Organizational Learning: How Companies and Institutions Manage and Apply Knowledge

ORGANIZATIONAL LEARNING

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Organizational Learning How Companies and Institutions Manage and Apply Knowledge Jerry L. Wellman

ORGANIZATIONAL LEARNING

Copyright © Jerry L. Wellman, 2009. All rights reserved. First published in 2009 by PALGRAVE MACMILLAN® in the United States—a division of St. Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010. Where this book is distributed in the UK, Europe and the rest of the world, this is by Palgrave Macmillan, a division of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries. ISBN-13: 978–0–230–60614–2 ISBN-10: 0–230–60614–8 Library of Congress Cataloging-in-Publication Data Wellman, Jerry L. Organizational learning : how companies and institutions manage and apply knowledge / Jerry L. Wellman. p. cm. Includes bibliographical references and index. ISBN 0–230–60614–8 1. Knowledge management. 2. Organizational learning. 3. Organizational behaviour. I. Title. HD30.2.W456 2009 658.4⬘038—dc22

2008036926

A catalogue record of the book is available from the British Library. Design by Newgen Imaging Systems (P) Ltd., Chennai, India. First edition: June 2009 10 9 8 7 6 5 4 3 2 1 Printed in the United States of America.

Contents

List of Figure and Tables

vii

Preface

ix

Acknowledgments Chapter 1 Introduction

xiii

1

Chapter 2 How Organizations Remember What They Know

27

Chapter 3 Culture—The Way It Is Around Here

51

Chapter 4 Old Pros—I Remember When

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Chapter 5 Archives—It’s In Here Somewhere

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Chapter 6 Process—The Way Things Work Around Here

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Chapter 7 Putting Them Together

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Chapter 8 Pragmatics of Managing Organizational Knowledge

165

Closing

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Index

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List of Figure and Tables

Figure 7.1

Comparison of Four Organization Knowledge Management Dimensions

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Tables 2.1 3.1 3.2 4.1

Human and Organizational Memories—A Comparison What Shapes Culture? Knowledge Management Attributes of Culture Leadership Responsibility in Managing Old Pro Knowledge 5.1 Same Words but Different Meanings 6.1 Acceptable Quality Levels, Sometimes Even 99.9 Percent Isn’t Good Enough 8.1 Centralized versus Decentralized Approach to Knowledge Management

44 58 70 91 113 138 175

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Preface

T

he core idea for the constructs described in this book first emerged in coherent form when I was given two hours to prepare a half-hour lecture on a new topic. The point of the exercise was to critique my presentation skills and the subject matter itself was relatively unimportant to the review panel. Such circumstances can foster either chaos or clarity. What emerged was a new perspective about a topic that had been bothering me for some time. The work for that presentation exercise led me to a series of assertions and a presentation titled “A Few Lessons Learned about Lessons Learned.” Two streams of thought led me to develop the model outlined in that presentation, a model for understanding how organizations handle knowledge. First, I had recently been frustrated about shortcomings in the way the organization I was leading at the time dealt with a couple of challenges. In one instance the organization seemed to have repeated a past mistake, apparently failing to have applied what we had already learned. In another instance the organization appeared to have misapplied some past learning to a new situation. Both instances cost us a great deal of money and dissatisfied important customers. Second, I had recently read Knowledge in Organizations (Prusak, 1997), a collection of papers about how organizations deal with what they know. The book brought together perspectives and insights from several academics who had studied the topic. Some of those researchers offered insights and perspectives that resonated with my own experiences, both recent and in the past. Others appeared to be either too narrowly focused or too abstract to be useful to leaders, like me at the time, dealing with real-world organizational learning challenges. The model and assertions I put together for that presentation, and the continuing frustrations in my own organization, led me to think more deeply about the topic. I delved more deeply into the literature, becoming both enlightened and frustrated. I also thought

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more deeply about how well or poorly the organizations around me were handling their knowledge. Competitors, suppliers, and sisterbusinesses within our corporation were struggling with the same challenges. It also prompted me to continue testing the model and assertions against the research, what I had experienced in the past, and what I observed now. A couple of years later that work matured into a paper published in the Organization Development Journal (Wellman, 2007). The response to the paper in turn prompted the work on this book. I began asking myself several questions: Just how do organizations recognize and capture the valuable lessons they learn? How are those lessons retrieved when needed? Do some old and now irrelevant or disruptive lessons learned still linger within the organization long after they are useful? Or has their usefulness been overlooked? In short, just what lessons have we learned about how organizations capture, store, and retrieve what they learn? Hopefully, this book sheds some additional light on the answers. A Note on Terminology Used in this Book The reader should note that four words/phrases (Culture, Archives, Old Pros, and Process) are being used as terms-of-art if you will for a collection of organizational behaviors, attitudes, and biases. Yet, the same words are also by necessity occasionally used in the text for their more traditional meaning. For example, I describe different types of archives (the traditional usage) such as logbooks, data files, test results, and the like, but I also use the word Archive to describe the organization’s overall approach to capturing, formatting, and storing its knowledge as one of the four ways the organization deals with what it knows. Thus Archive is a meta-concept while “archive” appears with its traditional meaning. I have worked hard to find alternative words for the traditional meaning of these four words. I have attempted to manipulate the sentences to avoid their traditional usage. I have tried having them appear in their traditional and their “meta” context without using italics or capital letters to distinguish the two usages. None satisfied the need. The reader is asked to keep in mind the distinction. References Wellman, J.L. (2007). Lessons learned about lessons learned. Organization Development Journal 25(3): 7.

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Organizations capture and deploy what they have learned in one of four ways: Culture, Old Pros, Archives, and Processes. This paper describes the four approaches, their strengths and shortcomings, and their interactions. Along the way, it offers guidance and perspective to assist a management team striving to build more effective organizational learning competence. Prusak, L. (1997). Knowledge in organizations. Boston, ButterworthHeinemann. This collection of papers gathers perspectives on organizational knowledge management from the information technology, organization theory, and leadership perspectives among others.

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Acknowledgments

A crusty old vice president for whom I worked many years ago was fond of saying there is no new learning in this world, only remembering and reminding. It may be that this book found its genesis in Bill Poe’s perspective. His admonition left its mark on my own worldview and in turn influenced how I chose to interpret what went on around me. Of course I also recall him once writing in my performance appraisal that I was too often pedantic—by that he meant I was a person who asserted to know more than his experience would warrant. I hope this book convinces Bill I’ve finally grown into my britches as it were. Years later, my Ph.D. advisor Bob Silverman provided the gentle guidance and encouragement that led me to understand information systems to be much more a social and cultural notion than a process and technology notion. He steered me toward Prusak, Davenport, Stinchcombe, and others whose work shaped my understanding of how organizations deal with what they learn. Those influences swirled in a lively stew out of which arose the perspective described here. No doubt I have unconsciously adopted as my own original notions thoughts that I learned, read, or inferred from others. For that I apologize. No doubt I have, albeit unintentionally, distorted or taken out of their intended context thoughts I have attributed to others, and for that also I apologize. This was my first attempt at writing a book. Had I known beforehand what was involved, I might well not have begun the journey. Chris Chappell, Laurie Harting, and Emma Hamilton at Palgrave Macmillan and Maran Elancheran at Newgen helped me survive the experience and no doubt made it much easier than I could ever know. Most importantly, to Barbara my wife and Adam my son, I appreciate deeply your patience and tolerance while I worked on this book over the past year. You indulged me more than I had any right to expect. Thank you both.

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Chapter 1

Introduction

A n agricultural expert visited a small mid-west community to give a lecture on state-of-the-art farming tools and techniques. All but one of the local farmers attended. Several days later, one of the attending farmers asked the one stubborn farmer why he did not come to the lecture. The old fellow replied, “I already know how to farm a lot better than I do.” We all know how to do our job better than we do it now and we, like the crusty old farmer, too often fail to use our knowledge effectively. Our habits and routines sometimes inhibit our doing what we know we should. Our conflicting agendas and the conflicting demands placed on us cause us to compromise what we know we should or could do for what seems expedient at the moment. Sometimes we just simply find it too difficult or cumbersome to do what should be done, instead doing what is convenient or easy. Organizations Generally Do Not Manage Knowledge Well Organizations behave in this way much like individuals because they too know more than they put to use. “If only TI knew what TI knows,” said Jerry Junkins, former chairman, president, and CEO of Texas Instruments. “I wish we knew what we know at HP,” echoed Lew Platt, past chairman of Hewlett-Packard (O’Dell and Grayson, 1998a). Junkins and Platt speak for many leaders when they acknowledge that capturing, retaining, sharing, and applying organizational learning is a daunting challenge too few organizations have met. O’Dell and Grayson assert Junkins and Platt recognized earlier than many that a vast storehouse of unknown, poorly appreciated, or poorly applied knowledge lies hidden inside their own organizations.

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Junkins and Platt make a somewhat different but equally important point than the one in the story about the stubborn farmer. They contend organizations do not know what they know, unlike the farmer who recognizes, even acknowledges, but fails to apply his knowledge. The problem as Junkins and Platt see it is one of failing to recognize knowledge rather than one of failure to apply knowledge. They seem to assume individuals and teams within the organization would readily apply knowledge if only they knew it existed and could make the relevant connection to the challenges at hand. The old farmer on the other hand would argue that his shortcoming, and perhaps the shortcoming of others as well, is a lack of will to apply what is known rather than a lack of knowing. The CEOs and the farmer are both correct with respect to organizational behavior because both shortcomings are omnipresent in nearly all organizations. Organizations certainly struggle to deal with learning then too often fail to effectively distribute what they have learned. Organizations also distribute what they have learned but then, like the old farmer, fail to effectively apply that learning. Consider the following examples of organizational and leadership frustration. Executives at a high technology aerospace business unit within a major corporation were dissatisfied that their organization continued to face recurring issues with the design and build of test equipment. The test equipment too often was delivered late, did not sufficiently test the product, or significantly overran the original cost estimates. Late test equipment caused delays in the shipment of new or redesigned products that in turn lead to unhappy customers, delayed revenues, and large financial penalties. Insufficient testing too often allowed flawed products to escape the factory. The flawed products got into the customers aircraft assembly processes and caused unnecessary delays and rework there. Such problems were a major cause of customer dissatisfaction. On the rare occasion when test equipment was designed, built, delivered on time, and working appropriately, it often cost far more than planned thus eating into profitability. The executives had good reasons to be dissatisfied. These test equipment issues were not new. Some veteran engineers and managers could remember similar problems occurring from time to time for the past twenty years or more. Teams had been commissioned in the past to resolve the problems. Each time the teams reviewed the past documentation, talked to those involved in designing and building the test equipment, identified root causes for failures and for successes, and recommended changes. Each time victory

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was claimed. But the problems remained or soon returned in spite of changes such as increased management oversight, more conservative estimating ground rules, or the change of personnel. Past efforts proved to be inadequate to resolve the problems. The current team assigned to identify root causes discovered during the course of its investigation that fourteen years ago another team had documented many of the very same problems that existed in the present. One of the individuals they interviewed to better understand the current problems happened to have been a member of the investigation team fourteen years earlier. He had kept a copy of their findings and recommendations. The earlier team had made specific recommendations, some of which had not been implemented and some of which had been implemented for a time but did not remain in place today. The documentation proved the organization had learned some valuable lessons fourteen years earlier but those lessons were either forgotten or ignored—or perhaps, as one veteran employee said, they were “given lip service, then ignored, and then forgotten.” Another example comes from a company that was suffering from significant cost and schedule overruns on several major product development programs. They convened a team of executives and senior managers to determine the root cause of the problems, recommend corrective actions, and implement those actions. After three months and countless hours of interviews and data review, the team concluded the problems were due to three specific failures. First, there was frequently a failure to understand and integrate cost with schedule and technical requirements before beginning work. The product development teams were often given an “affordability” budget based on how much management believed they could afford to spend, a schedule based on competitive market needs, and a set of technical requirements based on perceived customer desires. But the technical requirements were often too aggressive for the time or funding allotted. Other times the technical requirements were achievable within the targeted time but adequate staffing was not provided. Thus, the programs were begun with an impossible plan. Second, there was often a failure to acknowledge and manage changes to the original specifications and plans. The marketing team would promise new customers features or performance levels that were different than those the product development team had initially been given. On other occasions the design engineers would add features they thought would be attractive to customers, or that an individual customer had informally suggested, but then they would not fully coordinate the changes with other members of the design team. Such

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uncontrolled and uncoordinated changes created unplanned work, work that resulted in cost, schedule, and technical problems. Third, senior leadership too often failed to provide agreed-to resources and funding or failed to acknowledge and manage risks. The promised funding or staffing would be reduced to meet changing profit goals throughout the year, yet the product design team was expected to accomplish the original scope of work. This forced the project teams to take unwise risks, to skip or rush important work activities, and to make mistakes that forced otherwise unnecessary rework. The investigation team found that these three mistakes—failure to develop an integrated plan, failure to control changes, and failure to provide planned resources—were the root cause of most failed projects. At least one of the three contributed to problems on every troubled project they reviewed. The real surprise came when the review team discovered, during background document reviews, that their three significant findings were among the findings of no less than eight—that’s right eight— similar internal investigations conducted within the organization over the preceding two decades. The company certainly had the knowledge it needed to perform better but it was evidently unable or unwilling to put that knowledge into practice. The evidence of recurring investigations and similar findings argues strongly that in this instance the crusty old farmer’s perspective would be more fitting than Junkins’ and Platt’s perspective. Now let us consider an example with which Junkins and Platt could more readily relate. A manager, just completing her first significant project, wanted to share some of the valuable lessons she had recently learned about managing internally generated scope creep (engineers making unauthorized “enhancements” or changes to the design). For example, the specifications may call for the power supply of a piece of equipment to provide outputs of 1.5 volts plus or minus 5 percent, 5 volts plus or minus 5 percent, and 12 volts plus or minus 10 percent. But, an engineer designing the power supply might decide the 12-volt requirements are too lax and elect to design the system for 12 volts plus or minus 5 percent. The resulting design “creep” might lead to additional parts, more expensive parts, or circuit layout changes. Experienced and disciplined project teams use several techniques to discourage and/or detect such unauthorized changes. It turned out that this project manager had independently developed a technique

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similar to the standard practice on several other projects in another part of the organization. She was simply unaware of what others in the organization had already learned and were putting to use. Perhaps Mark Twain was correct when he observed “a person who undertakes to carry a cat home by the tail learns ten times as much as the person who simply watches.” But it is also true that organizations can ill afford to have every lesson be repeatedly learned through such direct and personal experience. These examples of lessons learned time and again but not being applied today reflect Junkins’ and Platt’s perspective that organizations too often fail to remember what they have learned. Some of the examples also reflect the crusty old farmer’s perspective that organizations may know more than they are willing to put to use. Many of these mistakes have bitten experienced technical managers several times. Yet, they recur. Organizations, it seems, too frequently fail to capture and share what they learn and then fail to apply what they capture. Organizations Must Manage Knowledge Better In Order To Survive Today, more than ever, an organization’s competitiveness depends on what it knows, how well it uses what it knows, how fast it can adapt what it knows to the rapidly changing environment, and how quickly it can acquire new knowledge. Those organizations that learn and apply learning more efficiently have the opportunity to reap great rewards in productivity, speed, and profitability. A 1997 study of the U.S. aerospace industry reinforced Junkins’ and Platt’s sentiments about the value of such unused knowledge. Although the study focused on the diffusion of federally funded research and development knowledge across the industry, a much broader agenda perhaps than the study of how knowledge is retained in and then moves within an organization, it offers insights to the challenges and opportunities for both the macro and micro situation. The study team asserted that diffusion of knowledge is the key to successful innovation. They asserted further “successful innovation depends more on the application of existing knowledge than on the creation of new knowledge, because technological innovation occurs incrementally rather than radically. . . . The ability of a firm to absorb, assimilate, and apply internal and external knowledge for commercial purposes is critical to its innovative capability” (Pinelli et al., 1997).

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Other researchers have made a case for the increased importance of knowledge management. Some have found that the knowledge economy has made an organizations’ know-how more important than the traditional sources of economic power such as working capital and infrastructure (Scarborough and Swan, 1999). Zack (1999) has asserted that an organization’s knowledge is its most important resource, and learning is its most important capability. There are several pragmatic reasons why today’s organizations must be better able to capture and apply business improvement lessons. First, the capacity to learn and apply learning is rapidly becoming one of few truly sustainable competitive advantages. Technology changes rapidly and markets are becoming more globally competitive. As a result organizations must very quickly recognize, adapt to, and take advantage of new learning before competitors do so. The most adept learners respond faster and, as a result, keep a competitive advantage while the less adept learners continue to fall behind. Second, learning and knowledge management is an asset not unlike intellectual property, capital investment, or a skilled workforce. Organizations that make the best use of their assets, including what they know, prosper while others fall behind. Third, an effective learning culture is a central element in a healthy organizational gestalt, one that can thrive in a rapidly changing environment. Learning effectiveness breeds a sense of organizational optimism about the future, the ability to deal with adversity, and a healthy willingness to take advantage of calculated risks. Organizations must go beyond being competent learners. They must excel at making good use of what they have learned. Of course, it has always been true that those organizations better able to use what they know have the opportunity to reap great rewards in productivity, speed, market penetration, and profitability. Such a statement could be said to some extent about organizations at any time in history. For example, a blacksmith learned how to make a sharper and longer lasting edge on a sword first by apprenticing to a master blacksmith, then by extending what he learned through his own trial and error. If he succeeded he had all the business he could handle until other smiths discovered or stole the secrets. Another example, the invention of the stirrup revolutionized mounted warfare and in turn combat tactics. Others learned to adopt the stirrup and adapted their battle tactics or they succumbed. Learning and knowledge management competence has always mattered. Even so, the pace of change was much slower in the past. The Bronze Age began about 4,000 BC in Iraq and continued until the

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Iron Age arose nearly 3,000 years later when iron tools first appeared in India and Greece. Similar iron tools did not emerge in Central Europe until another 2,000 years later in about 800 BC. Knowledge spread slowly and so each bit of knowledge remained valuable to its possessor longer. But the pace of technology quickens exponentially. Leonardo de Vinci was the first to seriously study the notion of human flight. His Ornithopter design in 1485 was never actually created, but it became the founding concept for the helicopter. Three hundred years later, in 1783, the first human flew in Montgolfier’s hot air balloon, after it was first tested with a sheep, a rooster, and a duck as passengers. Otto Lilienthal conducted the first glider flights just over one hundred years later in 1891, dying in a crash after over 2,500 flights. The Wright Brothers’ powered flights occurred about a decade later in 1903. This year, just over one hundred years after the Wright Brothers’ flights, the Federal Aviation Authority predicts more than 700,000,000 passengers will board a plane in the United States alone (FAA Aerospace Forecast 2006–2017 www.faa.gov/data_statistics). Human flight went from dream to reality in less than three hundred years and became a worldwide routine activity in the next century. Human flight, a much more complex technology than iron smelting and iron working, became ubiquitous in one-tenth the time. The pace continues to quicken. The Defense Advanced Research Projects Agency (DARPA) signed a contract to create the ARPAnet, the precursor to the Internet, in 1968. In 1970 the network included only five nodes: University of California in Los Angeles, Stanford, University of California in Santa Barbara, University of Utah, and the contractor responsible for establishing the network, Bolt, Beranek, and Newman (BBN). Today the Internet includes about 550 million hosts and has over two billion users. It took thirty-eight years for radio to develop a market of fifty million users. It took TV only thirteen years to do the same. The Internet did so in just four years. (http://www.ecommerce.gov/emerging.htm). Indeed, the pace continues to quicken and an organizations ability to effectively learn then manage what it learns is ever more vital. This particular technological revolution, the Internet, has had a dramatic impact on some preexisting business models. In 1994 CompuServe offered people the first opportunity to buy products using their home computer. A year later eBay.com and Amazon.com began doing business as well. By 1999, a mere five years after Compuserve offered the first e-biz portal, retail spending over the Internet reached $20 billion. Amazon also adapted the Internet to revolutionize the way

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books are sold. Jeff Bezos started the company in 1994 and Amazon sold its first book in 1995. Ten years later in 2005 it generated $8.5 billion in revenues. The next year Amazon sold more books than the Borders/Waldenbooks chains and nearly as many as the combined Barnes & Noble and B. Dalton chain. In fact, Amazon now powers and hosts the e-tail operations for Borders/Waldenbooks and some other notable book sellers. Clearly, adaptation has occurred rapidly in the book selling industry and so-called e-tailing has quickly become a major force for creating, shaping, or destroying many business models. E-tailing has evolved from an odd notion to worldwide acceptance in less than fifteen years. Such acceleration is driven by several interacting factors, factors that have profound implications and cannot easily be avoided or mitigated. First, the rate of change of technology shortens the product life cycles and disrupts or obsoletes business models. Electronic component life cycles are a good example. Thirty years ago, a typical electronic component could be purchased for perhaps ten to fifteen years after it was first introduced. Ten years ago a typical component might have been available for perhaps three to five years. Today a typical component is available for perhaps eighteen months. It is not at all uncommon in the aerospace industry to find that a selected part is obsolete before the product design has been completed or the first production parts have been ordered. Engineers must consider parts obsolescence during the initial design of the products. They must also consider anticipated performance of parts not yet available, or perhaps not yet designed, rather than actual part performance. This shortening of the part availability life arises because technology rapidly obsoletes the designs. Sometimes the component itself is made obsolete by the introduction of a newer and more effective or more powerful component. Sometimes the component is made obsolete because the manufacturing technology has evolved to enable introduction of a significantly less expensive but slightly modified component. Sometimes the component is made obsolete because the functionality has been successfully integrated with other functionalities into a single component that is more reliable, consumes less power, takes up less space, and is less expensive. This shortening of part availability life in turn enables or forces continual cycles of design changes to the products and systems that use the parts. Shorter part availability cycles are thus one significant cause of shorter product life cycles. For example, the typical product life cycle for a cell phone is currently about eighteen months.

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These shorter product life cycles in turn more often disrupt business models. This increasing rate of change of technology obsoletes business models at an ever more rapid pace. The Internet certainly gave Amazon, eBay, and others a chance to redefine retailing and forced traditional retailers to adapt quickly. The Internet has also given automobile buyers more information and with it more buying power. For example, my neighbor just bought his new Toyota online. His first visit to the local dealership was to pick up the car. He comparisonshopped for, selected, and then ordered his car online. Industry experts believe the era of the traditional new car dealership may be coming to an end. Local dealers will no longer carry an inventory of cars available for immediate delivery. Traditional sales staff will disappear to be replaced by advisors who can help a potential buyer use a kiosk in the showroom to make their purchase directly with the manufacturer. Manufacturers will be able to build-to-order rather than having to build large speculative inventories then distribute them around the country. Dealerships will no longer have investments tied up in onsite inventory and the land on which that inventory sits. As a result, prices will fall, giving buyers the ability to order exactly what they want and pay less for it. Second, the dramatic expansion of near real-time global communication makes it ever more critical for organizations to be efficient and effective managers of knowledge. During the 1800s, a drought in France may have had little effect on the price of wheat in England, but a change this morning in the probability of such a drought will be reflected in the futures prices of wheat this afternoon. Commodity traders, grain farmers, and cereal manufacturers must all be able to learn about and act quickly on changing information from around the globe. The impact of global communications is not isolated to a specific bit of knowledge like the probability of rain. Consider how Google and Wikipedia make huge volumes of knowledge available to so many people. Google is working with the University of Michigan, Harvard, and several other libraries to put millions of books online. Some have begun to plan for the day when all human knowledge (that is to say all explicit knowledge along with virtual mountains of opinions, assumptions, inferences, and interpretations such as are in this book and millions of other writings) will be available to anyone with Internet access. The global communications change is also revolutionizing traditional models for education and that in turn is revolutionizing the

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expectations of the work force of tomorrow. When the pioneers settled and expanded across America, most children were educated at home or in very small community schools. Many of our founding fathers got their education through home schooling and tutors. Later, as populations became denser, and education succumbed to bureaucracy, the public school system became largely a one-size-fits-all activity. But recently the tide has turned. Major universities are offering the opportunity to earn a fully accredited college degree online. The Massachusetts Institute of Technology (MIT) has posted online the reading lists and syllabuses for over 1,800 courses. Yale is following MIT’s example, having already posted about forty of its courses and moving rapidly to post more. This change in communications and education affects the worldview of individuals who will populate tomorrow’s organizations. Consider a personal example. My son Adam at age fourteen came to me asking if I remembered anything about nuclear fusion. I said that I may have read something about it in college physics classes but had long forgotten anything useful, and my learning was probably out of date anyway. Adam nodded and left the room only to return a couple of hours later. He told me he had just been chatting online with someone who worked on the first nuclear fusion experiments in the late 1940s. My response was, “Be careful Adam. On the Internet I can be young, handsome, and rich (I am by the way none of those.). How do you know the person was who he said he was?” Adam replied that after he asked me about fusion he went to an MIT Engineering Labs Web site, found his way into a chat room, asked his questions, and was told to go to another chat room where he might find better answers. One of the people in that chat room answered his questions and in passing commented that he had been involved in the early research. I said again that anyone can be anything in a chat room. Adam replied that while chatting with the person he used another screen to look up his name, cross-reference to several articles about him and about the early research, then asked a few specific questions. He also crosschecked some of the person’s responses to the technical questions against some reference sources. He concluded the person was indeed who he said he was. When my son goes to work for an organization he will take with him a bias that he should be able to get immediate access to anything he wants to know. That will influence his expectations of the behavior of the organization as a whole, not just some of the individuals in it. Third, global competition makes organizational learning and knowledge management competence more important than ever before. Several

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years ago, I wanted to buy a particular book, Anatomy of a Win, by Jim Berveridge. I tried the neighborhood franchise bookstores with no luck. They said the book was unavailable. The bookstore’s competitor was the franchise store on the other side of town but their story was the same. I bought something else instead and picked up a novel while I was there. About five years later I decided to search again for a copy of Anatomy of a Win. I went to a similar bookstore but got the same response. I then tried an online bookstore with no luck. A friend suggested I try abebooks.com, a global network of booksellers. My query uncovered independent booksellers in Tyler Texas, Wewoka Oklahoma, Huntsville Alabama, Oxford England, and Delhi India who would be delighted to sell me a copy of the book. I was able to compare price and book conditions, finding a copy in excellent condition for $2.50 plus $2.00 shipping. ABE also sells new books at prices comparable to my local bookstore. Today, my local big name bookstore is competing with thousands of new and used booksellers around the world for my book-buying budget. The survivors in the bookselling arena will be the organizations that learn and apply what they learn to quickly adapt in a fast-changing environment. Fourth, knowledge continues to be more and more perishable. The village blacksmith might have been able to keep his trade secrets for a lifetime. In fact the knowledge might have died with him and have to be rediscovered by someone else. But today a blacksmith must keep up with progressively better understanding of horse anatomy and its impact on shoeing techniques, new understandings about the effects of environment and terrain on horse’s hoofs, about orthopedic horseshoe designs, about more efficient and compact portable forges, about lighter and sturdier materials for making the shoes themselves, and the list goes on. All these dimensions change faster and faster and every cycle of change makes some old learning obsolete, makes some old learning suddenly very important, and creates the need to learn anew. Knowledge has become ever more essential yet ever more perishable. Organizations must understand and apply quickly the relevant knowledge. They must also be prepared to abandon it immediately when it is no longer relevant. The perspectives and examples above set the stage for several questions. Just how do organizations recognize and capture the valuable lessons they learn? How is this precious organizational knowledge retrieved when needed? Does some old and now irrelevant or disruptive knowledge still linger within the organization long after it is useful? Or, has its usefulness been overlooked? In short, just what lessons have we learned about organizational knowledge management and

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how can those lessons be applied to help leaders build organizations that learn faster and make better use of what they have learned? Author’s Background and Foundation My answers to these questions have emerged from both industry and academic experience. These parallel yet entirely different experiences continually reminded me about the strengths and weaknesses of each when trying to understand organizational behavior. First, I have enjoyed over thirty years experience, working in complex organizations in the aerospace industry as an engineer, project manager, functional manager, and general manager. From that experience, I developed a visceral understanding of how organizations behave, how they evolve, and how the members of those organizations both adapt to and shape the organizations. Second, this real-world experience has been complemented by an eclectic academic background, including a degree in electrical engineering, an MBA, a Masters in Human Organization Development (HOD), and a Ph.D. in Human and Organizational Systems (HOS). Both my HOD and HOS research focused on leadership and culture in complex organizations. The real-time intermingling of industry experiences with academic models and research gave me an ever-richer insight into how organizations acquire knowledge and how they make use of what they know. Henry Mintzberg, author of The Structuring of Organizations (Mintzberg, 1979), describes complex organizations as those that deal with “sophisticated innovation, the kind required of a space agency, an avant-garde film company, a factory manufacturing complex prototypes, or an integrated petrochemical company . . . one that is able to fuse experts drawn from different disciplines into smoothly functioning ad hoc project teams.” These are the sorts of organizations in which I have worked, organizations that perpetually encounter new information and must adapt to it, organizations that must be competent learners, and organizations that must be competent users of what they learn if they are to survive. My business and industry responsibilities required close interaction with inter- and intracompany engineering development and manufacturing teams in complex organizations. Some of these teams collaborated with other teams on major projects including the International Space Station, the Iridium satellite constellations, aircraft navigation simulators, and worldwide communications networks. As an individual contributor, I have time and again witnessed a group of truly motivated and capable people collectively behaving as a very stupid

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organization, while at other times behaving brilliantly. As a manager, I have tried, at times successfully and at times unsuccessfully, to influence the organizational work activities and systems to make them more efficient and to avoid recurring problems. As a leader, I have tried to build culture and infrastructure to foster organizational learning competence. As a member of industry-wide councils, I have witnessed the efforts of customers, peer companies, and suppliers as they struggle with similar challenges. I’ve seen the rise and fall of organizational learning competence in my own organizations, and in others. Those experiences, the successes and the failures, left their mark, having taught me a few lessons about how organizations learn and how they manage what they learn. My Ph.D. studies led me to explore the literature on knowledge management, information systems, and organizational behavior. The works of Davenport, Prusak, Leonard, and Brown were especially influential. Although much, but happily not all, of that literature tended to compartmentalize different organizational learning concepts and constructs, my real-life work experiences continually drove me to understand that real world challenges could best be understood and addressed by understanding the interactions among those concepts and constructs. Individuals with cross-discipline insights proved time and again to be far more influential and powerful than those that remained in a silo perspective and organizations that developed and deployed holistic strategies succeeded far more often than those that deployed one-dimensional strategies. This book, then, offers an organizational knowledge management model rooted in a cross-discipline perspective, a perspective that some others have argued for as well. For example, Thomas Davenport (1997) argued for the “holistic management of information” giving consideration to strategy, politics, culture, and processes as well as the information architectures. Davenport began working in the information technology (IT) field and extended his interests to broader organizational knowledge issues, presumably because he recognized the importance of organization behavioral and environmental influences on information management competence. This book builds on Davenport’s argument with a framework for understanding the cultural dynamics, conscious and unconscious, in managing knowledge within an organization. The organizational knowledge model described herein is founded on a cultural perspective and then ties in the IT dimensions as appropriate, a trajectory opposite the one from which Davenport started but similar in destination.

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The model proposed here is deceptively simple yet very challenging to successfully deploy. Several years ago, while having an annual physical exam I asked my doctor for advice about how best to lose the twenty pounds I had gained over the past year. The doctor was a quiet, efficient, and pragmatic sort of fellow and his advice fit his personality. The doctor said, “It’s simple. Eat better. Eat less. Do more.” He must have noticed the crestfallen look on my face because he then said with a bit of a sneer, “If you are looking for a trick, avoid ‘whites’—white bread, pasta, potatoes, sugars, etc.—that your body more quickly breaks down and stores as fat. But, you will have more sustained success if you just eat better, eat less, and do more.” The doctor’s advice was simple but not so easy for a person like me, one who is addicted to carbohydrates and idleness, to implement. The organizational knowledge management model described here is similarly simple in concept but not so easy for an organization to implement. Central Themes My themes are simple although their application is not easy. The foundational assumptions are: ●

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Organizational learning and knowledge sharing is organic. It occurs whether or not it is managed. Individuals bring to an organization what they know, learn from their experiences, and share their knowledge with one another. The organization’s social norms and collective worldview are the manifestation of collective learning from past organizational experiences, manifestations that in effect impose that past learning on current employees. Work routines and procedures also capture and make available knowledge that was acquired in the past. All these activities are forms of organizational knowledge management that occur in every organization. Unmanaged organizational knowledge may be constructive but is more often benign and too often destructive. Individuals may opt to not share what they know, instead using the knowledge as a form of power base to gain personal advantage. The organization’s social norms may be built on beliefs and experiences that are no longer relevant to the environment in which the organization is currently competing. Work routines and procedures may be out of date or even incorrect. Thus, knowledge may be misused or underutilized. Worse it may prompt destructive or harmful organizational behavior.

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Organizational knowledge practices can be understood and managed. Leaders can influence how well the organization learns and how well it applies what it learns. Leaders can guide their organizations along an evolutionary maturity path to greater knowledge management competence.

This book is about how knowledge, once it comes to exist, is captured, saved, and deployed within an organization. It describes a model for understanding where knowledge resides within an organization, how it is stored, how it is retrieved, and most importantly how leaders can help their organizations more effectively use what they know. Understanding what this book is not about may be as useful as understanding what it is about. This is not a book about knowledge acquisition. Organizations acquire knowledge by drawing from outside sources when they are first formed. They acquire knowledge from experience as they interact with their environment. They learn by observation of others in the business environment. They learn by integrating other firms or individuals knowledge into the organization. They also learn by creating new knowledge through purposeful research. Knowledge acquisition is a complex and situation-specific endeavor. The recent interest in innovation is further expanding our understanding of how organizations acquire knowledge. This book focuses on what organizations do with that knowledge once it has been acquired, that is, where it is retained and how it is distributed. Nor is this a book about the quality or relative value of some piece of knowledge versus another. The value of a particular piece of knowledge is a function of context, the problems of interest at the time, and even coincidence or serendipity. Its value, like beauty, is in the eye of the beholder. The material herein focuses on how information is distorted but not on its intrinsic value. This is also not a book about the nature of knowledge itself. Although I offer a few definitions to set a foundation for the material in the book, I do not attempt to fully describe what is or is not knowledge. Approaches to Knowledge Management The field of organizational knowledge management is diverse and accommodates several perspectives that may be roughly grouped into three broad areas: the technology perspective, the organizational structure perspective, and the environmental perspective.

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The technology perspective asserts that IT can be used to enhance knowledge storage and knowledge sharing. Large storage capacities, data base management tools, and search engines enable organizations to store, search, and retrieve more information than ever imagined possible. Communications networks enable organizations to share vast amounts of information across physical distances thus making knowledge available to more people faster than ever before. Advocates assert that today’s technological advances offer solutions that enable an organization to capture, retain, distribute, and extend what it knows. The technology perspective rests on a foundation of a few key assumptions. First, it assumes important organizational information can be codified in storable form without significantly impairing its value. One might agree that knowledge about product reliability is important and may be codified, but some certainly would also argue that knowledge about customer satisfaction cannot be reduced to statistical data without a significant loss of richness and valuable insight. Second, it assumes the overall challenges involve the capture, storage, and retrieval of knowledge. In short, organizational knowledge management is seen as a data transaction problem. The technology perspective does not address such challenges as identifying knowledge or codifying it into storable form without loss of valuable content. Nor does it address the social and political factors that influence how the stored data is interpreted or applied. Third, and this is a point that many technology advocates would refute, the knowledge itself must be adapted, even perhaps severely distorted, to fit the knowledge management tools available. The context surrounding a bit of knowledge may be more important than the knowledge itself but it will be jettisoned if it cannot be readily captured within the constraints of the available tools. These assumptions, and their validity, will be addressed later during the discussion about Archives. The organizational structure perspective asserts the bureaucracy must accommodate, even encourage, the flow of knowledge from where it resides to where it is needed. Structure should be compatible with the nature of the work. The conduits for knowledge flow are viewed to be the social interactions and administrative practices by which work is accomplished. For example, the organizational structure advocates may assert that project-oriented activity such as consulting, medical, product development, or construction may benefit from a matrix organization structure that relies on the ad hoc transfer of talent and experience from project to project as the means of accomplishing knowledge transfer while a manufacturing

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organization may benefit from a more formal and rigorously defined functional structure wherein the functional groups develop and manage the knowledge necessary to accomplish their particular work activity. The structural advocates see the organizational knowledge challenge as one involving the removal of structural obstacles and installation of structural facilitators to what would otherwise be the natural flow of organizational knowledge from where it resides to where it is needed. The environmental perspective is founded on the notion that human behavior and organizational social norms is the crucible that determines how effectively an organization manages what it knows. One culture may encourage team problem solving and the open sharing of knowledge while a different culture may encourage the notion that knowledge is a source of power and that it should not be readily shared with others. The environmental perspective sees the organizational knowledge challenge as one of social facilitation rather than structural facilitation. This book argues that all three perspectives have merit; all three can be useful in understanding some particular dimensions of organizational knowledge management. However, the perspectives are not independent in the real world of organizational life. Indeed, it is necessary to understand all three if one hopes to understand organizational knowledge management behavior. A Few Definitions to Ease Understanding The organizational knowledge management literature is rife with terminology conflicts and contradictions. There is very little agreement about even the most fundamental terms. Knowledge, we all have some and most of us continually seek more, yet a mutually agreed definition is elusive. Davenport (Davenport and Prusak 1998) defines knowledge as “a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information.” He asserts, “Knowledge is information combined with experience, context, interpretation, and reflection.” Leonard and Sensiper (1998) have a different perspective choosing to define knowledge as a subset of information. He argues that knowledge is “information that is relevant, actionable, and based at least partially on experience.” The authors of the aerospace industry knowledge diffusion study mentioned earlier contend “Data are what come directly from a sensor(s), reporting on the measured level of some variable. Information is ‘data’

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that have been organized or given structure, that is, placed in context and thus endowed with meaning. . . . Knowledge goes further; it allows the making of predictions, causal associations, or prescriptive decision about what to do” (Pinelli, 1997). Much like pornography, we cannot agree on a definition, but we all know it when we see it, or perhaps we just think we do. Find below a few definitions that I have culled from this field of disagreement. Knowledge Knowledge is that which is known or thought-to-be known. We can possess and act on false as well as true knowledge. Knowledge may be archived and available yet not currently known by a particular individual. Knowledge may lie in the mind of an individual, in the collective minds of a group of individuals, in the cultural norms of a group, or embedded in the processes and methods used to accomplish a task. Knowledge Management As one would expect, since there is no consensus on the definition of knowledge, there is also no broadly shared definition of knowledge management. Here knowledge management means the conscious or unconscious approach(s) and techniques employed by an individual or an organization for the management of what the individual or organization knows. Knowledge management includes the generation, capture, storage, retrieval, and adaptation of knowledge. Quintas et al. (2004) define it as “the process of continually managing knowledge of all kinds to meet existing and emerging needs, to identify and exploit existing and acquired knowledge assets and to develop new opportunity.” For some, knowledge management embraces notions of fostering the creation of new knowledge, the current rage to discuss innovation, for example, as well as storing and applying knowledge previously learned. Most business leaders however will tell you they see the two as distinctly different organizational challenges. Leaders may talk about fostering innovation, sparking creativity, and building an innovative organization. Examples might include an activity as high tech as development of the touch screen interface on the new iPhone or as mundane as an insight about how to streamline a particular administrative business process. Innovation in particular has recently reemerged as a popular theme for business writers, consultants, and industry leaders. On the other hand, leaders may talk about capturing

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lessons learned, avoiding past mistakes, or sharing what they already know. They are talking not about the creation of new knowledge or insights but the retrieval and application of what has already been learned. These conversations usually arise after some particularly galling fiasco that they feel could or should have been avoided if the organization or individuals had applied such past learning. Leaders rarely make a connection between lessons learned management and innovation management because they see them as two distinct organizational activities. This book will not deal with innovation management, a subject that has been explored and described often by others. Instead, this book will deal with how organizations handle with what they already know, their lessons learned. In fact, at one point this book was to be titled “A Few Lessons Learned about Lessons Learned.” Facts Most writers on the subject think of facts as a category, or subset, of knowledge. The dictionary would tell us that a fact is a “piece of information presented as having objective reality (Merriam-Webster’s Collegiate Dictionary, Eleventh Edition, 2003). Experiences and observations deceive. I may know from the experience of looking in the mirror or compared to the other males in my workgroup that I am quite handsome, but others may disagree. I may also know that the oven temperature is 320°F but someone else looking at the gauge may say that I transposed the numbers and the oven temperature is actually 230°F. So, let’s agree for now that a fact is independently verifiable. Examples include; 2007 revenues were $200,000,000, the current temperature on the front porch is 83°F, or eight people attended the staff meeting today. Each can be independently verified or refuted by a third party. Information Information is subject to wide disagreement. Some consider it a subset of knowledge while others consider it a superset of knowledge. Others argue that information is any knowledge acquired through some form of communication—as opposed to being divinely inspired I suppose. We’ll make do with a few simple examples of what information will mean when reading this book. Examples of information may be; the President’s Daily Threat Assessment, the “Complete Idiot’s Guide to Microsoft Office,” or the maintenance records for

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the robotic arm at production line station #3. In each example, the information may include some facts, some interpretation of those facts, and some assertions or inferences derived from those facts. It may also include assertions or inferences not founded on any of the facts included in the information. In theory, someone should be able to independently confirm or affirm the facts and the logic leading to the assertions. But, the assertions themselves may be subject to different interpretations and perspectives. Information may be subjective while facts may not. Skill There is broad agreement in the literature about the definition of a skill. There is even disagreement about whether skills are a form of knowledge. Examples of skills include riding a bicycle, shoeing a horse, making an 18-foot jump shot, or calibrating the robotic arm at production line station #3. One may read about the underlying physics or engineering principles. One may be told about the physical actions required. One may even witness others accomplishing the feats. But one must actually perform the tasks time and again before they can hope to become skilled at them. The relevant knowledge may not all be fully understood, some of it may even be subconscious muscle memory, for example, but we will assert for the purposes of this book that skills are indeed a form of knowledge. Explicit Knowledge Explicit knowledge, as opposed to tacit knowledge described below, is relatively easy to identify, store, and retrieve. Once we learn the temperature at which water freezes, or the number of tickets sold for a sporting event, or the clean room requirements for an integrated circuit manufacturing process that learning can be documented, retrieved, and applied as appropriate. These explicit facts or pieces of information are generally accepted as truth because they can usually be readily verified. Of course, even explicit knowledge can be misunderstood or misapplied. After all, most of us know that water freezes at 0°C, but we often forget that is true only at sea level barometric pressure. Water exists in the ocean depths at well below 0°C where the pressure is greater than at sea level and freezes well above 0°C in the Andes Mountains where the pressure is lower than at sea level. Even the weather-induced changes when a low-pressure system moves through

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a region can shift the boiling point of water by a degree or two. So, explicit knowledge, like water freezing at 0°C may be relatively easy to identify, store, and retrieve and is generally quite useful, but such explicit knowledge is only useful if applied in appropriate context and may be quite misleading if applied far enough outside that context. Tacit Knowledge Brown and Duguid (1998) characterize knowledge as either “knowwhat” or “know-how.” They view the former as explicit knowledge that may be readily retained and shared with others, while the latter is the less tangible or tacit understanding about how to apply the explicit knowledge effectively. The explicit circulates freely and is readily applied, while the tacit is usually embedded in work practices and the minds of individuals. Tacit knowledge is relatively much harder to recognize, capture, or apply. Polanyi (1967), who coined the phrase “tacit knowing,” asserted “We can know more than we can tell.” For example, “We recognize the moods of the human face, without being able to tell, except quite vaguely, by what signs we know it.” Leonard and Sensiper (1998) tell us that tacit knowledge is “semiconscious and unconscious knowledge held in peoples’ heads and bodies.” Although explicit knowledge can be readily handled with information technologies, tacit knowledge is often much too subtle to be handled with those technologies. Indeed tacit knowledge must nearly always be perverted and distorted in order to make it compatible with the information technologies. Although tacit knowledge is the most difficult to recognize and handle, it is often the tacit knowledge that leads to significant breakthroughs and is of more value to the organization. In fact, the American Productivity and Quality Center asserts that 80 percent of our individual and organizational knowledge is tacit versus explicit (APQC Teleconference, 2002). So, 80 percent of what we know is not compatible with, and is often mishandled by, our IT knowledge management tools. As a side note, we will see later that explicit knowledge is not without some vulnerability as well. Lessons Learned “Personally I’m always willing to learn, although I don’t always like being taught,” said Winston Churchill. In my experience the term “knowledge management” is very rarely used among aerospace

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organization leaders and, although my sample size is smaller, I believe the same is true of leaders in other industries. But “lessons learned,” now there’s a phrase that gets used with a great deal of emotion and shared understanding. Just like Junkens and Platt at TI and Intel, leaders often bemoan the fact that their organization cannot seem to remember or share what it has learned. In this book I may occasionally use the term “lessons learned” rather than “knowledge management” because it resonates so well with the practitioner, reminding us just what it is that organizations struggle with rather than what it is researchers would like to build a field of study around. Organization An organization is for our purposes any systemically arranged group of individuals working toward shared objectives. The individuals may have many objectives, some shared and some not shared, but if they have arranged themselves so as to pursue one or more common objectives, then they are an organization. An organization may be large or small and collocated or distributed. An organization may be a small group of people operating an independent neighborhood drycleaners. It may be hundreds of people working within a municipal government. It may be a thousand or more people managing and operating a factory that belongs to a larger corporation. It may be a large number of people working as individuals and small teams scattered across the country to maintain equipment such as office copy machines, or medical equipment. It may be a hundred thousand member conglomerate with operations around the world. It may even be members of different conglomerates working together in an industry consortium. Size and collocation do not define organization, systematic arrangement intended to accomplish shared objectives does. How This Book Is Organized This book is best read from front to back because the early chapters lay a foundation for what follows. Chapters one and two lay a foundation for understanding the proposed organization knowledge management model. Chapter one has introduced the subject and made the case for why organizational knowledge management competence is important. It has also provided a foundation of terminology that will help the reader better understand the material that follows.

