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Knowledge Management
in Theory and Practice
Second Edition
Kimiz Dalkir
foreword by Jay Liebowitz
Knowledge Management in Theory and Practice
Knowledge Management in Theory and Practice
Second Edition
Kimiz Dalkir
foreword by Jay Liebowitz
The MIT Press
Cambridge, Massachusetts
London, England
© 2011 Massachusetts Institute of Technology
All rights reserved. No part of this book may be reproduced in any form by any electronic or
mechanical means (including photocopying, recording, or information storage and retrieval)
without permission in writing from the publisher.
For information about special quantity discounts, please e-mail special_sales@mitpress.mit.edu
This book was set in Stone Sans and Stone by Toppan Best-set Premedia Limited. Printed and
bound in the United States of America.
Library of Congress Cataloging-in-Publication Data
Dalkir, Kimiz.
Knowledge management in theory and practice / Kimiz Dalkir ; foreword by Jay Liebowitz.
— 2nd ed.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-262-01508-0 (hardcover : alk. paper)
1. Knowledge management. I. Title.
HD30.2.D354 2011
658.4’038—dc22
2010026273
10
9
8 7
6 5
4 3 2
1
Contents
Foreword: Can Knowledge Management Survive?
Jay Liebowitz
1
xiii
Introduction to Knowledge Management
Learning Objectives
Introduction
1
1
2
What Is Knowledge Management?
5
Multidisciplinary Nature of KM
8
The Two Major Types of Knowledge: Tacit and Explicit
Concept Analysis Technique 11
9
History of Knowledge Management 15
From Physical Assets to Knowledge Assets 19
Organizational Perspectives on Knowledge Management
Library and Information Science (LIS) Perspectives on KM
Why Is KM Important Today?
22
KM for Individuals, Communities, and Organizations
Key Points
26
Discussion Points
References
2
27
27
The Knowledge Management Cycle
Learning Objectives
Introduction
31
32
Major Approaches to the KM Cycle 33
The Meyer and Zack KM Cycle 33
The Bukowitz and Williams KM Cycle
38
The McElroy KM Cycle 42
The Wiig KM Cycle
45
An Integrated KM Cycle
51
Strategic Implications of the KM Cycle
54
31
25
21
22
vi
Contents
Practical Considerations for Managing Knowledge
Key Points
57
Discussion Points
References
3
57
58
Knowledge Management Models
Learning Objectives
Introduction
57
59
59
59
Major Theoretical KM Models
62
The Von Krogh and Roos Model of Organizational Epistemology 62
The Nonaka and Takeuchi Knowledge Spiral Model
64
The Choo Sense-Making KM Model 73
The Wiig Model for Building and Using Knowledge
76
The Boisot I-Space KM Model 82
Complex Adaptive System Models of KM 85
The European Foundation for Quality Management (EFQM) KM Model
The inukshuk KM Model
90
Strategic Implications of KM Models
92
Practical Implications of KM Models
92
Key Points
93
Discussion Points
References
4
93
95
Knowledge Capture and Codification
Learning Objectives
Introduction
89
97
97
98
Tacit Knowledge Capture
101
Tacit Knowledge Capture at the Individual and Group Levels
Tacit Knowledge Capture at the Organizational Level
118
102
Explicit Knowledge Codification 121
Cognitive Maps 121
Decision Trees
123
Knowledge Taxonomies 124
The Relationships among Knowledge Management, Competitive Intelligence, Business Intelligence,
and Strategic Intelligence
131
Strategic Implications of Knowledge Capture and Codification
133
Practical Implications of Knowledge Capture and Codification
134
Key Points
135
Discussion Points
References
136
