positional power and personal power. Leonard-Barton and Kraus also identify one more character, the hedger. These people sit on the fence waiting for signals that give them some idea of which way the implementation is going. These people tend to avoid risk and can be found at any level within the organisation. The best way to counter their influence, according to Leonard-Barton and Kraus, is for those in charge of the implementation to send out the right signals so that the hedgers are in no doubt. This can take almost any form, from a speech or presentation to a simple quiet word. It is also crucial that the managers at all levels are speaking the same words at the right time. Finally, Leonard-Barton and Kraus consider the important step to be that ‘Managers…bring the criteria used to judge the performance of the users of the innovation into conformance with the demands of the new technology’ (ibid.: 109). They conclude by saying that the task of converting hedgers is not an easy one to achieve but it is the most inescapable. Indeed: as the competitive effects of new technologies become even more pronounced, the work of implementing those technologies will increasingly pose for managers a distinctive set of challenges—not least the task of creating organisations flexible enough to adjust, adapt and learn continuously. (Ibid.: 109) Power is a key feature of change programmes. Etzioni (1964) discusses the difference between position power and personal power, the distinction springing from his concept of power as the ability to induce or influence behaviour. Etzioni postulates that the best situation for a leader is when he or she has both personal and position power. It is then necessary to consider the use of this power as to whether it will result in success or effectiveness or both. Hersey and Blanchard (1972:8) consider this by saying: Success has to do with how the individual or group behaves. On the other hand, effectiveness describes the internal state or predisposition of an individual or group and thus is attitudinal in nature. If an individual is interested only in success, he tends to emphasize his position power and uses close supervision. However if he is effective he will depend also on personal power and be characterised by more general supervision.

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Positional power tends to be delegated down from the organisation, while personal power is generated from below through follower acceptance. This leads Hersey and Blanchard to the conclusion that: ‘a manager could be successful, but ineffective, having only short-run influence over the behaviour of others. On the other hand if a manager is both successful and effective, his influence tends to lead to long-run productivity and organisational development’ (ibid.). Change/implementation models and conflict resolution examined Katz and Kahn (1978), like Checkland (1981), developed their approach to organisations with a clear association with open systems theory. A key feature of their work is the careful definition of aspects such as cycles of input, throughput and output in a systems framework. They also recognise the different levels of systems and the interrelationships that exist within the system. It is precisely this relationship that is at the core of the effect-cause—effect logic of the CMTP. Through the connection of the logic the CMTP attempts to reveal the true causality that exists within the system, and thus the core problem. Katz and Kahn also recognise the importance of conflict and the dynamic outcome of such. They cite a number of potential sources of conflict, but offer little in the way of conflict resolution. They do suggest that ‘conflicts can have both dysfunctional and functional consequences’ (Katz and Kahn 1978:104). Katz and Kahn go into the area of conflict in some detail, to them ‘conflict requires direct resistance as well as a direct attempt to influence or injure’ (ibid.: 617). Though focusing on conflict at an organisational level they do suggest there are three commonly used concepts of conflict: conflict of interest, competition, and conflict itself, by which they imply incompatible interaction. This last concept of conflict is precisely the type of conflict most identified with this research. They go on to argue that ‘every aspect of organisational life that creates order and co-ordination of effort must overcome other tendencies to action, and in that fact lies the potentiality for conflict’ (ibid.). With respect to change, they suggest that: ‘Organisational change is necessary for survival, but an organisation with no internal resistance to change would be no organisation at all; it would move in any direction, and in response to any suggestion. Change and resistance to change, however, mean conflict’ (ibid.). It is the recognition that conflict is inevitable that is so encouraging. Whilst many people are trying to avoid conflict, they are actually trying to avoid what is natural in organisations. The key to the reality of conflict lies in the knowledge that the conflict can be used to good effect, much in the way that Follett (1995) suggested. This means that some form of conflict resolution is vital to on-going improvement and change.

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Therefore the reason why many improvement programmes fail to achieve the expected targets and benefits claimed of them is the absence of a conflict resolution mechanism. These conflicts can occur at almost any point of an improvement process but are most prevalent at two key points. The first is when the core problem of the area under review has been identified and verbalised, and the second is during implementation. These two points are part of any improvement process. This is precisely the role of the cloud technique, which has proven itself to be one of the most powerful tools for the resolution of any conflict. Organisational learning The final section of the chapter covers the area of organisational learning. In the field of managing change, a key feature of successful change programmes is the way in which the organisation learns from what has happened. This may apply either to the individuals concerned on their own or collectively or to the organisation as a whole. Whichever is applicable, and it may be both, the opportunity to learn from the experience should not be missed. Kolb et al. (1971) outlined such a learning model as shown in Figure 7.1. They observe that: This learning cycle is continuously recurring in living human beings, Man continuously tests his concepts in experience and modifies them as a result of his observation of the experience. In a very important sense, all learning is re-learning and all education is re-education. Second the direction that learning takes is governed by one’s needs and goals. We seek experiences that are related to our goals, interpret them in the light of our goals, and form concepts and test implications of these concepts that are relevant to our felt needs and goals. The implication of this fact is that the process of learning is erratic and inefficient when objectives are not clear. (Ibid.: 28) Checkland (1981) in his application of soft systems methodology (SSM) also considers the importance of learning. He argues that the methodology of SSM is a learning system in itself. If the process is being used to address problems, in particular soft, fuzzy, unstructured problems, then as far as Checkland is concerned ‘the methodology is a learning system, and in tackling unstructured problems, could only be a learning system, rather than a prescriptive tool, due to the special nature of human activity systems’ (ibid.: 214). This raises the question: why do people do what they do? Checkland argues that this is a function of the view the individual has of the world. Their actions are conditioned by their thinking. The interpretation of what is happening is also conditioned by this view of the world. Checkland uses the term Weltanschauung