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Chapter two briefly describes how individual memory works and relates it to how organizational memory works. It lays the groundwork for understanding how organizations deal with what they know. It describes the manner in which individuals retain, recall, and apply what they know in order to provide a frame of reference for how groups of people working together retain, recall, and apply what they know. It then introduces the four fundamental constructs of the organization knowledge management model, describing the means by which organizations cope with learning. Those four constructs, Culture, Old Pros, Archives, and Process are defined with examples, introducing them within an organizational context. The chapter defines and describes each construct, cites real-world examples, and explains their attributes. It describes how all organizations have embedded within them the first two constructs but not always the latter two. It describes how organizations may or may not consciously acknowledge and manage these constructs. It closes with a summary of the key points of the chapter and sets the stage for the next chapter. Chapters three through six describe the essential constructs of the model in depth. Their relative strengths and weaknesses are described. Each chapter also offers insights as to how senior leadership must shape the environment and manage the constructs to enable effective learning. The four constructs are described independently, even though they are very much interactive and interdependent, to promote a clear understanding of the fundamental nature of each of them. Chapter seven integrates those parts into a whole by describing the interplay between the four constructs. It describes how the four are mutually interdependent, either reinforcing or inhibiting one another. This chapter introduces the complexity and interaction that was stripped away in chapters three through six. Chapter eight offers vignettes on specific knowledge management topics, topics that may help leaders understand how to drive positive change in their organizations. For example, it explains how organizations typically evolve their learning competence and describes how senior leadership can facilitate progress along that evolutionary path. The trek from Stage I—Organizations Forming, to Stage II—The Way It Is Around Here, to Stage III—If Only We Could, to Stage IV—We Are Making Progress, to Stage V—We Know What We Know and Use It Effectively is described and supplemented with advice to leaders about how to accelerate the journey. Other topics include the role of IT, cautions about the

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relationship between structure and knowledge management competence, knowledge sharing outside the organization, and how to sustain progress through appropriate monitoring and knowledge management metrics. The closing summary offers a brief recap and suggests areas for further study. References APQC Member Teleconference: Six Sigma and KM—Exploring the potential of two powerful disciplines. Presented in 2007. Accessed via Web site (www.apqc.org) July 24, 2007. APQC, previously known as the American Productivity & Quality Center, is a member-based nonprofit worldwide organization with about 500 corporate members. It conducts research, develops benchmarking data, and disseminates learning about best practices in the areas of knowledge management and process improvement. These periodic member teleconferences support that agenda. Brown, J.S., and P. Duguid. (1998). Organizing knowledge. California Management Review 3: 90–111. This paper was written at a time when some argued that the new information economy would sweep away many traditional organizations such as the press, media, universities, and even governments and nations. The authors counter that many such organizations will adapt and propose an organizational architecture for organizational knowledge management. Davenport, T.H. (1997). Information ecology. New York, Oxford University Press. Davenport offers a holistic view of the information and knowledge environment, explaining why technology is insufficient to address the broader needs of dynamic organizations in today’s environment. Davenport, T.H., D.W. DeLong et al. (1998). Successful knowledge management projects. Sloan Management Review 39(2): 43–57. The authors describe several successful knowledge management initiatives then summarize a set of factors influencing success including; linkage to economic performance or industry value, technological (IT) and organizational (roles and groups responsible for knowledge management) infrastructure, standard yet flexible knowledge structures, and a knowledge-friendly culture. Davenport, T.H., and L. Prusak. (1998). Working knowledge: How organizations manage what they know. Boston, Harvard Business School Press. This book is among the most practical of the academic books on the subject. It offers real insight to real-world issues and opportunities with respect to improving organizational knowledge management. FAA Aerospace Forecast, 2006–2017 (2006). www.faa.gov/data_statistics.

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This recurring forecast provides insights to trends across the aviation industry. Leonard, D., and S. Sensiper. (1998). The role of tacit knowledge in group innovation. California Management Review 40(3) (Spring): 112–131. Innovation, the source of sustained advantage for most companies, depends upon the individual and collective expertise of employees. Some of this expertise is captured and codified in software, hardware, and processes. Yet tacit knowledge also underlies many competitive capabilities—a fact driven home to some companies in the wake of aggressive downsizing, when undervalued knowledge walked out the door. Mailloux, E.N. (1989). Engineering information systems. Annual review of information science and technology. M.E. Williams, ed. Amsterdam, The Netherlands, Elsevier Science: 239–266. Merriam-Webster’s Collegiate Dictionary (2003). Eleventh Edition, MerriamWebster, Incorporated, Springfield Massachusetts. Mintzberg, H. (1979). The structuring of organizations. Englewood Cliffs, NJ, Prentice-Hall. This is an excellent source for understanding the practical dimensions of organization structure, what should drive it, and how to optimize it for the specific nature of the work the organization is trying to accomplish. O’Dell, C., and C.J. Grayson. (1998a). If only we knew what we know: identification and transfer of internal best practices. California management Review 40 (3) (Spring): 154–173. According to O’Dell and Grayson, Junkins and Platt recognized early what many other managers are just beginning to realize: that inside their own organizations lies, unknown and untapped, a vast treasure house of knowledge, know-how, and best practices. If tapped, this information could drop millions to the bottom line and yield huge gains in speed, customer satisfaction, and organizational competence. Pinelli, T.E., R.O. Barclay et al. (1997). Knowledge diffusion in the U.S aerospace industry. London, Ablex Publishing. This two-volume book presents the results of a ten-year study to examine knowledge diffusion as a source of innovation across the aerospace industry. The study was particularly interested in understanding how government funded research and development results found their way into the industrial complex. Polanyi, M. (1967). The tacit dimension. New York, Doubleday & Company. Polanyi, a scientist turned philosopher, wrote this small book of less than 100 pages in a 4 inches by 7 inches that is often cited as the first published usage of the notion of tacit knowing. Polanyi described tacit knowing as knowing more than one is capable of describing. For example, we can recognize a person’s mood by looking at their face but can describe only vaguely what we see that gives us that insight. Prusak, L. (1997). Knowledge in organizations. Boston, ButterworthHeinemann.

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Prusak argues that leaders have been quick to acknowledge the importance of knowledge to organizational success but lack completely any notion of how to manage that capability. He proceeds to describe techniques and approaches that have been beneficial. Quintas, P.R., K. Ruikar, C. Anumba, A. Al-Ghassani, C. Egbu, E. Kurul, and V.J. Hutchinson. (2004). Techniques and technologies for knowledge management in UK construction. Proceedings of the 1st International Conference on Construction Project Management. Toronto, Canada. Scarborough, H., and J. Swan. (1999). Case studies in knowledge management. London, Institute of Personnel Development. This review of several case studies offers insights into practical issues and challenges when deploying knowledge management projects. Zack, M.H. (1999). Developing a knowledge strategy. California Management Review 4(3): 125–145. Zack asserts that while most organizations focus on the management of explicit knowledge, a smaller number of organizations are finding relatively greater success when they take actions that foster the use of tacit knowledge.

Chapter 2

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ur ability to think, our capacity to use what we know, has been subject to question for as long as we have been thinking. Chapter two explores some of the elements of individual and organizational memory and thought, beginning with a brief description of how individual memory operates and how individuals handle, or mishandle, what they know. Memory is after all the acquisition, storage, and retrieval of knowledge. This sets the stage for an analogous discussion of how organizations remember and how they deal with what they know. Individual memory and thought certainly operates and behaves different than does an organization’s collective memory. Even so there is benefit to understanding the way individuals store and use what they know as a prelude to understanding how organizations accomplish the same feats. The first benefit is that individuals operate within the organization and each of their brains contains a massive amount of knowledge, much of it is what the organization needs to know. So, it is useful to be reminded of just how the individual mind stores and recalls knowledge. The second benefit is that organizational memory can be described in terms of how it is like or different from individual memory, giving us a useful if not entirely accurate analogy. So a reminder about individual memory sets a useful reference point for the description of organizational memory. Individual Memory The core element of memory is the stored pattern of neuron, or nerve cell, interconnections in our brain. Each point where one neuron connects with another is called a synapse. A particular memory is

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merely a specific pattern of those synaptic interconnections. A human brain contains about one quadrillion (1015) such interconnections. As a point of reference, a well-equipped personal computer contains about 100 billion (100 gigabytes) bytes of memory. Although an individual brain synapse and a computer byte are hardly equivalent, one might stretch the analogy for illustrative purposes to assert it would take about 10,000 well-equipped personal computers to approach the memory capacity, but certainly not the reasoning capacity, of a single human brain. An individual’s brain, dominantly made up of this collection of neurons and synaptic interconnections, includes several segments and processes each specializing in a unique activity. However, these segments and processes must often work together to deal with a particular memory task at hand. For example, snow skiing draws on distinctly different memory activity than does memorizing a shopping list. Yet, setting at the computer to compose a shopping list requires muscle memory to operate the keyboard, near-term memory to recall what is missing from the pantry, and perhaps longer-term memory to recall the ingredients that go into that special barbecue sauce we made last summer. The act of skiing relies on muscle memory but also draws on longer-term memory to recall what sort of terrain lies around the turn or over the rise as well as short-term memory to recall what the instructor said this morning about traversing moguls more smoothly, a skill that may over time become part of muscle memory. Researchers do not yet agree about the number, structure, relationship, or processes of these different memory systems, although they continue to make progress toward a more complete understanding. Steven Pinker (1997) offers one provocative and entertaining compilation of theories about the mind in the aptly titled How the Mind Works. The curious reader may find it interesting. Find below some examples, not necessarily from Pinker’s book, of the distinctions and models being debated. There is general agreement about the major physical segments of the brain and the types of memory or knowledge they contain and influence. A specialized part of the frontal cortex captures and very briefly stores, for fractions of a second, the information you are reading on this page. The frontal cortex keeps the information ready for immediate use, helping you recall what the preceding sentence said and what this chapter is about. Another part of the brain, the cerebellum, contains the habit and motor skills we have learned, skills such as controlled eye movement, turning the page, or repositioning the head relative to the location of the words on the page so that we

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see and read clearly. The hippocampus and adjacent areas are where our long-term memories reside. This is where we keep information about that great novel we read last summer or something we read a month ago in a National Geographic article about why people remember and why they forget. The amygdale is the part of the brain where our emotional recollections are stored. Examples include our recollection of that first day at Army basic training, the smells and sounds of a childhood trip to the circus, or memories that trigger our sense of déjà vu. This part of the brain also controls our fight-or-flight responses. These four parts of the brain control our so-called working memory, supporting our routine activities if you will. The overall process for handling knowledge is straightforward: information is received, encoded, stored, retrieved, and perhaps too often forgotten. The frontal cortex handles the short-term reception of new information. The hippocampus, cerebellum, and amygdale manage the encoding and longer-term storage, depending on the nature of the memory activity. The bit of information or recollection remains in that part of the brain where it was processed, waiting to be retrieved. Another useful construct is to think of a memory task as either automatic or effortful depending on how hard one has to work to remember. A person may automatically remember the score of last night’s football game. On the other hand, she may have to work a bit harder to recall the birthdates of her nephews and nieces, especially if she has several. One may have to work harder yet to recall all the relevant equations for a college physics final exam. Just where to draw the line between automatic and effortful memory is quite subjective, and hotly debated in some circles. Even so, the notion of relative effort to recall information can be useful in understanding how individuals and organizations handle what they know and why some knowledge seems easier to manage. Memory is also often thought of in terms of the learning activity rather than the remembering activity. Three commonly referred to types of learning memory are motor memory, procedural memory, and declarative memory. Motor memory involves technique and “feel.” My son and I recently began learning to sail. He and I both read a fundamentals book and attended a series of classroom sessions where we learned terminology, safety regulations, and theory. Then we began taking the boat out with an instructor along to assist us. That’s when we began to learn how to spot a wind change by looking at subtle differences on the surface of the water, how to adjust the sail tension to get optimum

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speed for the conditions, how to judge the relative speed of nearby boats, and a host of other things that could not be captured in a book or a lecture but that we had to understand if we were going to be successful sailors. We are still working to develop the motor memory that allows seasoned sailors to fine-tune their boat to the environment without consciously thinking about it. Athletes often talk about muscle memory, another form of motor memory, in which the body learns to operate in a specific manner when reacting to a pitch, diving to block an attempted goal, or making a three-point shot. The knowledge we have stored as motor memory is subtle, almost indescribable, yet it is often invaluable. We will describe later how organizations also employ a form of motor memory. Procedural memory is sometimes considered a variation of motor memory. Procedural memory involves how to do something but may or may not involve muscle or motor memory. For example, knowing how to ride a bicycle involves motor memory related to starting off, balance, leaning into turns, and so on. On the other hand, adjusting the gear assembly or aligning the wheels by adjusting the spokes involves procedural memory about the sequence of activities, the tools required, and the technique for each task. Procedural learning and motor learning are often intertwined and inseparable. For example, someone may be able to follow a carefully written procedure to disassemble, clean, reassemble, and tune the bicycle gears, but an experienced mechanic will notice and correct subtle problems that the novice would never detect. The experienced mechanic makes use of both procedural and motor memory just as the experienced machine operator or design engineer makes use of both procedural and motor memory. We will see that organizations as a whole do so as well. Declarative memory is a term typically used in reference to personal and factual memory. For example, a person may recall vividly the day they were married and they need exert no specific effort to capture or retain that recollection. It seems to occur without effort. They may recall the five items they need to purchase at the grocery store without having to write it down. They may remember a physics problem from last week’s homework assignment, and more important how to solve it, that now appears on the exam. This is the form of memory that we most often think of when the topic arises. It is what most of us would generally describe as memory. Organizations certainly exercise this sort of memory. The three forms of learning activity are not always so easy to separate. One may first learn the combination to their locker at the gym as a declarative memory act. One may, after opening the lock several

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times, retain the combination as a procedural memory because they can lift the lock and begin to make the appropriate movements to cause it to open. The numbers do not come to the conscious mind but the mechanical sequence of spins and pauses do. Motor memory may later come into play if one opens the lock frequently enough that they are able to do so without thinking about it at all. Their body just knows what to do when it grasps the lock and it does it. No conscious recall takes place at all. The nature of the memory being used evolves as the student becomes more proficient at the task. Our individual memory capability is not stable over time. Our overall ability to remember improves as we grow up, then declines after middle age. A one-year old may have the capacity to recall only a very small fraction of what it experiences and even a nine-year old may be able to recall only about 15 percent of his experiences. A young adult may recall 75 percent or more while an eighty-year-old may recall less than half of what she experiences. This phenomenon occurs because early on our brains have relatively few synapses. As we grow, and our brain develops, the number of synapses increase and memory improves. Later in life our body finds it more difficult to build new connections between neurons and some established connections deteriorate, causing our ability to make new memories more difficult and destroying or distorting old memories. Organizational memory does not improve then decline as a function of age because there is no physical counterpart to the synapses in the individual’s brain. However, we will see that an organization’s memory can improve or deteriorate depending on other factors. Keep in mind that an individual’s memory is malleable. People actually adjust what they remember to make it align with what they currently believe. We actually add false recollections to our memory and delete some existing recollections in order to align our memories with our current beliefs as our experiences and beliefs change over time. For example, my sister and I recall some events from our childhood in entirely different ways, and our mother has absolutely no recollection of some of those events. Neither my sister nor I are lying or consciously distorting the truth—at least in these instances. Instead, what she originally remembered was influenced by what mattered to her at the time of the event, her emotional state, and so on. What she now remembers is the result of her adaptation of that original memory to be consistent with her perceptions of herself and her place in the world. I on the other hand started from a different initial frame of reference and thus a different initial memory that was later modified by my own experiences and changing worldview. Our mother did

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not at the time register the events as having any particular importance and so they were not strongly imprinted in her memory. We each participated in the same events. We each interpreted the events through our own unique context. We each stored away different memories. Then we each adapted those memories to fit our uniquely evolving worldviews as time passed. Thus, we ended up with entirely different memories that we each “know” to be true. Organizational memories are also malleable. The individuals operating within the organization retain their version and interpretation of organizational events, versions, and interpretations that evolve as time passes. We will also see that other organizational memory repositories are susceptible to a similar phenomenon. The “truth” changes in organizational memories just as it does in individual memories. The past decade has opened the doors to a great deal more understanding and appreciation for the mechanics of how the mind captures, stores, and retrieves information and knowledge. We are faced with some disturbing implications as we learn more about how the mind shapes and modifies what it remembers, forcing us to appreciate just how fallible our memories can be. Consider the implications for our legal system and its dependence on eyewitness testimony or personal recall of past events and conversations. If two people testify truthfully—that is to say that from their personal recollection their testimony is absolutely true—about what they recall, but their testimonies differ, did one of them perjure themselves? Which one? If only one person testifies, then how do we know that their recollection is “truth”? If two people testify to the same “truth,” does that make it true or merely a coincidently shared belief? These hazards exist for individuals and for organizations. Keep these attributes of individual memory in mind. We will describe later how individuals act as a repository and manipulator of organizational knowledge. We will also describe how groups of people and organizations as a whole display similar attributes that influence overall organizational memory. Individual Thought and Knowledge This brief section is inserted as a reminder about some of the human frailties when it comes to dealing with our memories, that is to say how we think when we use what we know. Diane Halpern’s book, Thought and Knowledge: An Introduction to Critical Thinking (Halpern, 1996), is a fine source for those interested in learning more about the topic. What are offered below are merely a few examples of some

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of the recurring fallacies of human thinking and brief explanations of why the fallacies may recur. The reader should come away with a refreshed humility about his or her own clarity of thinking, a greater tolerance for the fallacies of others, and a greater appreciation for the complications that beset organizational knowledge management. Let us begin with self-perceptions. Steven Kerr, at one time the Chief Learning Officer of General Electric and a direct report to Jack Welch, asserted, “80% of us typically believe we are in the upper 30% of performers” (Kerr, 1994). He presented research results that when it comes to interpersonal skills, 100 percent of those polled believed they were above average, 60 percent believed they were in the top 10 percent, and 25 percent believed they were in the top 1 percent. When it comes to leadership, 70 percent believed they were in the top 25 percent and 2 percent believed they were below average. With respect to engineers who should understand statistical and mathematical logic better than most, 100 percent believed the were above average and 86 percent believed they were in the top 25 percent. This sort of nonrational thinking demonstrates that individuals are often cognitively dissonant. That is, they are quite capable of holding two contradictory opinions at the same time. In this instance, most people, and certainly one would hope all the engineers, would assert that despite what Garrison Keillor might say to the contrary, it is not possible for everyone to be above average. Yet, at least collectively, we insist on believing just that. This behavior, called “egocentric bias” by the psychologists, occurs when an individual thinks about the world from his own point of view too much. This belief that one’s own ability or attribute is above average may occur because the amount of information available for the judgment is greater for oneself than others, not because one is motivated to think better about oneself than others. In effect they have information about their own rationale but lack information about other people’s rationale. Consider another example of frequent yet flawed thinking from Halpern’s book. She asserts that most people are barely aware of the thinking processes that drive how they address complex issues. She offers this experiment about thinking as an example. “Researchers (Wilson & Nesbitt, 1978) asked consumers in a large bargain store to select which of four pairs of nylon pantyhose they preferred. The stockings were hung on a rack above the researcher’s table. The consumers examined the weave, the heel, and the toe. Very few had difficulty making a choice. The stocking in the left-most position was preferred by 12% of the consumers; the one to its right by 17%; the

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next one to the right 31%; and the right-most stocking by 40%. This indicates that there were clear preferences among the shoppers. This is especially interesting in light of the fact the four stockings were identical. Position alone accounted for the consumer preferences, yet none of the consumers indicated that position influenced his or her decision. People are simply not aware of the variables that affect how they think.” Recall an earlier comment about memory being malleable. This occurs because our personal beliefs are not easily changed. In an effort to cling to our preconceived notions we will actually change our memory of what we saw and heard to align it with our beliefs. This is rarely a conscious act but instead a subconscious tweaking that we have no idea is occurring. We may as time passes learn and experience things that change our biases. When that occurs, we subconsciously “adjust” our recollections to better align with our current opinions. Let us examine an example of self-deceptive thinking taken from Dan Ariely’s recent book Predictably Irrational (Ariely, 2008). “As early as 1993, J.B. Moseley, an orthopedic surgeon, had increasing doubts about the use of arthroscopic surgery for a particular arthritic affliction of the knee. Did the procedure really work? Recruiting 180 patients with osteoarthritis from the veteran’s hospital in Houston, Texas, Dr. Moseley and his colleagues divided them into three groups.” One group got the standard treatment described as: anesthetic to numb the knee, three incisions to gain access to the bone and tissue, scopes inserted to inspect the knee for damage and determine a plan for making repairs, cartilage removed as necessary, correction of softtissue problems as necessary, and ten liters of saline washed through the knee to clean out any debris or residue. The second group got anesthesia, three incisions, scopes inserted, and ten liters of saline, but no cartilage was removed. This group experienced every step in the process except that cartilage was not removed and tissue was not repaired. They experienced surgery but received no corrective changes of any sort. The third group experienced all the same steps, including the incisions but the scopes were not inserted into the knee and thus no corrective actions were taken. The first group received the standard surgery. The second group received the surgery but no repairs. The third group thought they had received surgery but did not. For two years following the surgeries, all three groups were monitored. They were tested for a lessening of their pain, and for the amount of time it took them to walk and climb stairs. The groups

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that had the full surgery were delighted, and said they would recommend the surgery to their families and friends. But the placebo group also got relief from pain and improvement in walking. In fact, they recovered at the same rate and reported a level of relief that was the same as those who had the actual operation. Expectations influence beliefs. The point of these few examples is to remind us that individual memory and thinking is slippery business. We are prone to misremember. We are prone to modify what we learn and what we remember to fit our current beliefs. We are prone to disregard facts or create facts out of whole cloth in an effort to support our biases. Nor are we consistently logical in dealing with the facts we embrace. Individual knowledge is indeed a slippery subject. Now let us move on to the subject of organizational memory and knowledge, remembering that organizations are composed of individuals with all the shortcomings and tendencies described above and supplemented with a few organizational groupthink shortcomings and tendencies. Organizational Memory Practitioners, that is to say organizational leaders, often have little understanding of the matter of organizational memory. Some have no time for such notions and dismiss the topic as not relevant to the pressing issues of the day. Others may acknowledge the notion of organizational memory when they talk about recalling and applying lessons learned. They may describe the veteran employees who hold essential knowledge. They may also refer to databases containing documented past experiences. But their notion of organizational memory rarely goes beyond that point. A very few leaders understand that their organization does indeed have a complex and sometimes faulty memory that must be managed. The notion of organizational memory is also subject to some academic debate even though it is a fundamental requirement for capturing and applying learning. Although we don’t need research or academic insight to tell us that memory is an essential concept in understanding how individuals process information, researchers disagree on whether organizational memory exists, just what it is, and where it resides in the organization. Some argue that organizational memory is only a metaphor having no real-world presence (Argyris and Schön, 1978) while others assert that organizations may be capable not only of memory but of thought (Sandelands and Stablein,

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1987). My own practical experience and study leads me to conclude that indeed organizations do have memories and are capable of collective thought. Walsh and Ungson (1991) argue that organizations do have memories, or what they call “retention facilities,” made up of the minds of individuals, culture, transformations, structures, and ecology. They contend that individuals learn, remember, recall, and apply learning on behalf of the organization. The individual memories are essentially a distributed network in which memories are somewhat randomly and even redundantly stored. They assert culture stores memories in the form of learned behaviors that are socially reinforced over time. Transformations are, according to Walsh and Ungson, embedded in the logic that guides the transformation activities whether the conversion of raw materials into a product or the conversion of a new hire into a more productive employee. Structures, the roles and resulting interactions between employees, also contain the residue of past experiences, a form of memories. They describe ecology as the physical work environment that, like culture, contains the residue of past experiences and shapes interactions and behaviors in the future. They also describe archives as a form of organizational memory that lies outside their notion of the organization itself. The five memory “retention facilities” described by Walsh and Ungson have some real merit in that they articulate the notion of an organizational memory and thus offer a framework for exploring how organizational knowledge is retained and utilized. However, one sometimes struggles to understand some of the distinctions between culture, structure, and ecology, distinctions essential to understanding organizational knowledge management. Nonetheless their work offers useful insights. This book embraces the notion that indeed organizations do have memories and do “think” collectively. That is to say, the individuals within the organization possess and use knowledge and that the collective organization benefits or suffers from those individual capabilities. But the organization is imbued with other memory and knowledge management capacities and abilities as well, capacities and abilities from which they also benefit or suffer. Organizational memory and knowledge management are relatively new topics for those who study organizations. The research has so far generally followed one of two paths. The IT path emphasizes the acquisition and storage of organizational knowledge including data warehousing, document management, and search tools. The organization development (OD) path emphasizes tacit knowledge, coaching,

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social interactions, and encouraging ad hoc knowledge exchange. The IT path has perhaps been more prevalent because one can readily develop tools, methods, and deployment approaches around it, making it more attractive to overworked managers. The OD path is popular with many academics but has found little traction within organizations, perhaps because it offers less certain and less specific benefits. The IT approach can be clearly defined and deployed while the OD approach cannot. The resulting performance improvement track record has been disappointing or uncertain for both. As will be described in more detail later, the IT approach has consistently delivered disappointing results. The OD approach has not clearly demonstrated benefits either. First, OD based approaches have been deployed less often, providing fewer opportunities to refine the deployment or measure the results. Second, the OD approach to knowledge management, like other OD concepts, lacks the specific and tangible causal connections that enable one to clearly demonstrate benefits. The past two decades has spawned a new enthusiasm for understanding how organizations have deployed, or might be able to deploy, IT to improve how they make use of what they know. This enthusiasm has arisen because of the dramatic advances in memory capacity, search engines, and communications capacity. The Acquire, Organize, and Distribute (AOD) framework described by Schwartz, Divitini, and Brasethvik (1999) is one IT oriented model for describing the basic tenets of organizational knowledge management. “Acquire” includes the gathering of knowledge that is known to exist in the organization (documents, reports, etc.), inquiries to search out knowledge that is desired but not presently held within the organization, verification and validation of the accuracy of knowledge, and encoding or codifying the knowledge in some form making it accessible and useful in the future. “Organize” includes the profiling or context association of the knowledge so future users can understand under what context the knowledge was created and interpreted, the association of the knowledge with other potentially related knowledge, the classification and sorting of the knowledge making it easier to retrieve, and the ranking of the importance and relevance of the knowledge versus other knowledge so future searches will be efficient and fruitful. “Distribute” includes raising the awareness in the minds of potential users that relevant knowledge may be available, the ability to identify the relevant knowledge, and the delivery of that knowledge to where it can be effectively applied.

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Schwartz also provides some definitions and relationships helpful to the discussion of organizational knowledge management. He defines organizational memory as the content, the specific knowledge resident in the organization. He defines knowledge management as the handling of that content—the storing, retrieving, and distributing that makes it useful in the future. He defines the organizational memory information system as a subset of the knowledge management system, the tools with which the system is implemented. Notice that these definitions reflect the IT perspective. A “memory” is the actual bit of knowledge or information rather than the place where the knowledge resides. Of course IT professionals are used to thinking of memory in a hardware sense—it is the electronics in which data as stored. “Knowledge management” is defined in such a way that the activity is accomplished once the knowledge has been distributed rather than once it has been embraced and applied. Again, this is consistent with an IT perspective. Let us move on to an example of the OD perspective. Karl Weick at the University of Michigan (Weick, 1991) raises an interesting consideration about the similarities and differences between individual and organizational learning. He describes the defining property of individual learning as the combination of same stimulus and different response. That is, if an individual adopts a new or different behavior in response to the same stimulus or situation, then it is assumed the individual responded differently as a result of new learning. Recall that insanity is often said to be doing the same thing over and over while hoping for a different outcome. Learning is, per Weick, apparently defined as doing something different in hopes of a different outcome. Weick argues that this same situation but different response dynamic rarely occurs in organizations because subsequent organizational stimuli or situations are quite often different in substantive ways than past stimuli or situations. Therefore, if one sticks with this traditional definition of learning, then very little learning ever occurs in organizations. Weick contends organizations are not built to learn in this traditional way. Instead organizations strive to encourage the same response to different stimuli and situations. The organization seeks to establish an ideal response or process that will be activated in the face of different situations. They are seeking consistency of behavior. Organizations with very strong culture and a robust bias toward a process or procedure perspective will tend to respond to different situations in a consistent way.

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He suggests that organizational learning researchers may approach their work with one of two strategies. They may accept the samedifferent notion of learning as one that fits both individuals and organizations and as a result accept that very little learning occurs in organizations. Conversely, they may accept the different-same definition of organizational learning thus leading to a study of how organizations impose or encourage consistency of behavior. I do not necessarily embrace all these definitions and models but offer them as an example of research perspectives. For example, the AOD model is a useful way to begin a discussion about organizational knowledge management but it is too simple to be relevant to the practitioner. After all, one could use a similar model for publishing a book. All one need do is “acquire” a few interesting bits of knowledge, “organize” them in some useful and interesting way, and then “distribute” the result through publication. The problem is that the acts of acquisition, organization, and distribution are so challenging that the model provides no help toward competency in organizational knowledge management. Weick’s definition of individual and organizational learning also suffers from some practical weaknesses. Many would argue that individual learning is not necessarily demonstrated by the “same stimulus prompts different response” behavior. Nor is organizational learning necessarily demonstrated by the opposite behavior. Organizational Thought and Knowledge Recall the earlier descriptions of individual peculiarities with respect to memory and thinking. Organizations may collectively suffer from very similar challenges. Just as an individual may have an egocentric bias, that is, an inability to see others’ perspectives, so too may an organization collectively act as if it has a similar bias. Organizations may elect to bid on an important contract because it has become convinced it must win the contract. It may well disregard compelling evidence that it cannot win, or that the project will lose money, or that they cannot accomplish the work. The organization’s desire and perceived need to win and its egocentric bias blinds it to these formidable challenges. Organizations also display symptoms of having malleable memories. Researchers have demonstrated that individuals actually revise their memories to fit their current biases. Organizations may do the same thing. Certainly historians revise historical perspectives as time passes. Organizational leaders often reinterpret the past to fit

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the current agenda. These reinterpretations over time can erase or modify the old memories, replacing them with new versions of what happened and why. That’s not to say that every member of the workforce embraces the revisionist memory. The collective organization may embrace the new interpretations when a sufficient number of key employees decide to behave in accordance with the new interpretations, even if several of those individuals do not personally believe that version of historical events and the learning that emerged from them. Organizations also suffer from groupthink, a type of thinking exhibited when individuals try to minimize conflict within a group. Members strive for consensus instead of attempting to critique, analyze, or evaluate ideas openly. Such individual thinking induces the collective group to make irrational decisions. In essence, a group of truly bright and capable individuals can come together to form a truly stupid group. Leadership behavior and organizational Culture are two critical factors that encourage or inhibit such thinking. The point is that individuals are vulnerable to mishandling what they know and how they process it. As members of an organization, they bring that same vulnerability to the collective. Beyond that, the organization as a whole has yet another set of knowledge and thinking vulnerabilities, vulnerabilities that must be acknowledged and factored into the structure of the organizational knowledge management system. The Knowledge Stream and Its Obstacles Knowledge flows erratically through organizations. Along the way it is captured or discarded, fostered or inhibited, amplified or weakened, or otherwise influenced. Several organizational traits such as structure, geography, and culture influence how well or poorly the knowledge flows. Every organization has inherent attributes that encourage or discourage information flow and distortion. The most proficient organizations understand those attributes and take actions that encourage knowledge to flow more freely and with minimal distortion. For example, a highly functionalized structure may encourage learning about functionally relevant technology but lack curiosity about markets and competition. The leaders of the manufacturing department may invest in and encourage learning about the latest manufacturing techniques. The head of engineering may focus his teams’ attention on design methodologies and tools. The head of marketing may encourage learning about customers and competition. But there may be little

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interest in cross-discipline learning because there are no natural mechanisms for funding or encouraging such activity. There may also be real resistance to the free movement of knowledge between the manufacturing, engineering, and marketing departments. Such a functionalized organization may find it easy to understand and improve processes within the function but have difficulty understanding and improving cross-functional processes. On the other hand, a customer-focused structure, one organized to align the firm with its most important customers and their needs, may encourage learning about individual customers, about markets, and about competition but lack curiosity about internal manufacturing or design technology. The organization may have an affinity for learning about and improving processes that touch the customer but lack any real interest in internal processes. There may be a free flow of customer and market knowledge but there may well be no mechanisms to encourage the flow of technical and internal process knowledge. Again, this is because there are no natural mechanisms for funding or encouraging such activity. Geography nearly always inhibits knowledge flow and increases knowledge distortion. Therefore a geographically dispersed organization faces special challenges. Video conferencing and the Internet have mitigated, but by no means eliminated, the dampening effect geographic distance has on sharing knowledge. People who are collocated bump into one another in the hallways, eat lunch together in the cafeteria, and play golf together on the weekend. These frequent ad hoc interactions foster a sharing of issues and experiences that lead to new understandings. Such sharing of knowledge arises as a result of serendipity, the phenomenon of finding valuable things not sought. Geographic distance reduces the number of opportunities for serendipity to emerge. Geography also distorts knowledge. Suspicion and distrust are greater when communities within the organization are geographically separated. One community or individual has less opportunity to understand the environment, constraints, and intentions of the remote group or individual. That absence of context fosters different interpretations of the knowledge offered and raises the potential the knowledge will be discounted, misinterpreted, or misused. Organizational culture may foster or inhibit new learning and knowledge sharing. An organization that is inwardly focused, or is driven by recurring crises, or lacks a coherent vision for the future, is less likely to be an efficient and effective learning organization. A culture that encourages feudal warfare—each department leader

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believing he must keep his borders secure and his neighbor’s weak— will use knowledge as a personal weapon not as an organizational asset. On the other hand, a culture that values knowledge, problem solving, and curiosity will be more likely to seek new knowledge and more likely make better use of the organizations’ existing knowledge. Once knowledge emerges it must be acknowledged. Someone must recognize the new information or insight. It must be appreciated. Winston Churchill, speaking about Stanley Baldwin, three-time prime minister of the United Kingdom, said, “He occasionally stumbled over the truth, but hastily picked himself up and hurried on as if nothing had happened.” Perhaps the same might be said of organizations that repeatedly stumble across new and previous learning but fail to appreciate it or apply it. Organizations that appreciate power and position will treat knowledge as an asset to be hidden or shared when it is most politically useful, while organizations that appreciate shared learning and problem solving will treat knowledge as a shared asset to be appreciated and leveraged by all. Knowledge, once acknowledged, must be appropriately captured or retained in some way. Perhaps those who were present will remember it. Perhaps it will be documented and filed hoping those who need it will know where to seek it. Perhaps it will be communicated widely hoping others will find it useful, apply it appropriately, and recall it in the future. But, many challenges arise. What was really learned? How best to document it accurately? What context may be useful in the future? The organization structure and social norms influence how, or even whether, these questions are answered. Capturing organizational knowledge is not so easy to do well. Knowledge, once captured, must be shared if it is to be useful. Knowledge buried where no one knows about it, or in a place no one cares to look, may as well not exist at all because it provides no organizational benefit. Sharing may occur ad hoc or formally. It may reside in either a push or a pull system; a push system being one in which the knowledge is literally pushed out to potential users while a pull system may be a repository to which those seeking information must come. Next, knowledge must be accepted. Too often individuals presented with new insights, approaches, or solutions reject them. They may be reluctant to accept something new or different. They may believe the new information was relevant to some other situation but not to the current one. They may lack regard for the source of the information and so reject the information itself. They may fail

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to understand or appreciate the benefit of the new learning and so reject it. One may accept new learning but fail to apply it. I’ve taken Spanish lessons three times in my life, first as a high school language class, second while in the Army stationed in Tucson, Arizona, and third while working in Phoenix, Arizona, some twenty years after leaving the military. Today I can readily recall a few phrases but am unable to take part in even a simple social conversation. Clearly I’ve failed to apply what I learned, and as a result the knowledge has become lost to me. Organizations suffer a similar frailty. They may engage with a specific customer or technology or process once every few years. Each time the organization experiences what seem to be new or unusual circumstances. Each time they struggle to succeed. Each time they learn valuable lessons. Yet, each time they seem to have forgotten much of what was learned before. Applied learning opens the door for additional insights and learning. The more the new knowledge is put to use the more likely it is to spark connections or extrapolations that enhance the learning or even create new knowledge. Knowledge flows erratically through any organization under the influence of structure, geography, and culture and an array of other factors. Organizations that understand how they deal with what they know will be more competent learners and more effective users of what they learn. Researchers have made great progress in understanding how humans retain and use knowledge. They have developed a shared understanding of what parts of the brain are used for what particular memory tasks. They are working to develop a shared understanding of what memory is and how the different parts of the brain handle the different forms of memory. They are working to develop a shared understanding of how individuals retrieve and apply what they know. These understandings and frameworks provide a foundation for even greater understanding. Organizational researchers are not as far along. There is currently much more debate than agreement. A viable model of the parts of organizational memory would be a step toward progress. The model described below is one attempt to take that step. It is founded in an integration and extension of decades of organizational experience assessed against a review of academic research on the topic. It attempts to use language and constructs to which both researchers and practitioners could relate.

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How Organizations Manage Knowledge Organizations capture their learning in one or more of four repositories analogous to the parts of the brain and types of individual memory described earlier. The four repositories for organizational knowledge are Culture, Old Pros, Archives, and Process. Each has unique attributes. Different organizational memory activities engage different combinations of the four. And just like the parts of the brain, each influences the other to some extent (see table 2.1). Note that the reader may wish to refer to the last paragraph in the Preface where the use and intent of italicized words is described. Culture is that set of behaviors and operating principles that nearly everyone knows, but that are not written. Culture may tell us that we should always preview a presentation with the attendees before the formal meeting. Failure to do so will make some individuals feel “out-of-the-loop” and will cause them to raise objections. Culture may tell us that those with information have power over those without it, or it may tell us that information sharing and joint problem solving is valued more than individual power. The organizational Culture is a receptacle and disseminator of what the organization has learned, or chosen to practice, throughout its history. Neither the practice nor the reasons for that particular practice are captured in formal policies or explained as part of employee orientation. Instead, they are learned through observation and experience in the work Table 2.1

Human and Organizational Memories—A Comparison

Human

Organization

Amygdala ● emotional memory ● fight-or-flight responses ● “that’s just the way I feel”

Culture ● instinctive reaction to stimuli ● often rationalized but not understood ● “the way things are around here”

Hippocampus ● long-term memory ● current interpretations of past experiences

Old Pros ● possessor of historical learning and context ● “I remember when”

Cortex ● stores facts and data ● works closely with hippocampus

Archives ● holds test data, employee records, etc. ● repository of explicit learning

Cerebellum and basal ganglia ● habits and routines ● motor skills

Process ● work routines and procedures ● methods and techniques

Source: Author’s Illustration

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environment. One may recognize and practice the acceptable behaviors without ever knowing why that particular practice is in place. Indeed, there may be multiple “explanations” for why the behavior or practice exists, and those explanations may well conflict. In short, the employees may well not know why they do these things but they do them all the same. Culture influences the organization’s instinctive reaction to stimuli, much like an individual’s fight-or-flight response. It houses conditioned responsive behavior rather than the knowledge that caused the behavior to develop. It serves the organization much like the amygdala serves the individual. Nearly all large organizations have a cadre of Old Pros, those who have been around long enough to amass a great deal of experience about the organization and its products, processes, environment, and capabilities. These individuals have memories of their own as well as memories of the organization’s past experiences, memories shaped and distorted as described earlier. They know that a particular customer is fussy about flawless documentation. They know that a particular piece of production equipment tends to drift out of tolerance and cause rejects within a day or so after it has been idle for several days. They may recognize in the facts of a current problem the clues that relate to previous problems and their solutions, and from those clues they may be able to come up with a quick fix to the problem at hand. The Old Pros provide an organizational memory management function somewhat like the hippocampus provides for individuals. Just as the hippocampus retains and retrieves knowledge learned in the distant past so to do the Old Pros. Frustrated organizations that become aware of their poor use of valuable lessons learned often begin to talk about formal Archives. “We need to document our lessons learned for future use. If only we could capture and retrieve what we already have experienced!” Sound familiar? It should. Every few years someone in the organization mounts a campaign to document and capture that knowledge. They often get distracted and give up or persevere but fail, and a few years later another attempt is made. In the last decade or so we’ve seen the maturation of databases and search engines, causing some to believe that greater computing capability will finally enable us to effectively store and retrieve our lessons learned. So far there has been too little success to turn that hope into a reality. These Archives are often created using IT systems that house and make available those pieces of learning the organization elects to capture. Organizational Archives are analogous to the cortex and hippocampus in that they manage the storage of facts and events. One might also stretch an analogy to assert

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that Archives are to an organization what rote memory is to an individual. Just as an individual may memorize the Gettysburg Address and be able to recite it on cue, so to an organization may memorize specific pieces of information hoping to retrieve them when desired. Formal Process, when appropriately managed, can serve as both a repository and a disseminator of organizational lessons learned. Process includes the understanding of each of the individual work routines within the organization and between the organization and its customers, suppliers, and partners. It includes the work routines and procedures by which the organization accomplishes its tasks. For example, the organization may have a methodology by which the annual strategic plan is assembled, reviewed, and communicated. Other examples may be the methodology for calibrating a particular piece of test equipment, the methodology for gathering and reviewing customer satisfaction information, or the way in which office supplies are ordered. The work routines and procedures are modified to incorporate new learning about how to more efficiently accomplish the task. The modified routines are then the means by which the knowledge is retrieved as needed. A formal organizational Process discipline is perhaps the most challenging and yet most effective means of managing what the organization knows. The individual work routines and procedures within the organization represent the most successfully demonstrated means of capturing and using lessons learned. Just as the basal ganglia and the cerebellum contains the habit and motor skills we have learned, so to does Process contain the habit and motor skills the organization has collectively learned. As a side note, the reader may notice that the frontal cortex has not been addressed. Indeed, this model does not identify an organizational knowledge management faculty analogous to the human frontal cortex. Humans all have, unless they have suffered a birth defect or severe trauma, a frontal cortex, a cerebellum, a hippocampus, and an amygdale. Each of us is born with roughly the same human machinery and programming that enables us to capture, store, and retrieve memories. However, the same cannot be said for organizations. Some of these parts of organizational memory, Culture and Old Pros in particular, are almost certainly present and very active in every organization while others, including Archives and perhaps Processes, may not be in place or may not be openly acknowledged by the organization. Every organization has a Culture or begins to develop one immediately after it is first created. Whether it is weak or powerful, helpful or destructive, pleasant or challenging, it almost certainly exists. Every organization

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has a few Old Pros among its population. They may have been hired or transferred from other organizations. There may be a few knowledge gaps. But surely some of the employees will be considered by the others to be the Old Pros to whom they will go for advice. Archives are quite often but not always present. If they are, they may be very weak or even dysfunctional. Process is much like Archives in that it is often but not always present and that it may well be weak or dysfunctional. In short, humans possess all the equipment needed to have fully functioning memories while organizations must build and program some of the equipment needed for a fully functional memory. Culture, Old Pros, Archives, and Process have unique attributes just as the parts of the brain that control and contain our memories have unique attributes. For example, the four differ in their ability to respond to tacit versus explicit learning, just as the parts of the human brain differ. Tacit knowledge, those things that we know but cannot explain, are the dominant form of knowledge residing within the Culture and Old Pros. Archives can handle explicit knowledge effectively but often distort or even make invalid tacit knowledge. Processes are more adept than Archives at handling some forms of tacit knowledge but they are far less adept than Culture and Old Pros. We will learn in later chapters about the strengths and weaknesses of each. This notion of Culture, Old Pros, Archives, and Process as repositories and managers of organizational knowledge finds some resonance in the research literature. Three examples are briefly described below. Edgar Schein (Schein, 1993) described three distinct kinds of organizational learning: knowledge acquisition and insight, habit and skill learning, and emotional conditioning and learned anxiety. This concept fits well with the notion of Old Pros as embodying knowledge acquisition and insight, Archives and Processes as habit and skill learning, and Culture as emotional conditioning and learned anxiety. Schein argues the greatest impediment to successful knowledge acquisition and insight is anxiety about the complexity of the problem at hand or the disruption that may ensue if new approaches are implemented. He argues that habit and skill learning is facilitated when organizations create safe environments where individuals and teams can practice and make errors without serious risk or retribution. He argues that emotional conditioning and learned anxiety are more effective learning mechanisms when they are founded on past successes rather than past failures. Learning rooted in past failures carries with it the specter of retribution, while learning rooted in past successes speaks to the opportunity for reward and appreciation. An

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organization is more likely open to change and adaptation in the later circumstance than the former. Walsh and Ungson (Walsh and Ungson, 1991) contend organizational memory plays three important roles. First, it actually stores what the organization knows for use when needed. Second, it acts as a controlling mechanism because the stored knowledge shapes how the organization is likely to respond to a given situation. Third, it acts as a political force. Those who control information make others dependent on them, thus creating power for the knowledge holders and controllers. They also identified six means by which an organization stores what it knows. The six are individuals, culture (their definition is quite similar to the one proposed here), transformations, structures, ecology, and external archives. “Individuals” refers to the memories of each individual working in the organization. The organizational knowledge is distributed among those individuals and influenced by their individual biases. They define “culture” as the embodiment of “past experiences that can be useful for dealing with the future.” It is a collective shared recollection rather than an array of individual memories. “Transformations” is the phrase they use to define work activities and procedures that transform inputs into outputs. These work activities and procedures are storehouses of organizational knowledge. “Structures” is defined as the social roles and boundaries established by the organizational structure. These roles and boundaries establish relationships, interactions, and behavior patterns that embody organizational knowledge. “Ecology” refers to the physical structure and workplace in which the organization operates. They contend it shapes and reinforces behavior patterns because of the information retained in its form. “External archives” refers to former employees, competitors, suppliers, and industry regulators that hold knowledge about the organization. Davenport and Prusak (Davenport and Prusak, 1998) describe three basic types of knowledge repositories, or what is called here Archives; external knowledge (competitive intelligence reports), structured internal knowledge (research reports, product oriented marketing materials and methods), and informal internal knowledge (discussion databases full of know-how, sometimes referred to as “lessons learned”). Davenport said “Although machine-engineering purists might argue that we just haven’t used the technology and tools of information design correctly, forty years of failure is forty years of failure. The tools most frequently employed to design information environments derive from the fields of engineering and architecture; they rely on assumptions that may be valid when designing a building

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or a power generator, but rarely hold up in an organization. The sheer volume and variety of information, the multiple purposes to which it is put, and the rapid changes that take place overwhelm any rigorous attempt at central planning, design, and control.” Schein, Walsh, Ungson, Davenport, Prusak, and others have wrestled with many of the same questions and constructs that brought about the model described in this book. Perhaps it will contribute to the effort. What Lies Ahead Each of the next four chapters focuses on one of the four elements of the organizational memory and knowledge management model. Each chapter describes the particular construct, how it retains and influences organizational knowledge, and how leaders can enhance its performance. The next chapter, chapter three, Culture—The Way It Is Around Here, offers an in-depth description of Culture as a means by which organizations capture, store, retrieve, and apply what they have learned. The next three chapters, four, five, and six address in turn Old Pros, Archives, and Process. Chapter seven brings the four constructs together as an integrated whole.