135
Contents
5
vii
Knowledge Sharing and Communities of Practice
Learning Objectives
Introduction
141
141
142
The Social Nature of Knowledge
147
Sociograms and Social Network Analysis
Community Yellow Pages 152
149
Knowledge-Sharing Communities 154
Types of Communities 158
Roles and Responsibilities in CoPs
160
Knowledge Sharing in Virtual CoPs 163
Obstacles to Knowledge Sharing
The Undernet 169
168
Organizational Learning and Social Capital
170
Measuring the Value of Social Capital
171
Strategic Implications of Knowledge Sharing
173
Practical Implications of Knowledge Sharing
175
Key Points
175
Discussion Points
References
6
176
177
Knowledge Application
Learning Objectives
Introduction
183
183
184
Knowledge Application at the Individual Level 187
Characteristics of Individual Knowledge Workers
187
Bloom’s Taxonomy of Learning Objectives
191
Task Analysis and Modeling 200
Knowledge Application at the Group and Organizational Levels
Knowledge Reuse
211
Knowledge Repositories 213
E-Learning and Knowledge Management Application
214
Strategic Implications of Knowledge Application
216
Practical Implications of Knowledge Application
217
Key Points
218
Discussion Points
Note
219
References
219
218
207
viii
7
Contents
The Role of Organizational Culture
Learning Objectives
Introduction
223
223
224
Different Types of Cultures
227
Organizational Culture Analysis
229
Culture at the Foundation of KM 232
The Effects of Culture on Individuals 235
Organizational Maturity Models
KM Maturity Models
239
CoP Maturity Models
244
238
Transformation to a Knowledge-Sharing Culture
Impact of a Merger on Culture 256
Impact of Virtualization on Culture 258
246
Strategic Implications of Organizational Culture
258
Practical Implications of Organizational Culture
259
Key Points
262
Discussion Points
References
8
262
263
Knowledge Management Tools
Learning Objectives
Introduction
267
267
268
Knowledge Capture and Creation Tools 270
Content Creation Tools
270
Data Mining and Knowledge Discovery
271
Blogs
274
Mashups 275
Content Management Tools 276
Folksonomies and Social Tagging/Bookmarking
277
Personal Knowledge Management (PKM) 279
Knowledge Sharing and Dissemination Tools
280
Groupware and Collaboration Tools 281
Wikis 285
Social Networking, Web 2.0, and KM 2.0 288
Networking Technologies
292
Knowledge Acquisition and Application Tools
Intelligent Filtering Tools 298
Adaptive Technologies
302
297
Strategic Implications of KM Tools and Techniques
303
Practical Implications of KM Tools and Techniques
304
Contents
Key Points
ix
304
Discussion Points
References
9
305
306
Knowledge Management Strategy
Learning Objectives
Introduction
311
311
311
Developing a Knowledge Management Strategy
Knowledge Audit
318
Gap Analysis
322
The KM Strategy Road Map
325
316
Balancing Innovation and Organizational Structure
Types of Knowledge Assets Produced
Key Points
336
Discussion Points
References
10
337
338
The Value of Knowledge Management
Learning Objectives
Introduction
339
362
362
Additional Resources
11
359
360
Discussion Points
References
339
339
KM Return on Investment (ROI) and Metrics 343
The Benchmarking Method
345
The Balanced Scorecard Method
351
The House of Quality Method 354
The Results-Based Assessment Framework
356
Measuring the Success of Communities of Practice
Key Points
328
333
364
Organizational Learning and Organizational Memory
Learning Objectives
Introduction
365
365
365
How Do Organizations Learn and Remember?