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Figure 7.1 Kolb learning cycle diagram

to describe this, though usually abbreviates it to ‘W’. Checkland describes this in more detail when he writes: We attribute meaning to the observed activity by relating it to a larger image we supply from our minds. The observed activity is only meaningful to us, in fact, in terms of a particular image of the world or Weltanschauung, which in general we take for granted. (Ibid.: 215) This suggests that the W any one individual has determines actions. Another term for W is paradigm. For many years a particular paradigm may be appropriate for a particular set of circumstances. However, reality changes and with that change pressure is placed on the ruling paradigm, until it gives way to new thinking, a new paradigm. This is what Kuhn (1970) defines as ‘paradigm shift’. Hence, given a set of problems, the way in which the problem is addressed is a function of the W or paradigm of the problem-solver. If the solution is successful, the paradigm continues to be valid. If the solution is unsuccessful, then the paradigm eventually faces a major challenge to the assumptions of validity that lie behind it. Checkland (1981:216) observes this when he writes: It is characteristic of us that we cling tenaciously to the models which make what we observe meaningful. We celebrate Newton and Einstein as the very greatest scientists precisely because they forced the establishment of new Ws. Both were able to establish hypotheses which survived severe tests and hence became public knowledge, and were based on

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Figure 7.2 Basic control model

revolutionary frameworks, on Ws different from the prevailing ones of their time. He then goes on to note: The Ws of an individual man will in fact change through time as a result of his experiences. And the Ws of a group of men perceiving the same thing will also be different. It is because of these two facts that there will be no single description of a ‘real’ human activity system, only a set of descriptions, which embody different Ws. In a certain sense, human activity systems do not exist; only perceptions of them exist, perceptions which are associated with specific Ws. (Ibid.: 219) For Checkland the power of SSM is in bringing about the ability to break out of one W and move to another. The same is true of the CMTP. An analysis of change control models Within most systems the normal procedure is for some kind of input to the system to trigger, or lead to, an output from the same system. There is also usually some form of feedback to give a degree of control to the system, as shown in Figure 7.2. The control mechanism usually serves to regulate the input in line with the output in order to prevent the system moving to an out-of-control position. This model is a fairly standard description of such systems. It is equally applicable to human activity systems or to most other types of systems. It does have limitations, however, particularly when one important aspect of the system is the ability to learn and thus avoid errors in the future. This ability to learn is a necessary function if the ruling paradigm of the organisation requires changing

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Figure 7.3 Single/double loop learning

at any time. This ability to change paradigm has been discussed at great length by Argyris (1990, 1992, 1993), Argyris and Schon (1996) and also by Argyris et al. (1985). They have developed a number of key concepts within the process of organisational learning. These include the distinction between espoused theory and theory in action; the nature of single and double loop learning; and the relationship these all have with organisational learning. The model developed by Argyris (1992: 8) is shown in Figure 7.3. Argyris notes that: Learning is defined as occurring under two conditions. First, learning occurs when an organisation achieves what it intended; that is, there is a match between its design for action and the actuality or outcome. Second, learning occurs when a mismatch between intentions and outcomes is identified and it is corrected; that is a mismatch is turned into a match. (Ibid.) Referring to the models, Argyris defines them in the following way: Single loop learning occurs when matches are created, or when mismatches are corrected by changing actions. Double loop learning occurs when mismatches are corrected by first examining and altering the governing variables and then the actions. Governing variables are the preferred states that individuals strive to ‘satisfice’ when they are acting. (Ibid.: 9) When change is necessary, Argyris suggests that single loop learning is very much in line with the model first introduced by Lewin (1948) comprising three stages, these being unfreezing, changing to a new pattern and then refreezing.

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However, the model proved to be inadequate when change of a deeper nature was required. Thus the need for double loop learning was established. Argyris (1992:11) argues that: Such significant changes require changes in the organizational governing variables and master programs, that is double loop changes. But double loop changes cannot occur without unfreezing the models of organizational structures and processes now in good currency. These models, in turn, cannot be unfrozen without a model of a significantly different organizational state of affairs; otherwise, toward what is the organization to change? There is, however, an important aspect to what Argyris is saying here. The current model, though still working, is no longer valid. This implies that people are using an approach which they already know is not the one that is required. This leads to the distinction between espoused theory and theory in use. Argyris (ibid.: 89) argues that: One of the paradoxes of human behaviour, however, is that the master program people actually use is rarely the one they think they use. Ask people in an interview or questionnaire to articulate the rules they use to govern their actions, and they will give you what I call their ‘espoused’ theory of action. But observe these same people’s behavior, and you will quickly see that this espoused theory has very little to do with how they actually behave. He then goes on to say: When you observe people’s behavior and try to come up with rules that would make sense of it, you discover a very different theory of action— what I call the individual’s ‘theory in use’. Put simply, people consistently act inconsistently, unaware of the contradiction between their espoused theory and their theory in use, between the way they think they are acting and the way they really act. (Ibid.: 90) At this point Argyris returns to the governing variables when he argues that: most theories in use rest on the same set of governing values. There seems to be a universal human tendency to design one’s actions consistently according to four basic values: 1 to remain in unilateral control; 2 to maximize winning and minimize losing;