References Argyris, C., and D. Schön. (1978). Organizational learning: a theory of action perspective. Reading, MA: Addison Wesley. Argyris and Schon argue that people have mental maps with regard to how to act in situations and that it is these maps that guide people’s actions rather than the theories they explicitly espouse. Few people are even aware of the maps or theories that drive their actions. Ariely, D. (2008). Predictably irrational: the hidden forces that shape our decisions. New York, Harper Collins. Ariely, a behavioral economist at MIT, offers multiple examples of irrational economic decision making, examples that resonate well with seemingly irrational decisions made by individuals in other arenas. Davenport, T.H., and L. Prusak. (1998). Working knowledge: how organizations manage what they know. Boston, Harvard Business School Press. Halpern, D. (1996). Thought and knowledge: an introduction to critical thinking. Mahwah, NJ, Lawrence Erlbaum Associates. The first three chapters of this textbook address thinking, memory, and language as it relates to decision making. The book pulls together information and insights from a variety of sources putting them in an easy to grasp context.

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Kerr, Steven. (1994, February). Radically improving corporate performance: practical change interventions that work. Presentation at the Executive Focus International 1994 Executive Forum. Orlando, Florida. Kerr began as an academic, was spotted by Jack Welch and wooed into industry. He is currently the chief learning officer at Goldman Sachs. Pinker, S. (1997). How the mind works. New York, W.W. Norton. This book provides a clear, entertaining, yet detailed description of how the mind works. He addresses the questions of what makes intelligence possible and what makes sentience possible. He also provides insights into how the brain evolved and how it functions, including how memory functions. Sandelands, L.E., and R.E. Stablein. (1987). The concept of organization mind. Research in the sociology of organizations, vol. 6. N. DiTomaso and S. Bachrach, eds. Greenwich, JAI Press: 135–161. These two were among the first to portray organizations as “mental entities capable of thought.” Schein, Edgar. (1993). How can organizations learn faster? The challenge of entering the green room. Sloan Management Review (Winter): 33–40. Schein describes three types of organizational learning: knowledge acquisition and insight, habit and skill learning, and emotional conditioning and learned anxiety. Schwartz, D.G., M. Divitini, and T. Brasethvik. (1999). On knowledge management in the Internet age. Hershey, PA. IGI Publishing. The authors brought together a collection of perspectives about knowledge management in general, and Internet-based knowledge management in particular. They acknowledge the perspective that IT is expected to be the Holy Grail of knowledge management success but that the results have remained elusive. They offer an integrated perspective that includes IT but does not rely solely on it. Walsh and Ungson. (1991). Organizational memory. Academy of Management Review 16(1): 57–91. Walsh and Ungson argue that the current representations of the concept of organizational memory are fragmented and underdeveloped. They attempt to better define organizational memory and elaborate on its structure. They also discuss the processes of information acquisition, retention, and retrieval. Weick, K.E. (1991). The nontraditional quality of organizational learning. Organization Science 2(1): 8. Weick agues that individuals demonstrate learning behavior when they display a different response to the same stimuli while organizations demonstrate learning behavior when they display the same response to different stimuli.

Chapter 3

Culture—The Way It Is Around Here

What Is Culture? Start with a cage containing five apes. In the cage, hang a banana on a string and put a ladder under it. Before long, an ape will go to the ladder and start to climb toward the banana. As soon as he touches the first step, spray all the apes with cold water. After a while, another ape makes an attempt with the same result—all the apes are sprayed with cold water. Now, turn off the cold water. If later an ape tries to climb the ladder, the other apes will try to prevent it even though no water sprays them. They have come to associate reaching for the banana with the icy water spray and will try to preempt being sprayed. Now remove one ape from the cage and replace it with a new one. The new ape sees the banana and wants to climb up to it. To his horror, all of the other apes attack him. After another attempt and attack, he learns that he will be assaulted if he tries to reach the banana. He has no idea why this is so, after all bananas are tasty, but he soon learns to not climb the ladder. Next, remove another of the original five apes and replace it with a new one. The newcomer goes to the ladder and is attacked. The previous newcomer takes part in the punishment with enthusiasm, although he still has no idea why he is doing so. Again, replace a third original ape with a new one. The third new one approaches the ladder and is attacked as well. Two of the four apes that beat him have no idea why they are not permitted to climb the steps. Even so they are participating in the beating of the newest ape. After replacing the fourth and fifth original apes, all the apes that have been sprayed with cold water have been replaced and none of

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the apes in the cage have ever been sprayed. Nevertheless, no ape ever again approaches the steps. Why not? Because that’s the way it has always been around here. That is Culture—and that is how knowledge get captured in and retrieved from the organizational Culture. This allegory, sent to me several years ago, but without attribution, captures the essence of an organizations social customs and norms of behavior, its Culture. Consider a real-world example. All government contractors must maintain a subcontractor and material procurement (S&MP) system that meets specific government criteria to assure fairness to suppliers, equal or preferential opportunity for small and disadvantaged businesses, and the best price to the government. Defense contractors are periodically audited to assure they have such a system, that it is documented and deployed, and that it is being used. Several years ago a government audit disclosed that one particular contractor’s system was unacceptable because individuals were not implementing it in compliance with the documented requirements. These shortcomings had been noted in previous audits but the contractor had failed to make sufficient improvements. Note that the shortcoming was a failure to follow documented requirements, not a failure to be fair, not a failure to employ small or disadvantaged businesses, and not a failure to provide the best price to the government. The organization was being reprimanded for failure to comply with its self-generated policies and procedures. Even so, the system was decertified, meaning the government no longer accepted the contractors assertions about procurement and subcontract activities complying with government regulations. So the contractor was barred from bidding on new government contracts until the system was revised, employees trained, and the government reaudited then formally recertified the system. In the meantime, several strategically important new contract opportunities were missed or put at risk because of the contractor’s inability to submit bids for the work. The company took quick and dramatic steps to regain certification. It made the S&MP organization more powerful by assigning high talent individuals to key leadership positions. The new vice president of S&MP also reported directly to the president in order to give the organization more independence and authority. Supplier decisions became the sole responsibility of the newly empowered department, leaving the program teams and functional departments with very little authority, or even influence, over those decisions. Over the next six month the newly empowered organization put in place an even more specific and stringent set of policies, procedures, and internal

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audits to assure the previous problems did not recur. The S&MP organization used its bully pulpit to make itself increasingly more independent of the program teams and functional departments for whom they negotiated subcontracts and bought material. The organization passed its next S&MP audit. Since then, over a decade has passed and the organization has passed every subsequent S&MP audit. However, there has been a cost. The trauma of decertification is now embedded in the organizational DNA, and its consequences are visible in the form of bureaucracy that causes delays and poor performance. Today, program teams struggle to cope with difficult relationships with an S&MP organization that views itself to have a legal and compliance mandate with little regard for specific program or project needs. The conflict enhances the likelihood the organization’s system will remain compliant but significantly imperils the likelihood a project will be done efficiently. Employees tell numerous stories about how the S&MP rules and bureaucracy have needlessly hurt suppliers, the contractor, and even the government customers. The lesson buried within the Culture determines how suppliers and subcontractors are treated, renders the organization less flexible and agile, and even impedes its ability to give the government the best value solution although its S&MP system has been deemed satisfactory. Today, fewer than a dozen of the tens of thousands of employees in that company have any idea why the S&MP department policies, practices, and attitudes are as they are, but they all know they are a problem that no one dares try to fix. The Culture stored a conditioned reaction to a traumatic event. The event was government decertification as a result of recurring noncompliance with S&MP policies, and the ensuing trauma as a result of decertification. The learning, in this case, was that strict compliance is required to avoid the trauma. The organization stored that learning in the form of a more independent and powerful S&MA department, in the shift of subcontractor and material selection decision authorities, and in an organizational fear about the consequences of noncompliance. Culture is shaped by the experiences an organization encounters as it deals with challenges to its survival and copes with its integration issues. Threats to survival, such as in the S&MP story related above, leave a deep and lasting impression on organizations. Forces that induce intense shared emotions among the members of the organization may include intense competitive pressures, traumatic financial losses, or environmental disasters. The emotional intensity leaves

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its mark on the minds of individual members. It also fosters bold actions that would otherwise be deemed unnecessary or unacceptable, changing organizational behavioral norms more rapidly and more significantly than would otherwise be possible. The emotional intensity also reinforces the changes, helping to embed them more deeply into all dimensions of organizational behavior. These intense organizational emotional responses are the equivalent of individuals’ fight-or-flight responses and of déjà vu responses. They are potentially helpful but also potentially harmful. Such instinctive responses may galvanize the organization to action quickly thus helping it respond to threat. On the other hand, such responses may have been embedded during a time when priorities, capabilities, and opportunities were different. The instinctive response may be inappropriate for the current environment but may be triggered nonetheless. The depth of a Culture is also shaped by the stability over time of the organization. Culture is inherently a property of a stable group, not necessarily a stable environment. Population stability allows the group to work together on more, and more complex, challenges. It allows the group to experience the positive reinforcement of meeting and overcoming challenges. It also allows for the recurring experience of shared anxiety in dealing with painful and tragic errors. Once present, Culture provides meaning, security, and predictability. Therefore, it is both a source of organizational strength and simultaneously a strong conservative force. Edgar Schein (1996) says, “Culture is a set of basic tacit assumptions about how the world is and ought to be that a group of people share and that determines their perceptions, thoughts, feelings, and, to some degree, their overt behavior.” It is “invented, discovered, or developed by a given group as it learns to cope with its problems of external adaptation and internal integration—that has worked well enough to be considered valid and, therefore, to be taught to new members as the correct way to perceive, think, and feel in relation to those problems.” Schein describes three levels of Culture; artifacts, values, and assumptions. Artifacts are the technology, art, and behavior patterns that one can observe in organizational behaviors but that may not seem rational or consistent. The apes’ refusal to allow anyone to reach for the banana is an example of such behavior patterns. Values or socially agreed norms can be recognized as those standards to which the members of the organization hold themselves accountable. Examples might include an organization’s sense of fair play or respect for the individual, or a commitment to quality products and

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services. Basic assumptions are the organizations’ views of how the world operates (Humans are naturally good or bad. We can influence the future or the future is determined by the fates.) that are taken for granted. These artifacts, values, and assumptions embody the organization’s conditioned response to prior experience. They in effect store prior learning and, through the behaviors they enable or restrain, make that learning operable in the present and future. Artifacts are visible organizational structures and processes that may be evident but are often hard to decipher. Examples include the physical environment, patterns of dress, patterns of communication, levels and type of emotionality, stories and myths. One business unit may be housed in a lavishly appointed and meticulously kept facility while another may work out of a converted warehouse. The former will argue for the importance of a positive image in the eyes of customers and competitors while the later will argue for the importance of being frugal so as to keep prices low and profit margins high. One business unit may impose a relatively strict chain of command, insisting that individuals talk to supervisors, who talk to managers, and so on while another business unit may encourage an open dialogue with little regard for hierarchy. The former values position and power while the later values information sharing and problem solving. Stories and myths are perhaps the most telling artifacts. I once led an organization with a smaller remote facility that was asserted to be the “low-cost” manufacturing arm of the organization. Whenever the facility was mentioned people would launch into stories about the seedy and rundown facility as “proof” that no money was wasted on so-called frills, about the fact that all their equipment was fully depreciated, thus lowering overhead expenses, and about their comparatively lower wages. Oddly though, very little of the new manufacturing work was ever handed over to the remote site. The home organization always seemed to find an alibi for doing the work at the home facility. In an effort to learn the truth behind this story, I insisted that new work be competitively bid at both facilities. I also asked for a review of past performance on previous manufacturing jobs at both sites. It turned out that the remote site did have some specific cost advantages. The remote site labor rate was lower. Their facility costs were lower. Their training costs were lower. However, the remote site required more labor per comparable task because its equipment was outdated and less reliable. The investigation also disclosed that the quality levels were much worse at the remote site, perhaps because of the older equipment and the lack of investment in adequate operator training. Most of the key decision makers in the

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home organization knew about these problems and so colluded to keep work in house while, at the same time, sharing the myth about the “low-cost” manufacturing center. Although the facts and data refuted the myth about the remote facility, two years later the myth was still being repeated from time to time. Values are strategies, goals, and philosophies (the publicly stated justifications for decisions and actions). Examples include statements of corporate philosophy, espoused goals, preferred means of achieving goals, ethical guidelines, and answers to why things are done as they are. A set of value statements may communicate what the organization holds to be important. On the other hand, it too often merely communicates what the leadership believes its customers or employees want the organization to hold to be important. Value statements can be more insightful for what they fail to mention than for what they include. Some leaders believe their sole responsibility is to the shareholders. Others believe they have obligations to customers, shareholders, and employees. Still others believe they have obligations to customers, shareholders, employees, suppliers, and their community. Value statements suggest which stakeholders the leadership honors and which ones they may not honor. One must remember that it is the actualized values that shape Culture, not the stated values. Underlying assumptions, unlike artifacts and values, are unconscious taken-for-granted beliefs, habits of perception, thoughts, and feelings. An organization may value independent thinking and entrepreneurship over shared problem solving and consensus. An organization may feel the need to have disagreements be resolved in private rather than in an open forum. These sorts of behavioral norms may be so woven into the daily routine that long-term employees do not even consciously know they exist. Indeed the members of a highly empowered organization may complain about how disempowered they are because they have never had the experience of working in a much less empowering organization. These underlying assumptions are best viewed in comparison to peers and competitors, or in comparison to the underlying assumptions the organization held dear in the past. Culture is not monolithic within an organization. A large institution, perhaps a 100,000-person corporation or even a 200-person business, may have a unique and pervasive Culture that distinguishes it from other corporations or businesses. However, smaller communities within those entities will have their own set of artifacts, values, and basic assumptions. Schein (1996) describes three such communities, referring to the executives, the engineers, and the operators as

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three groups that “do not really understand each other very well.” He asserts, “A lack of alignment among the three groups can hinder learning in an organization.” For example, he contends the operators typically believe knowledge and skill exists at the point of operator activity where real-time decisions are made, while engineers typically think of the organizational knowledge as being embedded in the processes and equipment used to accomplish the tasks, and executives typically think of the critical organizational knowledge as the broader competitive, financial, and business model insights residing in their own minds. This lack of understanding and alignment impedes both learning and the sharing of what has been learned. One need not embrace Schein’s example as valid for all organizations. For example, an organization with very powerful functional groups may have separate artifacts, values, and assumptions within each function. The marketing, production, or research departments may have entirely different, even conflicting, views that impede organizational learning. Or, a powerful union workforce may lead to rifts between management and labor. Or a recently acquired organization may have rifts between employees of the heritage company versus the new company, rifts that may split up executives into different constituencies. The point is that these sub-Cultures exist and interact to influence, or to define, the overall organizational Culture. What Shapes Culture? Culture, much like the landscape, is shaped over time by powerful external and internal forces. Just as the persistent forces of sun, wind, water, and ice shape the landscape around us, similar persistent external forces shape an organization’s Culture. Just as the traumatic forces of earthquakes and volcanic eruptions can suddenly redefine the landscape texture, an organization’s Culture can be suddenly shocked and thus made vulnerable to significant and rapid change. The persistent forces influencing organizational Culture include the nature of the competitive framework, the relative strength of the customers, the nature of the regulatory environment, the organizations core competencies, and the organization’s relative stability over time. The traumatic forces may include technological revolution, dramatic regulatory changes that allow the introduction of new competition, or sudden changes in corporate strategy. See table 3.1, What Shapes Culture? Geert Hofstede (1997) conducted extensive research in the late 1960s and early 1970s about how values in the workplace are influenced

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What Shapes Culture? Evolutionary Influencers

Industry technology and complexity Organization reaction to technology and complexity Regulatory environment Competition Customers Organization history Individuals

Aerospace versus retail Niche development and specialization Drug industry versus home construction Number and size of competitors Number, size, and power of customers Relative stability or core competencies developed Key personnel with customer or industry influence

Revolutionary Influencers Technology disruptors Ownership change Disasters Leaders

Internet, materials improvements, etc. Sudden imposition of different culture “9/11” impact on airline industry New leaders with mandate for dramatic change

Source: Author’s Illustration

by national societal norms and standards of behavior (national cultures). During this period, Hofstede founded and managed the personnel research department of IBM Europe and that work sparked an interest in how national differences influenced the IBM employees doing similar work in different countries. He developed a model that identified four dimensions of national and regional distinction. The first was Power Distance, a measure of the perceived willingness of employees to express disagreement with their managers and the perceived autocratic versus paternalistic bias of managers. Malaysia and Panama had very high Power Distance, denoting lesser tolerance for questioning authority and an autocratic leadership bias, while Denmark, Israel, and Austria had a much greater tolerance for openly question leadership decisions and a more paternalistic leadership bias. The United States, Italy, and Japan were in the middle. The second was Individualism, a measure of the value of the individual versus the group. The United States and Great Britain displayed a high regard for the individual while Panama, Ecuador, and Guatemala displayed a much greater sensitivity to the group needs over individual needs. The third was Masculinity, a measure of the relative importance attached to earnings, recognition, advancement, and challenge versus manager/employee relationship, cooperation, living area, and employment security. Japan was significantly more

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masculine than any other country while Norway and Sweden were the most sensitive to the so-called feminine factors. The fourth was Uncertainty Avoidance, a measure of the population’s tolerance for ambiguity. Greece and Portugal were not very tolerant of uncertainty, while Singapore was extremely tolerant of it. Hofstede’s later studies with the Chinese caused him to add a fifth dimension, Long-Term Orientation, a measure of whether people from a nation or region focused more on near-term or long-term goals and priorities. Hofstede’s work has been both praised and panned (Punnett and Withane, 1990). He is appreciated for the scope and size of the study, the large database it created, and for the appeal of the limited number of dimensions. His work has also been criticized on theoretical and methodological grounds. Subsequent studies have not always correlated well with his findings, but a debate continues on whether the national cultures have changed or the original study findings were incorrect. We may not be able to accurately define, measure, and track national culture dimensions, but anyone who has traveled widely would acknowledge that significant and influential differences certainly exist across social, geographical, and other arenas. One such nongeographic arena for differences is industry segments. A services industry has different meta-characteristics than does a manufacturing industry. A food service industry has different characteristics than does an insurance services industry. A job-shop manufacturing industry has different characteristics than does a high volume manufacturing industry. The interbusiness and intrabusiness dynamics drive organizations within a particular industry toward common behaviors, biases, and worldviews. Factors such as the relative strength and number of competitors, the power of suppliers, the power of customers, the regulatory environment, and the level of technology shape the industry environment. These factors may exert more influence than do the national and regional factors that Hofstede identified. Consider the major commercial airplane industry. Today, two competitors Boeing and Airbus serve dozens of major airlines around the world and dominate the industry. The large airliner marketplace contains a few titans on both the supplier and buyer side. There are only a few major opportunities every decade to start building a new airplane platform and the winners of that competition will draw revenues for decades to come. Some would argue that there are major similarities between Boeing and Airbus, similarities resulting from the shared competitive environment. However, others may find striking differences between the two firms, citing their financial relationships with their respective governments and the national cultural differences.

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Next, consider the regional and business airplane market where a dozen or more competitors including Embraer, Bombardier, Mitsubishi, Saab, Gulfstream, Dassault, and recently Honda all serve perhaps a few hundred regional airlines and many thousands of business and personal jet owners. This business segment is a much more dynamic environment where agility, innovation, and risk-taking are rewarded or punished frequently. These firms may have more similarities than differences because the competitive arena exerts more influence than does the nation or region in which they are located. Just this morning, while having a leisurely breakfast and delaying the time when I would have to sit in front of the computer to work on this book, I read a Washington Post newspaper article about Booz Allen Hamilton (BAH), a $4 billion consulting company with over 20,000 employees worldwide, potentially splitting into two separate business units. BAH is credited with developing an approach to assess a company’s or government agency’s “personality,” an approach they call Organizational DNA Analysis. It seems the commercial services segment and the government services segment of BAH have each evolved into distinctly different DNA strains. The commercial strain practices a ruthless policy of personnel promotion or replacement— those who do not advance quickly are asked to leave. It also recruits from the top business schools, assembles small agile consulting teams, and spends lavishly on entertainment events. The government strain, on the other hand, tends to recruit experienced engineers and managers from within the industry, new college graduates, and a few others who fit specific needs. These employees may work with the same customer doing the same activity for years, and the teams can be quite large. Of course, these government customers are forbidden to accept any gratuity of value and so these teams do not enjoy the lavish entertainment opportunities that the commercial employees enjoy. These distinct differences—hiring and promotion practices, nature of engagement with customers, length of projects, size of the teams, and spending practices—all foster differences in policy, procedure, decision-making time horizons, sense of stability, loyalty, and the list goes on. Over time, the two DNA strands have become more and more different. They have now become so different that BAH feels the need to completely separate them. One organization, with one Culture, has evolved into two distinct Cultures that need to be separated. The level and nature of technology and complexity within an industry segment certainly can shape Culture. An organization working in a complex and dynamic environment such as consulting, aerospace,

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medicine, or filmmaking is continually beset with unexpected challenges, changing information, and resource conflicts. Their world is one of perpetual reprioritization of resources and adjustment of plans. There is very little process repetition. They accept the world as a dynamic, ever-changing, environment. On the other hand, manufacturing businesses, whether they assemble television sets, soft drink cans, or automobiles, strive to achieve an orderly sequential and repetitive operation and seek to stabilize their environment. Even so, an organization’s reaction over time to the same level and nature of the technology and complexity can result in two distinctly different Cultures—one organization may respond differently than another to the same influences. Consider the organizational behavior differences of Boeing and Lockheed, two titans of the aerospace industry. It is conventional wisdom in the aerospace community that Boeing tends to compete more often than not on the basis of marketing and business deals while Lockheed tends to compete on the basis of technology and engineering solutions. Of course, like all conventional wisdom, this is a gross oversimplification. But one often finds that Boeing’s internal explanations of their wins and losses are business based while Lockheed’s internal explanations of wins are founded on claims of superior engineering and technology while their explanations of losses are that the competition bid unrealistically low or offered a unique business arrangement. There is certainly ample anecdotal evidence to support the argument that Lockheed is more engineering oriented than is Boeing. The Boeing and Lockheed example points out that even though the two companies are quite similar because of the nature of the industry in which they compete, they also have some marked differences. Both companies have been in the same industry for decades, competing head-to-head for the same opportunities, yet they have seemingly evolved to different worldviews. The nature of the industry pushes organizations toward similarities but does not drive them to be clones of one another. Another industry dimension that influences the Culture is the regulatory environment. Industries such as public utility, government contracting, nuclear power, and pharmaceuticals are very heavily regulated. The pervasive rules, regulations, monitoring, and bureaucracy shape the industry and the organizations operating within it. An organization that provides products and services to the U.S. Government may be required to document and disclose every dollar that goes into its overhead, material, and labor cost pools. It may also be required to comply with government mandated cost accounting

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rules. It may be subjected to frequent and multiple periodic audits. It may even have several government auditors residing in the building to monitor all activity. On the product manufacturing side, it may be required to comply with volumes of generic and specific design and manufacturing requirements, provide designs and manufacturing plans for prior approval, have auditors present to verify the manufacturing process and testing activity. It may also be required to hire specific quotas of small and disadvantaged businesses, deploy specific energy conservation programs, and address a host of other public interest objectives. Finally, it may be required to maintain detailed records for the life of the products or beyond. These constraints leave their imprint. They affect internal views about bureaucracy, innovation, risk taking, decision making, and a host of other perspectives and behaviors. The organization cannot help but be affected deeply by such a regulatory environment. The organization learns a set of perspectives, biases, and beliefs that become embedded as knowledge. The effects may help it compete within its particular industry but make it entirely noncompetitive in other industries. Competition also shapes Culture. Consider Caterpillar, a firm that became the largest manufacturer of earth-moving equipment in the world because of a driving focus on quality and service. As a result, it achieved a 35 percent share of the worldwide market for earth-moving equipment. However, a worldwide construction industry recession in the 1980s coupled with a lengthy and contentious union strike at many of their plants hurt Caterpillar. Komatsu, their strongest competitor, was the world’s number-two construction equipment company and had been competing with Caterpillar in the Japanese market for years. Although they too were hurt by the industry downturn, Komatsu adopted the slogan Maru-c, meaning, “encircle Caterpillar.” They used the slogan to emphasize quality improvement initiatives and productivity improvements that could enable them to take additional market share from Caterpillar while they were weak. Maru-c became the driving strategic force at Komatsu for several years. Customers shape Culture. An organization that works exclusively with the government tends to develop an organizational bias toward structure, documentation, and governance that aligns with their customers. On the other hand, a commercial firm is not subject to such monitoring, may deal with a variety of customers and preferences, and tends to not be so strongly influenced by any one customer. The former will be much more likely to embrace bureaucracy than will the later.

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An organization’s history—its past triumphs and disasters, its relative stability, the competencies it has developed, its reputation among customers, and the legends it believes about itself—all shape the Culture. Examples abound. Honeywell, a one hundred-year-old company, began as a “controls” company. The Minneapolis-Honeywell Regulator Co. began making mechanical furnace controllers in 1927. That perspective shaped the firm into the 1980s when it still considered itself to be primarily a controls company, even though controls had evolved to include automated factory control systems, aviation control systems, and satellite navigation and control equipment—a long way from a simple furnace controller. The word controls influenced how the company viewed its marketplace, its investments, and its competencies. The company saw itself as grounded in controls engineering innovation. As a result, engineers dominated the leadership. For decades, it was assumed that senior executives would come from within and have strong engineering experience. Those leaders with such a strong engineering bias therefore influenced the Culture further. Honeywell’s purchase of Sperry Defense Systems and Sperry Flight Systems, two major high technology sectors of Sperry Corporation, in 1986 further strengthened this notion of being an engineering and technology company. But during the late 1980s and early 1990s the company began to rethink its self-image as it grew and expanded internationally. It became more financially and market driven and less engineering and technology driven than in the past. For example, in 1996 Honeywell acquired Duracraft, a manufacturer of consumer home products such as fans, humidifiers, and ionizing air filters. More significant changes came about when Honeywell and Allied Signal merged in 1999. The new combined company included commercial automotive brands such as Prestone antifreeze and Fram oil filters. These sorts of product and market changes signaled that Honeywell now saw itself as more than a technology company. Honeywell, what was for eighty years a “controls” company, has been over the past two decades embracing a new self-image as a global conglomerate, an image that has torn at some long-treasured organizational social norms. It held onto its historical legacy, and the Culture that complemented that legacy, for a long time. Core competencies take time, energy, and sacrifice to develop. The investment in particular pieces of infrastructure, development of specific internal process efficiencies, and the amassing of specific knowledge sets create organizational capabilities that allow one organization to differentiate itself from other organizations and hopefully

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profit from that differentiation. Each decision is not only a decision about what to do but also what not to do. The organizational Culture is either reinforced or weakened by each decision. Individuals are not always mere captives of the Culture; they may shape it as well. Some employees have unique positions in the organizational society and thereby wield influence over the Culture. The individual may have a valuable relationship with a key customer, or industry regulator, or sit on an important industry panel. That role bestows the ability to wield greater influence and impact. Some individuals may derive their unique influence from their knowledge and experience rather than their position. These Old Pros will be discussed in depth in the next chapter. Finally, the individual employees in an organization tend over time to self-select, an activity that reinforces the current state of affairs within the organization. Those employees who embrace an organization’s current Culture will tend to stay while those who dislike the current Culture will tend to find employment elsewhere. Over time, the number of resisting employees will decline and the prevailing Culture will be resisted less. Not all Culture influencers are evolutionary. Traumas, the organizational equivalent of earthquakes and erupting volcanoes, befall organizations. Examples include sudden disruptive technology changes, ownership changes, and natural or man-made disasters. Technology disruptors are all around us. The Internet and e-commerce quickly traumatized the retail bookseller industry. The arrival of desktop publishing, inexpensive high quality small printers, and digital distribution capability is dramatically reshaping the publishing industry. E-commerce is allowing an array of niche business such as an antique dealer who handles pool and billiards collectables to build and serve a global customer community. Cell phone technology is allowing rural third-world communities to eliminate middlemen and redefine distribution channels. The list goes on. Organizations struggle to recognize the looming changes, develop an appropriate strategy, shed some of the knowledge manifested in their organizational Culture, and then embed new learning as quickly as possible. Those who adapt well and quickly thrive while those unable to make the necessary changes decline or die. Ownership change is another potential source of trauma. A major acquisition or spin-off can reshape a business unit’s position in the marketplace, driving significant changes. A change of senior leadership, with an attendant change of strategic direction, or leadership philosophy can traumatize an existing Culture. Moving from a private to a publicly held firm, or vice versa, can induce organizational

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trauma. Sometimes the Culture is deeply enough rooted that the change is weathered without significant impact. But if the Culture is weak, or the new ownership is persistent, change occurs. Old lessons are repressed or purged and new lessons are embedded. Disasters can spark sudden change as well. The 9/11 tragedy certainly affected millions of individuals around the world. Lives were lost, families were destroyed, and the ensuing actions led to further bloodshed and rancor. The global airline industry also suffered greatly from this tragedy. In the aftermath, over 80,000 airline employees were laid off in the United States alone. U.S. airlines posted a net loss of over $7 billion that year (Belobaba, 2002). The post–9/11 operating costs for increased security, higher labor costs, and currently higher fuel prices pose significant challenges that have made it impossible for many of the airlines to return to profitable operations even years later. Many of the airlines were struggling before 9/11 but the events of that day have been the death knell for several airlines and will force dramatic changes upon the survivors. Those traditional organizations with deeply rooted beliefs about roles, relationships, and appropriate behaviors have a much more difficult challenge than do younger more agile organizations. At times like this a strong organizational Culture can be a handicap rather than an asset if it causes the organization to behave inappropriately in a suddenly changed environment. Leaders shape Culture. I was once assigned to a leadership position in a troubled organization. They had struggled for years to make a reasonable profit and worse their small customer community had largely come to distrust the organization’s ability to perform. The organization had been operating internally in what some called a feudal warlord environment. The functional leaders behaved like warlords, striving to keep their departmental borders strong and their functional neighbors weak. Such an environment actively discouraged the free flow of information and discouraged the notion of shared knowledge. The senior leadership team had to take extreme measures to replace the feudal system with a cooperative cross-functional perspective. About twenty-five key managers, out of a population of hundred, were assigned new roles in new departments. Key leadership responsibilities were moved between functional departments. Key personnel activities such as performance appraisals and task reassignments were shifted from the functional leaders to the project leaders. All these actions were specifically intended to break down the old feudal loyalties and create an openness to building new loyalties at the business unit level rather than the functional department level.

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This leadership team stayed in place long enough to accomplish the intended outcome of a sustained change of Culture. Leaders embed and influence Culture, sometimes in an evolutionary way and sometimes in a traumatic revolutionary way. They influence it through what they measure, discuss, control, and care about. For example, a newly arrived vice president asserts that he intends to monitor financial performance weekly in order to assure he can provide the latest updates to the corporation. He requires all members of the senior leadership team to attend the weekly one-hour review of the financial status. He requires all functional leaders and project leaders to attend to explain their financial status. He requires the finance department to prepare a weekly financial report including a blow-byblow summary of all acknowledged risks and opportunities. His bias for such frequent and detailed reviews is rooted in the experience of his prior job where cost and revenue estimates varied dramatically daily. Never mind that the new business is a “long-cycle” business model in which financial performance is generally determined a year or more in advance, making significant financial surprises a rare occurrence. The vice president stays around for three years, just long enough to begin to embed this organizational shift toward a more intense financial perspective. Never mind that by the end of the second year the vice president has come to understand that the frequent financial reviews are of very little benefit, the meetings and bureaucracy surrounding them have become a part of organizational routine. After three years, another vice president arrives, with distaste for frequent meetings and a comprehension of the “long-cycle” nature of the business, because he has worked in similar long-cycle businesses. Within the first month he announces there is no need for the weekly reviews and cuts back on the number of financial metrics. He also brings with him a bias that operational leaders should report on financial performance for their respective business units rather than have functional finance people report on the aggregate financial performance. Suddenly, the organization is beset with a changing trend that may, given enough time and leadership attention, modify the budding changes begun by his predecessor. Leaders influence Culture by how they react to critical events. One leader I know views himself as responsible to be an integrator of emotional organizational swings. Individuals may tend to overreact to important organizational news that is often hyped as being far worse or far better than it turns out to actually be when fully understood. A big competitive loss may initially be seen as a disaster but within a few months may be almost forgotten, buried beneath the enthusiasm for

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a new emerging opportunity. A technological breakthrough may be seen as an opening for new and larger revenue streams but turn out to merely lead to yet another unforeseen technical challenge. This leader tries to foster a calm and deliberate reaction to such news events, encouraging a logical and fact-based bias in the organization. On the other hand, another executive I know is a very emotional person who tends to see tragedy in every piece of bad news and reacts accordingly. His organization rides a roller coaster of overreaction and then adjustment as the facts become clearer. The former encourages a calm, deliberate, fact-based environment while the later encourages a fast-acting, exciting, and emotional environment. Leaders influence Culture through the decisions they make about recruiting, promoting, or exiling employees. Those aspiring to leadership watch such decisions closely to learn what behaviors are rewarded or punished and then attempt to mimic or hide those specific behaviors. Promotion from within reinforces the existing Culture while promotion from without weakens or fosters changes in it. The punishment or exile of those who challenge conventional thinking sends a strong message that encourages groupthink and discourages creativity. Leaders influence Culture in several other ways as well. The design of the organization structure influences the relative importance of some functions over others. Organizational procedures such as the frequency of reporting, signature authority level, and number of signatures required, all influence the creativity and entrepreneurship of an organization. The relative rigor of those procedures communicates whether individuals are encouraged to exercise judgment or adhere to specific directions. The design of physical space, facades, offices, and buildings influences how the organization sees itself and wants to be seen by competitors, customers, and the community. The stories, myths, rituals, and ceremonies communicate what gets rewarded and what does not. They also provide a forum to pass on the social norms. Leaders also influence Culture when they make formal statements of organizational philosophies, creeds, charters, missions, and so on. Culture may also evolve naturally in reaction to outside environmental forces. Technology changes may force the organization to abandon long-held practices, to automate rather than rely on personal labor, to shift from a blue-collar to a white-collar workforce, or to rely more on process and less on individual initiative. Regulatory changes may allow new competitors into the marketplace thus leading to a more cost competitive environment and forcing the elimination of some long-held and coveted perks. Organizations may shift on their

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own to a different level of competence—they may devolve to less competence or evolve to greater competence. Culture may also be managed toward change through organization “therapy.” Leadership may decide to launch a purposeful effort to revise the social norms through planned change and organization development, a change to new priorities and focus introduced by a charismatic leader, or the purposeful explosion of accepted organizational myth. A new leadership team was assigned to make dramatic changes at a struggling business unit that had difficulty making financial goals and had many unhappy customers. The business unit also tended to rely on heroes to accomplish major objectives. These heroes would be given carte blanche to “do what it takes” to complete an assignment, often leaving behind a mess of bruised egos, frustrated peers, unhappy employees, grudges, and an array of new crises requiring heroic efforts to overcome. These heroic individuals were wonderful firemen who also happened to be arsonists, creating new fires because of the techniques they used to put out the current fire. The new leadership team set out on a specific program to change behaviors by rewarding those who planned well and kept things running smoothly, by valuing team efforts over individual efforts, and by establishing goals that everyone could contribute to accomplishing. Ownership and the biases imposed by it shape Culture. One example is the aerospace industry where many contractors, including Boeing, Lockheed Martin, Raytheon, Harris, and Honeywell have within them service businesses. These business units provide customers with services rather than products. They may operate a satellite network, or maintain a seismic network that monitors earthquake activity, or operate warehouses, or maintain a fleet of vehicles for the military. These businesses do not invest in new products. Their employees typically work on customer facilities rather than in company facilities. Many of them may have retired from customer organization and have strong allegiance to the customer. The employees typically use specialized customer systems rather than company systems. In short, these services business units are significantly different than the product business units within the companies of which they are a part. Some companies have chosen to keep these services businesses entirely separate from the rest of the company. Some of them have become so separate that they do not even attempt to work cooperatively with the rest of the company on major projects. Leaders at those business units are quick to articulate the “reasons” why such separation is absolutely required to assure the services business can remain cost competitive and customer responsive. Other parent companies have encouraged

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cooperation between their product and services businesses. The leaders of these business units are equally quick to articulate the “benefits” of such cooperation. Ownership biases have influenced the cultures of their respective services businesses. Culture and Knowledge—The Literature What does the research literature have to say about Culture and organizational knowledge management? Allen (1977) described how communication issues between teams in research and development organizations affect their ability to digest technical information and pass it along to other teams. His study of the flow of information within a research and development team designing a new computer system revealed how important that information flow is to success. The study also described the powerful influence of such Culture dimensions as formal and informal organization structures, office configurations, and reward systems on the flow of information. Davenport, De Long, and Beers (1998) conducted a study of thirtyone knowledge management projects in twenty-four companies. They hypothesized eight likely success factors for effective knowledge management projects of which the most important was an organization’s social norms. They asserted, “A knowledge-friendly culture, one of the most important factors for a project’s success, is one of the most difficult to create if it does not already exist.” They described three components of Culture that influence organizational learning: ●

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People have a positive orientation to knowledge—employees are bright, intellectually curious, willing and free to explore, and executives encourage their knowledge creation and use. People are not inhibited in sharing knowledge—they are not alienated or resentful of the company and don’t fear that sharing knowledge will cost them their jobs. The knowledge management project fits with the existing culture.