368
Frameworks to Assess Organizational Learning and Organizational Memory
The Management of Organizational Memory
370
Organizational Learning
377
The Lessons Learned Process 378
Organizational Learning and Organizational Memory Models
379
369
x
Contents
A Three-Tiered Approach to Knowledge Continuity
Key Points
390
Discussion Points
References
12
391
392
The KM Team
Learning Objectives
Introduction
385
397
397
398
Major Categories of KM Roles
402
Senior Management Roles 403
KM Roles and Responsibilities within Organizations
410
The KM Profession 412
The Ethics of KM 413
Key Points
419
Discussion Points
Note
References
13
420
421
421
Future Challenges for KM
Learning Objectives
Introduction
423
423
424
Political Issues Regarding Internet Search Engines
425
The Politics of Organizational Context and Culture
427
Shift to Knowledge-Based Assets
429
Intellectual Property Issues 433
How to Provide Incentives for Knowledge Sharing
Future Challenges for KM
KM Research
A Postmodern KM
446
Concluding Thought
Key Points
14
447
448
Discussion Points
References
449
450
KM Resources
453
The Classics 453
KM for Specific Disciplines
International KM
455
KM Journals
440
442
455
Key Conferences
456
454
435
Contents
xi
Key Web Sites
457
KM Glossaries
457
KM Case Studies and Examples
KM Case Studies 458
KM Examples
459
KM Wikis
459
KM Blogs
459
Visual Resources 460
YouTube
460
Other Visual Resources
460
Some Useful Tools 460
Other Visual Mapping Tools
Note
460
Glossary
461
Index 477
458
460
Foreword: Can Knowledge Management Survive?
The title of this foreword, “Can Knowledge Management Survive?” is perhaps rather
strange for this second edition of this leading textbook on knowledge management
(KM). However, as the KM field has taught us to be “reflective practitioners,” this
question is worth pondering.
Knowledge management has been around for twenty years or more, in terms of its
growth as a discipline. Even though the roots of knowledge management go back far
beyond that, is knowledge management generally accepted within organizations, and
is KM a lasting field or discipline?
To answer the first question, we can review some anecdotal evidence that suggests
KM is more widely accepted within certain industries than others. Over the years,
the pharmaceutical, energy, aerospace, manufacturing, and legal industries have
perhaps been some of the leaders in KM organizational adoption. In looking toward
the future, the public health and health care fields are certainly well positioned to
leverage knowledge throughout the world. And as the graying workforce ensues and
the baby boomers retire, knowledge retention will continue to play a key role in
many sectors, such as in government, nuclear energy, education, and others. So, KM
has permeated many organizations and has the propensity to propagate to others.
However, there are still many organizations that equate KM to be IT (information
technology), and do not fully grasp the concept of building and nurturing a knowledge sharing culture for promoting innovation. Many organizations do not have KM
seamlessly woven within their fabric, and many organizations do not recognize or
reward their employees for knowledge sharing activities. It is getting harder to find
the title of a “chief knowledge officer” or a “knowledge management director” in
organizations, suggesting two possibilities. The first is that KM is indeed embedded
within the organization’s culture so there is no need to single it out. The second
proposition is that KM has lost its appeal and importance, so there is no need to
have a CKO or equivalent position, especially in these difficult economic times.
xiv
Foreword
Probably, both propositions are true, depending perhaps on the type and nature of
the organization.
So, returning to the first question about KM being widely accepted within today’s
organizations, the jury is still out. It may be simply an awareness issue in order to
show the value-added benefits of KM initiatives. Or it may be that KM was the “management fad of the day” and we are ready to move on. I believe that KM can have
tremendous value to organizations by stimulating creativity and innovation, building
the institutional memory of the firm, enabling agility and adaptability, promoting a
sense of community and belonging, improving organizational internal and external
effectiveness, and contributing toward succession planning and workforce development. KM should be one of the key pillars underpinning a human capital strategy for
the organization. As with anything else, some organizations are leaders and some are
laggards. Those who recognize the importance of KM to the organization’s overarching
vision, mission, and strategy should hopefully be in the winning side of the equation
in the years ahead.
Let us now address the second question posed, “is KM a lasting field?” In other
words, does KM have endurance to stand on its own in the forthcoming years? This
relates back to whether KM is more an art than a science. KM is certainly both, and
as the KM field has developed over the years, an active KM community of both practitioners and researchers has emerged. There are already well over ten international
journals specifically devoted to knowledge management. Worldwide KM conferences
abound, and individuals can take university coursework in knowledge management,
as well as being certified in knowledge management by KM-related professional societies and other organizations. There are funded research projects in knowledge management worldwide, both from basic and applied perspectives. In addition, there are
many KM-related communities of practice established worldwide. So certainly there
is an active group of practitioners and researchers who are trying to put more rigor
behind KM to accentuate the “science” over the “art” in order to give the KM field
lasting legs.