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3 to suppress negative feelings; and 4 to be as rational as possible—by which people mean defining clear objectives and evaluating their behavior in terms of whether or not they have achieved them. The purpose of all these values is to avoid embarrassment or threat, feeling vulnerable or incompetent. In this respect, the master program that most people use is profoundly defensive. (Ibid.) This last element of Argyris is fundamental. If the change is of some significance, then double loop learning is likely. If that is the case then the governing variables must also change. This is the same as the paradigm shift of Kuhn or the change in W of Checkland. However, Argyris suggests that at this point the whole approach of the individual becomes negative. If at the same time they are also aware of the conflict between the espoused theory and the theory in use, the individual can now find him- or herself in a degree of difficulty. They have to make decisions about change and whether they are prepared to take that challenge. Linking the paradigm lock cloud to models of change The notion of the paradigm lock cloud featured earlier in this book, but what of the impact in change management? In Unconstrained Organisations (Hutchin 2001 b) I put forward the model of change in Figure 7.4 as the area of study for the research. The research confirmed that in some cases the implementations failed to proceed past stage 5, solution implementation. Indeed, often no implementation took place at all. It was this factor that had led to the description of the paradigm lock cloud (PLC) as one of the primary sources of noncompletion. Noting this omission led to the next enhancement of the change model as shown in Figure 7.5. This shows the change process surrounding the implementation stage in more detail and in particular the arrow under which the PLC acts. It should be noted that there were occasions when problems did occur, but they fell into the category of a rational or functional explanation for the nonperformance. In those cases the people involved simply returned to the part of the process that required further work and carried it out and then moved to a successful conclusion. Examples of these included times when the original analysis was found to be wanting in some respect, perhaps inadequate analysis of the market, or poor product development. In other cases it was the recognition that the problems being addressed were in fact not the correct or the most urgent ones, and this forced those involved to return to an earlier stage of the model and re-evaluate their work and possibly change tack altogether. These reasons for not progressing with the implementation were seen as rational. However, this

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Figure 7.4 First review of the change model

research has shown that there is also an irrational, dysfunctional force operating that prevents the implementations taking place. This led to the revision of the change model to include that factor. The PLC as the implementation constraint related to change This constraint, the paradigm lock cloud, is not that of just any improvement project, it is much more of an organisational constraint. Within the companies taking part in the original research, initially the people involved were highly supportive of what the constraint management approach was trying to achieve. Once the implementation process was under way, however, it soon became apparent that other factors not initially recognised started to make their impact felt. This was always associated with the need for support and commitment from other people who had not been involved in the original decision process. The ability to determine whether the PLC was operating or not is difficult to develop. The first step is to assume that it is not operating, and to consider that the reasons for not moving forward are more related to the lack of subordination. This is for no other reason a safer place to examine, given the high levels of stress when paradigms are being challenged. The importance of subordination in change management Subordination is the third of the five steps of focusing contained within the TOC approach. It is also the most difficult to achieve. Time and time again we come across people who find it almost impossible to subordinate to the decisions that have been taken. The conflict of subordination cloud is a profound cloud. It sits at the core of many implementation problems in almost all aspects of change

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Figure 7.5 The change model incorporating the PLC

management. This is an area where time spent on surfacing the real assumptions of the individual will pay handsome dividends. There is a great deal of time to be allocated here, and there is often pressure to press ahead and gain the expected benefits of the investment. The reality is that applying that level of pressure is counterproductive and will almost always result in severely reduced benefit and greater degrees of animosity from the team. The constraint management wheel of change The wheel (Figure 7.6) represents the change process within the CMTP approach. Each part of the wheel contains specific TP tools. It also reflects the fact that it is not necessary to start at the beginning. If a suggestion is put forward and an idea proposed, it is by definition an injection, therefore it must break a cloud: is it possible to construct the cloud and surface the assumptions to check that the idea/ injection actually breaks the cloud? It is also possible to check further by using the idea and the cloud it breaks as the basis for constructing the CA and possibly

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Figure 7.6 The wheel of change

the full analysis called the current reality tree (CRT). If someone suggests a target, it can be seen as desirable effect (DE), which must have a complimentary undesirable effect (UDE), and from that the cloud can be checked and so the process goes on. Any starting point can be placed on the TP road map and an analysis developed from there. This of course does not come overnight, and the practitioners of constraint management world-wide have accepted the need to practise using these tools as often as possible. One clear outcome of our research is that only with mastery of the tools does real, on-going improvement come. What the CMTP represents is a coherent, focused, problem-solving tool containing a high degree of rigour and logic. If the intention is to seek specific solutions to specific problems then the applications of the CMTP seem to be most appropriate. In creating enhanced synergy between constraint management tools and the other primary tools of manufacturing, Lean and 6 Sigma, already many companies are drawing benefit. GM at the TOC world conference in St Paul, Minnesota, in 1999 highlighted the degree of synergy when they made it clear to the conference that the application of constraint management gave a clear

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indication as to the best use of all the other tools within manufacturing. This was echoed by Scheinkopf at the APICS 2000 conference in San Antonio when she discussed her research with respect to these three tools and made the observation that they all shared a systemic approach, a focus on value, the importance of relationships and dependencies, the necessity for simplicity and the role of flow within the manufacturing setting.

8 Pulling it all together Gaining a true enterprise focus

This book has described a journey. It is a journey that will never be complete. With the technology that is available today, most manufacturing companies are able to do things which even twenty years ago would have been unthinkable. I wonder what the discussion around the dining table, which once sat in the dining room of our home in Edinburgh, and which now sits in my own dining room, would be today. The two Johns, Garnett and Longmuir, men who had been through two world wars and seen dramatic advances in industrial technology, would have been overwhelmed by the impact of new technologies: the role of the Web, the integration of systems, the global capability of companies today, and many more innovations have changed the face of manufacturing over the past twenty years. They would not, however, have felt they had nothing to offer. All the technology that exists today is still managed, developed, implemented and created by people. For both men, people were both the starting point and the finishing point. I have found that whenever I forget that, I am in deep trouble. It is people who make enterprises work, it is people who need the products that these organisations produce, and it is people who gain a living from their involvement in that process. Enterprise focus revisited It is too easy to assume that technology will do it all for us, appealing to some perhaps, but not to me. Technology should reduce a limitation. This is hardly a new statement, but it is one that needs constant reinforcement. It lies at the heart of Goldratt et al.’s book Necessary but not Sufficient (2000) which examines the role of ERP systems within industry. The thrust of Goldratt’s premise is that any technology should reduce a limitation, but that often when such technology is implemented, the rules and procedures that predate the technology are not changed; they remain in place and effective. With this, what appears to be a simple oversight, most new technologies are crippled from the outset, condemned to local improvement at best. Constraint management is also a new technology, a new philosophy of managing a manufacturing enterprise. It is holistic, it is systemic, it