Brown and Duguid (1998) note that a study of interorganizational work done by Kreiner and Schultz (no date available) suggests “the tendency of knowledge to spread easily reflect not suitable technology, but suitable social contexts.” Handy (1993) describes four broad types of Culture: power, role, task, and person. Power Culture is one in which there is a central power source with influence spreading out around the central focal point. Examples may be found in small entrepreneurial organizations

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or trade unions. Role Culture is another label for bureaucracy where role and job description is more important than the individual filling the role. It is typically found in large institutions. Task Culture is one that is task or job oriented. It is often found in project-oriented organizations such as consulting, and product development. Person Culture is, according to Handy himself, quite rare, existing in some partnerships and small consultancy organizations. The examples above align well with the examples and experiences described earlier. However there is one significant difference. Researchers tend to think of an organization’s Culture as a factor that aids or impedes knowledge management rather than as a knowledge repository and management vessel in its own right. Indeed Culture may be both a knowledge bearer and a knowledge barrier or facilitator. That is to say, it may be an influence on other dimensions of organizational learning but it is also a learning mechanism in its own right. The knowledge it contains is the learned behavior imprinted from recurring or traumatic experiences. That learned behavior is distributed to and imposed on the current workforce. Attributes of Culture Culture has several attributes that make it very difficult to manage. These attributes also influence how capable it is of storing and distributing organizational knowledge. See table 3.2, Knowledge Management Attributes of Culture. Culture stores learned responses rather than the knowledge itself. It is not so much a receptacle for lessons learned as it is a receptacle and disseminator of how the organization has chosen to react in the future to what it has experienced in the past. In effect, the reactive behavior is captured and applied but the underlying context and rationale for the behavior is lost. One might consider this a form of tacit knowledge. Thus, there is little ability to recognize when the behavior should not apply and the lack of context also means there Table 3.2

Knowledge Management Attributes of Culture

Reactive—stores learned responses rather than knowledge Mysterious—reasons for responses are unknown Viscous—difficult to embed or remove knowledge Misleading—contains falsehoods and distorted knowledge Pervasive—affects everyone all the time Source: Author’s Illustration

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is no basis from which to adapt the behavior to future situations. Individuals in the organization may remember for a while why the system is so rigorous and so vigorously reinforced. But, as time passes and people come and go, fewer and fewer individuals understand why they should not reach for the proverbial bananas. They only know that they will be assaulted if they do so. Culture is mysterious. The reasons for a particular group norm may be lost in organizational antiquity; the original five apes may be long retired. The behavior may have arisen when the organization was doing a different type of business. For example, an organization that is used to working exclusively with the U.S. Government and all the very specific regulations may have very structured, documented, and perpetually auditable internal processes that comply with the mountain of government regulations. But, those processes may make the organization entirely too slow and too expensive to compete in a commercial marketplace. This dimension of the organization’s Culture has been built around a special environment and the lessons stored in that Culture may be wholly inappropriate for a venture into business with commercial customers. Consider the example below. The so-called dot-com bubble that occurred between 1995 and about 2001 was a speculative period during which many new Internet based companies suddenly emerged, seemingly had great potential, and then suddenly collapsed, as the market realities were better understood. This speculative bubble surprisingly carried over into several more staid and conservative arenas. Dot-com businesses were forecasting huge demands for high bandwidth global communications capabilities. They envisioned sending massive amounts of voice, digital, and video information to nearly any point on the globe. For example, the Iridium satellite constellation included sixty-six satellites orbiting the earth to provide data and telephone service. There were at the time perhaps a half-dozen aerospace business units occasionally building satellites for commercial communications applications but the Department of Defense, NASA, and NOA essentially drove the business. The businesses expected relatively modest profits but relatively low cost risk because the government customers often bore most of the cost risk themselves. The business requires large investments to design, build, test, and launch a satellite or satellite constellation must all be incurred before the first penny of income is generated through the use of the satellites. Additionally, a launch failure or any one of thousands of on-orbit component failures could make the satellite useless. For example, a $10 electronic component could develop a short that would deplete battery power far faster than the solar arrays

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could recharge them. As a result the satellite would be inoperable, and the entire investment lost. The benefits from such projects may have been worthwhile to the government, and the government was willing to accept the risks of failure, but the contractors were not. The front end of the bubble appeared to be an opportunity for aerospace companies to break free from government regulations and the associated modest profits into a purely commercial arena where customers had fewer rules and the companies could potentially earn big profits from the fast-growing commercial businesses. Most of the traditionally DOD and NASA satellite providers attempted to enter the commercial satellite market. None succeeded for several reasons. First, the bubble was just that and the promised business volume never materialized long enough to justify the major investments. Second, these traditional DOD businesses had little experience with investing their own money in satellites because they had relied on the government to make the heavy investments. So, the businesses were ill experienced to analyze the risks and rewards. Third, the businesses had relied on the governmentmandated quality, procurement, and other systems for so long that the rigor and bureaucracy were a part of the fabric of everyday behavior throughout the business units. No one understood clearly what was just bureaucracy and what was prudent discipline to avoid problems. This led to two different failure modes. Some followed all the traditional internal practices, and as a result lost out on new business because competitors had eliminated those costly practices and could bid lower. Others eliminated practices that then increased the likelihood of significant mistakes or on-orbit failures. Those businesses initially won several projects but eventually suffered huge losses when they had to rebuild or replace too many inoperable satellites. Businesses failed for several reasons but one clear reason was their inability to appropriately adapt their organizational Cultures to the new environment in which they found themselves. The mystery of Culture may also have its roots in the personality and style of prior leadership who leave their imprint long after they are gone. A senior executive who tends to be litigious may over time build a larger and more forceful legal department to deal with the legal challenges, perceived or real. That larger and stronger legal department remains after that leader leaves and, like all organizations or departments, attempts to justify its existence. Thus, the new leader may find his organization drawn into legal conflicts almost in spite of his best efforts to avoid them. Culture has high viscosity—it resists the flow of knowledge into or out of it. It is difficult and time consuming to embed lessons learned,

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sometimes taking years of persistence. The organization must experience the same or similar events time and again before it embeds the reactive behaviors into its collective psyche. Recall how often leaders complain that the organization cannot seem to apply what it has learned but instead keeps making the same mistakes over and over again. The recurring experiences are necessary to drive the learning into the way the organization reacts but recurring experiences take time to enable the recurrence. A particular organization had repeatedly made the mistake of taking on contracts to design one-of-a-kind mechanical devices for satellite payloads and instruments including precision pointing devices, vibration isolation platforms, and bearing assemblies for large rotating devices. These were all custom designed devices that pushed the stateof-the-art of the technologies for materials and lubricants. Time and again they took on such projects then suffered multiyear delays and two, three, or even five times cost overruns. Customers were unhappy and the corporation was infuriated. One savvy senior manager was heard to say after another disappointing project that the corporation had fired one senior leadership team for making such a mistake but their replacements had made the same kind of mistake a few years later and they too were fired. Now a third leadership team had made the same error. Perhaps this time the corporation would leave the leaders in place so they could apply what they had learned about taking on such challenging risks. Indeed that is what happened and the organization did not take on such a project during the next decade. The viscosity of Culture also makes it difficult to remove learning once it is embedded. An organization with a strong and powerful legal team will not easily give it up. An organization with an entrenched bureaucracy surrounding government audits will make every effort to rationalize the need for that bureaucracy even if the amount of government contracting work declines sharply. The reluctance to accept international business may persist for decades after the major fiasco that originally caused the sensitivity to such business. Culture contains falsehoods. As a result, the organization is likely applying lessons learned without even recognizing precisely what they are, and thus without the ability to disregard or adapt them where and when appropriate. As Will Rogers reminds us, “It isn’t what you don’t know that will hurt you; it’s what you do know that isn’t true.” Culture makes the statement as true for organizations as for individuals. Consider an example whose effects were witnessed by people around the world, the Space Shuttle Challenger disaster. The January 28, 1986,

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disaster was technically caused by the failure of a rubber-like O-ring, a device intended to seal a tiny gap for only a brief period. Instead hot gases impinging on the O-ring created a flame that penetrated into the fuel tank setting off an explosion that destroyed the Challenger and killed the astronaut crew. But, this tragic disaster was not solely caused by technical failure. Diane Vaughan, in her book The Challenger Launch Decision (Vaughan, 1996), offers a compelling analysis of both the technical decision making and the NASA Culture in which those decisions were made. Vaughan asserts, “mistake, mishap, and disaster are socially organized and systematically produced by social structures. No extraordinary actions by individuals explain what happened: no intentional managerial wrongdoing, no rule violations, and no conspiracy. The cause of disaster was a mistake embedded in the banality of organizational life and facilitated by an environment of scarcity and competition, elite bargaining, uncertain technology, incrementalism, patterns of information, routinization, organizational and interorganizational structures, and a complex culture.” Vaughan also points out “Decision making in organizations is always affected by how information is sent and received, the characteristics of that information, and how it is interpreted by the individuals who send and receive it.” “Most serious was the discovery that misunderstandings about the most critical technical rule used had contributed to a flawed decision. The temperature specifications had been misread, misinterpreted, and misused—for years.” “The launch decision rule had become dissociated from its creators and the engineering process behind its creation.” “What is important to remember from this case is not that individuals in organizations make mistakes, but that mistakes themselves are socially organized and systematically produced.” In this instance, the NASA culture itself facilitated the suppression of information that could have averted the disaster and instead fostered an environment that facilitated the disaster. Culture is pervasive. It is reinforced by the interaction of subtle and seemingly trivial policies, procedures, and processes woven into the fabric of everyday activity. Consider policies for signature authority levels. There is ample research confirming that quality declines when three or more people are required to sign an approval document. People are less likely to review a document carefully when they know at least two others must approve it. Why? Because they will assume the others have better knowledge or will be more diligent. They also assume the collective decision shields them from personal risk. So an organization with multiple approvals and approval levels assures not

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only delay in approvals but also spreading of accountability to avoid personal risk. Thus, the signature authority process may reinforce an organizational bias toward speed and accountability or toward bureaucracy and avoidance of accountability. In spite of this, the headquarters of a diversified services business implemented a policy requiring four levels of approval for a request for business travel within the United States and an additional two levels for international travel. A typical domestic trip cost the organization less than $2,000 and an international trip averaged about $3,500. The signature approval bureaucracy was reinforcing the Culture of risk avoidance and risk sharing. Other reinforcements included the formal and informal reward system that punished risk takers when they failed and the compliance-training curriculum that emphasized liabilities and personal risks. Leadership’s Role in Fostering a Knowledge Friendly Culture An understanding of the management of organizational social norms and behaviors is well beyond the scope of this book. However, several suggestions for addressing Culture from an organizational learning perspective are offered here. First, senior leadership must acknowledge the existence and influence of Culture and its role within the organization. When people are able to speak of the strength and weaknesses of organizational biases and social norms, they become more attuned to just how Culture affects overall activity and performance. When it becomes less mysterious it becomes more malleable. Leaders can act in several ways to foster such openness. They can talk openly about the strengths, weaknesses, heritage, and mysteries of the current Culture, thus demonstrating that it is okay for others to do the same. They can encourage the senior leadership team to better understand the Culture and how it should change, thus creating a consensus leadership view that will be noticed by the broader employee population. They can lead specific initiatives to accomplish change demonstrating through action and resource allocation that the commitment is real. Second, senior leadership must have a very clear, holistic, and persistent vision of the Culture and of any changes to be made. It takes time and insight to understand a Culture, how it came to be, and its strengths and weaknesses in the current environment. It takes even more time and insight to divine how it must change to meet the anticipated new environment.

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The entire leadership team must clearly articulate and advocate that understanding and vision across the entire workforce. The leadership team must communicate clearly what must be changed and why. They must acknowledge the difficulty in making change. They must persist in the vision for change until the Culture has adapted. The leadership team at Komatsu developed a clear and compelling message about encircling Caterpillar, a message that shaped the Culture for years. Third, senior leadership must consciously manage Culture. The old adage that some people make things happen, some people watch things happen, and some people wonder what happened seems ever so true with respect to organizational Culture. Leaders must understand what the Culture is causing to happen in the organization, they must watch closely to understand its strengths and weaknesses, but most importantly they must make the necessary change happen. Helpful tools and techniques may include periodic organizational health assessments, correlation of those assessments with customer and supplier perceptions, and correlation with employee surveys. Health assessments foster dialogue and increased awareness. They also help leaders understand whether progress is being made toward desired changes. Customers and suppliers provide a valuable outside perspective that may enable the organization to see past its own blinders. Employee surveys can help leadership understand whether the change initiatives are understood and embraced by the workforce. What Lies Ahead Chapter four describes Old Pros, the second dimension of organizational knowledge management. The chapter describes the similarities to and differences between Culture and Old Pros with respect to knowledge management. It also offers insights into how to effectively manage the Old Pros dimension. References Allen, T.J. (1977). Managing the flow of technology. Cambridge, MA, MIT. Allen studied nineteen engineers who evaluated their use of several information channels including literature, vendors, customers, technical staff, and so on in terms of their accessibility and quality. He found that quality of the content correlated closely to frequency of use while accessibility did not. However, he found that the emotional cost of asking someone for help was considered to be high then the source was not used regardless of the quality.

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Belobaba, Peter P. (2002). The airline industry since 9/11: overview of recovery and challenges ahead. A presentation of the MIT global airline industry program. Washington, DC on March 26, 2002. This report outlines the pre- and post-9/11 airline industry and forecasts the coming decade. Brown, J.S., and P. Duguid. (1998). Organizing knowledge. California Management Review 3: 90–111. The authors make a case for the value of social networks, rather than information technology, as effective and productive transporters of organizational knowledge. Davenport, T.H., D.W. DeLong, and M.C. Beers. (1998). “Successful knowledge management projects.” Sloan Management Review 39(2): 43–57. Eight key factors can help a company create, share, and use knowledge effectively. Davenport, De Long, and Beers hypothesize that eight factors lead to successful knowledge management. They are: link to economic performance or industry value, technical and organizational infrastructure, standard yet flexible knowledge structure, a knowledge-friendly culture, clear purpose and language, change in motivational practices, multiple channels for knowledge transfer, and senior management support. They selected thirt-one knowledge management projects in twentyfour companies. Handy, C. (1993). Understanding organizations. New York, Oxford University Press. Handy has written a broad survey of the various aspects of organizations, including motivation, roles and interactions, leadership, power and influence, the workings of groups, and culture. The first third of the book describes the dominant concepts of each topic. The second part of the book addresses each topic with respect to its application in the organizational setting. The final part of the book offers further readings on each topic. The book is a good overview and orientation of the literature of organizations. It does not offer much original. Hofstede, G. (1997). Culture and organizations, software of the mind. New York, McGraw Hill. Although subsequent research has challenged many of his findings (see Punnett and Withane below), Hofstede’s work has been the underlying foundation for many MBA courses and professional seminars on international culture. Perhaps this is an example of a theory that resonates with how we choose to interpret the world, but not with the available research findings. Punnett, B.J., and S. Withane. (1990). Hofstede’s value survey module: to embrace or abandon? Advances in International Comparative Management 5: 69–89. Hofstede’s cultural value research has been both highly praised and severely criticized. Researchers face a dilemma regarding continued use of the indices and instrument (the VSM). This paper examined Hofstede’s framework in three diverse samples to address this issue.

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Hypotheses were proposed for two groups within each sample on the basis of Hofstede’s original results and organizational characteristics. Twenty-one of twenty-four hypotheses were supported, providing support for the Hofstede dimensions. The actual level of scores was, however, quite different from the scores obtained by Hofstede, and this suggests a strong organizational influence on scores. The results of this research suggest that the cultural values measured by the VSM may be useful both in cultural and organizational research but that there is a need for additional rigorous assessment of the VSM framework. Schein, E.H. (1996). Three cultures of management: the key to organizational learning. Sloan Management Review (Fall): 9–20. Schein suggests the alignment of the three cultures (executives, engineers, and operators) is key to effective organizational learning. He argues that the ability to create new organizational forms and processes is crucial to competitiveness and that learning across the three cultures is essential to understanding and implementing those changes. Although Schein’s description of the three cultures is oversimplified and does not apply well to all organizations, he does shed light on the need to manage such cultural differences in any organization. Vaughan, D. (1996). The Challenger launch decision; risk, technology, culture and deviance at NASA. Chicago, University of Chicago Press. Vaughn offers an in-depth yet interesting view of the NASA Culture and its influence on the Challenger Space Shuttle tragedy.

Chapter 4

Old Pros—I Remember When

What Is an Old Pro? I once visited a factory in North Carolina that manufactured radios, the type used by fire departments, police, and emergency responders. The company had an enviable and growing market share and this particular factory had a reputation for rigorous quality control and productivity techniques, enabling them to compete effectively with Asian companies. They had recently won a national quality award and I had gone to see what my business could learn from them. The facility was impressive—spotless and well organized. Stellar quality and productivity statistics were clearly displayed throughout the building, showing not only trends but also comparisons to bestof-industry competitors. Several project teams were hard at work on Six Sigma and Lean improvement projects. The improvement teams included appropriate cross-sections of employees from the factory floor to management and from materials procurement to sales. The esprit de corps was evident everywhere. The management team had adopted an interesting and unique approach to fostering mid-management engagement in the improvement teams, an approach that overcame some social and cultural barriers between the managers and the mostly blue-collar workforce. Six Sigma and Lean practices had originally caught on with senior management and then, due to one particularly influential shop worker, caught on with the factory floor workforce, to some extent bypassing middle management. As a result, improvement teams had in the past found it difficult to get the appropriate managers to engage actively as project sponsors and participants. So, the idea of staging a Six Sigma/Lean “draft” was born. The idea was to create a social

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incentive for mid-level managers to engage more proactively with the factory improvement teams. Here’s how it worked. Draft Day was announced about six months in advance of the actual date. It was to be the day when the improvement teams, typically made up of individual contributors and first-line supervisors, were able to draft managers onto their teams. The draft sequence was determined according to the anticipated value (cycle time reduction, cost savings, quality improvement, etc.) of the proposed projects, the most promising projects and teams getting earlier picks than the less promising projects and teams. Each project team would proceed in rotation until all the teams had their predetermined number of managers selected. The managers became progressively more anxious as Draft Day drew nearer. No manager wanted to be passed over. Some of the more competitive managers even began campaigning to be selected on the more visible and potentially more successful teams. After a couple of years with Draft Days in place, the competition became so fierce that managers took their lobbying efforts to a new level. Some of them developed “trading cards” describing the skills they would bring to a team, their experience, and their participation in past project successes. The idea became such a hit that eventually all managers had trading cards and the statistics on them were often the basis for draft selections. Draft Day completely changed the social and cultural environment surrounding improvement projects. It also institutionalized Six Sigma and Lean projects as an organization-wide initiative rather than just a senior management initiative. But I digress—back to the Old Pros topic. One stop on my daylong tour was in the case preparation room, a place where bare metal and composite cases were cleaned and prepared for painting. The cases were inspected to verify the absence of any metal or composite shavings and to insure all edges were smooth. They were then dipped in a bath to remove any surface contamination. Even the body oil from a fingerprint could create a problem when the paint was applied. After being thoroughly cleaned, the cases were spray painted then dried in ovens. A base primer coat and several topcoats were sequentially applied. Both the cleaning and the painting operations were fully automated. Bulk quantities of cleaning solvents and paint were manually loaded into the machines and computers controlled the process from there. Sample cases were pulled from the line and tested to confirm the process was working correctly. On the day I visited, a small group was trying to determine why the paint was not consistently adhering properly. There were instances

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of paint flaking off the cases during the packaging process. The problem had caused painting production to be stopped for the past two days. The cleaning process had been reviewed. The cleaning solvents had been tested. The drying equipment and process had been tested. Chemists had been unable to find anything wrong with the primer or the paint. The team was stumped. Our small group of visitors was being briefed about the problem when a worker who delivered cleaning solvents and paint from storage and loaded them into the machines came into the area with the regularly scheduled delivery. He walked up to the equipment and pulled the dipstick to determine if more primer was needed, disregarding the troubleshooting team huddled in the corner of the room and disregarding our group of visitors as well. I noticed that he ran his finger across the dipstick, rubbed the primer between his fingers, raised the stick to the light then said loud enough for everyone in the room to hear, “Why are you guys using this bad primer?” There was a long moment of silence. Finally a technician from the troubleshooting team walked over to the worker, took the dip stick, inspected it and said, “Joe, there’s nothing wrong with this primer. The vendor certification is correct. The lab tested it. It’s fine.” Joe was adamant. “No sir. This primer doesn’t have quite the right sheen to it. See, when I hold the dipstick up the primer doesn’t reflect the light quite like it should. This looks just like that bad stuff we got about five years ago when we had customers complaining about the paint coming off the radios. This primer is bad.” The team flushed the suspect primer out of the system, replaced it with primer that Joe said was good, painted and tested some cases, and found the problem seemed to have disappeared. The painting operation resumed after a few additional tests. It turns out that indeed there had been a problem with bad primer five years earlier. The remaining two barrels of that bad primer had been sent to the lab for more testing, testing that never actually disclosed what was wrong with it. That earlier investigation had been suspended for some unknown reason. The two barrels of bad primer had been sitting in a remote corner of the lab, largely ignored, until a house cleaning exercise a week earlier when they were placed in the paint supply area where they “belonged.” Joe had been on vacation the past week and someone else had been loading the cleaning and painting machines. Joe’s temporary replacement knew nothing about the incident of bad primer five years ago. He certainly would not have recognized the subtle difference in the sheen of the primer. He had innocently loaded one of the two barrels

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of the old “bad” primer into the paint machine, and the problems began to appear shortly thereafter. But Joe, our Old Pro in this story, instantly recognized the problem. He had stored away in his brain knowledge that even he would not likely have remembered but for the circumstances that brought the knowledge to mind. It turns out that Joe was the only employee still working in the paint area who had been deeply involved in the primer problem five years earlier. The knowledge about bad primer existed nowhere except in Joe’s memory. As a side note, this experience led the radio manufacturer and the primer supplier to jointly conduct a series of tests that eventually identified a difference between the “good” and the “bad” primer. The subtle difference was known by a few engineers where the primer was made but they had never heard of that subtle difference causing a problem for any users. They assumed it was a benign difference. But, in this case interactions between the “bad” primer and the solvents used to clean the painting equipment caused the flaking problem. This anecdote makes two points. First, it demonstrates tacit knowledge. No one had, and perhaps no one could have reasonably, quantified the nature of the primer sheen. What Joe saw was influenced by the lighting in that particular area, the texture of the surface of the dip stick, subtle characteristics of the primer, and even perhaps by Joe’s visual sensitivity to those subtle differences in the reflection from the primer. The laboratory and the vendor had been unable to detect a chemical or physical difference but Joe spotted it instantly, perhaps because his specific past experience raised his sensitivity to those differences. Second, Old Pros like Joe are a repository of this sort of valuable tacit organizational knowledge, knowledge that neither the organization nor Joe himself may know beforehand that he has. The organization knowledge is there tucked away for future use but we typically rely on serendipity to allow it to be put to use. Joe must be in the right place and the right frame of mind to allow the knowledge to be brought to the surface. Consider a second example of an Old Pro’s involvement in managing organization knowledge. Many years ago, a young manager was given the opportunity to lead a major new project to develop a set of computer chips for use on military satellites. It was his first job as a project manager and his first experience with what was at the time state-of-the-art computer chip design work, called very-high-speed-integrated-circuit (VHSIC) design. In fact, our young manager was in the engineering library looking up the definition of VHSIC when the announcement about

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his new role went out over the facility intercom. He clearly was working on a steep learning curve and would not have survived the experience were it not for his relationship with a particular Old Pro. He immediately began asking his more experienced peers who might have some relevant experience to share what they had learned with him, but they were not very helpful. By coincidence, he happened to overhear a conversation about Frank, an ex-director of engineering who had fallen from grace with senior leadership a couple of years earlier and was now working as a staff consultant. Frank had a great reputation among his peers but had gotten afoul of some corporate political agenda and was now sitting in purgatory. It seems that Frank had overseen a couple of the very first VHISIC computer development programs. Frank, who had always been a bit aloof and cold, had become even more so since his demotion. Even so, our young manager decided he needed to learn what Frank knew about VHISIC technology, about leading high-technology projects, and about how to get things done in this organization. So he started finding ways to bump into Frank, to get to know him personally, and eventually to get him interested in the new project. Frank did develop an interest in the project, and took our young manager under his wing. He never realized that the young manager had purposely worked to tuck himself under the Old Pros wing. The Old Pro proved to be an invaluable resource for technical, leadership, and political knowledge. However, it was Frank himself who insisted that the manager keep quiet about his involvement. Frank was concerned that the stigma from his demotion, and his subsequent relationship with senior leadership would be a handicap to the project if others knew he was involved. There is no doubt the project succeeded in large part because of Frank’s “secret” advice. This is an example of organizational knowledge residing within the mind of an Old Pro but not being made widely available because of organizational politics and personality. Senior leadership had effectively isolated the valuable knowledge and Frank had further isolated that knowledge by the way he chose to react to his demotion. It was serendipitous that the young manager even learned of Frank’s existence and his invaluable experience. The organizational knowledge in Frank’s head became useful, at least for this particular team, in spite of rather than because of organizational dynamics. Most businesses have a few, perhaps even several, of these Old Pros around. They have learned many personal and organizational lessons that are critical to organizational success. They have stored in their

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memories many years of experience that is not available anywhere else. Too often all this valuable knowledge is randomly encountered rather than proactively managed. Research on Old Pros The anecdotal and case history literature often refers to “gray beards,” a sexist term that has recently been replaced by “gray hairs.” Members of an organization can often cite the names of a few Old Pros and describe how valuable they are to the organization. They are mentioned often in the organization development literature and in studies about product development as a critical factor in organizational learning. Sadly, there is little substantive research on Old Pros and how organizations make use of what they know. Adler and Zirger (1998) addressed Old Pros briefly in their study of learning in a research and development organization. They asserted, “Unfortunately, traditional R&D and product development organizations do not learn well from product development experience.” They went on to propose an organization structure that encourages and enhances the role of the “gray hairs” (their phrase equivalent to Old Pros) in fostering better use of organizational knowledge. Their proposed structure fostered a broad program charter on macro product development issues encountered in the development process, tighter association of the gray hair to the program core team, and senior program leadership direct access to the gray hair’s knowledge. They go on to say “it is the presence of the gray hairs that in part distinguishes (the proposed) virtual research and development organizations from traditional structures.” Adler and Zirger cite the Air Force Missile Command (AFMC) as one example of an organization that makes good use of its gray hairs, saying, “AFMC relies on the gray hairs as information sources . . . At the project’s completion, gray hairs typically return to their functional homes and serve as policy makers and disseminators of project lessons learned until new development opportunities appear that match their particular expertise.” The AFMC is representative of organizations that do attempt to make use of their Old Pros. The effort is typically an informal, unofficial, and social one rather than a formal part of the organization and its operating systems. Organizations rely on informal, even casual, acknowledgment of the Old Pros and what they know. Serendipity is a big determinant of whether or not the knowledge gets applied where it can be useful.

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It is easy enough to find similar literature acknowledging the presence and value of Old Pros. However, one is hard pressed to find research about them and their role. There is much more research to be done in order to more fully understand and optimize the role of Old Pros in capturing, storing, and retrieving organization knowledge. Attributes of Old Pros That Influence Knowledge Management Old Pros and Culture are alike in several ways. They are both present in most organizations. They both handle tacit knowledge. They are both too often ignored or misunderstood by senior leadership. Both are present in nearly any organization. A relatively new organization may have an immature Culture and the most experienced employee may have been on the job only a brief time. Yet, some degree of Culture is almost certainly present and someone is considered to be the most knowledgeable about a particular work activity, to be the Old Pro as it were. A new business unit made up of employees drawn from established organizations and newly hired employees may initially be a fragile mix of social norms brought to the new organization, but leadership biases and the daily interchange quickly begin to drift toward mutually acceptable behavior patterns that become the Culture of the new organization. These new organizations will often have a few Old Pros because senior leaders will want to draw on the expertise of such individuals while the organization is developing its infrastructure. Older and more stable organizations tend to have more, and more experienced, Old Pros. Both are repositories of the all-important yet mysterious and fragile tacit knowledge, learning that is difficult or impossible to retain any other way. The Culture and the Old Pros embrace tacit knowledge. Culture imposes the behavior derived from past learning without the recall of specific facts or data, in effect disregarding explicit knowledge entirely. Old Pros certainly possess explicit knowledge but very often it is their tacit knowledge that is most valuable. Recall the anecdote about the worker who observed the sheen on the primer and just “knew” something was amiss even though no amount of laboratory testing had detected a problem. Both Culture and Old Pros are often poorly understood and poorly managed receptacles of organizational learning. Leaders often acknowledge and attempt to shape the Culture, thinking of it as a motivational factor that impedes or encourages entrepreneurship, or attention to detail, or a customer focus, or any other social dimension.

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However, rarely do leaders talk about the knowledge buried within the Culture and being applied daily to decisions across the organization. Likewise, leaders often acknowledge the existence of their organization’s Old Pros but can rarely describe what is being done to proactively take advantage of the vast amount of organizational knowledge buried within their brains. Old Pros and Culture also differ dramatically in how they handle organizational knowledge. One retains knowledge while the other retains only conditioned responses to prior experiences. One can deal with both tacit and explicit knowledge but the other cannot. One stores the learning in an intensely compact way, requiring serious and focused effort to assure distribution while the other distributes its knowledge broadly and persistently. One retains the ever so critical context surrounding the knowledge while the other does not. The ability to retain context and factual data makes the knowledge in the Old Pro’s head much more useful. Culture retains the organizations conditioned response to repeated occurrences; it does not retain any of the context, perspective, or situational facts that would enable the organization to adapt the response to different situations. The Old Pro, on the other hand, is able to remember relevant facts and conditions surrounding past learning that would enable him to adapt the learning to a current and somewhat different situation. Later material will describe some of the ways Old Pros distort and skew what they have learned, but at this point we should simply acknowledge that Old Pros can retain and apply context while Culture cannot. The Old Pro’s ability to handle both tacit and explicit knowledge is a powerful advantage. It enables the Old Pro to retain knowledge rather than conditioned response and to adapt the knowledge to new situations, as described above. Beyond that, explicit knowledge is a useful foundation for new learning. An organization may have been conditioned through bitter experience to never bid on government contracts, but an Old Pro who recalls the circumstances and specifics of those failed contracts may well recognize that the current opportunity is different and represents an opportunity to have a successful government contract. The Old Pro can interpret and adapt the knowledge but the Culture cannot. The most important difference between Culture and Old Pros is one of distribution. The knowledge residing within the Culture is pervasive. Everyone in the organization knows that they do not bid government contracts, or that they do not share information with other departments, or that they must get S&MP Department

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approval before any subcontractor agreements are made. That sort of knowledge is part of the social norms and is reinforced by policies and procedures, by peer expectations, and by senior management. An employee will find it difficult to avoid complying with that sort of knowledge. On the other hand, the knowledge stored in the Old Pro’s brain is isolated from the rest of the organization because it exists in her mind and nowhere else. The knowledge can only be applied if the specific Old Pro who has it is directly engaged in a situation where it may be relevant. So, although the knowledge is richer and more adaptable, it is not readily available. The knowledge resident in the Culture is omnipresent and too often misapplied while the knowledge resident in the minds of the Old Pro is isolated and too often not applied at all. This problem of bringing the knowledge and the need together has several dimensions. After all, Old Pros simply cannot always be available when and where they are needed. We can only capture and apply the lessons stored in Joe’s brain when he is directly engaged in the specific problem that requires his knowledge. The radio manufacturing facility in North Carolina had no access to Joe’s knowledge until he returned from vacation and happened to wander into an area where the situation brought that specific bit of knowledge to the fore. Suppose Joe had been reassigned to work on the receiving dock or operating a machine rather than refilling the painting equipment. He may have never shared his knowledge, or even known consciously that he had the knowledge. The organization may never have learned that Joe had that hard-earned knowledge, instead suffering through relearning the lessons from the past. Another dimension to the challenge is that we may not recognize we need a particular Old Pro, and so may fail to use the knowledge we have. The technician currently replenishing the primer may not recognize the difference in primer characteristics. But, even if someone recognizes the odd primer sheen, that individual may not know that Joe, who now works in another department, has years of knowledge about primers and would immediately understand the meaning of the unusual sheen. So we see that lessons learned are too often not applied because the problem-knowledge connection is never made. Yet another dimension of the challenge is that the Old Pros often do not consciously recognize the lessons they have learned or when they are being applied. Their stored knowledge may only emerge when they happen to come across a specific set of circumstances that evoke some subconscious connection with a past experience. Since no one, not even the individual herself, knows just what lessons are stored in

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her brain, those lessons are of only accidental use to the organization. The knowledge emerges serendipitously or not at all. Finally, Old Pros retire. When Frank decides to spend more time with his grandchildren, he leaves with decades of precious knowledge that will no longer be available to the business. This year the first of the baby boomers will retire, heralding the beginning of a decade’s long loss of knowledge, as more and more of that generation leaves the workforce. Loss of this massive knowledge base may be one of the greatest challenges for organizations in the next decade. Organizations that find a way to better meet the challenge will have a great advantage over those that do not. How Organizations Deal with Old Pros So, how do organizations successfully deal with their Old Pros? How do they manage them when they are present and how do they manage their departure? Here is one example. Honeywell Federal Manufacturing & Technologies (FM&T), a subsidiary of Honeywell International, operates the U.S. Department of Energy (DOE) facility in Kansas City, Missouri, where the company makes electronic, mechanical, and specialty material components for the defense industry. The organization’s knowledge management challenge is extraordinary, in that many of the products and materials are designed and manufactured nowhere else in the world. Certainly the processes are themselves quite unique. More than 3,000 FM&T employees, overseen by a small cadre of DOE employees, currently operate the 141-acre complex. Several of the people working at FM&T are second-generation employees whose father or mother started working at the plant when it opened in 1949 then retired in the late 1970s or early 1980s, and who are now approaching retirement themselves. Several employees have thirty years experience making specific parts using one-of-a-kind machines, tools, and processes. These folks know very well how to do their job, so well that they accomplish the work flawlessly time and again without referring to documented procedures. A lot of what they know has become “muscle memory” or instinctive behavior learned through recurring activity over many years. They often don’t recognize what they know as knowledge that should, or even could, be passed on to others. The FM&T executives have been faced with a large and persistent Old Pros challenge for decades. Here’s how they have dealt with that challenge.

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In the beginning they failed. The executives first viewed the problem of knowledge not being applied effectively as one of poor coordination between the designers and the manufacturing teams. They felt that tighter connections, more appreciation of the others’ challenges, and joint problem solving would lead to more producible products through more repeatable manufacturing processes. The idea was to take some of the “art” out of the processes thus no longer needing some of the expertise buried in the heads of the Old Pros. So they launched intense cross-training programs for design engineers and manufacturing engineers. But they soon found the disciplines were such that the two groups had difficulty relating to one another. They also discovered that some of the processes were subtler than originally thought and could not so easily be simplified or streamlined after all. Success was far more a function of tacit knowledge than of explicit knowledge. So then the FM&T executives tried a different approach. They asked the designers and manufacturing leaders to work with operators and technicians to capture the current processes within simulators and other training tools. The idea was to capture some of the tacit knowledge and make it more explicit. The Old Pros helped design the simulations, used them, and then described how they differed from the real work. They understood how a particular machine may react to different materials and helped the designers incorporate that realism into the simulations. They also described how things “feel” when the equipment is misaligned, or there is too little lubricant, or when any of a number of atypical conditions exist. That information was also incorporated into the simulations and the training. Much like an airline pilot can fly a simulated emergency landing, the people being trained with these simulators could “experience” unusual as well as routine situations. This approach offered several advantages. It effectively transferred some of the Old Pro knowledge into Process knowledge in the form of training activity. It also made tacit knowledge somewhat more explicit, but under controlled circumstances such that the Old Pros could verify the translations were accurate and useful. The approach also sped up the learning curve for new employees because they are able to run simulations over and over without having to interfere with the production lines or use real and expensive materials. The approach offered other benefits. Engineers could try out process changes on the simulation, thus learning about problems and making improvement before they made changes on the production line. The simulations highlighted variables that the designer might not

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otherwise think about our even understand. The engineers could then try out their changes continuing the cycle until they were ready for production. The FM&T executives also invested in Archives, a topic to be addressed in more detail later. These Archives were taken to a much richer and more productive level than a mere notebook or data file. The knowledge was stored on a variety of multimedia applications made readily available to all engineers. High-level process maps gave an introductory systems overview. Video clips were used to capture interviews with engineers explaining in their own words how they understand the process steps and how the materials respond. The clips were connected to copies of engineer’s notes and to other video footage of experts describing how and why they designed things as they did, and more importantly why they did not do things in a different way. The result was an oral and written history that captures some of the rich tacit learning. These Archives have been especially important for processes that are seldom done, perhaps going unused for a few years. Even the operators who are still employed may have forgotten or misremembered some of the subtleties of the processes. This oral history helped bring the process back to full operational status more quickly and with less risk of mistakes. The FM&T team took a truly robust approach to capturing organization knowledge, an approach too expensive for many organizations. But, their approach demonstrates that effective knowledge management techniques do exist, that the knowledge buried in Old Pros’ heads can be captured for others to use, and that the various mediums for storing organizational knowledge can be coordinated and integrated. Perhaps these specific methods and techniques are too expensive or complex for every organization. Even so, many organizations should be able to glean ideas and encouragement to develop their own methods and techniques. Leadership Role in Managing Old Pros So, what might leaders do to improve how their organization manages its perhaps less-demanding Old Pro organization knowledge challenge? See table 4.1, Leadership Responsibility in Managing Old Pro Knowledge. First, leaders should understand that Old Pros are a fact of organizational life and acknowledge them. They will be working across the organization spreading their interpretation of organizational knowledge, an

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Publicly acknowledge the existence, activities, and contributions of Old Pros. Formalize the Old Pros’ role in the organizational structure. Assure the Old Pros’ work focus and priorities are managed for overall organizational benefit. Establish means to encourage knowledge sharing among Old Pros and between Old Pros and other employees. Maintain a living inventory of Old Pro knowledge areas. Invest in capturing the knowledge possessed by Old Pros.

Source: Author’s Illustration

activity too important to be ignored. The knowledge they hold may or may not be put to good use. The knowledge they hold may leave the organization when they leave. Astute managers must appreciate their strengths and weaknesses and facilitate their effectiveness across the organization. Failure to do so minimizes their effectiveness and weakens the ability to apply precious organizational knowledge effectively. It allows a significant portion of the organization’s most valuable asset, its knowledge, to go and come randomly. It may allow minor organizational roadblocks to completely prevent the knowledge from being applied. Leaders can acknowledge that Old Pros are operating in the organization, whether or not they are actively managed. Leaders can treat them as a valuable asset that must be appreciated and facilitated. Leaders can express appreciation for their activities and their contributions. In return, employees will acknowledge them, seek them, anoint them, and respond to them. Second, leaders may give Old Pros a place in the organizational structure. They may be given a title such as “engineering fellow” reporting to a senior executive with discretion to assign them to tasks and projects where their experience is potentially most relevant. Such an approach accomplishes several important outcomes. It formally communicates to the organization the value of Old Pros and the value of their experience to the business. The formal placement in the organization is also a step toward institutionalizing this acknowledged value. Employees may come and go but the organization structure will remain, informing each new employee that the Old Pros are valued in this organization. Of course, structures do change from time to time but they are hopefully durable enough to provide this service. Giving them a formal place in the organization empowers Old Pros to work across different parts of the organization, increasing their

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overall experience as well as their overall utilization. Employees know where to find them. They know who to ask for their participation in problem solving. Giving them a formal place in the organization also acts as a retention device. Old Pros nearing retirement may be flattered by the organizational recognition, may have a personal desire to share their storehouse of knowledge before departing, and may be delighted to have the opportunity to solve problems across the business. Third, leaders can assure the Old Pros’ work priorities are managed to assure they are assigned where they are able to have the most beneficial organizational impact. For example, one government services business was dominated by cost plus contracts in which the contractor is reimbursed for all their costs plus a predetermined fee rate or a variable award fee based on the customers’ satisfaction with contractor support. Over the past four years the organization has been expanding the logistics business in areas where firm fixed price contracts occur from time to time. The former contract structure encourages the workforce to be extremely cooperative with changing customer needs whether or not they were considered in the original contract negotiations. People and systems are conditioned to give the customer what they want. On the other hand, contractors cannot afford to do out-of-scope work under a fixed price contract because it would reduce the company profitability. So they have been entering territory where behavioral norms and systems may be inappropriate. They have mitigated this risk by introducing an Old Pro. George, a veteran of fixed price contracts in the nuclear power industry and the construction industry, became involved in the assessment of every fixed price bid, in the start-up of every fixed price contract the organization wins, and in the review of every fixed price contract problems that arises during the contract. George brings his decades of fixed price contracts savvy to these situations. In effect, the organization has forced an infusion of his tacit knowledge into an area where people and systems are relatively naïve. Fourth, leaders can elect to invest in gathering and sharing organizational wisdom through the use of Old Pros. These experienced employees may be used to facilitate lessons learned workshops at the end of major activities. Those involved in the activity can share their experiences with one another and with outsiders. As a result, the lessons learned are identified, codified, and embedded in the collective memories of the participants. Thus, Old Pros themselves become wiser while other individuals have also captured some of the knowledge, lessening the dependence on a very few Old Pros.

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For example, the U.S. Army conducts After Action Review (AAR), exercises during which participants discuss what was supposed to happen in a mission or action versus what actually happened, why things were different, and what might be learned from the experience. In another example, teams of heart surgeons from leading medical centers observed one another’s techniques, exchanged ideas, and collaborated to develop or improve their methods. As a result the mortality rate fell significantly. (Both examples taken from Davenport and Prusak, 1998.) These sorts of peer reviews are not without their problems. One study (Williams, 2007) pointed out several impediments to successful reviews of this sort. The Culture in most project-based organizations tends to view the learning in one project as unique to that project, thus inhibiting its transfer to other seemingly unrelated projects. The project teams form to accomplish the project goals, then disperse to other assignments. Each individual may carry his own learning with him, but group insights rapidly dissipate into individual perspectives. Lessons learned from a project are typically articulated as unique to the project itself rather than in some broader way that may help others benefit. The learning process itself does not happen naturally and requires management and investment of resources. These findings emphasize how important it is for senior leadership to endorse and facilitate this sort of knowledge building and knowledge sharing. Organizations do not necessarily have to deploy such formal structures to enable Old Pros and to aggregate their knowledge. At Honeywell, the field technicians who work on aircraft electronics on the flight lines do most of their work in relative isolation, diagnosing and repairing or replacing electronics boxes to keep the airplane flying. Each technician carries with him his own set of documentation and notes. But when these technicians get together they spend hours trading stories about unique or subtle problems, the clues to understanding them, and the crafty solutions they worked out. These informal get-togethers foster both individual and group learning. Astute managers recognize the value of these get-togethers and make an effort to encourage them often. Brown and Duguid (1998) describe an example of informal knowledge sharing and knowledge integration at Xerox. The technicians who maintain and repair the equipment typically work alone at customers’ offices. Yet they make it a point to spend time together to share experiences and, in so doing, to share what they had individually learned. Occasionally the technicians would work collectively in ways that extended learning or built new understandings. Brown and

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Duguid described the incident as follows, “an extraordinary scene in which one technician brought in another to help tackle a machine that had defied all standard diagnostic procedures. Like two jazz players involved in an extended, improvisational riff, they spent an afternoon picking up each other’s half-finished sentences and partial insights while taking turns to run the machine and watch it crash until finally and indivisibly they reached a coherent account of why the machine didn’t work. They tested the theory. It proved right. And the machine was fixed.” Such communities of practice are valuable repositories of current knowledge, creators of new or deeper knowledge, and disseminators of that knowledge. Astute leaders recognize their value and encourage them. Fifth, leadership can create an inventory of Old Pros’ knowledge. Many organizations do a periodic high talent review, identifying employees with advancement potential and making specific plans to help foster their growth and advancement. Some organizations have adapted those techniques to periodically identify key personnel with critical knowledge and skills that would be very difficult to capture or replace. Once those individuals are identified, the organization can then create an inventory of the critical bit of knowledge and competencies they possess. Next the organization can develop a plan to mitigate the risk of losing them. The plan can then be monitored and assessed to assure the risks are reduced. Leadership teams may embrace the need for such an inventory when they realize they have an aging workforce, because it is easy to understand the risk when a large and growing percentage of the workforce, often mid-level managers and key long-term staff, is soon going to leave. But, the risk is always present. A layoff may cause a great deal of knowledge to leave the firm, and perhaps flee to the competition. Some critical manufacturing process may be well understood by only a few key employees. Thus, the loss of only a couple of key people could be a devastating loss of organizational knowledge. These key personnel and key knowledge inventories are a practical and useful step toward mitigating such risks. Of course, a lot of what an Old Pro knows is tacit knowledge that cannot be easily documented. Often the Old Pro possesses knowledge that even she does not know exists. But, this practice of a periodic inventory will, over time, expose and extract more and more of that subtle but critical knowledge. Sixth, once the truly critical knowledge and skills are identified, leaders may invest in the appropriate tools and techniques to capture them. The F&MT organization mentioned earlier invested in videos,

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simulators, protégé/mentor pairing, and other techniques to assure their critical knowledge was captured. Leaders may not see the value in such effort to capture and save all the knowledge, but they now at least have the information to enable them to make the cost versus benefits tradeoffs. Individuals versus Old Pros Some may ask why the knowledge tucked away in the minds of the Old Pros is addressed in this organizational knowledge management model but the knowledge in the many other individual employees is not addressed. Indeed each individual in the organization, be they newly hired or a veteran employee, carries around a set of knowledge that gets used on behalf of the organization. Much of it is redundant with what others know and with what is captured in Culture, Archives, Old Pros, and Process, yet some of it is unique and valuable. This knowledge may have first been learned while in school, while part of a different organization, or while part of the present organization. Nonetheless, it is knowledge available to the organization and could be considered an integral part of the organizational knowledge management challenge. Certainly one might elect to add an element that includes the memories of all the employees. One might even elect to replace Old Pros with such an element. The rationale for not doing so is perhaps more subjective, and perhaps one could say more tacit, than not. First, individual knowledge is subject to well-established traditional management techniques from performance evaluations, to training and development plans, to training programs. The research and literature on employee development and training is robust. Second, the overall knowledge management model described here exerts a powerful influence on the content and utilization of the knowledge resident in those individual minds. In a sense the model describes how they are impacted and enabled. Third, individuals operate with their own agenda, an agenda that may or may not include the organization and its benefit as a major priority. Fourth, Old Pros represent an important special subset of individual employees. They possess more of the unique knowledge that may not be present anywhere else. They typically represent the result of significant investment made by the organization to acquire that knowledge. Their knowledge base is likely to be more important to the success of the organization than is the knowledge other individual employees possess. Finally, Old Pros have extraordinary influence on the overall organizational knowledge management competence.

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These factors led to a decision to distinguish Old Pros from the rest of the workforce. What Lies Ahead Chapter five describes Archives, the third dimension of organizational knowledge management. It explains the hope and the reality of what Archives can contribute. It explains why Archives are so attractive. It also explains why they are inherently incapable of more than a modest role in overall knowledge management. References Adler, T.R., and B.J. Zirger. (1998). Organizational learning: implications of a virtual research and development organization. American Business Review 16(2) (June): 51–60. Adler and Zirger propose a virtual R&D organization structure that facilitates organizational learning in three ways. First, it allows the Old Pros (they call them “gray hairs”) to engage actively as a team technical resource. Second, the team is cross-functional, fostering the sharing and recall of learning from project to project. Third, customers are involved more directly in the R&D process. Brown, J.S., and P. Duguid. (1998). Organizing knowledge. California Management Review 3: 90–111. This article advocates a few radical notions including, “So it’s not surprising to hear that cyberspace has served notice on the firm that its future, at best, may be only virtual.” Nonetheless, they do offer some insights about the value of Old Pros. Williams, T. (2007). Post-project reviews to gain effective lessons learned. Philadelphia, Project Management Institute. The author documents a research project that identified some of the organizational difficulties that inhibit post-project reviews from being effective and recommends approaches to making the learning process more successful.