On the other hand, there is the “art” side of KM. Like many fields that draw from
a multidisciplinary approach, especially from the social sciences, there is art along
with the science. Whether KM contributes to “return on vision” versus “return on
investment” indicates some of the difficulty in quantifying KM returns. There certainly
is a “touchy-feely” side to KM, but there is a sound methodological perspective to KM,
too.
Here again, the jury is still out on whether the KM field will last. So what needs to
be done? This is where textbooks such as Knowledge Management in Theory and Practice
Can Knowledge Management Survive?
xv
play an important role. This textbook, in its second edition, marries the theory and
practice of knowledge management; namely, it provides the underlying methodologies for knowledge management design, development, and implementation, as well
as applying these methodologies and techniques in various cases and vignettes sprinkled throughout the book. It addresses my first question of having knowledge management being more widely accepted in organizations by discussing how KM has been
utilized in various industry sectors and organizational settings. The book also emphasizes the “science” behind the “art” in order to address my second question regarding
providing more rigor behind KM so that the field will endure in the years ahead.
Professor Dalkir, a leading KM researcher, educator, and practitioner, uses her
insights and experience to highlight the important areas of knowledge management
in her book. People, culture, process, and technology are key components of knowledge management, and the book provides valuable lessons learned in each area. This
book is well-suited as a reference text for KM practitioners, as well as a textbook for
KM-related courses.
This book, and others, is needed to continue to take the mystique out of KM and
provide the tangible value-added benefits that CEOs and organizations demand. Professor Dalkir should be commended on this new edition, which will hopefully propel
others to be believers in the power of knowledge management. As this happens, the
answers to my two KM questions will be quite obvious! Enjoy!
Jay Liebowitz, D.Sc.
Professor, Carey Business School
Johns Hopkins University
1 Introduction to Knowledge Management
A light bulb in the socket is worth two in the pocket.
—Bill Wolf (1950–2001)
This chapter provides an introduction to the study of knowledge management (KM).
A brief history of knowledge management concepts is outlined, noting that much of
KM existed before the actual term came into popular use. The lack of consensus over
what constitutes a good definition of KM is addressed and the concept analysis technique is described as a means of clarifying the conceptual confusion that still persists
over what KM is or is not. The multidisciplinary roots of KM are enumerated together
with their contributions to the discipline. The two major forms of knowledge, tacit
and explicit, are compared and contrasted. The importance of KM today for individuals, for communities of practice, and for organizations are described together
with the emerging KM roles and responsibilities needed to ensure successful KM
implementations.
Learning Objectives
1. Use a framework and a clear language for knowledge management concepts.
2. Define key knowledge management concepts such as intellectual capital, organizational learning and memory, knowledge taxonomy, and communities of practice
using concept analysis.
3. Provide an overview of the history of knowledge management and identify key
milestones.
4. Describe the key roles and responsibilities required for knowledge management
applications.
2
Chapter 1
Introduction
The ability to manage knowledge is crucial in today’s knowledge economy. The creation and diffusion of knowledge have become increasingly important factors in
competitiveness. More and more, knowledge is being thought of as a valuable commodity that is embedded in products (especially high-technology products) and
embedded in the tacit knowledge of highly mobile employees. While knowledge is
increasingly being viewed as a commodity or intellectual asset, there are some paradoxical characteristics of knowledge that are radically different from other valuable
commodities. These knowledge characteristics include the following:
•
Using knowledge does not consume it.
•
Transferring knowledge does not result in losing it.
•
Knowledge is abundant, but the ability to use it is scarce.
•
Much of an organization’s valuable knowledge walks out the door at the end of the
day.