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demands measures, rules and policies that reflect that notion. It demands the use of a rigorous and logical thinking process. That substantial results can be gained from constraint management is not in doubt. The roll call of companies that have successfully utilised the constraint management approach is both long and comprehensive, and includes many of the top companies around the world. Yet constraint management has still not gained the place it so richly deserves. There is more than a hint of paradigm lock here. Today the big three movements are coming together: Lean, 6 Sigma and constraint management. With Lean concentrating on the reduction of waste, with 6 Sigma concentrating on zero defect and with constraint management concentrating on improving sales (throughput), the scene is set. With areas such as revenue mapping, pull systems, set-up reduction, 5s/Visual Workplace and kaizen all figuring within Lean, with process analysis, SPC, the Deming Cycle all figuring within 6 Sigma, and all that has been discussed within this book figuring within constraint management, all come together to form the foundation for manufacturing for many years to come. With the core elements and competencies of constraint manufacturing in place, with the new technologies, in particular the Web, in place, the time is right for a fundamental shift in thinking with respect to manufacturing management. By reducing waste to minimum levels, by creating maximum value, and transforming inventory into profitable sales without wasting operating expense, the ability to create the wherewithal for any country is enhanced. The dependency on customers, on suppliers, on tasks and resources has been taken into account. If the importance of finite capacity and variability is also taken into account, we are led to a situation where the fitness of our manufacturing companies can be assessed and addressed. It is possible to be lean, strong and continuously improving. Final thoughts This book set out to describe a different way of managing a manufacturing enterprise. By putting forward the notion of constraint management within manufacturing, the intention was to create an alternative approach to the management of the manufacturing area which offered a far higher chance of success than the methods being used today. By drawing together the various other strands such as lean thinking and supply chain management into a constraint management perspective I hope I have been able to show the role that constraint management plays. The use of technology, the need for clear thinking, the importance of the people all have a contribution to make, but without the focus and leverage offered by constraint management, without the changes to the measurement systems, little will appear on the bottom line. In my first book, Enterprise Focused Manufacturing (Hutchin 2001a), I finished the first chapter with the following paragraph, which I feel is still relevant today:

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To my mind there is only one key constraint in any organisation. If the intention is to substantially increase throughput I have discovered only one genuine constraint. It is not the market, it is not capacity, it is not the size of the warehouse, it is not a lack of people, and it is not a lack of money. In fact it is not the lack of anything except one dimension that only human beings can bring. Sure the rest all seem to be potential constraints. To my mind they are only obstacles on the path to the goal. They can all be overcome if, and it is a big if, we unleash the intuition of our people. The only constraint operating within all of the companies I have worked in over the years has been, to my mind, a serious lack of imagination being allowed to develop. This book, the research that lies behind it, the TOC/TP tools are all about allowing people, from board room to shopfloor to think, to release the energy of the mind. That is what the rest of this book is about. (Ibid.: 17) The environment that existed when I wrote that has not changed. I still find a great deal of inertia in the boardrooms and shop floors of our manufacturing industry; I find it in the financial quarters and in government; I find it in our educational establishments and in our support organisations: it is endemic. Yet we possess some of the finest minds in the world, so why do we persist in using outdated tools and techniques to improve the wealth creation capability of our nation, indeed any nation, for the same problem affects the rest of Europe, the USA and beyond? This is not a problem for technology to solve, it is a problem for people to solve. Once we teach people to think, to examine, to challenge with a set of logical tools that allow for proper analysis, then we might be able to address the many problems of manufacturing, of commerce in general, and perhaps of the world.

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Index

A plants 111 absorption costing 23, 24 accountancy: cost accounting 22, 24–5, 29, 110; generally accepted accounting procedures (GAAP) 23; management accounting 24, 29; production costs see costs of production; throughput accounting (TA) 22, 110 additionality reservation 49 advanced planning systems (APS) 4 Argyris, C. 150–3 Atkinson, P.E. 140–1, 142, 143

Brooks, E. 137 buffer management (BM): buffer violators 30, 75; distribution 120, 132–4; drum-buffer-rope (DBR) 112–13, 115, 118, 120; project management 74–6, 88–9; sales 113, 118 buffers: assembly buffers 110; buffer violators 30, 75, 88, 89, 113, 115; clients 132, 133, 134; constraint buffers 108–9; DBR see drum-buffer-rope; feeding buffers 72, 74, 81; finished products 130–1, 132–3; inventory 112, 131; paranoia consumption 131; penetration 75–6, 78, 81; project buffers 72, 74, 81, 84, 88, 89; project management 71–6, 78, 81, 84, 88; resource buffers 71–2, 74, 81; shipping buffer 109, 117; strategic resource buffer 88–9; zone management 74–6 Burns, T. 137

batches: idle inventory 10; lead time 102; process batches 11; release batches 11; set-up costs 96; small orders 100; transfer batches 11; V plants 111 Belbin team dynamics methodology 143 Bell, J. 22, 23, 24 Bicheno, J. 10 blame culture 60, 76 Blanchard, K.H. 137, 141, 146 bottlenecks: bottlenecked operations 23; general-purpose machines 11; meaning 25, 97; policy constraints 27, 97; secondary constraints 30

capacity: collaborative 16; constraint schedules 112; customer demand 128; individual resources 106; productive 108, 128;