Chapter 5

Archives—It’s In Here Somewhere

What Is an Archive? The U.S. Air Force operates several individual satellites and constellations of satellites orbiting the earth. The Global Positioning System (GPS) satellites enable precision navigation for the military, for our automobile navigation systems, for tracking wildlife, and for an evergrowing number of previously unimagined purposes. For example, some countries are embedding very small GPS sensors in relics and other national treasures, hoping that if the items are stolen it will be possible to track and retrieve them. Another such satellite constellation is the Defense Satellite Communications Systems, a group of nine satellites that enable communication between military units. The Defense Meteorological Satellites provide weather information to deployed military forces and to strategic planners. Other satellites detect and track missile launches; recall the tracking of the SCUD missiles during the Iraqi conflict in the early 1990s. These orbiting satellites and constellations are controlled from two command centers in the United States and several remote-tracking sites around the world. The equipment at these command centers and remote sites is a patchwork of original equipment, some of it more than thirty years old, and upgrades that have occurred from time to time. The equipment includes everything from fifteen-meter-wide rotating antenna dishes, to electronic boxes, to satellite command and data collection software. Some of the equipment is so old that documentation does not exist. Some equipment has been modified so many times that few people fully understand its current design or even how to operate it. If not for the Old Pros, these systems would soon become inoperable.

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The command centers and remote sites are operated and maintained by a combination of Air Force and defense contractor personnel. One contractor team is responsible for the maintenance, repair, and modifications at the remote tracking sites. The team includes about 600 people who travel to the sites to perform periodic maintenance, repair or replace broken equipment, and design and install major changes or improvements to the overall system. This team relies heavily on those Old Pros as a source of systems knowledge. The contractor team and their Air Force customers too often find themselves struggling to relearn or effectively apply what they once knew about the systems and the equipment of which they are composed. The team suffers perpetual loss of critical knowledge, as the Old Pros retire or leave. The customer team is dominantly composed of Air Force officers who rotate through their assignments about every twenty-four months. The contractor teams mitigate the loss of knowledge by hiring a few of these military retirees to work a few more years as civilians. Even so, system knowledge perpetually slips away as people leave the community. In 2005, the contractor team decided to implement a so-called “lessons learned” system, a system that evolved into a hardware and software platform repository of important systems knowledge. A team of Six Sigma process trained engineers and technicians was assembled and given a charter to find a way to capture knowledge gained from current major projects and make it available to future project teams. Note that their charter was not to try to capture knowledge learned in the past, merely to capture new learning as it occurred. They developed an approach that included three fundamental elements. The three elements were, in their words, “input lessons learned,” “extract lessons learned,” and “use metrics to monitor system usage and gain insights to improve the lessons learned system.” The input element was further broken down as “recognize a learning event,” “access the system,” and “enter the learning.” The extraction element was further broken down as “recognize an opportunity to apply prior learning,” “access the system,” and “query the system for relevant information.” The metrics were supposed to track the amount of information stored and how often the system was used to seek information. The team, being good systems engineers and project managers, characterized their task in such a way that it could be addressed through currently available hardware and software tools. They decided to adapt ClearQuest, an IBM Rational Tool, typically used at the time by systems engineers to track design changes and to track

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action items. (Isn’t it odd that we usually conclude our problems are best solved by the tools we have at hand? When you are holding a hammer every problem seems to be a nail.) The tailored ClearQuest application interface provided for data entry, searching through the lessons learned database, and gathering lessons learned metrics. Lessons were evaluated as value-added and non–value-added—it was unclear who decided whether a lesson was value-added or what criterion should be used. Individuals were responsible for entering items into the system. Project and team leaders were responsible for approving lessons learned inputs, identifying corrective actions taken at the time of the event, and communicating the lessons learned to other team leads. Project teams were supposed to search the database for projectrelevant knowledge at four major project milestones or events. The four key points were during preparation of the project description, during the project proposal approval process, during the workplanning phase at project start-up, and when any significant technical or administrative issues might arise. The database was supposed to be updated at the end of each project to capture any new learning. Finally, the benefits of the lesson learned were to be documented to capture positive impacts on cost, schedule, and performance. This last step was seen as a way to demonstrate later that the system was cost beneficial. The project costs were nontrivial. It took about nine months and 4,200 labor hours to develop and deploy the system, at a cost of $250,000. The recurring hardware and software costs were about $25,000 per year. A manager and administrator spend about onequarter of their time maintaining the system at an additional recurring cost of about $50,000. A nonrecurring effort of $250,000 over nine months and a recurring cost of more than $75,000 per year, plus any future changes to accommodate hardware and software obsolescence was not insignificant for this group. But this customer and the contractor team felt the investment would be well worth the cost. After all, employees often told one another anecdotes about how failure to apply existing knowledge had cost the program millions of dollars. A system that proved useful would more than pay for itself, and quickly. So, what did they get for their money and effort? After eighteen months there were about 190 lessons learned records entered in the database and two years late the number had declined to 141 records— yes declined. There was no available data on the number of times the systems had been accessed (that metric was never implemented) but

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over 80 percent of the contractor and Air Force personnel working on the project, when asked, did not even know the system existed. The few who were aware of the system asserted it had not been successful, with one exception. The manager responsible for originally creating the system asserted it had been beneficial, although even he admitted it had recently fallen into disuse. No one, not even the manager who created and still defended the system, could cite a significant example of knowledge being retrieved from the system and then being applied to solve a problem. What did they get for their time, effort, and money? Not much. What went wrong? Here’s how the manager currently responsible for the software system answered that question. “The project champion relocated to another business team and interest in the system disappeared with him. The system has seen only spotty use because of mission execution priorities, the press of day-to-day work, and a lack of management focus on capturing lessons learned. The volume of entries has been less than hoped for because of resistance to change, reluctance to take on and keep up with new software systems, and because some feel the ClearQuest interface is hard to work with. This also could potentially be attributed to insufficient manager emphasis, competing employee activities, reluctance to submit information that may be perceived as being critical of other departments, and simple unfamiliarity.” A resounding indictment! That same manager described how shortfalls in the overall lessons learned process might have also contributed to nonuse. His statement quoted here makes the point in spite of its apparent confusion: All employees are charged to use the system to record the lessons they learn but no central agency or individual is charged with responsibility for overall management. The Process Owners Group is charged with implementing changes to Work Instructions and processes in response to lessons learned but there is no documented periodic mechanism in the Work Instruction forcing review and closure into a process revision. While an Office of Primary Responsibility (OPR) for the Work Instruction is identified, recurring reporting requirements to drive accountability are decentralized. Within the projects arena a documented review of lessons learned is part of the Program Management Record Book. Additionally, some Government Work Authorizations now include a requirement for lessons learned. Informally, when new projects are started, the team is generally briefed on the lessons learned process and a report is sought at the end of the effort [This statement was apparently incorrect because few employees were aware the system existed.]. Metrics are available from ClearQuest but they

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are not included in quality reviews, leadership meetings, or process management group meetings at this time. The Engineering Review Board (ERB) process provides an excellent model for lessons learned oversight, but the ERB processes focus on engineering review and do not specifically address lessons learned outside of engineering.

In short, the lessons learned system was not fully integrated with the other contractor and government systems or the work processes. The lessons learned system described was an attempt to build an Archive system. Thirty years ago the solution may have been composed of log books in which engineers recorded observations as they went about their work. Today, although such a system is typically implemented via software and computer hardware, much like the system in the example above, it very often is merely a digital rather than written storage system that is in many ways like the engineering notebooks used decades ago. The knowledge is transposed into a written or recorded format then coded and stored where it can be later retrieved. More elaborate systems may include video clips and cross-correlated materials. Some form of documentation is present in nearly every organization. Auditors may require documentation trails. Customers may require test documentation. Higher corporate levels may impose documentation requirements. Industry consortiums may ask for material to feed aggregated metrics. Operating procedures may be written down for training purposes. Certainly, documentation is omnipresent in organizations and at least some of it contains organizational knowledge. But these informal or ad hoc repositories do not rise to the level of being an Archive. An Archive exists for the specific purpose of storing and retrieving what the organization has learned. It does not exist to provide information to auditors, or to meet customer requirements, or to feed the senior management “bear,” or to meet industry consortium obligations. It exists to capture learning, retain it, and then make it available when it can be useful. An Archive should include three parts. The first and the simplest is the software and hardware repository in which the transcribed knowledge resides, along with the associated administrative processes for maintaining that repository. The second is a discipline and methodology by which knowledge is accurately and usefully transposed into the written or recorded format to be saved in the repository, perhaps modified, and eventually purged from the repository. Note that the lessons learned Archive described above did not include this second part, a shortcoming that by itself may well have doomed it to

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failure. The third is the means by which knowledge can be retrieved when appropriate. Developing an Archive system The development of an Archive repository is more challenging than might be assumed. It includes decisions about defining the system requirements, what hardware and software platforms to select, compatibility with existing systems, installation and integration of the selected solutions with existing systems, user training, functional department(s) responsibility for the system and its usage, assessments of how well the system is performing against its stated purpose, and responsibility for modifications and upgrades. Sadly, many implementations focus almost entirely on the core software and hardware, paying very little attention to the other two equally, if not more, important parts of the overall system. The reason is that the hardware and software part of the challenge is relatively mechanical—make a guess at how much information must be stored, how many people may enter information, how many may simultaneously retrieve information, select vendors, install the system, and do some training. These sorts of questions can be understood and answered. The system requirements for the repository can be relatively straightforward. A project team can specify how much information will be stored, specify the storage demands by media types (text, narrative, video, etc.), and establish requirements for future expansion. The team can establish the number of people who will have database change authority and data entry authority. They can establish the number of people who will have access to the contents. They can establish whether the data can be accessed remotely and what levels of security are appropriate. They can determine what interfaces are required to other systems in the organization including the intranet, existing data files, project or functional documentation, and so on. A diligent and knowledgeable team can define the requirements and there are dozens if not hundreds of consultants who would be delighted to help any organization with the task. The organization can also readily procure a set of software and hardware that meets the specifications. Dozens of companies offer knowledge management software solutions either as part of their overall enterprise resource planning (ERP) system, or as a stand-alone tool. The available software can be as simple or sophisticated as the organizational checkbook can stand. These vendors can define the

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hardware platform and interface requirements or they can purchase the hardware, integrate the software, and deliver a turnkey solution. Installation and integration may be relatively simple or quite complex. A 500-person construction firm may buy a canned database management tool, install it on a PC, and tell people in the field how to access it. On the other hand, the database management tool in use at a 5000-person organization may have to interface with a dozen other tools, be completely redundant, support multiple sites, and have robust firewall protection that complies with stringent corporate guidelines. The repository part of an Archive requires training for at least two groups, administrators and users. Administrators must learn how the software works, how to add or delete authorized users, and how to manage the contents. They must also manage the interfaces with other systems. For example, the field service organization may have an existing database housing information from every maintenance and repair visit. That information may complement the proposed knowledge management system, but only if the interface between the two is relatively transparent and if common terminology is established for the contents of the two different databases. Of course, both systems will change over time as software and hardware become obsolete, systems users add new features, and software updates create unexpected problems. Archive users must, at the very least, learn what the repository contains, how to access it, and how to search the contents. They may also need to learn how to enter new bits of knowledge. The training must be recurring to accommodate new employees, to implement system changes, and to explain changes that affect the users. Organizations that deploy Archives typically have some level of success with specifying, buying, and installing a repository. Training, on the other hand, is very often poorly addressed. Administrators are often involved in determining specifications and in installing the repository and so they tend to emerge with adequate knowledge to do their jobs. Users however, are too often subjected to “hit-and-run” training via e-mail with an attached set of Power Point charts and a number to call for assistance. Users should be given an opportunity to ask questions and get immediate answers, to make mistakes and get immediate coaching about their errors, to hear other people’s questions and the answers thus learning things they might not have thought to ask, and to establish relationships with instructors so they have a friendly source for help in the future. These social interaction dimensions of training are simply not possible with a set of charts attached to e-mail.

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Now we reach the point where even the simplest part of an Archive, the information repository, too often falls apart. Assume the organization has just purchased, installed, and adequately trained its workforce on the new repository tool. Now some part of the organization must be responsible for keeping the system operating and encouraging its use. Should this be an IT responsibility because it involves a software package installed on the computer system? Should it be an Engineering responsibility since most of the users will be engineers? Should it be an HR responsibility since communications and knowledge sharing is an HR “thing”? Who will hold the budget for the software lease? In which organization will the administrator reside? Who will assure that new employees are trained? Who will be accountable if the training is inadequate? How will the training adequacy be determined over time? All these questions and more must be addressed to assure the new Archive, that in this simple example is nothing more than a database management tool and some training, is actually kept available for use. Organizations too often fail to address these questions thereby assuring the early demise of the Archive. Assuming these last hurdles have been cleared, the organization hopes to have a very simple Archive in place, have the workforce trained in its use, and have responsibilities aligned to assure it remains operational. This is also the point where most organizations declare victory asserting they have deployed a robust knowledge management system that will help them capture and use what they know. But organizations that stop here very often find a year or so later that the system is unused. Why? Let us assume the organization has overcome all the previously described hurdles and now has a simple Archive deployed and in use. How well is it initially performing against the stated goals for the system? Is it providing the improvement in organization knowledge management that was envisioned? Is the initial performance being sustained over time? Is the organization continuing to get good value for its investment in the Archive? What data do we gather to answer these questions? How frequently and at what level is the data reviewed? Who is responsible for acting on the data? The Air Force effort to deploy a “lessons learned” system described above highlights what happens when these questions are not addressed and solutions are not deployed. The organization needs to deploy a set of metrics, a review schedule, and accountabilities to initially and then periodically assess the performance of the Archive. Metrics should address utilization (number

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of queries per month, number of people making queries per month, number of queries per person per month, number of new users per month, etc.) and availability (system uptime percentage). They should also address user satisfaction via periodic surveys. Surveys asking about ease of system use, availability of information sought, value of information sought, and so on should be collected and reviewed quarterly. Managers should be surveyed periodically to assess their perceptions of the value of the Archive because a disenchanted supervisor or manager can discourage dozens of employees from using the system. Finally, data should be reviewed periodically to assess the cost of the Archive versus its relative value to the organization. These metrics accomplish several purposes. They communicate to the organization the commitment to the Archive is serious. Over time they communicate that the commitment is continuing. They provide feedback on utilization and benefit. The reviews of the metrics provide forums for discussion of knowledge management competency, not only with respect to Archives but with respect to other aspects as well. Even a simple repository is not stagnant. Software upgrades must be deployed. Hardware platforms must be replaced. New users need training. Interfaces must be adapted to address user feedback. Metrics may uncover the need for system changes. New capabilities must be incorporated to adapt to changes in what the organization is learning or needs to learn. Some part of the organization must be responsible for identifying changes, evaluating them, and incorporating those deemed beneficial. This is the point where all but a very select few organizations declare victory. They have established a repository for what they know, they have deployed initiatives to encourage its use, and they have established the bureaucracy to manage and maintain the system. But the Archive deployment task has just begun. Recall that I said earlier an Archive has three parts, a repository as described above, a transposition and input capability, and a retrieval capability. Let’s move on to the transposition and input capability. Accurately transposing a fragment of organization knowledge can be very difficult. It requires shared understandings about what constitutes knowledge worthy of being retained, methods and disciplines for agreeing what lesson was actually learned, and methods and disciplines for agreeing on the words, data, video, or other material that accurately capture the learning. These occur as social norms and consensus-building agreements more than as formal processes. Even so, they are perhaps the most critical to success.

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Transposing explicit knowledge—recall that typically less than 20 percent of what the organization knows is characterized as explicit knowledge—can be relatively straightforward. Someone may decide to retain the calibration data from each piece of manufacturing equipment. The data may be coded for entry into a database and the database may be accessed via the knowledge management system. Someone may decide to retain sales history information hoping to use it to predict seasonally adjusted sales, better match production output with future sales, and thus reduce scrap and inventory costs. In these examples, it is easy enough to agree on what explicit knowledge is to be stored, in what form to store it, and how it might be usefully retrieved. Even so issues arise and must be addressed. What test equipment calibration information should be retained? Should the database include only the equipment settings before and after calibration? Perhaps it would be useful to include the name of the technician doing the calibration work, the serial numbers of the calibration instruments, the time interval since the last calibration, data about equipment wear or deterioration, and a host of other bits of explicit knowledge that might be helpful in the future. What sales data should be retained? Do we need the name of each customer or will anonymous sales figures serve our purpose? Perhaps we do not need the individual sales data to project future sales volume but will we later want that knowledge for some other purpose and should we save it just in case? It is important to have an approach for raising and addressing these questions before knowledge is codified and stored. This is also the step where tacit learning is transposed into explicit learning, or perhaps more accurately where it is attempted. More often it is the point where rich and valuable tacit learning is distorted and perverted into something much less useful, or even harmful. More will be said later about the challenges of transposing knowledge into a format compatible with the Archive repository. For now, let us just acknowledge that it is very difficult to codify tacit knowledge without destroying or perverting it, and that this difficulty is at the root of why Archives are so often unsuccessful. The retrieval piece of an Archive system includes the capability of searching the repository for useful and relevant learning. It also includes responsibilities for keeping people aware of the Archive system, identifying ways to make it more user friendly, and sharing success and benefit stories so that retrieval actually occurs across the organization. There must be some mechanism encouraging people to search for answers in the new system, to enter new learning in

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the system, and to adapt the knowledge resident in the system to the ever-changing environment. There are many techniques to encourage such activity. Organizations can choose to highlight examples of frequent and successful user experiences by widely publicizing the information. They can choose to reward users, thus encouraging others to become users. One organization conducted a periodic lottery for those who used the system—more frequent users had more opportunities to win. Organizations can set and monitor goals by department or function to encourage initial usage. They can establish user groups to foster peer-to-peer learning. They can establish feedback loops to understand problems with the information content, the system performance, the user interfaces, or the training, and then respond rapidly to fix them. Such actions help encourage employees to get to know the system. They also help uncover problems that might otherwise discourage its use. In the absence of such actions, the Archive may well fall into disuse. The Archives Track Record Is Poor Consider the following example: The National Aeronautics and Space Administration (NASA) have attempted to deploy effective knowledge management systems, what they called lessons learned systems, for several years. One NASA group, the Earth Observing System (EOS) Program Office at the Goddard Space Flight Center in Maryland conducted a one-year experiment to improve their lessons learned process. That experiment emphasized two automated information retrieval systems, the Reusable Experience with Case-Based Reasoning for Automating Lessons Learned (RECALL) and the Lessons Learned Information System (LLIS). Their experience concluded that there was limited sharing across different projects, it was difficult to retrieve the “right” lessons at the “right” time, and there was a reluctance to share negative lessons. They cited cultural history and management practices as specific barriers to learning, including such cultural phenomena as “silo” thinking within areas, the value placed on personal technical expertise over knowledge sharing, and overreliance on explicit rather than tacit information (Goddard Space Flight Center Report, 2003). A 2003 study of knowledge management practices in the construction industry (Carrillo, Robinson et al., 2004) reached the conclusion that organizations deployed knowledge management tools and practices in an attempt to share the tacit knowledge of key employees and to disseminate best practices. It found that over 62 percent of the

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firms used some sort of database system and that nearly 40 percent used a document management system of some sort. However, none of those organizations used data mining or data warehousing tools to facilitate using those databases. Most interesting is that the study also emphasizes that these IT tools “do not adequately address the difficulties often associated with managing tacit knowledge.” In short, the organizations somewhat consistently deployed an inappropriate and ineffective tool. The American Productivity & Quality Council research has determined that although explicit knowledge may be dealt with through self-service portals and directories, tacit knowledge requires a great deal of human engagement to be successful. Tacit knowledge demands facilitated transfer via best practice teams, group sharing, process masters, and the like. Too many organizations deploying Archives are unaware of the critical need for these complementary social activities and they do not deploy them (APQC, 2005). Davenport and Prusak describe three basic types of knowledge repositories, or what is called here Archives: external knowledge (competitive intelligence reports), structured internal knowledge (research reports, product oriented marketing materials and methods), and informal internal knowledge (discussion databases full of know-how, sometimes referred to as “lessons learned”). Davenport said, “Although machine-engineering purists might argue that we just haven’t used the technology and tools of information design correctly, forty years of failure is forty years of failure. The tools most frequently employed to design information environments derive from the fields of engineering and architecture; they rely on assumptions that may be valid when designing a building or a power generator, but rarely hold up in an organization. The sheer volume and variety of information, the multiple purposes to which it is put, and the rapid changes that take place overwhelm any rigorous attempt at central planning, design, and control” (Davenport and Prusak, 1998). They too make a compelling argument that Archives are insufficient to meet organizations’ knowledge management needs. The research literature confirms my own experience that Archives are too often deployed in a naïve attempt to handle something that is poorly understood—tacit knowledge. The deployments also often fail to consider how the organizational Culture influences how the Archive will be used. Why are Archives so often deployed if they are so rarely successful? The answer is that Archives typically emerge as a result of management frustration. Some senior executive may become upset that the

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organization seems to have repeated a preventable mistake, costing a lot of money and upsetting a customer. That executive may then decide to capture, store, and retrieve lessons learned to prevent such a recurrence. Consultants offer to relieve the executives’ frustration by offering a specific, easy-to-comprehend, and apparently ready-todeploy solution—a quick fix if you will. The explosion in IT capability has made this perception seem more achievable. The maturation of databases and search engines over the past decade has offered hope that more powerful computing capability would enable us to build Archives that can more effectively store and retrieve organizational knowledge. But so far there has been little sustained success. The Problem with Archives I have personally witnessed six attempts to deploy Archives, yet only two were ever actually deployed and both systems fell into disuse within two years. The research suggests my experience is representative of what has happened across most organizations. The reasons for failure in those six instances I observed had little to do with the tools that were deployed, and more to do with complex human interactions when knowledge was entered into a system, and again when it was retrieved and interpreted. The root cause is often grounded in the fact that such systems and tools are inherently incapable of dealing with tacit knowledge. The effort to reduce tacit knowledge to something compatible with the tools nearly always skews the knowledge and separates it from its vital context. The lack of complementary social mechanisms inhibit use of the stored knowledge. The following are typical social barriers to addressing tacit knowledge. As you read you will be reminded about the ways in which individuals deal with learning, knowledge, and remembering. You will see that individual traits have a powerful influence on how, or even whether, Archives are a useful organizational knowledge management tool. Some significant problems are discussed below. Problem #1—Whose Knowledge Should Be Kept? It is a challenge to determine whose lessons should be archived. We each have a different personal rationalization for the experiences we live through together. We each interpret events, relationship, and causation subjectively through very personal filters, including past experiences, training, worldviews, and ambitions to name only a few.

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Our individual past experiences cause us to rationalize current events and causations in different ways. A production manager who previously worked on a line with recurring problems with equipment calibration will be inclined to think a current problem in a different factory is related to equipment calibration. On the other hand, a manager who worked in a plant with recurring raw material problems will look first to material issues as the cause of current problems. This particular challenge often occurs with Old Pros who may overgeneralize their personal experiences, attempting to apply them where they are not relevant. Two Old Pros with different experiences may have a passionate disagreement about the lesson to be learned from a current situation. In these situations power politics or individual passion may determine what version of learning is saved for future use, a poor criteria indeed. Our training also influences how we interpret events and causation. Consider this example: A team of engineers had designed an aircraft navigator simulator, a ground-based system for training navigators how to use instruments in flight. The $22 million contract called for the delivery of twenty simulators. The project had been under way for two years when Frank, a newly graduated engineer, joined the project team to test circuit cards before installing them in the simulators. About four months later six simulators had been assembled, none were operational, and $18 million had been spent. The project was in serious financial and technical trouble and a new manager was brought in to address the problems. Two months later the new manager told Frank that he was now assigned to “help out” Jim, the last remaining member of the original design team and the current leader of the team testing the simulators. Four weeks later the manager informed Jim that he was to be reassigned to another project across town and informed Frank that he was now the new test leader. Frank was shocked by the news and intimidated by his new responsibilities. A few months later Frank was more shocked than anyone that things had begun to improve. The build and test time was shorter. Equipment was failing less often. Simulators were being shipped to the customer and they seemed to be working well once installed. Several months later, Frank, while having lunch with the manager, asked “Why did you put me in charge of the test activity? We really needed Jim’s design knowledge and I didn’t know what I was doing for quite a while.” The manager replied, “Sometimes what we know gets in our way. Jim understood the design in great detail. Because of that, every problem was in his mind a potential design problem; perhaps the circuit design was stressing the components,

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perhaps there was a timing problem with the signals, perhaps there was an aging problem with components. Jim approached every failure as if it required an in-depth design analysis. You on the other hand weren’t encumbered with that design knowledge. When something failed you tried to find the bad component, or poorly seated circuit card, or broken wire then repair or replace it and move on to the next problem. Jim’s training conditioned him to look for design problems while yours conditioned you to look for production problems. We had more of the latter and very few of the former. Jim was always looking for the infrequently occurring problems. You were conditioned to look for the more frequently recurring problems. So, you were more productive than Jim.” Our individual worldviews about how life works also influence how we understand events and causation. An individual who tends to believe in powerful behind-the-scene forces and conspiracies will interpret outcomes as having been manipulated in some way and will rationalize the underlying causes of an outcome accordingly. She will embrace a logic that fits with her conspiracy view of the world. On the other hand, another individual may view the world as chaotic and significantly beyond the control or influence of any behind-the-scenes schemers. He will tend to discount any underlying cause for a particular outcome and embrace a logic that fits his “stuff happens” view of the world. These differing worldviews reinforce different perspectives about what is to be learned from a situation. Which one should prevail? Can both be retained? Would retaining both be helpful or hurtful to future users? Personal objectives also influence how events are interpreted. Suppose a new software system is deployed and subsequently results in a factory shutdown. The leader responsible for deployment may see failure as due to a lack of top management support, of workforce resistance to change, or flaws in the software. Senior management may see failure as due to a lack of adequate team planning or a lack of team leadership. Functional department managers may see failure in a flawed approach that caused the wrong software solution to be purchased, dooming the project from the start. It may be impossible to arrive at a mutually agreed truth about what has been learned because all these biases and fears in the air skew everyone’s perspective. If so, who decides what lessons are to be learned from the experience? Watzlawick (Watzlawick and Bavelas, 1967) describes an experiment conducted by Bavelas demonstrating that explanations may be more related to the social dynamics of a group than to the facts present. Each subject was told to formulate concepts about a gray abstract

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image on a card. The subjects were grouped into pairs who were seen separately but concurrently. One of the two subjects was told eight times out of ten that his interpretation of the card was correct while the other subject of the pair was told he was correct only five of ten times. The subject who was more often “correct” tended to keep his concepts simple, while the subject who had more “incorrect’ conclusions tended to conceive more and more complex concepts to describe the image on the cards. Even so, when the two subjects were brought together to discuss their conclusions, the subjects with the simpler concepts quickly agreed that the more complex explanations were correct. So, even though the subject with the simpler descriptions had been reinforced more often, he tended to defer to the more complex descriptions. Such human behavior cannot help but influence what “knowledge” is gleaned from an organizational experience. These dilemmas raise several questions. Who decides just what lessons learned should be retained for future reference? Can, or should, all perspectives be saved? Will such information be useful or confusing when it is retrieved? Do the relative power positions of the individuals involved impact what lessons are accepted? Is the consensus of the lessons learned worthy of being saved or merely a result of the relative power of those involved? These questions, and the difficulty in answering them, suggest why it is so tough to determine just what lessons should be retained, and why knowledge stored in Archives may go unused. Problem #2—Learning Is too often Not Accurately Captured Assume for a moment that there is a clear consensus about just what lesson was learned from an experience. Assume both Old Pros, the design engineer and production engineer, agree because their personal agendas happen to be aligned that day. Or more kindly, assume everyone is completely unbiased, completely logical, and has the same broad experience base enabling them to interpret events in the same rational way. Now someone is faced with the dilemma of choosing the specific words and data to capture that mutually agreed learning. The perspective of the individual assigned to document the learning colors that mutually agreed-to bit of knowledge. Will the author include enough information, background, and perspective to capture the knowledge accurately, completely, or clearly? Will he omit a critical underlying assumption? Will his language capture the knowledge appropriately?

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Table 5.1

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Same Words but Different Meanings

Statement

Almost certain Highly likely Very good chance Likely Probable We believe Better than even We doubt Improbable Unlikely Probably not Little chance Almost no chance Highly unlikely Chances are slight

Range of Interpretations (in Percentage) 60–100 60–100 60–100 60–90 60–90 60–100 60–70 20–40 20–40 20–40 20–40 20–30 5–10 5–10 5–10

Source: Data derived from results of a 1989 study by Reagan et al. cited in Vick (2002) as well as a study by Chew (2006)

A single word or descriptive phrase like “unlikely,” “probable,” or “highly likely” can have quite different meaning to different individuals. Table 5.1, Same Words but Different Meanings depicts a range of individual interpretations of some typical descriptive phrases. The table derived from the results of a 1989 study shows that individuals may intend or infer entirely different meanings for the same phrase. Does a phrase like “very good chance” connote 60 percent likelihood or 100 percent likelihood? Should the author who attempts to capture a bit of mutually agreed knowledge use percentages and avoid descriptive phrases entirely? Will that reopen a debate about what was really learned? Will it infuse precision when no such precision was part of the learning? Should the author use a range of percentages? If so what range? Does a range of 60–100 percent contain any useful information for the readers? The challenge is not restricted to probabilistic phrases. For example, will the author use technical jargon that has rich meaning to the agreeing parties but much less meaning to the potential readers? Will some of the agreed learning be lost if he employs common prose in place of the technical jargon? Will the loss matter? What compromises must be made? Who is to say those compromises will prove to be appropriate?

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The structure of the Archive system itself imposes constraints on what can be saved. A system that only supports narrative will be more restrictive than one that can store narrative, graphics, photos, video clips, and so on. Such restrictions shape how the knowledge is formatted and in turn influences how accurately and fully the knowledge is saved. The Honeywell F&MT system described offered a wide array of storage formats and the ability to interlink them, while the NASA Earth Observation System merely captured and retrieved text information. The former permits the capture of a much richer knowledge set than does the later. Both organizations may gain the same knowledge from an experience but F&MT is far more likely than the NASA team to accurately capture that knowledge. Problem #3—Critical Context Is often Lost or Distorted The context in which the learning occurred is too often captured incompletely, inaccurately, or not at all. The organization may be far more competent today than it was yesterday when the learning event occurred. Perhaps more skilled employees are now employed. Perhaps processes have been improved and are monitored more closely. Thus the lessons learned may no longer apply. An incomplete, inaccurate, or missing context description creates a real risk of future misapplication of the knowledge. The context challenge is very difficult, so difficult that it alone can effectively disable an Archive system. Paul Watzlawick (1967) describes an example of the importance of frame of reference or context as follows: A man collapses and is rushed to hospital. The examining physician observes unconsciousness, extremely low blood pressure, and, generally, the clinical picture of acute alcohol or drug intoxication. However, tests reveal no trace of such substances. The patient’s condition remains unexplainable until he regains consciousness and reveals that he is a mining engineer who has just returned from two years working at a copper mine located at an altitude of 15,000 feet in the Andes. It is now clear that the patient’s condition is not an illness in the customary sense of an organ or tissue deficiency, but a problem of adaptation of a clinically healthy organism to a drastically changed environment. If medical attention remained focused on the patient only, and if only the ecology of the physician’s customary environment was taken into account, his state would remain mysterious.

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Such “seeing” from an inappropriate context may keep an individual or team from solving a problem. But what is worse, an inappropriate context may lead an individual or team to “solve” a problem incorrectly, thus creating and carrying forward false learning, learning that perpetuates harm across the organization. Quoting Watzlawick again, “a phenomenon remains unexplainable as long as the range of observation is not wide enough to include the context in which the phenomenon occurs. Failure to realize the intricacies of the relationships between an event and the matrix in which it takes place, between an organism and its environment, either confronts the observer with something ‘mysterious’ or induces him to attribute to his object of study certain properties the object may not possess.” Lack of context can blind us to alternate interpretations of a situation and thus cause us to learn something that is not true. But each of us can also have entirely different contexts that lead to different interpretations of events and situations. Arie de Geus (1997) describes a wonderful anecdote about how our experience defines our context and in turn constrains what we can learn or how we can interpret what we are exposed to. Consider, for example, the story of the tribal chief who was brought to Singapore by a group of British explorers at the beginning of the 1900’s. The explorers had found him deep in the high mountains of the Malaysian peninsula, in an isolated valley. His tribe was literally still in the Stone Age. Its people had not even invented the wheel. Nonetheless, the chief was highly intelligent, and a delightful man to talk to (once they made themselves understood). He seemed to have a deep, meaningful perception of his own world. So, as an experiment, they decided to convey him to Singapore. It was at the time already a sophisticated seaport, with multistory buildings and a harbor with big ships. Economically, it had a market economy with traders and professional specializations. Socially, it had many more layers than the society from which the tribal chief came. They marched the chief through this world for 24 hours, submitting him to thousands of signals of potential change for his own society. Then they brought him back to his mountain valley and started to debrief him. Of all the wonders he had seen, only one seemed important to him: He had seen a man carrying more bananas than he had ever thought one man could carry. What the mind has not experienced before, it cannot see. The tribal chief could not relate to multistory buildings or giant ships; but when he saw a market vendor pushing a cart laden with bananas, he could make sense of it. All the other signs of potential change were so far outside his previous life experiences that his mind could not grasp what his eyes were telling him.

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De Gues’ anecdote reminds us that context influences what we can comprehend and thus what we can learn. This is true for individuals and for organizations. Problem #4—Revisionist History Reshapes Learning Lessons learned often change as time passes. What today seems mundane may turn out to have been a critical event or decision. What today seems tragic or wonderful may turn out to have had very little impact on the business. This leaves the question of how to determine the appropriate time to capture our perspective of the lessons learned. Should it be captured immediately after the event, or perhaps six months later? Why not two years later? Quite likely the interpretation of just what lessons were learned may be different at these different points in time. Which is correct? We as individuals practice revisionism in how we recall and retell the story of our own lives. Halpern (1996) explains that “Our beliefs are not easily changed; instead, we tend to change our memory for what we saw and heard so the memory is made consistent with the beliefs. Most often, memory is altered without conscious awareness that the information is being recalled in a way that does not match the events. . . . Memory is malleable. Our memory depends on how we encoded or interpreted events, not the events themselves. What we remember changes over time. When our knowledge and experience change, our memories also change.” Such revisionism is a part of the human condition. We witness it on a personal scale when we share our version of an anecdote with someone else who was present, discovering that we each have different recollections about the events being recounted. My son had a school playground accident when he was in the sixth grade, breaking both wrists. I have told the story of how this happened and what ensued several times in the ensuing years. About six months ago I told the story while my son was present. Afterward he challenged my version of events asserting the accident happened in a completely different way than I described. Who revised the facts over time, him or me, or perhaps both of us but in different ways? We witness the phenomenon in the revisionist history of important historical figures. Consider how historians have revised their interpretations of the presidencies of Abraham Lincoln or Theodore Roosevelt. Consider how Lyndon Johnson was perceived when he left office versus how he is seen now. We witness the phenomenon in the revision of historical events from the rationale for a treaty to the

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causes of a war. Napoleon Bonaparte said, “History is the version of past events that people have decided to agree upon.” They may later decide to agree on a different version of those past events. At what point in time should the learning from an organizational event be agreed upon? How long will that version of the “truth” remain a mutual agreement? It is thus no surprise that organizations shape the interpretation of an event to fit their collective biases and beliefs. Nor should it be a surprise that organizations also practice revisionism as time passes and their beliefs change. Consider the different perspectives held by a tobacco company over the past fifty years. Consider the different perspectives held by toy manufacturers as public opinion about child safety and the ensuing litigation liabilities have changed. Consider the different perspectives held by a public school administration as the number of violent school incidents increase, or become more widely publicized and sensationalized. Organizations adapt their interpretation of past events to better fit their current biases, just as do individuals. Problem #5—Hypersensitivity to Current Events The knowledge stored in Archives suffers from another time dimension issue. It has been said that we are all victims of our most recent history. If we get food poisoning from eating bad mushrooms on a pizza then we may for months be repulsed by even the smell of pizza, even pizza without mushrooms. If a business suffers from bad publicity about a product failure it will be extremely sensitive about any future product failures. A new product development project at one business encountered major supplier problems that cost the business a few million dollars and delayed the product release by about a year. A similar supplier issue arose about six months later on a different project. The organization perceived a trend and declared the need to better understand the problems, capture a lesson learned about supplier management, and implement appropriate changes to prevent similar problems. What may have been two random events has now become, in the organization’s collective mind, a problem. The team assigned to study the problems and develop a solution did just that. Every new product project team implemented the solution. The organization congratulated itself on having learned and applied an important lesson about managing suppliers. Time moves forward. A third supplier issue arose that was very similar, or so it seemed, to the two earlier issues. A new team of experts

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was convened to study the three problems. This team concluded the first two problems had almost nothing in common. One was caused by a mistake in the specifications given to the supplier while the other was caused by a quality problem with a second-tier supplier. The third and most recent supplier problem occurred because the supplier had recently suffered some severe financial losses. They had chosen to substitute some lower-cost materials that turned out to also be lower quality. The organization-wide anxiety about two seemingly similar and expensive supplier problems occurring close together had created an environment that encouraged the team to perceive a problem that did not exist. Sadly, the “solution” deployed to address the first two problems remained in place even though it had been confirmed that none of the three problems were related and the solution was addressing a problem that did not exist. Thus, too often Archives capture current anxieties rather than learning. Problem #6—Knowledge Is Not Accurately Retrieved Let us assume that everyone in the organization agreed about what was learned from a past event. Let us assume that the learning and its relevant context were accurately and completely captured without bias or distortion. Let us assume the learning was real rather than an overreaction to current events. Now that carefully crafted knowledge must be retrieved. Recall the challenge of trying to accurately capture a lesson learned in a format that all could agree is accurate and complete. Those retrieving that carefully crafted information and its appropriate context must interpret it, and in doing so they may fall victim to many of the same perils that befall those entering the knowledge. The people reviewing the knowledge database cannot help but see the information from their own personal perspective and thus may interpret it differently than intended. They may also misunderstand the documented context, projecting their current context into the translation. They may attempt to extend the learning to a different context where it is not applicable. In every event the learning is at risk of being misinterpreted and misapplied. Large satellites such as the Skylab, Soviet MIR, and International Space Station use a device called a Control Moment Gyroscope (CMG) to stabilize and point the satellite while it is in orbit. These rotating devices operate on a principle similar to a rotating bicycle wheel stabilizing the bicycle while it is ridden. The spinning wheels

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generate a force that helps keep the bicycle upright. The CMGs generate a force that keep the satellite stable or can be used to point it in a specific direction. These devices rely on very high precision bearings. They are subjected to traumatic temperature swings as the satellite moves into and out of direct sunlight. They sometimes operate at very high speeds. They must rotate smoothly even after a decade or more of operation and wear. The manufacturing process for these very special bearings is something of a black art because they are so seldom used and manufacturers “lose the recipe.” Bearing manufacturers and satellite manufacturers have tried to capture the materials, manufacturing, and testing processes necessary to make bearings that will reliably accomplish the task but, time and again, when a new project gets its bearings they do not meet requirements and must be redesigned, rebuilt, and retested, thus delaying the project and costing a great deal of money. These efforts to capture all of the relevant materials, design, and manufacturing information have been elaborate. They have included careful recording of every decision and process step. They have included recorded narratives of key Old Pros. They have included samples of materials. They have included retention of the equipment used in the manufacturing process. Yet, time and again the new bearings have not worked. Some Old Pros who have worked in this industry for forty years or more assert that the problem is twofold. First, current design teams too often believe they understand the requirements and capabilities better than their predecessors. They are too quick to discount or disregard some of the approaches and techniques used in the past, replacing them with their own more current but unverified approaches and techniques. The current design teams often argue that they are eliminating unnecessary cost or schedule delay only to discover too late that there was an important reason the more costly or longer technique was used. Second, things inevitably change over time and the effects are often unexpected. A materials manufacturer may no longer be able to buy a particular lubricant, or a unique grade of titanium. Modern cutting tools may operate at a higher speed than did tools in the past. Perhaps no one knew that lubricant allowed the titanium to be cut at a particular speed that did not induce micro-stresses, while the new lubricant does not have the same effect. Perhaps the subtle change in the titanium itself makes it more brittle after many extreme temperature cycles, cycles only experienced by a satellite in orbit. Perhaps the faster cutting tool stresses the titanium in an unexpected way.

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So, today’s engineering team discovers through testing that the bearings are bad and then must launch a series of science projects to understand what has changed and how to overcome the consequences of the change. These engineering teams either discount the past experience that was so carefully captured and saved for them or they discover the past experience is not completely relevant to what can be done today. Retrieving useful knowledge and usefully applying it in a different environment is very challenging. Archives by their very nature are unable to accommodate much of what we know as individuals and as groups. Organizations find themselves arbitrarily selecting a version of “truth,” capturing it inaccurately, disregarding the useful context, misinterpreting the result, and then misapplying that misinterpreted, inaccurate, politically negotiated truth. Archives, if they are to be helpful, must be integrated with a Culture, Old Pros, and Process scheme that mitigates these weaknesses. Even then Archives should be recognized as the least important of the four dimensions. Leadership Role in Managing Archives Archives are perhaps the most perplexing of the four means of dealing with organizational knowledge. They are so attractive—buy some software, do some training, store what we know, and retrieve it when we want it. Yet they are so misused—tacit knowledge distorted and stripped of its value in order to fit it into the system, installed in a Culture that rejects it, and not fully integrated into the business operations. So, what can leaders do to help assure Archives are used effectively? First, leaders can resist the temptation to deploy Archives as a quick fix to their organizational knowledge management problems. Successful Archives are few and far between. The number of failures continues to far outweigh the number of sustained successes. Carstensen and Snis (1999) conducted a field study of a group of quality assurance experts working in the central quality assurance support department at a large Danish pharmaceutical company to better understand how the actors gathered and disseminated knowledge. They hoped to identify a set of design requirements for an Internetbased information and knowledge management system. They referred to an array of oft-referenced prior studies and theories as a foundation for their own study. They particularly cited Nonaka’s (1998) assertion that social interactions are essential for effective knowledge

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management. Nonaka identified four modes of interaction that facilitate the management of knowledge: ●

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Socialization—one individual shares knowledge with another individual Combination—one piece of explicit knowledge is combined with another piece of explicit knowledge Externalization—tacit knowledge is converted into explicit knowledge Internalization—explicit knowledge is converted into tacit knowledge

Nonaka further asserted that an effective knowledge management system must facilitate these interactions through any effective means including documents, meetings, telephone conversations, or computerbased networks. Carstensen and Snis concluded, “There is still a long way to go before we can claim to have sufficient knowledge for designing a near-perfect (or just good or useful) Internet-based information and knowledge management system.” Second, leaders can be very sensitive to how poorly Archives handle tacit knowledge. An organization with a great deal of potentially useful explicit knowledge may find it beneficial to deploy an Archive to help manage it. Organizations may find it useful to store test data, sales data, inspection and audit results, delivery and cycle time performance, and an array of other explicit data that in aggregate is useful knowledge. However, organizations must be very cautious about attempting to load tacit knowledge into the system. Third, leaders should recognize that rudimentary Archives already exist in the organization. Explicit knowledge may well already be stored and accessed in several parts of the organization. Some of these systems may be mishandling tacit knowledge and the systems should be assessed to assure they are doing minimal harm. It may or may not be useful to integrate the systems, depending on the cost of integration versus the benefit derived from integration. Some of those systems may not now be worth the cost of maintaining them. Some may be inexpensive to maintain and may prove beneficial in the future. The point is that leadership and the organization as a whole should understand clearly how it is storing what it knows, and whether it is doing so efficiently and effectively. Fourth, leaders must remember that Archives can only thrive in a Culture that appreciates and shares knowledge. The system will fail if knowledge is viewed as a source of power rather than a shared asset.