The advent of the Internet, the World Wide Web, has made unlimited sources of
knowledge available to us all. Pundits are heralding the dawn of the Knowledge Age
supplanting the Industrial Era. Forty-five years ago, nearly half of all workers in
industrialized countries were making or helping to make things. By the year 2000,
only 20 percent of workers were devoted to industrial work—the rest was knowledge
work (Drucker 1994; Barth 2000). Davenport (2005, p. 5) says about knowledge
workers that “at a minimum, they comprise a quarter of the U.S. workforce, and at
a maximum about half.” Labor-intensive manufacturing with a large pool of relatively
cheap, relatively homogenous labor and hierarchical management has given way to
knowledge-based organizations. There are fewer people who need to do more work.
Organizational hierarchies are being put aside as knowledge work calls for more collaboration. A firm only gains sustainable advances from what it collectively knows,
how efficiently it uses what it knows, and how quickly it acquires and uses new
knowledge (Davenport and Prusak 1998). An organization in the Knowledge Age is
one that learns, remembers, and acts based on the best available information, knowledge, and know-how.
All of these developments have created a strong need for a deliberate and systematic
approach to cultivating and sharing a company’s knowledge base—one populated
with valid and valuable lessons learned and best practices. In other words, in order to
be successful in today’s challenging organizational environment, companies need to
learn from their past errors and not reinvent the wheel. Organizational knowledge is
Introduction to Knowledge Management
3
not intended to replace individual knowledge but to complement it by making it
stronger, more coherent, and more broadly applied. Knowledge management represents a deliberate and systematic approach to ensure the full utilization of the
organization’s knowledge base, coupled with the potential of individual skills, competencies, thoughts, innovations, and ideas to create a more efficient and effective
organization.
Increasingly, companies will differentiate themselves on the basis of what they know. A relevant
variation on Sidney Winter’s definition of a business firm as an organization that knows how to do
things would define a business firm that thrives over the next decade as an organization that knows
how to do new things well and quickly. (Davenport and Prusak 1998, 13)
Knowledge management was initially defined as the process of applying a systematic approach to the capture, structuring, management, and dissemination of knowledge throughout an organization to work faster, reuse best practices, and reduce costly
rework from project to project (Nonaka and Takeuchi, 1995; Pasternack and Viscio
1998; Pfeffer and Sutton, 1999; Ruggles and Holtshouse, 1999). KM is often characterized by a pack rat approach to content: “save it, it may prove useful some time in the
future.” Many documents tend to be warehoused, sophisticated search engines are
then used to try to retrieve some of this content, and fairly large-scale and costly KM
systems are built. Knowledge management solutions have proven to be most successful
in the capture, storage, and subsequent dissemination of knowledge that has been
rendered explicit—particularly lessons learned and best practices.
The focus of intellectual capital management (ICM), on the other hand, is on those
pieces of knowledge that are of business value to the organization—referred to as intellectual capital or assets. Stewart (1997) defines intellectual capital as “organized knowledge that can be used to produce wealth.” While some of these assets are more visible
(e.g., patents, intellectual property), the majority consists of know-how, know-why,
experience, and expertise that tends to reside within the head of one or a few employees (Klein 1998; Stewart 1997). ICM is characterized less by content—because content
is filtered and judged, and only the best ideas re inventoried (the top ten for example).
ICM content tends to be more representative of the real thinking of individuals (contextual information, opinions, stories) because of its focus on actionable knowledge
and know-how. The outcome is less costly endeavors and a focus on learning (at the
individual, community, and organizational levels) rather than on the building of
systems.
A good definition of knowledge management would incorporate both the capturing
and storing of knowledge perspective, together with the valuing of intellectual assets.
For example:
4
Chapter 1
Knowledge management is the deliberate and systematic coordination of an organization’s
people, technology, processes, and organizational structure in order to add value through reuse
and innovation. This is achieved through the promotion of creating, sharing, and applying
knowledge as well as through the feeding of valuable lessons learned and best practices into
corporate memory in order to foster continued organizational learning.