161

162 INDEX

protective capacity 13, 108, 118, 124; set-up saving 131, 132–3; spare capacity 10–11, 108, 113, 118; subordination to the constraint 105 carrying costs 101, 126 Caruth, D.L. 142–5 case studies: drum-buffer-rope (DBR) 114–22; new product development (NPD) 89– 91 cash flow: slow payments 7 causality reservation 49 Central and Eastern European Countries 5 change management: challenges of change 138–9; change agents 140–3, 144; change control models 150–5; changing environments 137; clouds 147–8; communication 144–5; conflict resolution 147–8; consensus 140; constraint management thinking processes (CMTP)137, 138, 139, 141, 147; depersonalisation 144; disruption 144; implementation 136, 138–40, 144, 146, 147–8; improvement projects 147; in-house personnel 142; introduction of change 139–40; key variables 137; leadership 60, 62, 140–2; learning cycle 148; managing change 137–40; marketing perspective 139–40; models 147–8, 150–5; motivation 142–3; negative branch reservation (NBR) 138, 145; opinion leaders 140; organisational learning 148–50; ownership 140; paradigm lock cloud (PLC) 153–5; politics of change 145–7; real change leaders (RCLs) 141–2;

resistance to change 138, 143–5; risk 137–8; role of change 136; single/double loop learning 151; strategic importance 136–56; subordination to the constraint 155; threat perceived 144; wheel of change 155–6 Checkland, P. 33, 147–8, 153 China 5 Christensen, C.M. 16 clarity reservation 49 clouds: assumptions 40, 46, 48, 49, 51, 100, 101, 129; change management 147–8; communication analysis (CA) 49, 50, 51; composite (construction) 46–51; conflict clouds 40–1, 43, 44, 100–2; distribution 128; generic 47; necessity statements 44; paradigm lock (PLC) 59–61, 153–5; problemset 25–6; production 100–2; UDE cloud (application) 43–6, (assumptions) 44, (checking) 44–6, (cross-connection) 44, 45, (desirable effects) 43, 44, 45, 51; validation 49 Cohen, Oded 59 collaborative capacity 16 common cause variation 16, 75, 98, 108 communication analysis (CA) 49, 50, 51 competition: constraint management thinking processes (CMTP) 61; retail outlets 124, 126 Concerto 91 conflict: conflict clouds 40–1, 43, 44, 100–2; inherent in production 100–2; inventory 126–9; key performance indicators (KPIs) 33; resolution 112, 147–8; undesirable effects (UDEs) 39–41

INDEX 163

consensus: change management 140; problems 34–5, 103–5; solutions 35, 51 constraint management (CM): causality 25; cloud see clouds; common sense 19; critical chain 65, 88; laws 29–32, 60, 96–8, 99; manufacturing perspective 13–14; measurement 6, 21–2; milestones 70; new product development (NPD) 61, 62; origins of approach 14; paradigm lock 58–61; production 122–3; project management 63, 65; repeatability 25; TOC see Theory of Constraints; wheel of change 155–6 constraint management thinkingprocesses (CMTP): basic questions 34; change management 137, 138, 139, 141, 147; clarity 39; competition 61; concerns 115; enterprise analysis methodology 136; origins 33; performance improvement 30; pre-requisite trees (PRTs) 55, 114; problems 34–5; production 100; UDEs see undesirable effects; wheel of change 155–6 constraint manufacturing: collaborative capacity 16; core competencies 17–18; core elements 14; definition 14–17; designing for demand 17; reach 15–16; speed 14–15; uncertainty/variation 16–17 constraints:

decision-support systems 31, 98; designed-in 105; elevation 28, 105; exploitation 28, 97, 104–5, 107; identification 27–8, 97, 104, 112; implementation 154–5; improving other links 30–1, 97; information systems 118; key resources 88; levered performance 28, 30, 97; maintenance 28, 108; markets 107; paradigm constraints 27, 28, 97, 104, 105, 112; physical constraints 26, 27, 28, 61, 97, 103, 104, 105, 112; PLC see paradigm lock cloud; policy constraints 26–7, 28, 97, 103–4, 105, 112; prevent inertia 28–9, 105, 112; protection 28; schedule construction 28, 108, 112; set-up reduction 28, 113, 131; subordination see subordination to the constraint; supply base 107; tolerance compliance 28; typology 26–7; variation 31–2, 98; waste 28; weakest link 26, 29–30 construction projects see project management contribution margin 23 Corbett, T. 22, 24, 25, 110 core solutions: assumptions invalidation 51; core future reality tree (CFRT) 51, 52, 53; development 51–2; injections 51; sensitive dependence on initial condition 51 costs of production: carrying costs 101, 126; cost accounting 22, 24–5, 29, 110; cost allocation 1, 21, 101, 102, 112; cost controls 27, 104, 126, 129;

164 INDEX

cost per part 96; globalisation 5; operating expense (OE) 22, 23, 101; product costing 102; set-up costs 96; variable costs 22, 24 Cox, J.F. 11, 22, 33, 46, 93, 115, 142 critical chain: behaviours 76; buffers 71–6; collaboration 90, 91; constraint management (CM) 65, 88; delayed starts 81–4; enterprise resource planning (ERP) 77; feeding chains 70, 72, 81; identification 70–1, 78, 80; implementation 77–8; key resources 84, 87–9; longest path of dependent events 69, 70, 74; multi-project environments 84–91; new product development (NPD) 63; paths 70, 78; project management (CCPM) 64, 65– 70, 77–91, 136, 139; reporting 74, 76, 81, 89; schedule construction 68, 77–8; specialist software 70, 78, 89, 90–1, 98; staggered projects 88; subordination to the constraint 76 critical path 70, 78 current reality trees (CRT) 155 customer demand: capacity 128; designing for demand 17; forecasts 126–8; product life cycle 1–2; stock out 124, 126, 127, 134; variation 124 defects: operational competency 18; production 62; quality control 17; variation 31; waste 11–12

delivery performance: inventory 12, 13; measurement 130; project management 76–7 demand see customer demand Deming, W.E. 16, 33, 48 Deming Cycle 158 design: competency 17–18; design, build and finance 64; designed-in constraints 105; designing for demand 17 desirable effects (DEs): distribution 130; solutions 52–3; targets 155; UDE cloud 43, 44, 45, 51 disruptive technologies 16, 17 distribution: analysis 125–9; basic process 124–5; buffer management (BM) 120, 132–4; clouds 128; customers 124–35; DDP see due date performance; delivery performance (inventory) 12, 13, (measurement) 130; demand see customer demand; desirable effects (DEs) 130; injections 130–1, 132, 133; inventory see inventory; loss of trust 127; new product development (NPD) 62; on time and in full (OTIF) 130, 132; replenishment 124, 130–4, 136; returned products 126, 130, 132; solutions 129–34; stock out 124, 126, 127, 134 Drucker, P.F. 145 drum-buffer-rope (DBR): A plants 111; assembly buffers 110; benefits 116; bottom line results 19; buffer see buffers; case studies 114–22; concerns 115, 116;