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References Carrillo, P., H. Robinson, A. Al-Ghassani, and C. Anumba. (2004). Knowledge management in UK construction: strategies, resources, and barriers. Project Management Journal (April): 46–56. Knowledge management (KM) has received considerable attention in recent years. Some consider knowledge the most strategically important resource, and learning the most strategically important capability for business organizations. Major UK construction organizations have recognized the benefits that KM can offer and have thus invested in KM. This paper reports on a survey of these companies. The purpose of the survey was: 1) to examine the importance of KM to UK construction organizations, 2) to investigate the resources used to implement KM strategies, and 3) to identify the main barriers to implementing KM strategies. The survey found that the main reasons for implementing a KM strategy was the need to share the tacit knowledge of key employees and to disseminate best practices. Also, significant resources in terms of staff time and money were being invested in KM, but the main barrier to implementing a KM strategy was the lack of standard work processes. Carstensen, Peter H., and Ulrika Snis. (1999). Here is the knowledge— where should I put it? WET ICE 1999 Proceedings. Findings from a study of how knowledge spaces are used within a support group. Enabling Technologies: Infrastructure for Collaborative Enterprises. Chew, S.C. (2006). “I-solation” study on verbal uncertainty expressions. Proceedings of the 2nd IMT-GT Regional Conference on Mathematics, Statistics and Applications Universiti Sains Malaysia, Penang, June 13–15, 2006. Davenport, T.H., and L. Prusak. (1998). Working knowledge: how organizations manage what they know. Boston, Harvard Business School Press. This article outlines one model for understanding knowledge management within organizations. De Geus, A. (1997). The living company. Boston, Harvard Business School Press. The author who worked for Royal Dutch/Shell for thirty-eight years advocates a theory that those firms that last for a long time (even hundreds of years) do so because they see their “mission” or purpose as survival rather than profitability. Goddard Space Flight Center. (2003). EOS pilot for lessons learned. http:// eos.gsfc.nasa.gov/eos%2Dll/ retrieved May 13, 2007. This article, much like the DOE article referenced above, captures the NASA experience with Archive deployments. Halpern, D. (1996). Thought and knowledge: an introduction to critical thinking. Mahwah, NJ, Lawrence Erlbaum Associates. This is an instruction book written to be a college level text. Its premise is that one can learn to think, argue, and solve problems better. The first

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three chapters set the stage by offering current views about thinking, memory, and language as it relates to our decision making. Chapters four to ten address a specific topic such as reasoning, analyzing arguments, decision making, and creativity. Nonaka, I. (1998). A dynamic theory of organizational knowledge creation. Organization Science 5(1): 23. Nonaka advocates a complex and interactive model of organizational knowledge management not unlike the one advocated here. Vick, Stephen, K. (2002). Degrees of belief: subjective probability and engineering judgment. American Society of Civil Engineers. Vick cites a 1989 study by Reagan et al. that reviewed several previous studies of numerical responses and ranges for probability expressions. The first sigma valuations were relatively narrow although the ranges were quite wide. Watzlawick, P., J.B. Bavelas, and D.D. Jackson. (1967). Pragmatics of human communication. New York, W.W. Norton. This book provides interesting and enlightening approaches and models of human communication.

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Chapter 6

Process—The Way Things Work Around Here

What is Process? In 1980 my daughter and I built a computer from a kit, the Heathkit H-8. The computer case was about 6 inches tall, 16 inches wide, and 17 inches deep and was powered from an electrical outlet, no batteries here. It had a sixteen-digit keypad for entering data and a light emitting diode numerical display. One of our most memorable discussions was about whether to upgrade from the standard 8k (8,192 storage locations or bytes) to the optional 16k of memory. This week Kelly and I looked at an Apple iPhone with 8 gigabytes (more than 8,000,000,000 bytes) of memory, 1 million times more than the computer she and I assembled in 1980. The iPhone is 1/300th the size of the H-8 (less than 5 cubic inches). It has an integrated touch keypad and a video display. It also contains a phone and a camera. It can store thousands of songs and I can listen to music for up to twenty-four hours without recharging the device. This amazing technical progress was made possible by research, design, and manufacturing improvements in batteries, displays, materials, communications networks, and integrated circuit devices among other technologies. The power density of batteries, more power and smaller size, has steadily improved. Displays have become more complex, clearer, and more vibrant. Materials have become lighter and more durable. Wireless communication access seems to have become ubiquitous. Integrated circuit devices are smaller, faster, and consume less power. Moore’s Law is often used to describe the phenomenon of continually increasing integrated circuit density and complexity. Gordon

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Moore, a cofounder of Intel, observed in the 1960s that the number of transistors that could be inexpensively placed on an integrated circuit was increasing exponentially, doubling approximately every two years. That trend has continued since then, and is widely expected to continue for at least a few more decades. The integrated circuit devices benefit from the trend in several ways. Processing speed has improved exponentially, allowing the devices to deal with progressively more complex calculations—consider the automobile navigation systems that continually monitor satellite signals and movement on the ground to calculate the cars’ position and the route to your destination. Memory capacity has also doubled every two years allowing that same automobile navigation system to contain a digitized map of nearly every road in the United States along with millions of pieces of information about the location of gas stations, restaurants, points of interests, and much more. So what does this have to do with how organizations deal with what they know? It turns out that this revolution in integrated circuits is a particularly good example of Process at work as a repository and distributor of knowledge. Just after my daughter and I assembled that H-8 computer, I was assigned to lead a team under contract to design a computer for military satellites. The computer had to be sturdy enough to survive the intense vibration of a launch vehicle as it climbs into orbit and to withstand the thermal stress of going from perhaps 90°F at the launch pad to as cold as –450°F in space in only a few minutes. Now that is an example of what engineers call thermal shock! The computer had to operate even though exposed to the intense radiation environment of space. It also had to operate in the dramatically higher radiation environment that might be present after a nuclear blast because the Air Force feared an enemy might launch and detonate nuclear warheads near the satellites in an attempt to disable them. It also had to operate at speeds comparable to other cutting-edge computers being designed for use in much less severe environments here on earth. This particular computer was made up of five core processor chips plus several peripheral chips including memory, special interfaces to displays and data entry devices, and interfaces to the special sensors mounted on the satellites. At the time, an individual integrated circuit chip could contain as many as 100,000 gates—a gate is a controllable electronic switch that allows or prevents the flow of current in a circuit. Those 100,000 gates and all the connections between them would reside on four to six layers of silicon that were perhaps 3/8ths of an inch square and collectively only a few millimeters thick.

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As a matter of perspective, one might think of the integrated circuit design and manufacturing challenge at that time as follows. Draw a vertical line from top to bottom of an 8.5 inches by 11 inches sheet of paper. Now attempt to draw 1,000 parallel lines on that sheet of paper without allowing any of the lines to touch. Now imagine drawing those 1,000 lines in loops and turns, but still without touching one another. Now imagine trying to draw the 1,000 looping and not-touching lines on the edge, that’s right the edge, of the sheet of paper. That’s more or less the challenge faced by the design teams in the 1980s. Our team planned to have a successful design of the five main processor chips, the heart of the computer, after three design cycles. The initial design cycle included the planning, design, computer simulation and testing of the design, design modification, simulation changes and retesting, fabrication, packaging, and finally the testing of an actual chip set. The second design cycle included the correction of any major problems or errors uncovered by the testing of the chips, then the redesign, resimulation, fabrication, packaging, and testing of the modified chip set. The third design cycle included the correction of any problems masked by earlier problems that had now been corrected, then the redesign, resimulation, fabrication, packaging, and testing of the improved chip set. Our plan assumed these third-pass chips would be sufficiently problem free that they could be used to build the first computer. Our schedule allowed about four years to complete all three of the design cycles. The team included several senior staff engineers, Old Pros, with many years of integrated circuit chip design experience supplemented with a small cadre of young engineers. At that time much of what we were doing was considered “black art,” in that experienced professionals had learned through personal experience, or by working directly with other experienced professionals, the subtleties of the work before us. We relied heavily on the direct personal experience of the technical team to plan and accomplish the work. We relied more heavily on that experience when things went wrong and we had to understand the problems then correct them. The design challenge has grown more than a 100-fold since then. Ten years later, in the mid-1990s, a team was expected to be able to design a 1,000,000-gate chip (ten times more gates than in our computer chip design task) in one or two design cycles rather than three cycles, completing its work in approximately eighteen months rather than in four years. It is noteworthy that the typical design team from the 1990s had an average of ten years less experience than their

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predecessors in the 1980s. Today, an application specific integrated circuit (ASIC) can accommodate more than 100,000,000 gates and can be designed in less than twelve months, with a 75 percent probability of first time success—and the team might have an average of only two to three years design experience. Progressively less experienced engineering teams were accomplishing the progressively more complex task. How? The answer is Process. Today’s computers, GPS navigators, and our new iPhones are possible because of these dramatic improvements in circuit density, design quality, design methodology, and fabrication methodology. These designs are created through the use of sophisticated computer programs, design databases, and carefully controlled procedures. Design teams around the world have been using the tools, procedures, and methodologies over and over again, discovering good practices and bad, finding useful shortcuts, and building on what was learned in the past. The tools, procedures, and methodologies have been improved over and over again, enabling dramatic improvement in performance. The knowledge possessed by Old Pros during the 1980s, and much of what has been learned since then, now resides within the ground rules, constraints, standards, and procedural norms that, in essence, capture those lessons learned and require current designers to use them as a part of the work activity itself. The Process now holds within it not just the organization knowledge but also the industry knowledge about complex electronic chip design and manufacture. The Process makes that knowledge available to design teams around the world. The Process essentially imposes that prior learning and discipline on the current design teams, making them more effective than prior generations of teams. Note specifically that the Process may contain historical industry knowledge as well as proprietary organizational knowledge. Competing organizations may buy the same design support tools, or use the same suppliers, or have their designs built in the same manufacturing facility. They will be sharing industry knowledge. At the same time, one of the organizations may be using proprietary design tools or proprietary modifications of the same tools. One of the organizations may have worked with a supplier to develop a proprietary material or methodology that the competing organization cannot use. One of the organizations may have its own manufacturing facility and have developed design techniques that take optimal advantage of unique characteristics of their manufacturing methodology. Industry and proprietary knowledge may both be retained as

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part of each organization’s particular Process. Over time, that which is proprietary may become industry standard practice, or become obsolete, or be enhanced and remain proprietary. In any event, it is the organization’s Process that captures, retains, distributes, and helps apply the knowledge. What Shapes Process? Any given organization has a particular Process perspective depending on several factors, including the nature of the work activity, the volume and standardization of the work, industry fads, customer influences, and even leadership and corporate influences. The organization may find itself either being driven toward or away from a stronger Process perspective subject to the aggregate of these influences. The nature of the organization’s work activity influences its Process bias. For example, organizations in the integrated circuit design and manufacturing industry will likely have a strong Process bias because their business is so driven by the rigor and discipline required in the design and manufacturing activity. They must use highly disciplined techniques to design and test chips. They must maintain extremely clean manufacturing environments. They must use very sophisticated and complex equipment. Process surrounds them. This highly technical environment is also dominated by a technically trained work force. Many employees are engineers or technicians who, through personal disposition and training, are prone to have a linear and structured worldview that will likely enable them to embrace a Process perspective. The volume and standardization of the work output influences an organization’s Process perspective. An organization that performs high volume manufacturing operations will be very sensitive to the linear nature of its operations, will focus intently on sequence, inputs, outputs, variability, and so on, all factors that make its employees, its decision-making activity, and its leadership more sensitive to Process. An organization that performs job shop activities, that is to say, relatively small quantity build of multiple products or multiple configurations of products, will be less receptive to Process than will a large scale manufacturing organization. A custom projects oriented organization will be even less receptive to a Process perspective. Thus, organizations that do the same work activity repeatedly will likely be more Process oriented than will an organization that has little repetition in its work activity.

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Consider a custom homebuilder who builds fewer than a dozen homes a year, each uniquely tailored to fit the buyer’s home site and their personal sense of style. Each house is unique. The design may involve curved walls, indoor water features, or an in-home theater. The contractor may have to hire hard-to-find craftsmen who know how to work with materials that may include stone taken directly from the house site, tiles removed from old buildings, or exotic imported woods. Each house is a unique project. On the other hand, another contractor in the same community may build tracts of homes, erecting hundreds every year. He may work with minor variations on no more than six different house plans. He will insist on using standard materials. His crews will move quickly from one house to another, doing the same work over and over again. The high-volume contractor clearly has a bias toward repetition and consistency, a bias that encourages a Process perspective, while the custom homebuilder is biased away from such a perspective. Industry fads often influence the Process perspective, at least temporarily. One recent fad, Six Sigma, became a mantra that organization after organization began to chant. Six Sigma is a suite of tools and techniques intended to help individuals and organizations understand their work activities and procedures, to understand how stable and predictable they are, to make them more stable, and to improve their performance. Some leaders have used the broad enthusiasm for Six Sigma to further their organization’s existing Process perspective, moving their business to a higher level of competence, while other leaders embraced the mantra in order to be a part of the fad. The fad caused both sorts of organizations to initially move toward a stronger Process perspective. The former were more likely to maintain that perspective than were the later. A powerful customer may influence the Process perspective. Organizations with a few key powerful customers often find themselves having to demonstrate to those customers that their work routines and procedures are effective and are being followed. A major aerospace contractor such as Lockheed or Boeing may impose very stringent requirements on their key suppliers. Government agencies may exert similar influence. They often impose requirements to comply with quality standards, financial reporting, small and disadvantaged supplier participation, worker safety, equal employment opportunity, and the like. Organizations serving the government find they must carefully document how they intend to comply, and demonstrate that they actually do comply, with the requirements. They find they must document their approaches,

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methodologies, and results in great detail in order to be able to demonstrate they meet the requirements. This activity fosters a Process perspective that might not otherwise exist in the organization. A heavily regulated organization may spend resources to document and monitor their work routines and procedures in order to demonstrate to auditors that such activities are under control. This effort to demonstrate control and compliance will reinforce the view that such activity is important, thus reinforcing a Process perspective. Certainly a leadership team influences the depth and breadth of an organization’s Process perspective. A leader with experience in a Process environment will naturally bring that perspective to a new assignment. A leader with a great deal of manufacturing experience will have a stronger bias than one with a sales and marketing perspective. Corporate bias can also be strong. Some corporations are loosely affiliated enterprises that give great autonomy to the business units. They are relatively free to operate as they see fit. Other corporations impose stringent requirements and constraints on their business units. The Ball Corporation is a nearly $6 billion a year company that makes containers. One of their traditional products is the “ball jar,” the type used by my grandmother to store “canned vegetables” from the garden for use during the winter. Ball is a large-volume manufacturer of a relatively mundane and standard line of container products—the company made almost 30 billion containers in the first half of 2008. One would be hard pressed to find a more standard and high-volume product line. However, Ball Corporation has within it the Ball Aerospace Corporation, a roughly $800 million per year business that designs and manufactures unique payloads and satellites for science and exploration purposes. The Ball Aerospace executives are given relatively free reign to operate their business as they see fit. They are not generally required to embrace Ball Corporate initiatives. Honeywell International is a $30 billion per year company with four major business units. The Transportation sector makes turbochargers for automobiles. It also manufactures automotive products under the Prestone, Autolite, and Fram brands, among others. The Specialty Materials sector manufactures an array of unique materials. For example, they make high-performance specialty materials such as fluorocarbons, specialty films, advanced fibers, customized research chemicals and elements for applications as diverse as telecommunications, ballistic protection, pharmaceutical packaging, and counterfeiting avoidance. The Automation and Control Solutions sector

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makes and maintains products and solutions for the home, office buildings, hospitals, factories, and industrial process plants. The Aerospace sector designs and manufactures aircraft subsystems for commercial and military platforms, subsystems for military land vehicles, and subsystems for space platforms. One would be hard pressed to find a wider array of products and services or industries. Yet, Honeywell strives diligently to maintain consistency in operating practices, manufacturing approaches, infrastructure, and a host of other dimensions. One might expect Ball to be the company driven to impose a single integrated approach and Honeywell to be the company that embraces approaches tailored to their various markets and businesses. Instead the opposite is true. Corporate bias can indeed shape an organization’s Process perspective. An organization’s Process perspective is restricted or enabled by a variety of outside and inside factors, not all of which can be resisted or embraced. Even so, organizational leadership faces similar forces affecting many dimensions of the business. Leadership must understand what its organization’s Process perspective ought to be and take steps to move the organization toward that goal. Process and Knowledge—The Literature The notion of organizational knowledge management being an essential part of how an organization accomplishes its work activity is addressed often. Some researchers assert that how an organization accomplishes its work and how it handles its knowledge must be tightly integrated. Jelinek (1979) noted, “Administrative systems are the mechanisms for impounding and preserving knowledge.” The administrative systems are in this instance the work routines and control mechanisms the organization uses to accomplish its work activity. Jelinek actually argues that these Processes are the sole repository of organizational knowledge, not just one of perhaps several repositories. One may disagree with Jelinek, asserting that the minds of the Old Pros in an organization certainly hold a great deal of useful organizational knowledge. Even so, Jelinek makes a forceful argument that Process, or what he calls administrative systems, is a vital knowledge repository. Walsh and Ungson (1991) argue that work routines are one important repository of organizational knowledge. They say, “Information is embedded in the many transformations that occur in organizations.

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That is, the logic that guides the transformation of an input (whether it is a raw material, a new recruit, or an insurance claim) into an output (be it a finished product, a company veteran, or an insurance payment) is embodied in these transformations.” These work routines, tasks, and procedures that accomplish the transformation are forms of Process. Davenport and Prusak (1998) contend, “the knowledge management process has to be ‘baked’ into key knowledge work processes. How companies create, gather, store, share, and apply knowledge must blend well with how market researchers, scientists, consultants, engineers, and managers work on a daily basis.” They also argue “Another important step is to build explicit linkages between knowledge management and the knowledge work process it is designed to support. The linkages must specify how knowledge should be imported to and exported from the process, when and how in the process this knowledge should be used, and what difference it should make in the outcome.” Although these statements would suggest a single repository for organizational knowledge, Davenport and Prusak have, unlike Jelinek, expressed an appreciation for the existence of other repositories. Moorman and Miner (1998) describe “procedural memory” as the skills or routines that guide the accomplishment of work activity. They say, “A key characteristic of procedural memory is that it becomes automatic or accessible unconsciously.” This notion of automatic or unconscious use describes how Process inherently makes organizational knowledge available when and where it is needed. Brown and Duguid (1998) describe how the work routines, what they call “business processes” can facilitate or inhibit organizational alignment, learning, and the retention of that learning. They argue that groups use the cross-group work routines as a venue for aligning themselves, negotiating relationships, and establishing work practices. Such activity “can result in coordinated, loosely coupled, but systemic behavior.” They also argue that many “business processes” “attempt not to support negotiation but to pre-empt it, trying to impose compliance and conformity.” These various assertions about organizational knowledge management highlight a distinct difference between the four dimensions of organizational knowledge described in this book. The knowledge stored in Culture and in Process is inherently linked with how work gets done. The former is in the ether surrounding the work activity and the latter is integrated into the work activity itself. On the other hand, the knowledge stored in Archives and Old Pros is not inherently

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linked with how work gets done. Those doing the work must seek Archives out. The knowledge is only applied if requested. The knowledge in the minds of the Old Pros can only be put to use in one place at a time and the Old Pros may not be located where that knowledge can be best used. There is some agreement among those who study organizational knowledge management that what we call here Process is an essential creator, repository, and disseminator of knowledge. Activities surrounding the improvement of a work activity foster new learning that can be captured as well. That knowledge is disseminated every time the documented activity is used. Attributes of Process That Influence Knowledge Management Process is the most disciplined and sustainable means of capturing and retrieving knowledge. It can be better managed because it is not so subtle and social in nature as Culture or Old Pros. It offers far more versatility than does Archives. It can be an integrating mechanism among the four means of dealing with organization knowledge. What are the attributes that make it so effective? Conversely, what attributes impede Process as an effective organizational knowledge management mechanism? Process handles tacit knowledge with less distortion or loss of fidelity than does Archives. As described earlier, Archives struggle with tacit knowledge because they are at heart a data and text repository and retrieval system—words and numbers go into the Archive and words and numbers come out. Some Archives also store video but these are relatively rare and too often poorly done. Tacit knowledge must be converted to words and numbers that are compatible with the Archive storage constraints and in the process both knowledge and its context is lost or distorted. Process, on the other hand, offers more flexibility. Indeed, some of the tacit knowledge may have to be converted to a format that can be captured in documented procedures, instructions, guidelines, and operating instructions, but Process allows for more learning than just what is written. For example, the documentation may call for an inspection step by a senior technician or inspector who can contribute the tacit dimensions of what is known about the activity. Additionally, the Process tools may themselves contain useful knowledge about alternative approaches. For example, software routines may contain heuristics that present alternatives to the operator, alternatives that may help him make

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decisions appropriate for the circumstances. Tacit knowledge is also integrated into Process through initial and refresher training that may be provided by Old Pros. Recall the description of the integrated circuit design activity and how the tools and practices have evolved to incorporate more and more of what is known about such work. Initially, a great deal of the knowledge, both tacit and explicit, resided in the minds of Old Pros, but iteration after iteration transferred much of that knowledge into the tools and practices. For example, initially the team relied on the Old Pros to point out that the signal in one circuit path could create noise in an adjacent circuit path if the two paths were too near one another, or one of the signals was especially strong, or some combination of the two. Later iterations of the tools incorporated design constraints requiring that all circuit paths have a minimum spacing between them and we relied on the Old Pros to make adjustments to the resulting designs if we needed to “cheat” and move some signal lines closer together. The Old Pros would evaluate the nature of the signals, the signal strengths, and the spacing between lines then decide whether to overrule the design guidelines. Still later iterations of the tools incorporated more sophisticated design constraints that included the factors the Old Pros considered. After several iterations, more and more of the previously tacit knowledge in the Old Pros heads, the “black art,” if you will, moved from their heads into the tools and practices. Process is inherently mandatory while Archives is essentially voluntary. The Process in the example above contained and distributed the knowledge making it unavoidable. The tools, techniques, and procedures were the only way to accomplish the work. For example, a purchasing agent must use the online purchasing system, along with its built-in constraints and approaches. That system prescribes among many other things the information to be collected, the approval levels required, and the authorized sources of the item to be procured. The system also spots unusual buyer activity and flags it to supervisors for evaluation. The buyer must deal with the buying Process in order to accomplish his job and the Process thus forces the buyer to apply the knowledge stored within it. Another example is a technician who uses specific tools and techniques to align and calibrate a piece of equipment. The technician is taught to do the task using those tools and techniques. Those tools and techniques likely enable the task to be done faster, easier, and more accurately. Those tools are available while alternate tools may not be readily available. Doing the task in the approved way is easier

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and less risky. In short, the technician finds it difficult to avoid using the Process to accomplish the task. In each example the Process enables task performance. Any knowledge stored within it is continually available, virtually unavoidable, every time the task is accomplished. So the knowledge in Archives may be forgotten, ignored, or misinterpreted while the knowledge in Process must be dealt with. Process is actively managed. Work routines and procedures have assigned owners responsible for their integrity, efficiency, and currency. These individuals or departments have a continual and formal interest in keeping them healthy. That interest extends to assuring that the knowledge within them is accurate, relevant, and is put to use. A procurement system may be measured with an array of metrics that track overall cost, cycle-time, delivery to need, and supplier performance, and many other factors, providing insight on individual and overall system performance. Those responsible for the tools, procedures, and methods are able to spot performance changes and adjust the system to adapt appropriately. Thus the knowledge within is continually pruned to meet the needs of the current environment. Process knowledge is also more efficiently pruned and expanded than the knowledge contained within the Culture, Old Pros, or Archives. As organizational strategy, technology, and competitive environment change, so do the procedures and methods, as well as their interactions between one another, change within the organization. People are more adept at managing these changes than they are at managing Culture, Old Pros, or Archives because they continually work with sequence flow maps, performance metrics, and improvement initiatives. An array of Process management tools and disciplines are reintroduced to the workforce every decade or so. Examples include the recent but now gradually fading enthusiasm for Six Sigma and Lean techniques and the spread during the 1990s of ISO (International Organization for Standardization) practices. Predecessors over the past thirty years have included the Baldrige National Quality Program that emerged in 1987 and is still acknowledged in some circles; Total Quality Management (TQM) that first emerged about 1960 when Edwards Deming, Joseph Duran, Philip Crosby, and Kaoru Ishikawa were the primary advocates for quality improvement techniques that mandated a full understanding and statistical control of work routines and procedures; and the Zero Defects initiative that was begun by Philip Crosby and quickly became part of the TQM movement. Each embodiment included an emphasis

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on work definition, mapping, metrics, controls, and improvement techniques. One Process Toolkit—Six Sigma Let us briefly consider Six Sigma, the current wave of Process discipline as it relates to knowledge management. In 2002, the American Productivity & Quality Center facilitated a practitioner discussion titled, “Exploring the Potential of Two Powerful Disciplines,” the two disciplines being knowledge management and Six Sigma (APQC, 2002). The discussion highlighted the results of Six Sigma-focused knowledge management at Ford, Compaq, and Schlumberger among others. The general theme was that Six Sigma offered a set of tools and techniques that could help organizations become better knowledge managers. The paragraphs below briefly describe those tools and techniques. The intent here is not to explain Six Sigma but to clarify how the tools, techniques, and philosophy can facilitate a Process perspective. Six Sigma is rooted in a statistical concept that represents the amount of variation present in a given work activity or procedure. (Six Sigma vernacular uses the word “process” to refer to any specific work activity composed of a sequence of steps, procedures, and routines rather than an overall organizational approach to capturing and retrieving knowledge. I have refrained from using the word “process” when describing Six Sigma so as to avoid confusion.) When a specific work activity operates at the six-sigma level, the variation is so small that the resulting products and service are 99.9997 percent defect free. That means there will be only 3.4 defects per every million opportunities. If operating at a six-sigma level, the airlines would mishandle only 3.4 out of every million pieces of luggage rather than the more than 5,000 bags per million actually mishandled according to the Bureau of Transportation Statistics. The quality levels for most business activities today fall within the three-sigma to four-sigma range (approximately 60,000 to 6,000 failures per million opportunities). In fact, Motorola, a bold user of Six Sigma techniques, found that humans are only capable of about four-sigma quality. Performance beyond the four-sigma level requires increased automation and reduced human involvement in the work activity. See table 6.1—Acceptable Quality Levels, Sometimes Even 99.9 Percent Isn’t Good Enough. The phrase Six Sigma is also sometimes used to refer to a broader business philosophy of focusing on continuous improvement by

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Table 6.1 Acceptable Quality Levels, Sometimes Even 99.9 Percent Isn’t Good Enough 99.9 percent means: ● ● ● ● ● ● ●

one hour of unsafe drinking water per month two unsafe landings at O’Hare International Airport each day 16,000 lost pieces of mail per hour 20,000 incorrect drug prescriptions per year 500 incorrect surgical operations performed each week 50 babies dropped at birth by doctors each day 22,000 checks deducted from the wrong accounts each hour

Source: Author’s Illustration

understanding customer needs, analyzing business procedures, and continuously monitoring their performance to assure the needs are being met. This broader definition accommodates within it the more rigorous statistical notion as a set of tools for enabling the broader business philosophy. The statistical version of Six Sigma came into widespread usage during the 1980s when Motorola Corporation discovered that production output with few defects yielded products that rarely failed later during actual use. A few years later Jack Welch embraced Six Sigma at General Electric and other major firms quickly followed suit. Six Sigma embraces the fundamental five-step methodology of Define, Measure, Analyze, Improve, and Control (DMAIC). Those using the DMAIC methodology first define the specific process to be understood and improved. The Define step involves determining the individual process steps and their sequence relationship, the inputs from outside the specific process, and the outputs from the process to other processes or users. For example, a team may set out to define the way they clean and paint a transmission case. They would define the specific steps beginning with receiving the unpainted case, then dipping it in a degreaser, then rinsing it, then washing it, then rinsing it, then dipping it in acetone, then spraying it with primer, then drying it, then painting it, then drying it, then painting it again, then drying it, then inspecting it, then sending it on to the assembly activity. The inputs would include the transmission case, the degreaser, the water, the washing solvents, the acetone, the primer, and the paint. The outputs would be the painted transmission case. Next, they would Measure the specific work output to establish a baseline performance level. The process may be found to perform erratically or to be quite stable. Perhaps finished cases are delivered every thirty-two minutes give or take one minute and the reject rate is consistently about one

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out of every five thousand cases. Or, perhaps the finished cases are delivered every thirty-two minutes give or take twelve minutes with an occasional unplanned shut-down that can last for hours. Perhaps the reject rate is inconsistent, with one out of every two hundred chassis being defective. In either case the performance may or may not meet desired quality levels. Next, the team would Analyze the work performance compared to the desired performance, seek to understand the causes of any undesired performance, and conduct experiments to verify those causes. They may determine that a case needs to be delivered every thirty-two minutes give or take thirty seconds. The may determine that the delivery rate needs to vary depending on overall transmission production volume and may vary from twenty-seven minutes to forty minutes. But once the rate is set, it must be consistently within thirty seconds of that target rate. The reject rate would also be established. Using these actual and desired performance levels, the team would determine what activities might be contributing to the differences. Next, the team would Improve the work flow by making the changes suggested by the Analysis results. The team would verify whether the changes accomplished the desired improvements or make additional changes seeking the desired level of performance. Finally, the team would put in place appropriate Controls including metrics, work activity owners, and reviews to assure the system remains stable and continues to perform at the desired level. Six Sigma training includes specific tools and techniques for each of the five DMAIC methodology steps and supplemental tools and techniques for understanding customer requirements, supplier performance, and so on. For example, the list of Analysis tools includes: ● ●

●

● ●

Brainstorming—to generate ideas about causes of error Cause-and-Effect Diagram—as a graphical representation of causes related to a problem Design of Experiments—a rigorous method for testing multiple potential causes of error at the same time Histogram—to identify patterns of process performance Hypothesis Testing—to statistically analyze cause-and-effect relationships

Each DMAIC step has a similar suite of supporting tools and techniques to enable teams to understand and improve the processes within the organization. These tools and techniques are not new. Most of them have been well understood and available for many decades. Each iteration,

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whether Six Sigma, Total Quality Management, Zero Defects, or some earlier approach, has included many of the same tools, tools that help employees and mangers identify, improve, and control their procedures, techniques, and methodologies. Organizations that deploy and effectively use such tools do have at least a minimal level of Process competence. They must have it in order to understand and use the tools. However, many organizations have deployed such tools only to see their use fade when the industry-wide enthusiasm has faded. These organizations have failed to recognize the fundamental organizational knowledge management value that Process brings. The tools may help the leaders and employees manage Process but they cannot create a Process perspective where none exists. Leadership Role in Fostering a Knowledge Friendly Process Perspective The senior leadership team must adopt and extol a Process business perspective. Leaders who understand and communicate openly about the critical organizational procedures, methods, and disciplines and their interactions will empower others to adopt a similar perspective. Over time, the organization will develop a maturity that will open the door to effectively managing the knowledge in them. This notion of a business-wide Process perspective is critical for organizational knowledge management competence because it helps shift the organization from a “knowledge is personal power” perspective to a “shared knowledge is organizational power” perspective. It fosters the free flow of knowledge. Leadership must acknowledge and reward those who demonstrate a Process perspective, while disregarding or even punishing those who do not. Acknowledgment and reward may take the form of public recognition, assignment to progressively important roles, movement of resources and talent from some groups to others, and so on. Employees watch what decisions are made, who gets promoted, and where resources are allocated as the clearest indicators of what matters. They pay relatively less attention to what leadership says about what matters. One leadership team at a Honeywell business unit achieved dramatic improvements in organization performance when they deployed a Process perspective. Their commitment began when the corporation decided to deploy Six Sigma across the corporation just as Jack Welch had done at GE. The leadership team at this business

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unit discussed their approach to deployment not from a compliance perspective but from one of building a strong and lasting organizational Process perspective that would persist long after the Six Sigma parade passed by. The leaders took several specific actions. First, they committed themselves to attend classes and earn formal Six Sigma certification. Within two years everyone on the leadership team had become a Six Sigma Black Belt. Second, the leadership team committed themselves to instruct classes for other employees. Initially, they made remarks at the beginning of each new class to express leadership commitment and support for the tools and disciplines, and to describe what they hoped the attendees would take back to their jobs. But within a few months they concluded these comments, while helpful, did not display the actions that reinforced the words. So, the leadership team committed themselves to become instructors rather than just kickoff speakers. This commitment caused them to learn more about the tools and techniques, to interact more with the employees, to be more competent in their own usage of the tools and techniques, and finally to be more effective sponsors of their use across the organization. Third, each leader committed to at all times be personally sponsoring one major cross-functional improvement initiative. This created a persistent energy around using the tools and disciplines on real-world problems across the workplace. Fourth, these projects were intentionally structured to address issues that crossed organizational functional boundaries and were staffed with employees and managers from multiple functional groups. This helped employees appreciate the needs of other work groups and to develop improvements that were optimal for the organization as a whole rather than just for one group, perhaps at the expense of other groups. One specific example had to do with the organization’s on-time delivery performance. Aerospace industry studies indicated that peer business units performing in the first quartile financially also consistently met over 96 percent of their delivery schedule and quality commitments. This particular business unit was a third quartile financial performer and also met its delivery commitments only about 75 percent of the time. The leaders started by discussing the industry data and by engaging the broader workforce in understanding why some peer businesses were able to consistently do better, what parts of the current organization were doing better and why, and what internal obstacles impeded better performance. In short, leadership asked: what do we know about the causes of our performance problems and what do we know about how to improve?

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As one would expect, the opinions varied and even conflicted. Some conventional wisdom turned out to be untrue. The organization knew but had been disregarding some important lessons form the past. Some work activity was poorly understood. In short, there were multiple causes and solutions. Several small and large scale improvement projects were launched over the next two to three years and slowly but steadily the on-time performance improved, until the business was able to accomplish eighteen consecutive months of 100 percent on-time delivery to customer commitments. More important is the fact that during the next six years that organization has been consistently among the very best quality and delivery performing business units across the corporation, often achieving both 100 percent on-time delivery and Six Sigma quality levels. The organization did not merely train the workforce in the use of several tools and techniques. Instead it used the industry-wide enthusiasm for Six Sigma as an opportunity to further instill a deep regard for Process as an essential element of how they appreciate and manage what the organization knew and could learn. That underlying perspective is what sustained the continuing stellar performance. What Lies Ahead Each of the four repositories of organizational knowledge, Culture, Old Pros, Archives, and Process has been described in some detail. Chapter seven, Putting Them Together, will describe the interrelationship among the four. As one would expect, there is a great deal of codependency and interaction among the four. The chapter will also describe how the relative influence of each repository has changed, and continues to change, as organizational environments have evolved. References APQC Member Teleconference. (2002). Six sigma and KM—exploring the potential of two powerful disciplines. http://www.apqc.org retrieved July 24, 2007. Brown, J.S., and P. Duguid. (1998). Organizing knowledge. California Management Review 40(3) (Spring): 90–111. This is an example of the enthusiasm about the information economy enabling, perhaps making inevitable, the spread of virtual organizations and the demise of traditional organization structures. Davenport, T.H., and L. Prusak. (1998). Working knowledge: how organizations manage what they know. Boston, Harvard Business School Press.

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The authors take a holistic view of how organizations deal with what they know. Jelinek, M. (1979). Institutionalizing innovation. New York, Praeger. Jelinek takes a narrower view of where and how organizations store what they know, asserting all such knowledge is stored within the work routines and procedures. Moorman, C., and A.S. Miner. (1998). Organizational improvisation and organizational memory. Academy of Management Review 23(4): 698–723. The authors describe organizational procedural memory (skill knowledge) and declarative memory (fact knowledge) as factors that influence how well an organization improvises with what it knows. Walsh, J.P., and G.R. Ungson. (1991). Organizational memory. Academy of Management Review 16(1): 57–91. The authors argue that the representations of the concept of organizational memory are fragmented and underdeveloped. Their approach emphasizes proposed definitions of the “locus” of organizational memory, an approach not unlike the one offered herein.

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Chapter 7

Putting Them Together

A typical automobile includes perhaps 2,000 parts. Individually

none of them enable us to travel safely and comfortably from place to place but assembled they provide us a means to travel over long distances. A typical college basketball team has about fifteen players, five of whom may be on the floor at a time. No single player can win a game playing alone, much less have a winning season. Yet, together those fifteen players may be able to win a championship. Just as the players can come together to form an integrated, powerful, and successful team, so to can Culture, Old Pros, Archives, and Process come together to enable an integrated, powerful, and successful learning organization. Each brings a unique set of strengths and weaknesses, yet together they can form a formidable organizational knowledge management capability. Those who study organizational knowledge management reinforce this common sense notion that knowledge repositories must be aligned. For example, Crossan et al. (1999) asserted “Repositories of learning need to be aligned with one another in a coherent way so that the culture, systems, structures, and procedures support the strategic orientation of the firm, given the competitive environment.” An Integration Example Honeywell Federal Manufacturing & Technologies, described in chapter four, is an excellent example of addressing the challenges of all four dimensions of organization knowledge management. The business faces a continual and formidable challenge when it comes to preserving organizational know-how. A great deal of the work activity done there is unique, demands great precision, and has often been conducted for thirty years or more by a small handful of individuals.

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Some individuals may have been operating the same machinery or assembling the same component for their entire careers. As a result they know intuitively far more about their work than they could possibly recognize, much less pass on to others. Many of these workers are baby boomers approaching retirement. Their departure could mean the loss of decades of painstakingly learned knowledge that resides in the heads of the Old Pros and perhaps nowhere else. The Honeywell FM&T executives were especially worried about those jobs involving as much craftsmanship as knowledge. Examples include precision welding, machining, and forging of unique materials as well as the assembly of complex components. Their multifaceted approach to dealing with the potential loss of organizational knowledge includes detailed analyses and simulation of work Processes, multimedia enhanced Archives, robust engagement by Old Pros, and a Culture that appreciates knowledge and facilitates knowledge sharing. Simulation engineers work with Old Pros to model a particular work activity by creating virtual machines that can be tailored to mimic the behavior of the materials and the operators’ movements. The simulation can react according to how much force the operator applies, the speed at which a cutting tool is rotating, the hardness of the material being machined, and even the proximity of the cutting tool to the edge of the material. The Old Pros play with the simulation then tell the simulation engineers whether it behaves correctly. Working together in this fashion they uncover knowledge the Old Pros did not know they had, and that knowledge is captured by enhancing and refining the simulation. The simulation becomes a form of Archive available to new employees as a training tool. An Old Pro who helps the new employees better understand how the equipment is responding and why it responds as it does can facilitate the training. Eventually the increasingly robust simulation becomes a very effective repository of knowledge and an effective disseminator of that knowledge—a fine Archive. This approach to training new employees is also faster, less expensive, less risky, and more effective than the trial and error approach with real equipment. Simulations can be run over and over with varying settings enabling the employee to gain experience much faster than if she were using the real equipment. Trainees can consume an infinite amount of virtual material learning a tricky technique rather than consuming real and expensive materials. Mistakes cannot damage the equipment or the materials as they would if the training occurred on the factory floor. Trainees learn faster and better than through on-the-job training.

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The simulation offers another significant advantage. Traditional Archives may capture knowledge about how to make something, but it fails to capture knowledge about how not to make it. The simulation captures some of this “negative” knowledge because incorrect or inappropriate technique will cause the simulation to respond badly. The trainee will quickly learn not only how fast to run the cutting tool but also what happens if he runs it too fast or too slow, presses down too hard or fails to apply enough pressure, and applies too little or too much lubricant. The simulation is also a form of Process capture. The methodology for accomplishing a task is captured within the simulation. It can be modified or adapted as needed to accommodate different materials, newer machines, revised quality requirements, improved techniques, or design changes. The modified technique can be thoroughly tested before deployment. The testing uncovers problems but it may also help to identify changes that would make the work activity quicker, more consistent, or easier. The methodology is also deployed in a uniform fashion. Each operator is taught in precisely the same way to accomplish the tasks. Such training consistency reduces the likelihood of operator technique differences that may create problems now or later. The Honeywell FM&T engineers also use an array of techniques for Archiving. One may consider the simulations themselves to be a form of Archiving. Other forms include detailed documentation of work routines and procedures whether they have been simulated or not. These documents are made available through the intranet to each person’s desktop. The material includes high-level overviews, flow diagrams, and detailed step-by-step instruction. The process maps and instructions are supplemented with video clips of interviews with Old Pros, current supervisors, and perhaps simulation engineers explaining how the work steps are accomplished, why a particular technique is helpful, or what to avoid. Engineer’s notes are often attached as well. The Old Pros offer commentary about how they arrived at a particular technique and why other techniques may cause problems. This approach is particularly beneficial for work routines and procedures that are not performed often. A particular piece of equipment may require very precise and long-lasting bearings made of especially difficult to work with materials, yet they may be manufactured and assembled only once every decade or so. A simulation and robust documentation may be the only way to preserve the process and technique from one manufacturing cycle to another. It also makes it possible to explore the impacts of technology changes that may have occurred

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during the intervening decade. This approach also serves as a good memory jogger for those who may still be around but have faulty recollections about just how something was done. The Honeywell FM&T leadership team also works hard to instill a Culture that respects knowledge and shares it freely. The Old Pros are recognized for their contribution. They appreciate the lengths to which the organization goes to capture what they have learned over the years. The business invests in resources to assure employees can easily get to the knowledge and that it is in a form they can readily use. Leadership communicates clearly and often about the value of the organizational knowledge, about the investments to preserve and use that knowledge, and about the business successes that occur as a result. Few organizations face the knowledge management challenges that FM&T face and few organizations are willing or able to invest so heavily in addressing the knowledge management challenges. Even so, FM&T provides an example of robust integration of all four dimensions of organization knowledge management, an example that may help other organizations recognize what is possible and beneficial for their unique situations and environments. The next section describes the interactions and relationships between the four elements of organization knowledge management. The reader will hopefully come to understand that these interactions and interrelationships are critical determinants of overall success or failure. Interaction All four means of capturing and codifying organizational learning are simplifications of complex, aggregated organizational interactions but Culture is the ethos. It is the most pervasive and influential of the four means of dealing with knowledge. It is the foundation upon which the others rest. Culture is the most pervasive of the four. All organizations have a Culture. They may fail to acknowledge their Old Pros. They may lack Archives. They may poorly document their work activities and procedures. But every organization has some sort of Culture that captures and influences how things get done. Culture is the environment that fosters or inhibits the others. Culture has the highest inertia. Knowledge is embedded as a result of experiences over time and can only be erased with great effort. A knowledge-appreciative and knowledge-competent Culture, once it

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is established, can withstand the shock of reorganizations, leadership changes, and business cycles. Such resilience enables the organization to retain a respect for knowledge during periods when senior leadership may fail to acknowledge and support it. Culture is both a repository of knowledge and an influencer of the capability of the other organizational means of dealing with knowledge. Even if the Culture had no knowledge stored within, it influences whether the organization values and uses its Old Pros, it influences whether the organization can effectively deploy and use Archives, and it influences whether the organization understands and manages its Process. McDermott and O’Dell (2001) conducted a study of companies reputed to have a Culture that supports sharing knowledge. The companies included Apple, Ford, Monsanto, and other global firms. The study found that “however strong your commitment and approach to knowledge management, your culture is stronger. Companies successful in promoting a strong knowledge-sharing culture do not try to change their culture to fit their knowledge management approach. They build their knowledge management approach to fit their culture. As a result, there is not one right way to get people to share, but many different ways depending on the values and style of the organization.” However, it should be noted that some companies are unable to effectively manage their organizational knowledge because the Culture inhibits their doing so. The knowledge management approach must accommodate the existing Culture but an inappropriate or resistant Culture may have to change as well. McDermott and O’Dell found several similarities among organizations with Cultures that supported knowledge sharing. First, those organizations emphasized the sharing of knowledge to solve specific and practical business problems. The companies asserted that the linkage to practical business problems gave the knowledge sharing purpose, purpose that was already reinforced by goals, compensation practices, communications messaging, and so on. Knowledge sharing was a tool with a purpose rather than an end unto itself. Second, those organizations deployed knowledge sharing approaches that match the style of the organization. The knowledge management tools and structures were tailored to be compatible with how the organization naturally prefers to get things done. They were an integrated part of the daily routine rather than being a new and odd bolt on. Third, knowledge sharing approaches were deployed as a way to reinforce existing core values. Again, the intent was to have the knowledge tools and methods as reinforcement of what is rather

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than a change campaign. Fourth, they built on existing networks. Existing informal sharing networks were acknowledged and further supported rather than being replaced. If Old Pros were an active part of the knowledge sharing activity, then new systems were deployed to make it easier to take advantage of them. Fifth, leaders encouraged sharing. The leaders in these companies were quick to identify, praise, and reward examples of knowledge sharing. They were also prompt and clear in expressing their dissatisfaction when individuals, departments, or business units were reluctant to share what they knew. This Culture-shaping fostered knowledge management appreciation and competence. Thus, research supports the assertion that Culture is the foundation for successful organization knowledge management. Let’s move now to descriptions of the interactions among the four dimensions of knowledge management. Culture and Old Pros Both these fundamental tenets exist in nearly every organization. They inevitably emerge when groups of individuals work together. Being so deeply rooted in the organizational soil, they cannot help but influence one another, as they form while the organization itself comes into being and matures. The artifacts, values, and assumptions that define a Culture shape and influence how effective Old Pros can be. In turn, the experiences and biases each Old Pro brings to an organization have an influence on the nature of the Culture of that organization. Old Pros are influenced by the bias a Culture may have for individual initiative and aggressiveness versus teamwork and cooperation. A Culture that respects individual achievers and entrepreneurship may more effectively use its Old Pros who have assertive personalities and may tend to isolate those with less assertive personalities. The knowledge in the minds of the more assertive Old Pros becomes more readily available. Worse, the knowledge in the minds of the less assertive Old Pros is less apt to emerge, and if it emerges is more apt to be discounted. As a result the organization limits its ability to use valuable lessons learned captured in the minds of more timid employees. On the other hand, an organization that values expertise and problem solving over personality may make better use of its entire Old Pro population, even the ones with more timid personalities, because the Culture will encourage both the seeking and the divulging of the knowledge. The more assertive Old Pros are still encouraged to contribute when they add value, but the timid Old Pros are also sought

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out for their contribution and are more willing to step forward on their own. More of the collective Old Pro knowledge is more readily available to the organization. Old Pros are influenced by the internal organizational allegiances. An organization with strong functional organizations operating as fiefdoms will discourage the sharing of the Old Pros’ knowledge across those functional boundaries, while organizations with weaker functional allegiances and more powerful business unit allegiances or project allegiances may be more open to the free flow of that knowledge. Other allegiances may also restrict or encourage the free flow of Old Pro knowledge. Consider the willingness of research departments to share with one another even though they are competing for the same research funding or priority. Consider the willingness of those working on different product lines that are competing for factory resources and priority or for advertising priority. The strength of these and other organizational allegiances is determined by the Culture and they directly influence how effectively the knowledge in the Old Pros’ minds is deployed. An organization biased toward optimism (growth and opportunity) instead of pessimism (problem solving and threat) will value some Old Pros more than others. The more technical Old Pros may find themselves marginalized, while those with marketplace experience may find more favor. One set of knowledge is embraced while another set of knowledge is pushed aside. This sort of bias influences which individuals are embraced as well as which experiences are embraced. The more optimistic Culture will reach out to those Old Pros who have a more optimistic outlook and will neglect those Old Pros with more negative personalities. Thus, important, perhaps vital, organization knowledge is used or marginalized, depending on the personality of the individual holding the knowledge. The organization suffers because it allows bias to marginalize potentially valuable knowledge. An organization biased toward a belief in the uniqueness of its business and technology will tend to discount the views of Old Pro “outsiders.” Some organizations believe their particular business environment and business model is a unique blend of competitors, technologies, market forces, and history that only an “insider” could appreciate. As a result, the members of the organization will tend to discount the wisdom and insights of those not steeped in their particular business. They may discount the perspectives and experiences of Old Pros from other business environments. They may even discount the perspectives and experiences of Old Pros

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from competitors. This rejection of knowledge from other arenas can handicap the organization, especially if their competitors are not similarly blinded. An organization that sees itself as technology driven rather than market driven will value some Old Pros more than others. Recall the anecdotal description of Lockheed versus Boeing in the aerospace industry. One might imagine a bias toward or away from Old Pros with technological versus market experience and insights. The list goes on. Culture shapes how well the organization makes use of its Old Pros. Old Pros also shape Culture and thus how well Culture deals with organizational knowledge. A small group of highly respected veteran employees may be able to influence dimensions of the organizational Culture. Other members of the organization may adopt their biases and preferences. They may influence whether the organization adopts a growth strategy, embraces a new technology, or views the environment as full of opportunity or threat. Over time they may shape the organization’s overall bias toward such decisions and thus shape the Culture. The Old Pros are power brokers who influence what knowledge is stored within the Culture and how the Culture handles that knowledge. Culture and Archives Culture and Archives interact although the relative influence is significantly one-sided, in that Culture exerts much more influence on Archives than Archives do on Culture. Culture influences whether an organization deploys Archives and what deployment approach will be adopted. It also influences how successful such deployments are apt to be. Cultures that have a more orderly worldview, that strive to shape their environment rather than react to it, and that are biased toward fact-based decisions over politically based decisions tend to embrace the notion of Archives. These types of organizations are biased to believe in the one right answer rather than in multiple truths depending upon perspective or majority interest. They tend to believe documenting the facts and data of an experience can accomplish the capture of the critical knowledge. They also tend to discount the value of the tacit knowledge about the situation or event. As a result, these organizations are prone to document a list of lessons learned but leave behind the context that help people understand in the future how to interpret those lessons learned.