When asked, most executives will state that their greatest asset is the knowledge
held by their employees. “When employees walk out the door, they take valuable
organizational knowledge with them” (Lesser and Prusak 2001, 1). Managers also
invariably add that they have no idea how to manage this knowledge! Using the intellectual capital or asset approach, it is essential to identify knowledge that is of value
and is also at risk of being lost to the organization through retirement, turnover, and
competition.. As Lesser and Prusak (2001, 1) note: “The most knowledgeable employees often leave first.” In addition, the selective or value-based knowledge management
approach should be a three-tiered one, that is, it should also be applied to three organizational levels: the individual, the group or community, and the organization itself.
The best way to retain valuable knowledge is to identify intellectual assets and then
ensure legacy materials are produced and subsequently stored in such a way as to make
their future retrieval and reuse as easy as possible (Stewart 2000). These tangible byproducts need to flow from individual to individual, between members of a community of practice and, of course, back to the organization itself, in the form of lessons
learned, best practices, and corporate memory.
Many knowledge management efforts have been largely concerned with capturing,
codifying, and sharing the knowledge held by people in organizations. Although there
is still a lack of consensus over what constitutes a good definition of KM (see next
section), there is widespread agreement as to the goals of an organization that undertakes KM. Nickols (2000) summarizes this as follows: “the basic aim of knowledge
management is to leverage knowledge to the organization’s advantage.” Some of
management’s motives are obvious: the loss of skilled people through turnover, pressure to avoid reinventing the wheel, pressure for organization-wide innovations in
processes as well as products, managing risk, and the accelerating rate with which new
knowledge is being created. Some typical knowledge management objectives would
be to:
•
Facilitate a smooth transition from those retiring to their successors who are recruited
to fill their positions
•
Minimize loss of corporate memory due to attrition and retirement
•
Identify critical resources and critical areas of knowledge so that the corporation
knows what it knows and does well—and why
Introduction to Knowledge Management
•
5
Build up a toolkit of methods that can be used with individuals, with groups, and
with the organization to stem the potential loss of intellectual capital
What Is Knowledge Management?
An informal survey conducted by the author identified over a hundred published
definitions of knowledge management and of these, at least seventy-two could be
considered to be very good! Carla O’Dell has gathered over sixty definitions and has
developed a preliminary classification scheme for the definitions on her KM blog (see
http://blog.simslearningconnections.com/?p=279) and what this indicates is that KM
is a multidisciplinary field of study that covers a lot of ground. This should not be
surprising as applying knowledge to work is integral to most business activities.
However, the field of KM does suffer from the “Three Blind Men and an Elephant”
syndrome. In fact, there are likely more than three distinct perspectives on KM, and
each leads to a different extrapolation and a different definition.
Here are a few sample definitions of knowledge management from the business
perspective:
Strategies and processes designed to identify, capture, structure, value, leverage, and share an
organization’s intellectual assets to enhance its performance and competitiveness. It is based on
two critical activities: (1) capture and documentation of individual explicit and tacit knowledge,
and (2) its dissemination within the organization. (The Business Dictionary, http://www.businessdictionary.com/definition/knowledge-management.html)
Knowledge management is a collaborative and integrated approach to the creation, capture,
organization, access, and use of an enterprise’s intellectual assets. (Grey 1996)
Knowledge management is the process by which we manage human centered assets . . . the
function of knowledge management is to guard and grow knowledge owned by individuals, and
where possible, transfer the asset into a form where it can be more readily shared by other
employees in the company. (Brooking 1999, 154)
Further definitions come from the intellectual or knowledge asset perspective:
Knowledge management consists of “leveraging intellectual assets to enhance organizational
performance.” (Stankosky 2008)
Knowledge management develops systems and processes to acquire and share intellectual assets.