INDEX 165

conflict removed 112; constraint buffers 108–9; development 105–11; education 113; gating operation 108, 110; implementation 12, 22, 95, 111–14; implementation plans 113–14, 115, 117; injections 115, 116, 120; lead time 108, 109, 112; management see buffer management (BM); non-constraints 110, 111; observation/ questioning 106–7; origins 93; problems 103–5; revenue chain 111–12; shipping buffer 109, 117; simulations 102, 103–5, 115; solutions 105–11, 136; supply chain 131; T plants 111; V plants 111 due date performance (DDP): improvement 23, 24, 118; production 62, 93–4, 95, 101, 109; shipping dock 109, 123; transfer batches 11 e-commerce: virtual enterprises 18 efficiency measures: overproduction 10; resources 87, 96, 98, 100, 111, 112 Emery, F.E. 137 Engineering Employers’ Federation 4 enterprise analysis methodology 33–62, 136 enterprise resource planning (ERP): critical chain 77; decision-support systems 8, 31; implementation 6–7, 9; virtual enterprises 18 entity reservation 49 ergonomics: unnecessary motion 11 Etzioni, A. 146 evaluation:

manufacturing xviii extended transition tree 57 fast-moving consumer goods 126 financial flow networks 7–8 financial mapping 8 finished goods (FG): inventory 11, 12, 23, 99, 111, 126, 129, 130; monetary value 23 finished products: buffers 130–1, 132, 133 focus: enterprise focus 157–8; misplaced focus 12–13; Theory of Constraints (TOC) 27–9, 34, 76, 97, 104–5 Follett, M.P. 147 forecasts: customer demand 126–8; inaccuracy 128; medium-term 127, 128 Fox, R. 93, 130 Gantt charts 65, 78 Garnett, John xvii, 157 general-purpose machines: inappropriate processing 11 generally accepted accounting procedures (GAAP) 23 geographical reach 15 Gergen, P. 137, 138 globalisation: supply chain 5–6 Goldratt, Eli M. xvii, 6, 9, 11, 14, 22, 32, 33, 40, 63, 65, 84, 93, 97, 104, 112, 115, 130, 142, 157 Goldratt Conferences 122 Goldratt Institute 59 Grove, Andy S. 21 Gryna, F.M. 16 Handy, C.B. 145 Hersey, P. 137, 141, 146 Hickson, D.J. 33 high-tech industry: profit margin 64

166 INDEX

Hutchin, C.E. 27, 32, 40, 43, 46, 63, 96, 136, 153, 158–9 identification: constraints 27–8, 97, 104, 112; critical chain 70–1, 78, 80 implementation: change management 136, 138–40, 144, 146, 147–8; constraints 154–5; critical chain 77–8; drum-buffer-rope (DBR) 12, 22, 95, 111–14; enterprise resource planning (ERP) 6– 7, 9; total quality management (TQM) 4, 17, 31 implementation plans: development 53–7; drum-buffer-rope (DBR) 113–14, 115, 117; extended transition tree 57; injections 53, 54, 55; intermediate objectives (IOs) 55; obstacles 54–5; pre-requisite trees (PRTs) 55, 114, 115, 120, 143; sequence of actions 55; transition tree 56, 57 improvement projects: change management 147; non-constraints 30–1, 97; production process improvement 30–1, 38, 94–5, 97, 98; undesirable effects (UDEs) 38; waste 30, 97 Industrial Society xvii inertia 28–9, 105, 112, 159 information systems: coherence 31; constraints 118; elevate the constraint 28; flow networks 8–9; Web see Web injections: core solutions 51; distribution 130–1, 132, 133;

drum-buffer-rope (DBR) 115, 116, 120; implementation plans 53, 54, 55; injection 10 120; injection 100 119; injection reference 118; leadership 60; paradigm lock cloud (PLC) 60–1; responsibility/accountability 60; risk 138; subordination to the constraint 60–1, 120 insufficiency reservation 49 inventory: absorption costing 23, 24; assumptions 129; buffers 112, 131; carrying costs 101, 126; conflicts 126–9; delivery performance 12, 13; excess 127, 129; finished goods (FG) 11, 12, 23, 99, 111, 126, 129, 130; forecasts 126–8; generally accepted accounting procedures (GAAP) 23, 99; idle inventory 10; lean production 10, 11; measurement 130; misplaced focus 12–13; obsolescence 126, 132; protection 13, 124, 126, 131; raw materials 12, 99; reduction 118; regional warehouses 124, 125, 126, 127, 129, 130, 131; shelf-life 132; shortages 94, 99; standard variance reporting 24; supply chain 13, 126; unnecessary inventory 11, 94; waste 126; work in progress (WIP) 11 Inventory Dollar Days (IDD) 130 Japan 4–5 Jones, D.T. 10