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Cultures that are more politically attuned will likely discount the value of Archives because they tend to view each situation as a unique balance of political forces. They will have less regard for the type of factual information readily stored in an Archive. They will tend to discount or reinterpret historical knowledge as irrelevant to the current situation. Thus, Archives are less frequently deployed and, when deployed, are less frequently viewed as being successful. Archives are also less likely to succeed in organizations that value individual achievers because they tend to discount the wisdom stored in the systems, not knowing from whom it came. They rely instead on the knowledge resident in the head of the current champion leading an initiative, or the Old Pro who is currently in favor with upper management. The depersonalization required to store knowledge in an Archive actually causes the knowledge to be suspect when it is retrieved. On the other hand, Archives are more often embraced by organizations that value teamwork and cooperation because they also tend to respect the efforts and accomplishments of those who preceded them. These organizations are also more willing to share knowledge, whether from the past or present. Archives may have a modest influence on Culture because they provide a repository of knowledge that over time can nudge an organization’s Culture to be more knowledge appreciative. However, such a shift can only occur within the context of a broad effort to accomplish such change. Archives are merely one useful, but certainly not vital, tool for accomplishing that intent. Culture and Process Let us begin with a reminder that unacknowledged Process may be viewed as Culture. That is to say, when an organization relies on informal on-the-job training and word-of-mouth to communicate its work routines and procedures, then that organization is relying on Culture rather than Process. Of course, one rarely finds an organization that has no documented and managed work routines and procedures. Today, legal requirements and outside regulatory agencies impose some level of rigor on nearly every organization. The level of control and monitoring in some industries is so pervasive that organizations are driven to extreme levels of detail. A few examples include the nuclear power industry, the drug industry, and commercial aircraft maintenance. In other industries, the technology itself drives the organization to very

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rigorous control of work routines and procedures. The integrated circuit design and manufacturing work described earlier is a good example. So an organization may find itself in an environment that drives it to have relatively more or less control than in other industries. These demanding environments shape the Culture of organizations operating within them. An integrated circuit manufacturing company such as Intel or AMD will be much more rigorous than a computer manufacturing company such as Lenovo or Dell and they in turn will be much more rigorous than a computer retail sales company such as Best Buy. Each business environment leaves a different imprint on both the Culture and the Process bias of the organizations operating in that environment. But organizations within industries will still have relatively different Cultures that influence their Process bias. Both work in a relatively regulated and controlled government-contracting environment, with cutting edge technologies, and engineering professionals make up a significant percentage of their workforce. However, Lockheed Martin thinks of itself as an “engineering” organization while Boeing thinks of itself as a “business” organization. The Lockheed Martin Culture is more prone than Boeing to embrace a robust Process discipline. This assertion may be provocative to many people in the aerospace industry as well as Boeing and Lockheed employees because there are no doubt robust examples of work routine and procedure discipline in Boeing organizations just as there are no doubt examples of lax disciplines in Lockheed Martin organizations. Even so, the point remains that the differences in Culture will tend to leave a unique imprint on the Process perspectives in organizations within competing organizations. Consider also an example of a cross-industry Cultural attribute that influences the Process dimension of organizational learning. As discussed earlier, there have been waves of interest in tools and methodologies related to stabilizing and improving work processes and procedures. Zero Defects, Total Quality Initiative, and Six Sigma are but three examples. Some fad-driven organizations or leadership teams embrace these initiatives when they become popular, creating the outward appearance of rigor and control but not willing to invest in the years-long hard work and discipline required to build a solid foundation and sustain it. These fad initiatives actually impede a Process perspective. First, they disillusion the veteran employees who have seen previous versions emerge and then fade. They are confident the current version will do the same. Second, the naïve approaches drain away resources that could be doing real foundational work to

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understand, define, document, control, and improve key work routines. Third, everyone is eager to show progress is being made but that too often leads to the celebration of trivial or sham successes that further disillusion employees who have seen previous efforts and failures. Shortly after being made the director of quality for a production line making sophisticated missile guidance system components, I was asked by my boss to deploy statistical process control (SPC) disciplines throughout the factory. My predecessor had been given a similar assignment and had failed, as had his predecessor. My own staff of quality control managers and engineers was as opposed to the use of statistical process control as were the production engineers and technicians. Some thought the disciplines could be useful but none thought we could successfully deploy them. The past failures had left a bad taste in everyone’s mouth. Some said the past failures were “proof” that SPC was inappropriate for the low rate production work being done in the factory. We just did not have enough production volume to make the statistics worthwhile. Some said the past failures were proof that senior leaders would not invest in the training and tools necessary to get the workforce appropriately educated. The leaders would not pay the price to deploy SPC. Some said the past failures were proof that the we didn’t need SPC. After all we had continued to ship product, satisfy customers, and make good profits. Why change what is not broken? Everyone had a rationale for why we should not deploy SPC and nearly everyone rationalized that past failures were the proof of their argument. During one of my factory tours I came across a young woman whose job was to supervise the plating of some of the individual parts in the assembly. She had an impressive array of statistics documenting the precision and consistency of the activity. Her work activity was under rigorous statistical process control and had been for some time. I asked Mary about the plating activity, the data, and how it was used. At some point the acronym SPC escaped my lips and Mary quickly said, “We don’t use that word around here.” When I asked why, Mary replied that her engineers and technicians were convinced, like nearly everyone else in the factory, that SPC was not appropriate for our work. Mary then told me that when she started her job she immediately recognized the need for SPC but she quickly came to understand it would be resisted. So, Mary had started a stealth SPC campaign, camouflaging it so that it would not be recognized. She asked the engineers and

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technicians to discuss aspects of the work that were tough to keep under control. She asked them to help her collect data, conduct experiments, and make changes to make the work more predictable and stable. Step by step she deployed a very sophisticated SPC system and brought the work activity into control. Everyone in her department was proud of what they had done and was eager to describe their accomplishments, complete with statistical charts. But everyone in her department still hated SPC and believed it would never work in our factory, certainly not on their work activity. A few weeks later I convinced Mary to take on a new assignment. I asked her to wander the factory floor, helping production teams solve problems. If along the way she managed to teach them a few SPC techniques that was great. A year later we had successfully deployed SPC across all the critical area of the production line and the supply chain. In year two we began to use the acronym SPC, but only because our teams were being asked by customers and competitors to speak at industry conventions about all the great SPC work at our plant. Culture and history had managed to impede the Process perspective for years before finally yielding. On the other hand, a strong production heritage may reinforce a Process perspective, not withstanding the example above. An organization with a strong production heritage may tend to see itself as organized around a linear flow, with one specific work activity leading to another, while organizations with a less repetitive work discipline (consulting, product development, or large scale construction) may more readily see themselves organized around parallel and interactive activities. The former find it easier to define and measure the work activities than do the latter. The former find it easier to apply the Process tools and techniques to their work than do the latter. A Culture that encourages cooperation and shared goals among functional groups may see work activities that exist across functional boundaries, while a Culture that encourages or enables fiefdoms will see work activities that exist primarily within each fiefdom. The former will more likely acknowledge and address the complex interaction between activities, while the latter will be apt to define the work activities with few, specific, and formal interactions. Culture will significantly influence the boundaries and interfaces between work activities. Culture will shape Process. Organizations deploy a Process perspective within a supportive Culture to give themselves the vernacular, tools, techniques, and methodology that enable them to understand how work gets done,

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to learn how to improve how it gets done, and to capture that learning. A supportive Culture will foster embedding the Process disciplines deeply and broadly across the organization. As a result, they will remain an asset for the organization even as industry or corporate enthusiasm for them may fade. Old Pros and Archives Influential Old Pros have impact throughout an organization. Their impact is amplified if those Old Pros happen to be senior executives or key managers, if they happen to be especially knowledgeable about critical technologies or methods, or if they happen to be well known and respected in the customer or competitor community. It is thus no surprise that the Old Pros may have influence over how an organization deals with what it knows. Certainly, they may influence Archives. Old Pros attitudes about knowledge and power are important. If the Old Pros believe that what they know makes them influential and powerful, then they will likely resist attempts to capture that knowledge so that it can be shared openly. They will likely oppose Archives. On the other hand, if the Old Pros are less focused on their personal power or prestige and more focused on helping the organization accomplish its goals, then they are more likely to support Archives. An Old Pro’s personal comprehension of the nature and form of her knowledge is important. If the Old Pros do not really understand what it is they know then it will be difficult, perhaps impossible, to capture that knowledge in an Archive. Recall the earlier story about the person who recognized the “bad” primer. If asked he may well have had no idea that he had special knowledge about primer. He needed a trigger, seeing the primer on the dipstick reflected in the light, to bring forward his knowledge. One cannot readily articulate knowledge if they do not realize they have it. Archives are seen as useless when a lot of the organizational knowledge is unrecognized. The comprehension problem also emerges in reverse form. Consider an Old Pro who truly believes a lot of what he knows is too complex or subtle or situational to be articulated and captured. A river pilot who has spent forty years guiding ships through a particularly dangerous strait may well believe that the complex interaction of tides, winds, ship sizes and steering characteristics, and shifting shallows could never be documented then understood and used by less experienced pilots. His reluctance to share the knowledge may not be rooted in a desire to preserve power but instead be founded on a sincere belief

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that the knowledge is so subtle and dynamic that it must be learned anew by each new pilot. The pilot will resist attempts to capture that knowledge in Archives. On the other hand, Old Pros may have a positive influence on Archives. A senior employee who is emotionally attached to the organization and to his job may want to leave behind everything he has learned over the years. He may be quite motivated to share his knowledge before he retires because he wants the organization to continue to thrive. Such people may be delighted to share what they know and pleased to see it captured in such a way that others can use it. The knowledge left behind in the Archive is in effect his legacy. Such an Old Pro may be enthused about Archives if he believes they can help capture and share his knowledge contribution. Once an Archive is built, the Old Pros’ attitudes and behaviors can determine whether or not it will succeed and sustain. If those influential Old Pros disdain the Archives, then others are apt to do so as well. If they use them as a resource, contribute to the knowledge base, and advocate them to others, then the Archives will be given a chance by others. Old Pros and Process Much of what has been said above about Old Pros and Archives can be repeated here. The relationship is similar. Old Pros who believe knowledge adds to their personal power and influence will be reluctant to see work activities defined, documented, controlled, and monitored. They may conclude that they will lose control over the knowledge and thus lose personal power and influence. They may even act to prevent or misdirect the efforts in an attempt to protect their power position. Old Pros who believe their knowledge is too subtle or complex to be defined, documented, controlled, and monitored may also be an impediment to success. These individuals may not cling to the knowledge as a base of personal power. Instead they may truly believe that what they know is too subtle or too contingent on immediate environmental circumstances to ever be captured as part of a documented work activity or procedure. These people think of themselves as artisans or craftsmen. On the other hand, a supportive Old Pro can help the organization truly understand and accurately capture the work activity so that others can benefit. They can foster a stronger organizational Process perspective.

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In summary, Old Pros who believe in personal power or in the “black art” of knowledge will impede a Process perspective. Those who understand and endorse the Process perspective can help bring it to life and sustain it. Archives and Process Archives and Process do not significantly influence one another. They can be complementary and supportive, but either can exist, even thrive, without being significantly affected by the other. Both are repositories of organizational knowledge. Archives may be used to retain historical knowledge about a particular work activity or procedure. Work activities and procedures may have been developed or adapted to take advantage of knowledge residing in Archives. Even so, one does not significantly influence the other. Although Process may encourage use of the tools and perspectives that enable a more effective application of Archives, this benefit is relatively modest on its own. Impact versus Value The four factors influencing organization knowledge management success have relatively different impact and value on the organization. They are also relatively more difficult or less difficult to use and manage. Certainly these differences may vary from one business model to another, or even from one organization to another, depending on the environmental and historical forces at work. Even so, fundamental differences do exist regardless of the business model or organization dynamics. See figure 7.1, Comparison of Four Organization Knowledge Management Dimensions. Archives are relatively easy to develop and deploy, certainly easier than any of the other three factors, but have relatively little impact or benefit. The apparent ease and speed of deployment makes them attractive solutions for frustrated leadership teams. Their very nature—they are generally viewed as a relatively direct application of a tool—makes them easy to use and to manage. Of course, the counter to this ease is that Archives provide a relatively low value benefit or impact, certainly much lower than that of Culture, Old Pros, and Process. Old Pros are also relatively easy to manage, perhaps as easy as managing Archives. They are already present in the organization. They are already being utilized by the organization. Managing them is essentially a people utilization and communications challenge, activities all

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Difficult

Management

Culture Process

Old Pros Archives

Easy Low

Benefit/Impact

High

Figure 7.1 Comparison of Four Organization Knowledge Management Dimensions Source: Author’s Illustration

organizations address daily. Organizations can certainly improve how their Old Pros facilitate organization knowledge management much easier than they can improve how Culture and Process facilitate it. Old Pros offer significantly more potential impact and benefit than do Archives. Old Pros handle both tacit and explicit knowledge, while Archives struggle to cope with the broad, diverse, and critical tacit knowledge. Old Pros already possess the knowledge. There is no need to capture and attempt to accurately interpret it. Old Pros already have established channels of communication and venues for sharing their knowledge. Old Pros provide context and interpretation that allows knowledge to be more readily adapted to current circumstances. Old Pros offer perhaps the best balance of impact and value versus management challenge. Leadership teams would do well to begin their knowledge management improvement initiatives by focusing on Old Pros. Culture presents an interesting dilemma. One may argue that organizations are adept at managing it and therefore it presents only a modest challenge. However, one may also argue that the management of Culture is one of the most difficult, and perhaps most neglected, challenges for senior leadership teams. Even those most proficient and capable leadership teams would likely admit how difficult it is to build and sustain Culture. However, the challenge cannot be avoided. As already stated, Culture is a vast repository of valuable organizational knowledge, it is a pervasive purveyor of that knowledge, it dramatically

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influences how capable Archives, Old Pros, and Process can be, and it is resistant to changes in the knowledge it has. Process presents major management challenges and offers dramatic rewards as described earlier. Its fundamental advantage is that it is more readily adapted to new circumstances than is Culture because it is more overt, because it retains knowledge and context rather than just the learned behavior in response to stimuli, and because it is founded on generations of management tools and techniques. A Word about Changing Impact The factors that have made organizational knowledge management ever more important have also changed the balance of power and influence among the four venues. What mattered most may now be less important or even harmful. Culture was, and still is, a powerful repository and disseminator of organizational knowledge. However, today it is at least as much an unavoidable handicap as an asset. Recall that learning is embedded in Culture as a result of multiple experiences and thus occurs over long periods of time. Recall also that the learning embedded within the Culture can only be modified or deleted with difficulty and over long periods of time. This viscosity was an asset when technology changed slowly, communications was more restrictive, and competitive markets were less dynamic. Today, and even more so tomorrow, organizations must be able to quickly acquire new knowledge, quickly adapt what they already know to a changing world, and quickly rid themselves of old knowledge that no longer fits the current and coming environment. Culture does not willingly cooperate with such an agenda. Leaders must foster an organization-wide appreciation for the challenge this raises and foster a behavior that copes with the challenge. The influence of Old Pros is subject to opposing forces. One trend is increasing their value as holders and disseminators of organizational knowledge, while another trend is decreasing their value. Old Pros have been, and still are, an invaluable repository and disseminator of organizational and individual knowledge. They have become even more critical to organizational knowledge management success, because today’s complex technologies and techniques create more rather than fewer individuals who possess invaluable knowledge and experience. Today’s highly mobile workforce enables those individuals to more easily move from organization to organization. Their knowledge moves with them. Today’s high-bandwidth

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communication environment facilitates the rapid transfer of knowledge as well. These precious Old Pros have ever more opportunity to share the knowledge they hold with competitors, customers, or suppliers. Thus, the organization may be less able to protect that knowledge and less able to build competitive advantage around it. Leaders must continue to find ways to retain the truly valuable Old Pros. But, the knowledge held by Old Pros generally declines in value more and more rapidly as the rate of change of technology increases. The veteran automobile mechanic was once appreciated for his years of experience and his knowledge about how to diagnose a problem and come up with an inexpensive repair. But, today’s automobiles have increasingly more computers on board, increasingly more complex systems, and increasingly more integrated components. The Old Pros’ knowledge becomes less relevant each year as the technology becomes more sophisticated. The emergence of fuel efficiency technologies and alternative fuel technologies will eliminate, alter, or replace some existing automobile systems, thus reducing the value of some of the knowledge held by the Old Pros. New technologies will call for mechanics with newer skills and experiences. But those technologies will be replaced after a few years and yet a different set of skills and experiences will emerge as important. This ever more rapid technology change is reducing the value of Old Pros, perhaps replacing them with an ever-changing wave of New Pros. Archives can be more robust than in the past. Technology has enabled the integration of text, narrative, and video. It has enabled user-friendly interfaces and sophisticated search engines that make the human interaction less difficult. However, technology has not yet overcome the challenges of dealing effectively with tacit knowledge, with context, or with adaptation. Archives are now able to more efficiently accomplish their relatively modest role in organizational knowledge management. Perhaps their time will come. Process has steadily become an increasingly vital part of organizational knowledge management. Ever more complex technology and ever more complex business environments have spawned dramatically more complex work activities and procedures that demand ever more sophisticated configuration control. The knowledge retained in Process is more readily adaptive to change than is the knowledge retained in Culture. It can also be kept proprietary more easily than can the knowledge in the minds of the Old Pros. In summary, the relative influences have changed and continue to change. Culture has become more of a threat to be managed and less of a useful tool. Old Pros remain invaluable resources and may have

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become even more important. Archives remain a niche contributor in spite of the enthusiasm for them. Process has become even more important to overall organization knowledge management competence. What Lies Ahead The next chapter, chapter eight, Pragmatics of Managing Organizational Knowledge, offers insights to several topics not yet addressed, including practical insights about what techniques have been found useful, the all-important role of tacit knowledge, how organizational structure influences the flow of knowledge, the positive role IT can play, knowledge management metrics, and knowledge sharing outside the organization, among other topics. References Crossan, Mary M., Henry W. Lane, and Roderick E. White. (1999). An organizational learning framework: from intuition to institution. The Academy of Management Review 24(3) (July): 522–537. McDermott, R., and C. O’Dell. (2001). Overcoming cultural barriers to sharing knowledge. Journal of Knowledge Management 5(1): 76–85. The authors describe how cultural barriers can dramatically impede an organization’s ability to make effective use of what it knows.

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Chapter 8

Pragmatics of Managing Organizational Knowledge

Every organization is a learning organization, although some are

more effective than others. Best-in-class learning organizations appreciate the power, the complexity, and the challenge of managing all four methods that determine just how effectively the organization learns and applies that learning. These organizations embrace the organizational development techniques that shape the Culture, make use of Old Pros, deploy Archives appropriately, and successfully master the principles and tools that enable them to perpetually control their ever-evolving Processes. The result is an integrated environment that enables the organization to make optimal use of what it knows and to extend its knowledge faster than its competition. This chapter offers a collection of best practice observations. It includes findings about why knowledge management projects fail or succeed. It offers a few comments about the benefits and shortcomings of knowledge management metrics. It addresses knowledge sharing outside the organization. It also touches briefly on a few other topics. The chapter is intended to provide leaders a set of tips that may help them better understand the unique challenges in their organizations and help them lay out a path to becoming more competent knowledge managers. What Works and What Does Not The American Productivity and Quality Center (APQC) provides an ongoing source of insights into what does and does not work when it comes to organizational knowledge management. Its membership includes hundreds of major industry and government organizations

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that have conducted thousands of knowledge management projects and participated in over a hundred cross-organization benchmarking studies. For example, the APQC International Benchmarking Clearinghouse member companies participated in a 1994 study of organizational learning transfer and came away with some disturbing conclusions. In short, they confirmed what many executives already know, knowledge does not transfer easily between organizations or work teams. They found examples of high-performance factories across the street from poor-performing units of the same company and a seeming inability to move best practices from one to the other (O’Dell and Grayson, 1998). Their study concluded there were three barriers to effective transfer of best practices. First was ignorance. Those using best practices were unaware that what was being done might be a best practice and unaware that others may find the practice useful. Those needing a better approach or method were generally unaware that others may have a best practice that could be adopted or adapted. Second was what APQC called absorptive capacity. Those in need of better methods, and even aware that better methods existed, often felt they lacked the resources, specific information, or authority to accomplish the changes. Third was lack of a relationship between the source and the recipient of the knowledge. Too often those in need were aware of an organization with a better approach but a lack of personal ties between managers was seen as an obstacle to successful transfer. The APQC found that the organizations that were most successful at knowledge transfer made use of benchmarking teams, knowledge and practice networks, internal assessment and audit teams, and a Culture that values the sharing of knowledge. They identified seven specific recommendations for fostering organizational knowledge transfer. The example below illustrates their seven findings. First, organizations should use benchmarks to create a sense of urgency and to develop a compelling reason for change. Benchmark data challenges acceptance of the status quo. People in the organization can quickly articulate all the reasons why the current performance is the best it can be under the circumstances. They often need to see that competitors are actually overcoming the circumstances and delivering better performance. One leader arrived at a new business unit with an on-time-tocontract-promise-date performance of about 80 percent. The managers were generally satisfied with the performance, until the leader gathered benchmarking data showing the industry peer average was about

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87 percent, the first quartile performers in the industry peer group were at about 93 percent, and the best in class performers were typically making over 98 percent of their contract commitment dates. The data also clearly showed that the best on-time-delivery performers were also consistently among the best financial performers. The new leader used the benchmarking data as evidence that the organization was performing at below industry average levels, that successful competitors were doing much better, and that the organization must improve. They did—three years later the organization achieved 100 percent ontime performance for the entire year, and they sustained an average of greater than 97 percent performance for the next four years. Second, organizations should initially embrace projects that can have real impact on critical business issues. Any disagreements about the value of change projects will drain away energy that could be better applied to the improvement project. Finding projects that everyone can agree would be beneficial to the organization. In this case, on-time delivery was an issue that customers cared about. It affected customer satisfaction and thus future business. Late deliveries created unplanned work and drained away resources needed for other activities. Potential profits were being drained off to deal with these unplanned costs. It was relatively easy to make a value and strategy connection that all employees could accept. Some employees argued that the poor delivery performance could not be significantly improved, or that it was “good enough,” but nearly everyone agreed that better on-time performance would please customers and cause less disruption in the factory. Third, only take on improvement initiatives that will be resourced and supported. Rhetoric is no substitute for action and commitment. Leaders must adequately staff the improvement projects, make working on them a priority, and be willing to make organizational changes in order to accomplish improvements. In this case, insufficient test equipment was widely viewed as a root cause for missing schedule. The organization put in place metrics to track test equipment availability and reviewed the data monthly at the senior leadership team meetings. The organization also established a system for predicting test equipment needs and for resolving conflicting needs. They also funded repairs of some older equipment that had been sitting idle. Finally, they invested in facility changes to allow for more efficient staging of equipment before and after testing in order to get more actual test hours out of the existing equipment. These additional resources and changes greatly reduced the test equipment bottleneck.

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The business invested in additional and updated equipment, thus eliminating bottlenecks and ensuing delays. Failure to do so would have clearly indicated that the management rhetoric was to be ignored. Supplier material problems also often caused delays. Again, the business invested key talent and energy to help suppliers improve or to find replacement suppliers. Unfunded mandates are soon disregarded and management loses credibility. Resourced mandates get employees’ attention. Fourth, don’t let measurement systems get in the way of progress. Organizations too often get bogged down in protracted debates about metrics definitions, what metrics matter, and whether the data is accurate. These debates can become an alibi for delay that may eventually kill the initiative. The organization was in denial about its bad performance. Some of the key leaders and managers wanted to parse the benchmark data, making excuses for why their business was different or why the industry data was flawed, but those discussions were squelched. Later, some individuals tried to manipulate the internal performance data by not counting late deliveries if a vendor caused the problem, or by asserting the customer did not yet need the product, or even by asking the customer for schedule relief and resetting the due date. The organization was moving from a state of performance-denial to a state of performance-alibi. In retrospect, leadership came to understand that the shift from denials to alibis was actually a sign of progress, although it did not seem so at the time. Again, senior leadership had to squelch this sort of behavior while still encouraging people to seek out and resolve internal issues that were impeding performance. As the organization made improvements leading to better on-time performance, they began to embrace the benchmark data and work even harder to improve performance. They also began to create and use a few internal metrics to help them understand where performance and predictability problems existed and when changes were working. Even so, specific internal metrics were a persistent challenge. What did on-time mean? Was it the contract due date? Was it the latest promise date? Did delivery within the month count or did it have to be on a specific day? Did partial shipments count? How much? Did early deliveries offset late deliveries? What if the suppliers caused the delay? What if the customer caused the delay? Did a missed delivery count as only one miss or did it count as a recurring miss until it got delivered, perhaps several months late? The scorekeepers found themselves on the defensive against the individuals and teams that were trying to demonstrate improved

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performance by manipulating the numbers rather than making substantive changes. Senior management found they continually had to explain that the metrics were a measure of how well, or poorly, the organization was keeping its promises to the customers. They continually had to remind the workforce that when they manipulated the numbers they were merely avoiding telling themselves the truth. Leaders had to work hard to keep measurements from becoming a goal unto themselves. Fifth, reward sharing and knowledge transfer efforts, not just results. Significant results may not occur for a while. It is important to reward efforts and to celebrate even the small gains. Effort was rewarded in several ways. Improvement team members were publically recognized. Teams met frequently with senior leadership, giving them opportunities to interact. Leaders described the projects as learning and exploration experiences, reminding people that the failed projects could be more valuable for what was learned than some of the successful projects for what was accomplished. The organization also celebrated any signs of improvement. They had a set of desk clocks and plaques made up, giving one to any project manager who demonstrated three consecutive months of improvement on meeting contract commitments. They held celebrations if the organization reached specific levels of improvement. Senior leaders hosted luncheons for individuals and teams that accomplished process improvements, particularly improvements leading to better on-time performance. Such recognitions communicated what behaviors would be rewarded. They communicated that improvement was being made. They also served as a way to spread knowledge to other groups where it might prove useful or insightful. Sixth, use technology where appropriate but remember that it is a tool rather than a solution. The deployment of an IT database is not a substitute for understanding the obstacles to knowledge flow across the organization. This particular organization had a great disdain for IT-based knowledge management because of several failed attempts in the past and because of a bias toward using knowledge as a personal or departmental power base. The Culture had not yet evolved to allow Archives to be successful. This organization also tended to only engage its Old Pros when a crisis arose. The leaders focused instead on projects directed toward the work activities, procedures, and resources that influenced on-time performance. In short, their change initiative began with a focus on Culture and Process.

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The point is that recipes, even recipes for organizational knowledge management, must be initially adapted to meet local tastes if they are to be embraced. The recipes may be further improved as local tastes improve. Seventh, leaders must consistently and persistently communicate their commitment to knowledge sharing. Employees often resist change and embrace the status quo. Change also requires the disruption of routines that can add risk of new problems. Leadership must provide the clear and powerful reminder that the benefits of successful changes outweigh the risks and discomforts of making the changes. The senior leadership faced three great challenges throughout this initiative. First, they were challenged to overcome the denial about the organization’s shoddy performance. Many people, some in key leadership positions, were unwilling to acknowledge the poor ontime delivery performance. Second, they were challenged to commit resources, money and talent, to make the necessary infrastructure changes. The employees eventually came to accept the reality of the poor performance but then doubted leadership’s willingness to make the tough decisions that would spawn real improvement. They had to witness those tough decisions being made and the resources being provided. Third, senior leadership had to remain steadfast in their commitment to real and lasting change rather than the manipulation of the data to create the appearance of change. Leadership could not permit false improvements created through manipulation of the data and metrics changes. To do so would have belied the stated commitment to real change and real improvement. The findings from this particular APQC research are consistent with the findings of other research. For example, Fahey and Prusak (1998) described the Eleven Deadliest Sins of Knowledge Management derived from their decades of studying organizational knowledge management. Their list of taboos complements the findings from the APQC study but the reader will see that the perspective is also somewhat different, because Fahey and Prusak take a more holistic view of knowledge management. They appear to be thinking about the organization’s overall knowledge management competence rather than thinking about deployment of specific improvement initiatives. Their Eleven Deadliest Sins of Knowledge Management are: 1. Not developing a working definition of knowledge. Left to struggle without a clear and mutually shared definition, the organization will drift toward the capture of explicit data and

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information leaving behind the ever so critical, but difficult to capture, tacit knowledge. Thus, this failure contributes to many other failures. But there is risk in delving too deeply into definition. Recall the earlier caution about not getting bogged down with metrics. Definitions of terms and metrics can mire an organization in debate thus preventing them from making real progress. On the other hand, too little clarity of definition can lead to confusion and conflict if people are operating with different understandings about what is meant. My own experience has been that some initial effort must be put into defining terms. A small cadre of leaders should develop the definitions, then communicate them clearly to the broader workforce. Inevitably, the initial definitions will be challenged and will have to be adjusted, but that work can occur in parallel with making progress, progress that will better ground the discussions in reality. 2. Focusing on knowledge stock to the detriment of knowledge flow. Knowledge that does not move readily from where it is to where it may be useful is worth far less than knowledge that moves readily throughout the organization. Recall that Jerry Junkins of Texas Instruments and Lew Platt of Hewlett-Packard were concerned about understanding what they already knew and moving it to where it could be made useful. They were less concerned about capturing and storing what they knew. They were convinced they already had a massive amount of knowledge within the organization. It simply was not flowing freely and thus was being underutilized. 3. Viewing knowledge as existing predominantly outside the heads of individuals. Knowledge inside people’s heads has broader and deeper context, is more readily adaptable to new situations, and is more readily combined with other knowledge. Knowledge resident in a database has been stripped of at least some of its context and is less adaptable. Archives, by their very nature, encourage an organization to strip the knowledge from the minds of individuals and convert it, some would say “pervert” it, into a digitized format. 4. Not understanding that a fundamental intermediate purpose of managing knowledge is to create shared context. Sharing knowledge fosters a shared belief system across the organization that in turn reinforces sharing knowledge. The active personal exchange of knowledge creates deeper understandings and thus more powerful knowledge. This “deadly sin” is consistent with the notion

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of knowledge flow. The activity of sharing knowledge builds shared context and thus organizational cohesiveness. 5. Paying little heed to the role and importance of tacit knowledge. Management too often does not understand the nature of tacit knowledge nor how to deal with it. This topic will be addressed in more detail later. 6. Separating knowledge from its users. Putting knowledge in sterile databases disconnects it from its users. The knowledge is more accessible but the insight, value, and utility of the knowledge is diminished. One might assume Fahey and Prusak are being redundant with items three and five above. But the point here is that knowledge was always acquired in a context that made it relevant and useful. It may or may not be so relevant—indeed it may be harmful—if applied in a different context. They are arguing that the users are best able to understand the knowledge and its relevant context for other situations. 7. Downplaying thinking and reasoning. The environment continually changes, making prior knowledge suspect in a new world. It is vitally important that the organization perpetually criticizes, adapts, and adds to its store of knowledge. Certainly Culture may override thinking and reasoning when it encourages us to do what has always been done without thinking about it. The organization needs to value thinking and reasoning rather than dogmatism. Process can be overly dogmatic and prescriptive thus inhibiting users from adapting to the situation at hand. Work routines and procedures should be documented and specific yet remain flexible enough to adapt to unique situations. 8. Focusing on the past and the present not the future. Knowledge is useful only in so far as it influences better decision about the future. An organization should seek to capture and build on knowledge that will be useful for its future challenges and opportunities, not its past. Probing the past too often leads to rationalization about why decisions and actions were appropriate. Looking to the future and asking what knowledge may be useful allows people to be more open to discussing the lessons from the past. 9. Failing to recognize the importance of experimentation. Knowledge cannot remain stagnant. The Culture must encourage perpetual challenge of prior knowing and adaptation to a changing world. Fahey and Prusak are making the point that organizations

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too often grapple with capturing their “lessons learned” but fail to build the social mechanisms and perspectives that enable them to adapt those lessons to the changing future. The former is wasted effort without the latter. 10. Substituting technological contact for human interface. Information technology, no matter how powerful, cannot replace the benefits of direct personal contact that leads to more robust learning. Organizations that build in multiple venues for interaction and sharing are inevitably more competent knowledge acquirers and managers. 11. Seeking to develop direct measures of knowledge. Knowledge itself is difficult, perhaps impossible, to measure. Knowledge management is just as challenging to measure. Instead organizations measure proxies such as patents, process innovations, new products, and so on. Einstein is reputed to have said, “The things which are not measurable are more important than those which are measurable.” How well an organization manages what it knows is certainly vitally important and there is no clear way to measure it. Organizations and leaders all too often commit these Eleven Deadliest Sins of Knowledge Management. Leadership teams would do well to visit them regularly as a reminder of how they can go wrong. Davenport and Prusak (1998) studied thirty-one knowledge management projects in twenty-four companies to discern the likely success factors and they found eight of them. The study focused on the success or failure of individual projects but it offers insights about the environmental influences that drive project success. Their study appears rooted in a perspective that includes both organizational knowledge management competence and project success. The eight success factors for individual projects are: 1. Link the project to economic performance—Tying project success to measurable economic benefits helped the organization make resource investment versus payoff decisions that kept the projects going. 2. Technical and Organizational Infrastructure—Projects found success more often when both technical (IT) and organizational (roles and responsibilities for knowledge sharing) factors were addressed.

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3. Standard yet flexible knowledge structure—Successful projects were sensitive to the need for flexible structures. Knowledge repositories must have enough structure to enable efficient searches yet must be flexible enough to accommodate context-rich knowledge. 4. Knowledge-friendly environment—Projects succeeded when they were deployed in a knowledge-friendly environment. The organization must value knowledge and curiosity. Employees must believe that knowledge sharing will be appreciated and knowledge hoarding will be frowned upon. The project must be structured to fit within and support the current way of doing things. 5. Clear purpose and language—Organizations that were careful to clearly define knowledge management terminology and the knowledge management project goals found success more often than those that did not do so. 6. Change motivational practice—Projects succeeded more often when the organization found new ways to encourage and reward knowledge sharing practices. 7. Multiple channels of knowledge transfer—Projects were more often successful when organizations understood that knowledge may flow through multiple channels and accommodated such parallel flows rather than discouraged them. 8. Senior management support—As is true for most organization initiatives, success is more likely when the project has strong and visible senior management support. These three studies show strong consistency as to what facilitates or handicaps organizational knowledge management. Leaders have before them a relatively clear, but certainly not easy, challenge. Tacit Knowledge—The Vital 80 Percent Perhaps when it comes to knowledge, the 80/20 rule gets upended. Many researchers, and many informed executives alike, agree that about 80 percent of what an organization knows is tacit rather than explicit. The tacit knowledge is difficult to recognize, difficult to capture, and thus difficult to apply efficiently. Yet, it is critical to do so. The caution to leaders is to not succumb to the temptation to work on only the explicit 20 percent of what an organization knows merely because it is visible and can be documented. Hellstrom et al. (2001), while studying knowledge transfer in a software engineering firm, identified two overall approaches used

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Table 8.1 Centralized versus Decentralized Approach to Knowledge Management Centralized

Decentralized

Top-down implementation Based on IT Generalizable solutions Knowledge centrally gathered and shared People are pushed to share knowledge Expensive

Bottom-up implementation Focusing on people interaction Unique solutions Knowledge gathered and shared in an open market Reactive and adaptive Cheap

Source: Author’s Illustration

by organizations within the firm. They observed that some groups used a centralized control approach, while others used a decentralized control approach. The former generally viewed the knowledge transfer as an activity to capture something tangible and specific that could be saved and retrieved on demand, while the latter viewed knowledge transfer as a social interchange that encouraged knowledge to move freely. They found the decentralized approach to be much more effective and enduring than the centralized approach, one reason being that it more readily accommodated the handling of tacit knowledge. The two approaches are characterized below. See table 8.1—Centralized versus Decentralized Approach to Knowledge Management. Von Krough et al. (2000) reinforced the perspective when they identified five keys to enabling the capture and use of tacit knowledge: (a) instill a knowledge vision, (b) manage conversations, (c) mobilize knowledge activist, (d) create the right enabling context, and (e) globalize local knowledge. Organization Structure Influences Knowledge Flow The old saw that strategy drives structure might be extended to assert that structure then drives organizational knowledge competence. It is often asserted that organizations partition and group labor to accomplish business objectives and to accomplish a strategy. As an aside, sadly, reorganizations all too often occur for entirely different reasons. No matter what the motivation for a particular organization structure, the structure compartmentalizes knowledge in ways that may enhance or restrict its use. Executives often begin a discussion about organizational structure with a conversation about broad choices. The conversation addresses

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whether the organization should be organized around customers, workflows, technology, or geography. The choice may be influenced by the relative power of the customers, by the most powerful factors in the value chain, by the biases of the current leadership, or by the current biases flowing through the corporation or industry. These influences and biases will shift over time, prompting structure changes. Consider the example of a machining business that makes metal parts for a variety of customers. They build components for automobiles. They also build factory tooling and machinery. They also build components for airplanes, both commercial and military. One structural option might be to organize into three or four customer groups, because each group has unique specification requirements, unique quality demands, and unique buying practices. Each customer-facing sector of the organization would have its own marketing and sales team and its own segment of the factory equipped to optimally meet their customer’s needs. Another option might be to organize around the critical internal workflows because all customers care about low cost, on-time delivery, and responsiveness to unexpected needs. Focusing on workflows efficiencies would potentially improve cost, cycle-time, and flexibility. The marketing and sales department would serve all customers. The design department would work on all new designs regardless of customer. The manufacturing department would control the entire factory. Yet another option might be to organize around key technologies because of the training and equipment requirements. One segment would focus on jobs requiring extremely high precision or special materials for unique applications. Another segment would focus on higher volume, less complex traditional work. Yet a third segment would focus on service and repair work. Yet another option might be to organize geographically in order to provide timely regional support to a variety of customers. One segment would be responsible for all the customers and factories in Northern California, another would be responsible for all the activity in Southern California, and a third would be responsible for establishing a capability in Phoenix, Arizona, to expand the business in the southwest. Each segment would have a regional sales team and their factories, and would manage procurement of materials. Each alternative is viable and no one structure is perfect. Each has advantages and disadvantages that must be recognized and managed. The environment in which the organization operates is dynamic and

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even a perfectly fitted structure would quickly become flawed because it would no longer fit the changed environment. One alternative will be selected. All organization structures have gaps between the segments and it is in these gaps where many organizational problems, including knowledge management problems, lie. Organizations sometimes force themselves through the pain of recurring structure changes in search of the elusive perfect structure, when instead they should focus on managing the inevitable gaps of what will always be a less-thanperfect structure. So what does this have to do with organization knowledge management? A lot. An organization structured around customers will likely develop deep knowledge about customers and markets but will not naturally share that knowledge with other customer teams who will tend to discount the knowledge as less relevant to their own customers and market anyway. The organizational structure itself has created a knowledge-sharing impediment. An organization structured around workflows will naturally develop a deep knowledge about internal work activities. Each department will come to understand deeply how to get its work done inexpensively and on time. But each department will tend to sub-optimize to make the work in its area of responsibility optimal rather than to optimize the overall work activity. A different knowledge gap has been created. An organization structured around technology will likely develop a deep understanding about unique and emerging specialty materials but that knowledge will not readily be shared with the other departments. They may have to discover the knowledge themselves. Yet a different knowledge gap has been created. Finally, an organization structured around geography may find itself learning the same lessons at different locations because there is little opportunity to share learning between sites. In this instance both geography (separation) and structure have created a knowledge gap. Each organization structure alternative encourages the development of different sets of knowledge. The structure also establishes natural bridges or gaps that foster or impede the sharing of knowledge. Culture, Old Pros, Archives, and Process are the vehicles by which organizations can understand, manage, and optimize what knowledge is created then assure it is optimally shared. They help create the bridges over which knowledge may cross the chasms between parts of the organization.