It increases the generation of useful, actionable, and meaningful information, and seeks to
increase both individual and team learning. In addition, it can maximize the value of an organization’s intellectual base across diverse functions and disparate locations. Knowledge management maintains that successful businesses are a collection not of products but of distinctive
knowledge bases. This intellectual capital is the key that will give the company a competitive
6
Chapter 1
advantage with its targeted customers. Knowledge management seeks to accumulate intellectual
capital that will create unique core competencies and lead to superior results. (Rigby 2009)
A definition from the cognitive science or knowledge science perspective:
Knowledge—the insights, understandings, and practical know-how that we all possess—is the
fundamental resource that allows us to function intelligently. Over time, considerable knowledge
is also transformed to other manifestations—such as books, technology, practices, and traditions—within organizations of all kinds and in society in general. These transformations result
in cumulated [sic] expertise and, when used appropriately, increased effectiveness. Knowledge is
one, if not THE, principal factor that makes personal, organizational, and societal intelligent
behavior possible. (Wiig 1993)
Two diametrically opposed schools of thought arise from the library and information science perspective: the first sees very little distinction between information
management and knowledge management, as shown by these two definitions:
KM is predominantly seen as information management by another name (semantic drift).
(Davenport and Cronin 2000, 1)
Knowledge management is one of those concepts that librarians take time to assimilate, only to
reflect ultimately “on why other communities try to colonize our domains.” (Hobohm 2004, 7)
The second school of thought, however, does make a distinction between the management of information resources and the management of knowledge resources.
Knowledge management “is understanding the organization’s information flows and implementing organizational learning practices which make explicit key aspects of its knowledge base. . . .
It is about enhancing the use of organizational knowledge through sound practices of information management and organizational learning.” (Broadbent 1997, 8–9)
The process-technology perspective provides some sample definitions, as well:
Knowledge management is the concept under which information is turned into actionable
knowledge and made available effortlessly in a usable form to the people who can apply it. (Patel
and Harty, 1998)
Leveraging collective wisdom to increase responsiveness and innovation. (Carl Frappaolo, Delphi
Group, Boston, http://www.destinationkm.com/articles/default.asp?ArticleID=949)
A systematic approach to manage the use of information in order to provide a continuous flow
of knowledge to the right people at the right time enabling efficient and effective decision making
in their everyday business. (Steve Ward, Northrop Grumman, http://www.destinationkm.com/
articles/default.asp?ArticleID=949)
A knowledge management system is a virtual repository for relevant information that is
critical to tasks performed daily by organizational knowledge workers. (What is KM? http://www
.knowledgeshop.com)
Introduction to Knowledge Management
7
The tools, techniques, and strategies to retain, analyze, organize, improve, and share business
expertise. (Groff and Jones 2003, 2)
A capability to create, enhance, and share intellectual capital across the organization . . . a shorthand covering all the things that must be put into place, for example, processes, systems, culture,
and roles to build and enhance this capability. (Lank 1997)
The creation and subsequent management of an environment that encourages knowledge to be
created, shared, learnt [sic], enhanced, organized and utilized for the benefit of the organization
and its customers. (Abell and Oxbrow 2001)
Wiig (1993, 2002) also emphasizes that, given the importance of knowledge in
virtually all areas of daily and commercial life, two knowledge-related aspects are vital
for viability and success at any level. These are knowledge assets that must be applied,
nurtured, preserved, and used to the largest extent possible by both individuals and
organizations; and knowledge-related processes to create, build, compile, organize,
transform, transfer, pool, apply, and safeguard knowledge. These knowledge-related
aspects must be carefully and explicitly managed in all affected areas.
Historically, knowledge has always been managed, at least implicitly. However, effective and
active knowledge management requires new perspectives and techniques and touches on almost
all facets of an organization. We need to develop a new discipline and prepare a cadre of knowledge professionals with a blend of expertise that we have not previously seen. This is our challenge! (Wiig, in Grey 1996)
Knowledge management is a surprising mix of strategies, tools, and techniques—
some of which are nothing new under the sun: storytelling, peer-to-peer mentoring,
and learning from mistakes, for example, all have precedents in education, training,
and artificial intelligence practices. Knowledge management makes use of a mixture
of techniques from knowledge-based system design, such as structured knowledge
acquisition strategies from subject matter experts (McGraw and Harrison-Briggs 1989)
and educational technology (e.g., task and job analysis to design and develop task
support systems; Gery 1991).