INDEX 167

Juran, J.M. 16 just-in-case syndrome 10 just in time (JIT) 4, 24 Kahn, R.L. 147 Kaizen l7, 31, 158 Kakabadse, A. 145 KanBan 36, 102 Katz, D. 147 Katzenbach, J.R. 141, 142 keeping busy 96, 99 key performance indicators (KPIs) 18, 33 Kolb, D.A. 148 Kraus, W.A. 138, 139, 140, 143, 145, 146 Kuhn, T.S. 149 Lawrence, P. 145 Lawrence, P.R. 137 Leach, Larry P. 63, 65 lead time: batches 102; drum-buffer-rope (DBR) 108, 109, 112; production 94–5, 98–100, 102, 108, 109, 127; project management 70; spare capacity 108; transportation 126, 127; work in progress (WIP) 98–100 leadership 60, 62, 140–2 Lean 156, 158 lean production: meaning 10, 12, 13; United States 4; waste 10–12, 23 lean thinking 10–12, 30 Lee, R. 145 Leonard-Barton, D. 138, 139, 140, 143, 145, 146 Lewin, K. 151 local optimisation 96, 97, 100–1, 113 Longmuir, John xvii, 157 Lorsch, J.W. 137 Mackey, J.T. 22 McMullen, T.B. 46 maintain competency 18

maintenance 28, 108, 112 management: buffers see buffer management (BM); change see change management; CM see constraint management; networks 6–7; new product development (NPD) 63– 92; production 93–123; projects see project management; status quo 60; supply chain 6–7, 125–6; TQM see total quality management management accounting: cost accounting information 24; limiting factors 29 manufacturing: constraint management perspective 13– 14; evaluation xviii; introduction 1–4; key themes 4–5 manufacturing automation protocol (MAP) 5 Managing Innovative Manufacturing (MIM) 7 markets: constraints 107; new product development (NPD) 20–1, 63; reach 15 Marks, David 10, 102 material flow networks 7 material release 96, 98, 111 materials requirements planning (MRP) 4 measurement: constraint management (CM) 6, 21–2; contribution margin 23; costs see costs of production; injection reference 118; Inventory Dollar Days (IDD) 130; investment (I) 22, 101; local optima 96, 97, 100–1; operating expense (OE) 22, 23, 101; profitability 23; return on investment (ROI) 22; revenue chain 21–5;

168 INDEX

subordination to the constraint 61, 98, 110; supply chain 102; throughput (T) 22–3, 101; throughput accounting (TA) 22, 110; Throughput Dollar Days (TDD) 130 Moore, G.E. 3, 4 Moore, M. 137, 138 multi-project environments 65, 70, 84–91 multiple single projects 64–5 NCX 10 machine 11 negative branch reservation (NBR): change management 138, 145; risk 138; undesirable effects (UDEs) 41–3, 54 networks: chain see critical chain; control 13; financial flow networks 7–8; information flow networks 8–9; management 6–7; material flow networks 7; PERT networks 65; project management 65, 70, 76, 78–81; validation 78 new product development (NPD): background 63–4; case studies 89–91; constraint management (CM) 61, 62; critical chain 63; designing for demand 17; distribution 62; management 63–92; market pressure 63; profit margin 64; sales and marketing 20–1, 63 Newbold, Rob C. 63, 65 non-constraints: assembly 110; buffer violators 30, 113; decision-support systems 31, 98; drum-buffer-rope (DBR) 110, 111; improvement projects 30–1, 97; set-up reduction 28 Noreen, E. 22, 24

objectives: intermediate objectives (IOs) 55; project management 63 on time and in full (OTIF): distribution 130, 132; production 100, 101, 109 open systems theory 147 operating expense (OE) 22, 23, 101 operational competency 18 optimised production technology (OPT) 4 organisational learning 148–50 overproduction 10 overtime: policy constraints 26–7, 104 paradigm constraints 27, 28, 97, 104, 105, 112 paradigm lock cloud (PLC): change management 153–5; constraint management (CM) 58–61; impact 59–61; injections 60–1 paradigm shift 149 Parker, C. 145 people development 62 PERT networks 65 Pettigrew, A. 137 Pfeffer, J. 145 physical constraints 26, 27, 28, 61, 97, 103, 104, 105, 112 policy constraints 26–7, 28, 97, 103–4, 105, 112 pre-requisite trees (PRTs) 55, 114, 115, 120, 143 problems: analysis 34–5; consensus 34–5, 103–5; constraint management thinking processes (CMTP) 34–5; core drivers 43, 51, 95, 136; drum-buffer-rope (DBR) 103–5; pet projects 36; problem owners 34; problem-set 25–6; production 93–102; revenue chain 25; solutions see solutions;

INDEX 169

systemic 48; UDEs see undesirable effects process batches 11 process issues 15–16 Prochain Inc 78 procurement: globalisation 5 product life cycle: customer demand 1–2; timescales 1–3, 61 product portfolio management 90 production: capacity see capacity; clouds 100–2; common parts 99; constraint management (CM) 122–3; cycle time 131; DBR see drum-buffer-rope; defects 62; due date performance (DDP) 62, 93–4, 95, 101, 109; expediting 94, 99, 100; inherent conflicts 100–2; inventory see inventory; keeping busy 96, 99; lead time 94–5, 98–100, 102, 108, 109, 127; lean see lean production; management 93–123; material release 96, 98; non-productive time 101; on time and in full (OTIF) 100, 101, 109; optimised production technology (OPT) 4; overproduction 10; priorities shuffling 95, 99; problems 93–102; process improvement 30–1, 38, 94–5, 97, 98; resources see resources; rush jobs 94, 127; simulations 102; waiting time 10–11, 95, 99; work in progress (WIP) 11, 23, 98–100 productive capacity 108, 128 project management: background 63–4;

buffers see buffers; commitment 67; constraint management (CM) 63, 65; critical chain (CCPM) 64, 65–70, 77– 91, 136, 139; delayed starts 68–9, 81–4; dependent events 65, 69–70; design, build and finance 64; elapsed time/estimations 68, 78, 81, 87; execution 67–70, 74; fractional head count 84; last minute syndrome 68; milestones 70, 72; multi-project environments 65, 70, 84– 91; multiple single projects 64–5; networks 65, 70, 76, 78–81; non-compliance 64; objectives 63; overall lead time 70; penalties 64; profit margin 64; project delivery 76–7; protective time 67, 68, 70, 71; resource managers 72, 84, 87; risk 74; single project environments 64, 70–4, 78–81; specialist software 70, 78, 89, 90–1, 98; task durations 66–7, 70; time estimation 65–8, 78, 81; variation 66, 67, 72, 75; worked example 70–4 projects: improvement see improvement projects; multiple single projects 64–5; pet projects 36; single project environments 64, 70–4, 78–81; staggered projects 88; typology 64–5 protective capacity 13, 108, 118, 124 Pugh, D.S. 33 purchase orders: approval 7; cost reduction 27;