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Multiple studies of knowledge-intensive organizations reveal that competitive advantage often emerges when sectors of an organization are able to appreciate and integrate their own knowledge with that of other sectors. The groups that are free to exchange and evaluate one another’s ideas and perspectives are able to build new more powerful ideas and perspectives leading to new knowledge (Boland and Tenkasi, 1995). Brown and Duguid (1998) made the point well: “The distribution of knowledge in an organization, or in society as a whole, reflects the social division of labor. As Adam Smith insightfully explained, the division of labor is a great source of dynamism and efficiency. Specialized groups are capable of producing highly specialized knowledge. The tasks undertaken by communities of practice develop particular, local, and highly specialized knowledge within the community.” They added, “From the organizational standpoint, however, this knowledge is as divided as the labor that produced it. Moreover, what separates divided knowledge is not only its explicit content but also the implicit shared practices and know-how that produced it. . . . communities develop their own distinct criteria for what counts as evidence and what provides ‘warrants’—the endorsements for knowledge that encourage people to rely on it and hence make it actionable.” Leaders should remember that when it comes to knowledge flow throughout their organizations they need to “Mind the gap,” as they say on the London Tube. The gaps between parts of the organization deter it from making the most effective use of what it knows. All gaps cannot be eliminated, because such an organization cannot function in any complex way. But the gaps can be bridged. Leaders can make sure the gaps are known and that multiple wide bridges are built to encourage knowledge to move freely across them. Information Technology Has a Role IT has traditionally been used to enhance the capture, storage, and retrieval of organization knowledge. Typical examples have included Archive devices such as data warehouses, document management, and search tools. These applications facilitate the handling of explicit knowledge but do little to facilitate the handling of tacit knowledge. Chapter five, Archives, described some of the failure modes when designing and deploying IT-based systems. Leaders should remember that IT systems do not handle tacit knowledge well, often destroying or maiming it in the attempt. Leaders should also remember that

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the IT systems must be compatible with the Culture and the existing work routines and procedures; if not, the systems will fall into disuse. Even so, IT has the potential to play a useful role in facilitating the informal interactions that encourage the exchange of tacit knowledge. Boland and Tenkasi (1995) describe studies by Dougherty (1992) and by Purser (1992) that found knowledge-intensive product development projects often failed when members of the product development teams encountered barriers to knowledge sharing between themselves. A second related factor was that the members were unable to reconcile their different perspectives about relative priorities, about risks and uncertainties, or about the appropriate path ahead. A third factor was that the members were unable to reconcile their different departmental perspectives about the project. Boland suggests that IT need not be limited to supporting Archives. The technology can be used to support forums that encourage the reconciliation of different perspectives and the free flow of knowledge. He identified five classes of forums: task narrative, knowledge representation, interpretive reading, theory building, and intelligent agent. Task narrative forums would capture narrative descriptions of work being done through the use of text, audio, and perhaps video. Knowledge representation forums would provide a venue for participants to openly discuss the narratives, share their interpretations, and develop new insights. Interpretive reading forums would provide a venue for discussing the deeper assumptions and meanings behind what is captured in the narrative and interpretations. Theorybuilding forums would facilitate the posing of theories and thought experiments that could be challenged by the broader community. Intelligent agent and expert system forums would include sophisticated search engines and relationship engines to help users find and filter useful material. The problem with these communication “enhancement” systems is that they are too often used to replace more capable systems rather than to enhance them. Remember that direct human interaction brings into play the most powerful processing and sensor suite on the face of the earth, the brain and the five human senses. Two people interacting face-to-face can accomplish far more knowledge transfer than any e-mail exchange could ever hope to accomplish. So IT does not facilitate knowledge transfer when it is used to replace face-to-face interaction. It only facilitates knowledge transfer when it supplements such interactions.

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Organizational Knowledge Management Maturation Frank is an ENTJ. He and his coworkers took the Myers Briggs Personality Type instrument and everyone was characterized as one of sixteen personality types. Those familiar with the Myers Briggs test will recognize Frank’s type as shorthand for someone who is an extrovert (E), who relies on intuition (N), who thinks (T) about a problem, and who makes judgments (J) about right and wrong answers. However, this is a very common but grossly simplified interpretation of what the instrument indicates. Each of these letters is the label for one end of a scale. To be more accurate, the instrument results suggested that Frank is more extroverted (E) than introverted (I), more prone to act on his intuition (N) than on what his five senses (S) tell him, more prone to make decisions on the basis of thinking (T) about logic and fairness than on the basis of feelings (F) people may have about the matter, and seen by others as someone who prefers to use judgment (J) to plan and order his life rather than perception (P) to adapt to life as it unfolds. But this too is an oversimplification. It turns out that Frank is quite an extrovert, scoring at the far E end of the E/I scale. He truly loves interacting with others and becomes energized by social interaction. He is most unhappy when alone with his own thoughts. It also turns out that Frank is extremely driven to understand what may be the logically or technically correct decision. He seeks to understand how people feel about a topic so that he can understand the reasoning behind their feeling. In the end, he believes there is usually a single logically best answer to most questions and so he has little regard for the most popular answer. Regarding the other two scales, Frank is almost exactly in the middle with no discernable bias toward sensing versus intuition or judging versus perceiving. He is just as apt to lean toward one as the other. Now we know quite a bit more about Frank than we assumed we knew when we read that he is an ENTJ. But of course, Frank’s personality is much more complex than even the most sophisticated analysis of the Myers Briggs assessment could describe. It is more complex than the results of a battery of personality tests and psychoanalyses could describe. Frank has had a unique life with a set of life experiences and genetic biases unlike anyone else. His is no doubt a unique personality rather than merely one of sixteen specific personality types. Even so, some people find the Myers Briggs shorthand is helpful in getting people to better understand themselves and one another. Its oversimplification and misuse does not negate its potential usefulness

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as a way to facilitate understanding and appreciation for differences in personality. Such understanding and appreciation lays a foundation for healthier, more rewarding, and more productive interactions between individuals. This little example highlights an important point about all constructs and models. They are all by their very nature wrong. They may or may not be useful, but they are always wrong. First, they are all dramatic oversimplifications of very complex relationships. In building the model we are forced to disregard some interrelationships and complexities. Second, we emphasize, perhaps dramatically overemphasize, by their inclusion, other relationships and complexities, giving them false importance. Third, these simplifications and exaggerations encourage us to make false assumptions about how the real world as represented by the construct or model operates. Just as every person is unique, so to is every organization unique. It has its own history filled with experiences, successes, and failures. It has a leadership team, each member of which brings his/her own history of experiences, successes, and failures. These pasts have instilled a unique set of biases about how the world works and what matters. The organization may be part of some larger corporate structure that imposes its unique biases. It operates in an ever-changing competitive environment with its own unique set of competencies. In short, each organization traveled a unique path to reach a unique relative position in its environment. It seems reasonable then to accept that each organization has its own unique approach to managing its knowledge. Even so, it is useful to keep in mind a model for organizational learning evolution. Such a model provides a vernacular and a context for understanding relative organizational maturity and for thinking about the path ahead. So let us being our description of an overly simplistic, no doubt wrong in some important ways, yet hopefully useful model of how organizations may advance their knowledge management capability. Organizations typically evolve through four stages on their way to mature and effective learning competency. Stage I, “Organizations Forming” Stage I organizations may be completely unaware of what they know. This is especially so for young organizations that have not yet established a Culture and have not yet come to recognize their Old Pros. Even so organizations cannot avoid developing a Culture, Old Pros

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will inevitably emerge from the group, and outside influences will impose some rigor, resulting in a modest level of Process perspective. Organizations that manage to resist these forces will soon cease to exist. Such an organization may be an entirely new one recently created to operate a franchise business in a new location or it may be a group drawn from existing business units to form a new business unit. The leader and the employees may all be strangers to one another. They may have come from different walks of life. Some of them may know nothing about the new organization or their role in it. Over time their biases and experiences will blend and adapt with one another and with the demands imposed by the franchise or corporation policies to evolve into a unique organizational Culture. But the immature Culture contains little knowledge. It also has less capacity to influence how knowledge is managed across the organization. An immature organization may also have not yet come to appreciate the knowledge that its employees have brought from their personal experiences. The members of the organization may not yet know which bits of knowledge are most important or who among them possesses that important knowledge. Over time, the individuals with the most relevant experience will emerge and be appreciated. Then the Old Pros will be acknowledged. Stage I organizations are also influenced by Process knowledge, but only to the extent work routine and procedure is mandated by outside forces. A parent corporation may impose specific requirements for how work is accomplished. They may also audit to assure compliance. Individual businesses have to file taxes, comply with food handling regulations, comply with Occupational Safety and Health Administration regulations, comply with hazardous materials regulations, comply with environmental requirements, or a host of other outside mandates that are imposed as soon as the organization comes into existence. These mandates immediately force some level of Process discipline on the organization. As a result, the only organizational workflow or procedure knowledge is that imposed upon it by regulation. Stage I organizations have immature but developing Cultures that may contain little knowledge and have little impact on other aspects of organizational knowledge management, they may not have yet recognized their Old Pros, and they have very little Process knowledge. Thankfully, organizations do not reside long in Stage I. They either perish or move on to Stage II.

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Stage II, “The Way It Is Around Here” Stage II organizations have survived beyond birth; they have a Culture, they know who their Old Pros are, and they have some established work routines and procedures giving them some level of Process discipline. But all three are somewhat mysterious. Senior leadership disregards or haphazardly pokes at the Culture. The Culture may be recognized, may even be understood well enough to describe its attributes, but there is no sense of Culture as a repository of organizational knowledge. There is certainly no sense of Culture as a disseminator of that knowledge. Nor is there a sense of Culture influencing how the organization deals with other knowledge. The Old Pros’ knowledge is applied, but only in an ad hoc, almost haphazard, way. Peers may call on them for help. The Old Pros may serendipitously come across challenges that call for their experience or insight. But too often, useful knowledge will not be made available to address serious problems. Procedures and work routines are often viewed as unnecessary bureaucracy to be worked around rather than managed and improved. Managers are rarely responsible for work routines or procedures in their departments. Few cross-departmental work routines or procedures are fully documented or controlled. The Process perspective is weak throughout the organization. Anecdotal evidence suggests that most organizations are in Stage II, a somewhat steady-state condition to which new organizations quickly move, from which many organizations never leave, and to which far too many organizations revert. These organizations do not generally appreciate what knowledge they have and so they do not actively manage that knowledge. Stage III, “If Only We Could . . .” Stage III organizations are typically born out of frustration—frustration that they have suffered financially from a recurring inability to apply lessons learned or frustration that an attempt to deploy an Archive system failed miserably. Occasionally, organizations relapse into Stage III because a new senior leadership team dismantles, through ignorance or neglect, an existing Stage IV or Stage V knowledge management capability. Stage III organizations typically don’t yet fully appreciate the influence of Culture and Old Pros. They may recognize the influence of Culture or Old Pros but have not come to terms with the need to

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shape them as knowledge management mechanisms. Their frustration drives them to deploy Archives as the all-encompassing standalone tool for managing what the organization knows. The organizations are often dissatisfied with the outcomes. Occasionally the Archive systems are abandoned before they can be deployed. Sometimes they are deployed but not maintained and thus fall into disuse. Sometimes they are fully deployed and supported but found to be expensive to maintain, difficult to search, and generally not worth the effort and cost. The result is nearly always the same, abandon the Archive and relapse to Stage II. Stage IV, “We Are Making Progress” Stage IV might be called the full awareness stage. The senior leadership recognizes both the importance and the difficulty of building learning competency. The organization has moved beyond seeking a quick fix, instead committing itself to building an integrated learning approach. Organizations in this stage recognize the influence of Culture. They talk openly about the strengths and limitations of their social artifacts, values, and assumptions. They acknowledge the learning they reflect. They also acknowledge the effects on dimensions of organizational knowledge management. Stage IV organizations recognize the value of their Old Pros. They are taking specific action to appreciate them and to encourage distribution of what they know. They have experimented unsuccessfully, perhaps more than once, with Archives and appreciate their strengths and limitations. They are often making firm decisions about the cost/benefit of Archives. Additionally, the Stage IV organizations are developing an appreciation for Processes and are developing training, disciplines, and governance to manage them more effectively. Stage V, “We Know What We Know and Use It” Stage V organizations have demonstrated recurring, if not consistent, success at managing the knowledge within their Culture, Old Pros, and Archives. They have also developed a mature understanding of their organizational Processes and are actively managing the knowledge within them. Stage V organizations have institutionalized the perspectives, competencies, and governance to understand, appreciate, monitor, control, and influence the lessons learned that are

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stored within their Culture, Old Pros, Archives, and Processes. These organizations may not have full control and performance consistency, but they have demonstrated a commitment to manage their learning competence. Knowledge Management Metrics Recall the earlier study findings suggesting that organizations not allow themselves to get overly engaged in metrics. Groups will too often become mired in debates about metrics rather than making real progress toward substantive improvement. It is also often the case that much of what is important cannot be readily measured, or even measured at all. Organizations too often settle for a poor substitute metric that subsequently leads them to take nonproductive actions. Indeed, the desire to have metrics may steer organizations toward Archive- and Process-based efforts because, unlike Culture- and Old Pros-based efforts, they are more easily measured. Leaders must remember that measurability has no relationship to importance. Knowledge management metrics may fall into three general categories: deployment, utilization, and results. Deployment and utilization metrics are common, although too often poorly developed or used, while results metrics are rare or falsely labeled. Deployment metrics track progress toward putting in place the changes, systems, and training intended to make knowledge management easier, more prevalent, and more productive. They are typical project deployment metrics used to monitor such dimensions as cost, schedule, staffing, and system performance testing. Even though deployment metrics have virtually nothing to do with organizational knowledge management competence, senior management often reviews them as if they were because they are at least an indicator that something is happening. Utilization metrics track knowledge transaction activity, assuming that greater activity will lead to more use of the organizations knowledge base. The metrics may track the number of times information is entered into the system, the overall increase in volume of information available, the number of queries made seeking information, the percentage of the population entering or seeking information, the frequency of inquiries, and segments of the population that do or do not enter information or make inquiries. Such transaction monitoring can be useful when an organization is deploying new Archives. They may also be used to encourage organizational dialogue about knowledge management and thus begin to change the Culture. Similar

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metrics have also been used occasionally to track how often Old Pros are being called upon by the organization. Utilization metrics have a role in facilitating change and in monitoring ongoing activity. Results metrics track how effectively the organization makes use of what it knows and how competent it is at managing its knowledge. Deployment and utilization metrics can usually be defined and data collected, but results metrics are much more challenging. Some would argue they are impossible. Utilization metrics are often used as a surrogate for results metrics because it is so difficult to define a knowledge management results metric that is measurable. The most productive attempts at results metrics have been based on anonymous survey data. Organizations may periodically ask employees a series of questions about how well knowledge is shared, whether improvements are noticeable, what barriers exist, and so on. The data may be sifted to gather perspectives from individual departments or from managers versus individual contributors, providing further insight to perceived obstacles and improvements. Such survey data can also be used in conjunction with benchmark data to better understand how the organization compares to others. Such metrics are crude and may be influenced by other factors. Even so, they can over time (perhaps two to three years) evolve into useful figures of merit of the organization’s knowledge management competence. A less productive approach to results metrics attempts to tie knowledge management activity to broader organizational performance. For example, one organization required that every documented application of a lesson learned from the past include an analysis of how much money was saved, or how much cost was avoided, or how much new revenue was gained. They also required every new knowledge management improvement proposal to include an analysis of the estimated project cost, likely financial benefit, and probability of success. The idea was to enable senior leaders to make effective cost benefit decisions. Their efforts had two outcomes. First, the analyses were nearly always subjective, because the financial outcomes were subject to so many different influences and certainly not solely due to the use of some particular bit of organizational knowledge or the application of some particular technique. Second, the mandate to provide this sort of analysis actually discouraged employees from admitting they used a lesson learned from the past. It even discouraged some employees from accessing the information. The organization needs to deploy a set of metrics, a review schedule, and accountabilities to initially and then periodically assess how well the organization manages what it knows. Metrics should address

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utilization (number of queries per month, number of people making queries per month, number of queries per person per month, number of new users per month, etc.) and availability (system uptime percentage). They should also address user satisfaction via periodic surveys. Surveys asking about ease of system use, availability of information sought, value of information sought, and the like, should be collected and reviewed quarterly. Managers should be surveyed periodically to assess their perceptions of the value of the Archive, because a disenchanted supervisor or manager can discourage dozens of employees from using the system. Finally, data should be reviewed periodically to assess the cost of the Archive versus its relative value to the organization. The real value is in the discussion that occurs, not in the metrics themselves. This activity fosters a healthy knowledge management environment, provides a venue for raising concerns about obstacles, and prompts action to overcome them. Knowledge Sharing Outside the Organization Knowledge networks extend beyond the boundaries of an organization to its customers, suppliers, industry councils, regulators, and many other associates. Some have argued that such networks of organizations may be more critical, yet less understood, than the networks within the organization (Powell, Koput, and Smith-Doerr, 1996; Dyer and Singh, 1998). Organizations learn through collaboration with other organizations, primarily by working with customers and suppliers. Some studies have found that a firm’s customers and suppliers were its primary sources of new knowledge (von Hippel, 1988 and Powell, Koput, and Smith-Doerr, 1996). Learning and knowledge transfer occurs in these interorganizational networks via the same mechanisms as within an organization. The Culture of the industry, the industry leading experts or Old Pros, the industry-wide databases or Archives, and the industry standards or Processes determined by regulators and accepted practice all have an impact on what knowledge can or cannot move between organizations and how freely or rapidly that knowledge can move. However, there are additional serious and daunting complications to be considered with respect to interorganizational knowledge management. First, leaders must be concerned about giving away or gaining competitive advantage. Leadership must seek to minimize intraorganizational rivalries that would impede effective knowledge transfer, but must accept that such rivalries will be present and will heavily influence interorganizational knowledge transfer. The challenge is to

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learn as much as possible, yet keep hidden that knowledge critical to current and future competitive advantage. Second, leaders must understand the extent of their dependency on interorganizational knowledge. For example, the commercial aerospace industry players are deeply dependent on one another. Many airlines subcontract the aircraft repair, aircraft operations, or both. The same subcontractor may be supporting competitor airlines. They lease airport facilities. Some of them even share ticketing systems with competitors. Organizations operating in this industry are extremely dependent on one another and thus must be able to share knowledge relatively freely. An organization with poor interorganizational sharing behaviors will struggle more than will its peers. On the other hand, organizations in the pharmaceutical industry are much more dependent on their own internal research and development than on industry-wide knowledge. Some interorganizational sharing will occur, but a great deal of vital knowledge must be protected if the organization is to succeed. Third, no matter how protective and isolationist an organization may be, knowledge travels as people move from organization to organization. When an employee goes to work for competitors he takes with him knowledge and insights that cannot be completely protected. Perhaps one can impose restrictions on the sharing of specific proprietary knowledge, but remember that 80 percent of an organization’s knowledge is tacit, meaning it cannot even be documented, much less blockaded. Any such knowledge residing in the ex-employee’s head will be available to the competitor. Organizational leadership should understand the industry and their own organizations’ level of dependency on industry knowledge sharing. Leadership should understand the benefits and risks of interindustry sharing. They should develop a knowledge management approach that will almost certainly be more restrictive than the intraorganizational system and assure the entire organization understands the differences and the reasons for them. Finally, they should understand that every organization is operating within their own set of beliefs and practices with respect to knowledge transfer, some will be more or less ethical than others. Knowledge Exploitation and Exploration Knowledge management involves both exploitation of what is already known and exploration to extend current knowledge or acquire new knowledge. The two compete with one another for resources and one can inhibit the other. Research done by Marsh (1991) found that in

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the short term an organization benefits from focusing on exploitation of what it already knows but in the long term it suffers from a lack of new ideas or distinctive competences that differentiate it from competitors. Leaders who overemphasize exploitation will reap shortterm gains but will cause harm over the long term. The recent enthusiasm for Six Sigma has led several organizations down this path. Leaders have seized on the tools, techniques, and principles as a way to get existing processes under control and have found success. However, the focus was too often exclusively on Six Sigma, leaving no time, energy, or resources to focus on the exploration for new knowledge or innovations from which to build competitive advantage. Many organizations found themselves in a competitive race to become more efficient and thus to become more and more alike. Sustained success comes from a balance between exploitation and exploration, a balance that encourages the organization to make good use of what it already knows while also eagerly seeking new knowledge. Thus organization knowledge management must be balanced with organization innovation management. There is No Substitute for Leadership Engagement A project team was about to start development of a unique mechanical system for use on a NASA science satellite. The team worked together for nearly a year on the proposal and had been under contract for about a month. The team was asked to participate in a twoday risk and opportunity workshop to help them better understand the challenges ahead. The Director of Engineering and the Director of Programs, two members of the senior leadership team at that location, conducted the workshop. Early on the first day of the workshop, the team members to participate in a nominal group technique exercise intended to bring out the major project challenges. Project team members were asked to separately write out their list of the top ten overall project challenges. After they finished, each member in turn stated the top three challenges on their list. The first person, a procurement manager, identified three challenges. The second person, a systems engineer, identified three different challenges. The third person, a mechanical engineering team leader, identified three challenges none of which had been previously named. The fourth person, the project manager, identified three challenges none of which had been previously named. It became obvious that this group of people were not yet a cohesive team in spite of having worked together for

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nearly a year. They each had a unique understanding of the task at hand and how to go about accomplishing it. They were collectively destined to fail because each person would be fighting to accomplish his or her own vision thereby thwarting others’ efforts. Over the next two days the team members came to understand that others had different worldviews and project-views. They talked through those different views and in the process discovered that several of them had real merit. Some team members came to understand that some of their concerns were less critical than they had believed. Some team members came to appreciate that they could help address major concerns that they did not previously know existed. By the end of the two days the team had an integrated view of the challenges ahead and how to approach them. Another more important action emerged from the two-day session. A senior engineering manager was asked to oversee the team activities for the next six months. He had two tasks. First, he was asked to better understand why after a year the team had not come together with a shared perspective. Second, he was asked to monitor the team interactions to assure the team would continue to become more integrated. It soon became clear that the project manager did not understand his role as a team facilitator and integrator. He understood the customer, their needs, and the relevant technologies but he did not understand the softer side of his role. It also emerged that the team included two or three “prickly” personalities who encouraged divisiveness. In short the team was encountering barriers to reconciling their different perspectives and thus barriers to sharing knowledge. Fortunately, those barriers were identified early and resolved. The project was successful. Success was unlikely because the individuals on the project had not developed a way to share knowledge productively. Three factors enabled the organization to identify the potential project failure and make the necessary changes. First, the risk and opportunity workshop provided a social mechanism for surfacing new project issues. Every new project team participated in such a workshop and so every team could be critiqued. Second, senior leadership actively engaged in the workshops thus interacting with each new project team for two full days. They had ample opportunity to understand what the project needed in order to succeed. Third, the leadership team was persistent. They assigned the senior manager to monitor progress toward correcting the problems that had been identified. They personally conducted follow-up reviews with the project teams.

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Over a period of five years the risk and opportunity reviews became an integral part of the way the organization did business. The reviews provided an institutional venue for sharing past lessons learned and applying them to current challenges, for identifying where the Old Pros could best be put to use, and for building a social environment where knowledge sharing was appreciated. References Boland, R.J.J., and R.V. Tenkasi. (1995). Perspective making and perspective taking in communities of knowing. Organization Science 6(4): 350–372. The authors offer an approach to facilitating knowledge work (new product and service development) by the design of electronic communication systems to support the work activity. Their emphasis is on the fostering of communication and collaboration rather than on the capture, storage, and retrieval of knowledge. Brown, J.S., and P. Duguid. (1998). Organizing knowledge. California Management Review 3: 90–111. The authors speak eloquently about the impact of organizational structure on knowledge building and knowledge use. They advocate social tools such as translators and knowledge brokers to bridge the gaps. They advocate information technology tools as a supplement only. Davenport, T.H., and L. Prusak, L. (1998). Working knowledge: how organizations manage what they know. Boston, Harvard Business School Press. The authors emphasize the need to use work processes to manage the organization’s knowledge. Dyer, J.H., and H. Singh. (1998). The relational view: cooperative strategy and sources of inter-organizational competitive advantage. Academy of Management Review 23(4): 660–679. The authors describe how organizations can cooperate effectively to both gain new knowledge and protect their own proprietary knowledge. Fahey, L., and L. Prusak. (1998). The eleven deadliest sins of knowledge management. California Management Review 3: 265–276. The summary of “sins” is derived from their years of study of overall organizational knowledge management competence across industries. Hellstrom, T., U. Malmqvist et al. (2001). Knowledge brokerage in a software engineering firm—towards a practical model for managing knowledge work in social networks. A report from the Institute for management of innovation and technology. Chalmers Institute of Technology, Gothenburg, Sweden, IMIT WP:2001_118. Antal sidor: 24. The paper outlines the case for decentralized management of knowledge work. The authors argue that top-down perspectives on knowledge have dominated management initiatives but have failed to provide the

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benefits of a decentralized system founded in organizational cultural norms and work routines. Marsh, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science 2(1): 16. The paper argues that organizations that focus on exploitation of what they know to the exclusion of the exploration of what they might learn may reap benefits in the short term but will likely suffer competitively in the long term. O’Dell, C., and C.J. Grayson. (1998). If only we knew what we know: identification and transfer of best practices. California Management Review 40(3) (Spring): 154–173. This paper summarized the findings of several studies about knowledge management success and failure across an array of organizations. Powell, W.W., K.W. Koput, and L. Smith-Doerr. (1996). Interorganizational collaboration and the locus of innovation: networks of learning in biotechnology. Administrative Science Quarterly 41: 116–145. The paper describes how knowledge-sharing networks enable knowledge sharing in the biotechnology industry. von Hippel, E. (1988). The sources of innovation. New York, Oxford University Press. The author describes how innovation is facilitated and enhanced. von Krough, G., K. Ichigo et al. (2000). Enabling knowledge creation: how to unlock the mystery of tacit knowledge and release the power of innovation. New York, Oxford University Press. The authors suggest the problem of knowledge sharing stems from distributed and diverse interests of organizational members rather than a problem with tools and infrastructure.

Closing

Organizations Too Often Do Not Effectively Manage What They Know The individuals operating within organizations often know how to do their jobs better than they actually do them. Much like the crusty old farmer they already know how to farm a lot better than they actually do. Organizations operate in much the same way. First, because they are made up of individuals and second, because they are infused with group social norms, work routines, and standards of behavior that collectively inhibit the organization from making best use of what it collectively knows. Some argue that the problem lies in “not knowing” rather than “not applying” what is known, a distribution and sharing problem rather than an appreciation and utilization problem. The former contend individuals, and the organization as a whole, would do better if only they knew more about what has already been learned. The later contend individual and collective social norms inhibit the use of what is known. The former look to better distribution and awareness as a solution while the later look to discipline and control as a solution. Organization Success Demands Organizational Knowledge Management Competence Three major trends make organizational management competence ever more important. The increasingly global competitive environment is forcing organizations to deal with competitors around the globe. Organizations must compete against or make use of the best of what is known no matter where on the earth it may have originated and no matter where on the earth it may currently reside. Those that fail to do so will pay a dear price in the competitive arena. Technology

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acceleration is shortening the time value of old knowledge and rapidly introducing waves of new knowledge requirements. Organizations that cling to obsolete knowledge or fail to appropriately embrace new knowledge will suffer competitively. Workers are increasingly more mobile. That mobility creates a conduit for transfer of knowledge into and out of the organization. Organizations that fail to manage the transfer will pay a dear price. Today, more than ever, leaders must understand what their organization knows and how they make use of that knowledge. Moreover, they must steer the organization toward greater knowledge acquisition competence and toward greater knowledge utilization competence. Organizations Manage Knowledge via Culture, Old Pros, Archives, and Process Each has a role to play. Culture contains the instinctive, self-preservation knowledge that the organization has acquired through recurring experiences. This knowledge and the way it is disseminated is similar to an individual’s fight-or-flight response. The learned behavior is deeply embedded and is triggered as an instinctive reaction to a stimulus. Because Culture contains a learned response rather than the actual knowledge and its context, this sort of knowledge is not readily adapted or modified to fit a changed environment. Old Pros retain knowledge gained from personal experiences that occurred inside or outside the organization. This knowledge is subject to a host of individual and interpersonal factors. It can easily become distorted, be misunderstood, or be misused. Nonetheless, Old Pros can be an invaluable repository and disseminator of organizational knowledge. Archives are a useful tool for storing explicit knowledge but are generally useless or harmful with respect to tacit knowledge. Archives have a useful place in an overall organizational knowledge management schema but they are too often inappropriately applied or are misused. Process retains and disseminates both tacit and explicit knowledge. It embeds the knowledge directly into the work activities and procedures, making it virtually unavoidable. However, Process demands a great deal of discipline, resource, and commitment from the organization and its leaders. These four dimensions of organizational knowledge management involve not just memory but wisdom as well. Each is a repository for some of what the organization knows, and collectively they constitute the bulk of an organization’s memory. But each fosters or impedes the distribution, integration, and processing of that knowledge, enabling the organization to be wise or foolish. The organization must build

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and maintain a knowledge management system that fosters both good memory and wisdom. Organizations Must Embrace a Holistic Approach The four work interactively to encourage or impede overall organizational knowledge management competence. Organizational knowledge management is built on a foundation of Culture. It is a receptacle and disseminator of organizational knowledge, to be sure. But it is much more than that. The artifacts, values, and basic assumptions determine how effective Old Pros can be and whether or not Archives and Process will even be implemented. In turn, an organization that sets about making effective use of its Old Pros, Archives, and Processes will be shaping and strengthening its Culture. Organizations must acknowledge, discuss, and adapt their social norms and standards of behavior, and they must be willing to change as their environment changes. More importantly, those social norms must include an appreciation for knowledge over power, encourage the search for understanding, appreciate the value of process management, and encourage free and open communication in order for Old Pros, Archives, and Process to work. Old Pros must be appreciated and embraced for what they know and what they can share. They must be integrated with the Archive and Process activities to assure the appropriate knowledge is retained and disseminated in the most efficient and useful manner. Archives must be used as a supplemental tool, integrating their explicit knowledge capability with the tacit capability of the other three. Process must be deployed in a manner that fits the prevailing and desired Culture, lest it be rejected or marginalized. There is No Substitute for Leader Engagement Leaders influence the Culture. Their priorities and actions determine the organizational priorities and actions. Their own appreciation for organizational knowledge competence, not just individual competence, will determine whether or not the organization can achieve or sustain knowledge management competence. Leaders can accelerate changes in social norms and behaviors, changes that may help or hinder organizational competence. Leaders establish the priorities. The people in the organization pay attention to what the leadership pays attention to. Leaders who seek knowledge rather than power will encourage others to do the same. Leaders who understand and emphasize Process discipline will

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encourage others to do so. Followers pay attention to where leaders allocate talent, time, equipment, and money. Those are the areas that get attended to. Leaders must provide the persistent and consistent focus that enables the organization to persevere, because organizational knowledge management competence is not quickly achieved nor easily maintained. There are many distractions. There are many difficulties. The organization will waiver if it senses a lack of leadership commitment.

Index

9/11, impact on airline industry, 58, 65 Acquire, Organize, and Distribute (AOD) framework, 37, 39 Adler, T.R., 84, 96 aerospace industry, 71–72 After Action Review (AAR), 93 Air Force Missile Command (AFMC), 84 Airbus, 59 Allen, T.J., 69, 76 Amazon.com, 7–8, 9 American Productivity and Quality Center, see APQC Anatomy of a Win (Berveridge), 11 application specific integrated circuits (ASICs), 128 APQC (American Productivity and Quality Center), 21, 24, 108, 137, 165–174 archives, 97–121 context and, 114–116 culture and, 152–153 Davenport and Prusak on, 108 De Geus on, 115–116 developing system of, 102–107 documenting knowledge, 112–114 explained, 97–102 explicit knowledge and, 106 hypersensitivity to current events, 117–118 individuals and, 111

information repository and, 104 installation and integration, 103 knowledge retrieval and, 118–120 leadership and, 120–121 metrics and, 104–105 old pros and, 157–158 personal objectives and, 111 poor track records, 107–109 problems with, 109–120 process and, 159 retrieval and, 106–107 revisionist history and, 116–117 system requirements, 102–103 tacit knowledge and, 106 Watzlawick on, 114–115 what to archive, 109–112 see also retrieval of knowledge Argyris, C., 35, 49 Ariely, Dan, 34, 49 ARPAnet, 7 artifacts, 54–57, 150, 184 Baldwin, Stanley, 42 Ball Corporation, 131–132 Barnes & Noble, 8 Bavelas, J.B., 111, 123 Beers, M.C., 69, 77 Belobaba, Peter P., 65, 77 Berveridge, Jim, 11 Bezos, Jeff, 8 Boeing, 59, 61, 68, 130, 152, 154 Boland, R.J.J., 178–179, 191 Bolt, Beranek, and Newman (BBN), 7

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Bonaparte, Napoleon, 117 Booz Allen Hamilton (BAH), 60 Borders/Waldenbooks, 8 brain, structure of, 28–29 Brasethvik, T., 37, 50 Brown, J.S., 13, 21, 24, 69, 77, 93, 96, 133, 178 business processes, 133 Carrillo, P., 107, 122 Carstensen, Peter H., 120–121, 122 Caterpillar, 62, 76 Challenger Launch Decision, The (Vaughn), 74 Chew, S., 113, 122 Churchill, Winston, 21, 42 CompuServe, 7 consensus, 40, 56, 75, 105, 112 Crossan, Mary M., 145, 163 culture, 51–76 airline industry and, 59–60 Allen on, 69 archives and, 152–153 artifacts and, 54–56 assumptions and, 54–55, 56–57, 150, 184 attributes, 70–75 company history and, 63–64 customers and, 62 Davenport on, 69 depth, 54 explained, 51–57 Hofstede on, 57–59 individuals and, 64 knowledge and, 69–70 leadership and, 65–68, 75–76 national cultural dimensions, 57–59 old pros and, 150–152 ownership and, 68–69 process and, 153–157 role, 70 Schein on, 54, 56–57 shaping of, 53–54, 57–69 stories and myths, 55–56 task, 70

traumas and, 64–65 values and, 54–57, 150, 184, 195 Vaughan on, 74 viscosity of, 73 customers APQC study and, 167–169 archives and, 98–99, 101, 109, 110 culture and, 55–56, 58–65, 67–68, 71–73, 76 knowledge sharing and, 187 old pros and, 85, 92–93, 157, 162 organizational knowledge and, 40–41, 43 organizational structure and, 176–177 process and, 129–130, 138–139, 142 SPC and, 155–156 technology and, 2, 3, 16 da Vinci, Leonardo, 7 data, defined, 17 Davenport, Thomas, 13, 17, 24, 48–49, 69, 77, 93, 108, 133, 173 De Geus, Arie, 115, 115–116, 122 declarative memory, 30–31 Defense Advanced Research Projects Agency (DARPA), 7 Define, Measure, Analyze, Improve, and Control (DMAIC) methodology, 138–139 DeLong, D.W., 24, 77 Department of Defense, 71 Divitini, M., 37, 50 DMAIC, see Define, Measure, Analyze, Improve, and Control (DMAIC) methodology dot-coms, 71 Duguid, P., 21, 24, 69, 77, 93–94, 96, 133, 142, 178, 191 Dyer, J.S., 187, 191 eBay, 7, 9 egocentric bias, 33, 39

INDEX

Eleven Deadliest Sins of Knowledge Management, 170–173 downplaying thinking and reasoning, 172 failing to recognize importance of experimentation, 172–173 focusing on knowledge stock to detriment of knowledge flow, 171 focusing on past and present, 172 not developing working definition of knowledge, 170–171 not understanding need for creating shared context, 171–172 paying little heed to tacit knowledge, 172 seeking to develop direct measures of knowledge, 173 separating knowledge from users, 172 substituting technological contact for human interface, 173 viewing knowledge as external, 171 explicit knowledge, 20–21 FAA Aerospace Forecast, 7, 24–25 facts, defined, 19 Fahey, L., 170, 172, 191 Federal Manufacturing & Technologies (FM&T), 88–89, 94, 114, 145–148 see also Honeywell fight-or-flight responses, 29, 44–45, 54, 194 flight, human, 7 General Electric, 33, 138 geography, 40–42, 59, 176–177 Global Positioning System (GPS), 97 Goddard Space Flight Center, 107 Google, 9 Grayson, C.J., 1, 25 groupthink, 35, 40, 67

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Halpern, Diane, 32–33, 49, 116, 122 Handy, C., 69–70, 77 Hellstrom, T., 174, 191 Hewlett-Packard, 1, 171 Hofstede, Geert, 57–59, 77–78 Honeywell, 63, 68, 88, 93, 114, 131–132, 145–148 see also Federal Manufacturing & Technologies (FM&T) How the Mind Works (Pinker), 28 hypersensitivity, 117–118 IBM, 58, 98 individual memory, 27–32 Individualism, 58 information, defined, 17–18, 19–20 information technology (IT) AOD and, 37–38 APQC study and, 163, 169 archives and, 45, 104, 108–109 Davenport on, 13, 24, 173 OD approach and, 36–37 role of, 178–179 Schwartz on, 50 storage and, 16 tacit knowledge and, 21 integration, 145–163 archives and process, 159 changing impact, 161–163 culture and archives, 152–153 culture and old pros, 150–152 culture and process, 153–157 example of, 145–148 impact vs. value, 159–161 interaction and, 148–150 old pros and archives, 157–158 old pros and process, 158–159 Internet, 7–8, 9–10, 41, 50, 58, 64, 71, 120–121 Iridium satellite constellation, 12, 71 Jelinek, M., 132–133, 143 Junkins, Jerry, 1–2, 4–5, 22, 25, 171

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Keillor, Garrison, 33 Kerr, Steven, 33, 50 knowledge defined, 17, 18 explicit, 20–21 flow of, 40–43, 169, 171–172, 175–178 tacit, 21 knowledge management, 15–17, 165–191 approaches to, 15–17 APQC study of, 165–174 benchmarks, 166–167 defined, 18–19 Eleven Deadliest Sins of, 170–173 improvement initiatives, 167–168 IT’s role, 178–179 knowledge exploitation and exploration, 188–189 leadership and, 170 leadership engagement, 189–191 measurement systems, 168–169 metrics, 185–187 organization structure and knowledge flow, 175–178 organizational knowledge management maturation, 180–185 rewarding efforts, 169 sharing knowledge outside organization, 187–188 success factors for individual projects, 173–174 tacit knowledge and, 174–175 technology and, 169–170 value of projects, 167 Komatsu, 62, 76 Koput, K.W., 187, 192 leadership archives and, 111, 120–121 culture and, 65–69, 72–73, 75–76, 160 knowledge management and, 18–19, 170, 189–191 “lessons learned,” and, 22

old pros and, 83–84, 85–86, 89, 90–95, 160, 162 organizational knowledge and, 15, 39–40, 148 organizational memory and, 35 process and, 111, 129, 130, 131–132, 140–142, 155 Prusak on, 26 self-perception and, 33 sharing and, 150 values and, 56 Leonard, D., 13, 17, 21, 25 “lessons learned,” defined, 21–22 Lessons Learned Information System (LLIS), 107 Lilienthal, Otto, 7 Lockheed Martin, 61, 68, 130, 152, 154 “long cycle” business models, 66 malleability culture and, 75 memory and, 31–32, 34, 39, 116 Marsh, J.G., 188, 192 Masculinity, 58–59 Massachusetts Institute of Technology (MIT), 10, 49 McDermott, R., 149, 163 memory, 27–49 declarative memory, 30–31 human brain and, 27–29 individual memory, 27–32, 31–32 individual thought and knowledge, 32–35 knowledge and, 29 knowledge stream and its obstacles, 40–44 managing knowledge, 45–49 motor memory, 29–30 organizational memory, 32, 35–39 organizational thought and knowledge, 39–40 procedural memory, 30 retention facilities, 36

INDEX

metrics, 104–105 Miner, A.S., 133, 143 Mintzberg, Henry, 12, 25 Moorman, C., 133, 143 motor memory, 29–30 NASA, 71–72, 74, 107, 114, 189 Nonaka, I., 120–121, 123 O’Dell, C., 1, 25, 149 old pros, 79–96 Adler and Zirger on, 84–85 archives and, 90, 157–158 attributes that influence knowledge management, 85–88 Brown and Duguid on, 93–94 culture and, 85–87, 150–152 explained, 79–84 how organizations deal with, 88–90 individuals vs., 95–96 knowledge sharing and, 93–94 leadership and, 90–95 peer reviews and, 93 process and, 89–90, 158–159 research on, 84–85 organization, defined, 22 organizational development (OD) path, 36–38 organizational knowledge management maturation, 180–185 “if only we could”, 183–184 “organizations forming”, 181–182 “the way it is around here”, 183 “we are making progress”, 184 “we know what we know and use it”, 184–185 organizational memory, 35–39 ownership, 68–69 peer reviews, 93 Pinelli, T.E., 5, 18, 25 Pinker, Steven, 28, 50 Platt, Lew, 1–2, 4–5, 22, 25, 171

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Polanyi, M., 21, 25 Powell, W.W., 187, 192 Power Distance, 58 Predictably Irrational (Ariely), 34–35 procedural memory, 30, 133 process, 125–142 archives and, 159 attributes that influence knowledge management, 134–137 Brown and Duguid on, 133 culture and, 153–157 customers and, 130 Davenport and Prusak on, 133 explained, 125–129 government agencies and, 130–131 industry fads and, 130 Jelinek on, 132 knowledge and, 132–134 leadership and, 140–142 Moorman and Miner on, 133 old pros and, 158–159 procedural memory, 133 shaping of, 129–132 Six Sigma and, 137–140 standardization of, 129–130 Walsh and Ungson on, 132–133 Prusak, L., 13, 17, 24, 25–26, 48–49, 93, 108, 133, 142, 170, 172–173, 191 Punnett, B.J., 59, 77 Quintas, P.R., 18 retention facilities, 36 retrieval of knowledge, 15–16, 18–19, 20–21, 37–38, 45–46, 101–102, 106–107, 109, 112, 118–120, 134, 137, 153, 175, 178 Reusable Experience with Case-Based Reasoning for Automating Lessons Learned (RECALL), 107

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revisionism, 116–117 role culture, 70 Sandelands, L.E., 35, 50 satellites, 12, 63, 68, 71–73, 82, 97, 118–119, 126, 131, 189 Scarborough, H., 6, 26 Schein, Edgar, 47, 49, 50, 54, 56–57, 78 Schön, D., 35, 49 Schwartz, D.G., 37–38, 50 Sensiper, S., 17, 21, 25 shareholders, 56 Sigma Six, 79–80, 98, 130, 136, 137–142, 154, 189 skill, defined, 20 Smith-Doerr, L., 187, 192 Snis, Ulrika, 120–121, 122 Sperry Corporation, 63 Stablein, R.E., 35, 50 statistical process control (SPC), 155–156 Structuring of Organizations, The (Mintzberg), 12 subcontractor and material procurement (S&MP) systems, 52–53, 86 success factors for individual projects, 173–174 Swan, J., 6, 26 tacit knowledge 80/20 rule and, 174–175, 188 archives and, 47, 106–109, 120–121, 152, 160, 162, 178–179, 194, 195 culture and, 47, 70, 152 defined, 21 Eleven Deadliest Sins of Knowledge Management and, 171–172

IT and, 178–179 old pros and, 47, 82, 85–86, 89–90, 92, 94–95, 160 process and, 47, 134–135, 194 task culture, 70 technology, 6–12, 64–65 disruptors, 64–65 global communications, 9–10 global competition, 10–11 knowledge life cycle, 11–12 product life cycles, 8–9 Tenkasi, R.V., 178–179, 191 Thought and Knowledge: An Introduction to Critical Thinking (Halpern), 32 traumas, 64–65 Twain, Mark, 5 Ungson, G.R., 36, 48, 49, 50, 132, 143 value statements, 56 Vaughan, Diane, 74, 78 VHISIC technology, 83 Vick, Stephen K., 113, 123 video, 41, 71, 90, 94, 101–102, 105, 114, 125, 134, 147, 162, 179 von Hippel, E., 187 von Krough, G., 175, 192 Walsh, J.P., 36, 48, 49, 50, 132, 143 Watzlawick, Paul, 111, 114–115, 123 Weick, Karl, 38–39, 50 Welch, Jack, 33, 50, 138, 140 Wikipedia, 9 Withane, S., 59, 77 Wright Brothers, 7 Zack, M.H., 6, 26 Zirger, B.J., 84, 96