170 INDEX

raw materials 99 quality control: 6 Sigma xviii, 156, 158 real change leaders (RCLs) 141–2 release batches 11 replenishment: complete system 133; distribution 124, 130–4, 136 rescheduling 12, 13 reservations: communication analysis (CA) 49 resources: buffers 71–2, 74, 81, 88–9; constraint resource 10–11; ERP see enterprise resource planning; high efficiencies 87, 96, 98, 100, 111, 112; individual capacities 106; interaction 96–7; key resources 84, 87–9; local optimisation 96, 97, 100–1, 113; resource managers 72, 84, 87 retail outlets: competition 124, 126; stock out 124, 126, 134 return on investment (ROI) 22, 101 revenue chain: components 6, 7; decision-making 15; defining the chain 20–1; disruptive technologies 21; drum-buffer-rope (DBR) 111–12; goal units 20; impact 20–32; interdependent elements 29, 96, 99; market reach 15; measurement 21–5; operational competency 18; organisational snapshot 25–6; performance maximisation 29–30; problems 25; return loop 20; subordination to the constraint 105; supporting functions 21; synchronisation 97;

systems theory 29 risk: change management 137–8; negative branch reservation (NBR) 138; project management 74 rush jobs 94, 127 sales: buffer management (BM) 113, 118; distribution see distribution; lost sales 1–2, 124–5; new product development (NPD) 20–1, 63 schedule construction: constraints 28, 108, 112; critical chain 68, 77–8 Scheinkopf, L. 156 Seagate 90 set-up: costs 96; reduction 28, 113, 131, 132–3 Shewat, W.A. 16 shipping buffer 109, 117 single/double loop learning 151 single project environments 64, 70–4, 78– 81 Smith, D. 22, 110 soft systems methodology (SSM) 149, 150 solutions: benefits 35, 51–2; consensus 35, 51; core see core solutions; desirable effects (DEs) 52–3; direction 35; distribution 129–34; drum-buffer-rope (DBR) 105–11, 136; full feature set 52–3; implementation see implementation; making it happen 35, 57–8; problems see problems; reservations 35 sourcing: globalisation 5–6 spare capacity 10–11, 108, 113, 118 special cause variation 16, 75, 98, 108 Speed to Market 91

INDEX 171

Spencer, M.S. 46 spreadsheets 98, 112, 117 Srikanth, M.L. 111 Stalker, G. 137 statistical process control (SPC) xviii, 28, 31, 158 Stein, R.E. 112 subordination to the constraint: capacity 105; change management 155; critical chain 76; importance 28, 31, 97–8; injections 60–1, 120; key drivers 110; measurement 61, 98, 110; paradigm lock 61; revenue chain 105 success: pressures 1–19 supply base constraints 107 supply chain: decision-making 2; drum-buffer-rope (DBR) 131; globalisation 5–6; inventory 13, 126; lost sales 1–2, 124–5; management 6–7, 125–6; measurement 102; partnerships 16; value stream xviii sustaining technologies 16 Swain, M. 22, 23, 24 synchronisation: competency 18; interdependent elements 29, 96, 99; revenue chain 97 systems theory 29, 147 T plants 111 tautology reservation 49 technical operations protocol (TOP) 5–6 technologies: change agents 140; disruptive 16, 21; optimised production technology (OPT) 4; reach 16;

stability 137; sustaining 16 technology adoption process: “chasm” 3–4 Theory of Constraints (TOC): clarity 39; financial measurement 24; focusing steps 27–9, 34, 76, 97, 104–5; “Jonahs” 33; origins xvii–xviii, 4, 14, 122; period expenses 23; profits maximized 23; variable costing 24 Theory of Constraints thinking processes (TOC/TP): origins xvii, 33–4; pre-requisite trees (PRTs) 115; supplier performance 12 throughput accounting (TA) 22, 110 Throughput Dollar Days (TDD) 130 total quality management (TQM): exploiting constraints 28; implementation 4, 17, 31; management accounting 24 transfer batches 11 transition tree 56, 57 transportation: excessive movement 11; lead time 126, 127 Trist, E.L. 137 Umble, M.M. 111 undesirable effects (UDEs): cloud see clouds; conflict created 39–41; control 38–9; core drivers 43, 51; destructive effects 41–3; financial impacts 38; improvement projects 38; mapped organisations 36–8; negative branch reservation (NBR) 41– 3, 54; non-financial impacts 38; poor communication 39; starting point 36–9; targets 155

172 INDEX

United States: lean manufacturing 4; replenishment 134 V plants 111 variation: common cause variation 16, 75, 98, 108; constraint manufacturing 16–17; constraints 31–2, 98; customer demand 124; project management 66, 67, 72; special cause variation 16, 75, 98, 108 waiting time 10–11, 95, 99 waste: constraints 28; defects 11–12; eradication 10–12, 23; improvement projects 30, 97; inventory 126; synchronisation competency 18 Web: collaborative capacity 16; enterprise resource planning (ERP) 7; information flow networks 8; new technologies 158; project management 89 Weltanschauung (W) 149–50 Whipp, R. 137 Womack, J.P. 10 Wooldridge, E. 139 work in progress (WIP): inventory 11; lead time 98–100; monetary values 23