This makes it both easy and difficult to define what KM is. At one extreme, KM
encompasses everything to do with knowledge. At the other extreme, KM is narrowly
defined as an information technology system that dispenses organizational knowhow. KM is in fact both of these and much more. One of the few areas of consensus
in the field is that KM is a highly multidisciplinary field.
8
Chapter 1
Multidisciplinary Nature of KM
Knowledge management draws upon a vast number of diverse fields such as:
•
Organizational science
•
Cognitive science
•
Linguistics and computational linguistics
•
Information technologies such as knowledge-based systems, document and informa-
tion management, electronic performance support systems, and database technologies
•
Information and library science
•
Technical writing and journalism
•
Anthropology and sociology
•
Education and training
•
Storytelling and communication studies
•
Collaborative technologies such as Computer-Supported Collaborative Work (CSCW)
and groupware as well as intranets, extranets, portals, and other web technologies
The above is by no means an exhaustive list but serves to show the extremely varied
roots that KM grew out of and continues to be based upon today. Figure 1.1 illustrates
some of the diverse disciplines that have contributed to KM.
The multidisciplinary nature of KM represents a double-edged sword: on the one
hand, it is an advantage as almost anyone can find a familiar foundation upon which
to base an understanding and even practice of KM. Someone with a background in
Database Technologies
Collaborative Technologies
Help Desk Systems
Organizational Science
Cognitive Science
KM Disciplines
Technical Writing
Artificial Intelligence
Electronic Performance
Support Systems
Document and
Information Management
Web Technologies
Decision Support Systems
Library and Information Sciences
Figure 1.1
Interdisciplinary nature of knowledge management
Introduction to Knowledge Management
9
journalism, for example, can quickly adapt this skill set to capture knowledge from
experts and reformulate this knowledge as organizational stories to be stored in corporate memory. Someone coming from a more technical database background can
easily extrapolate his or her skill set to design and implement knowledge repositories
that will serve as the corporate memory for that organization. However, the diversity
of KM also results in some challenges with respect to boundaries. Skeptics argue that
KM is not and cannot be said to be a separate discipline with a unique body of knowledge to draw upon. This attitude is typically represented by statements such as “KM
is just IM” or “KM is nonsensical—it is just good business practices.” It becomes very
important to be able to list and describe what attributes are necessary and in themselves sufficient to constitute knowledge management both as a discipline and as a
field of practice that can be distinguished from others.
One of the major attributes lies in the fact that KM deals with knowledge as well
as information. Knowledge is a more subjective way of knowing, typically based on
experiential or individual values, perceptions, and experience. Consider the example
of planning for an evening movie to distinguish between data, information, and
knowledge.
Data
Content that is directly observable or verifiable: a fact; for example, movie list-
ings giving the times and locations of all movies being shown today—I download the
listings.
Information Content that represents analyzed data; for example, I can’t leave before
5, so I will go to the 7 pm show at the cinema near my office.
Knowledge At that time of day, it will be impossible to find parking. I remember the
last time I took the car, I was so frustrated and stressed because I thought I would miss
the opening credits. I’ll therefore take the commuter train. But first, I’ll check with
Al. I usually love all the movies he hates, so I want to make sure it’s worth seeing!
Another distinguishing characteristic of KM, as opposed to other information
management fields, is the fact that knowledge in all of its forms is addressed: tacit
knowledge and explicit knowledge.
The Two Major Types of Knowledge: Tacit and Explicit
We know more than we can tell.
—Polanyi 1966
Tacit knowledge is difficult to articulate and difficult to put into words, text, or
drawings. Explicit knowledge represents content that has been captured in some
10
Chapter 1
Table 1.1
Comparison of properties of tacit versus explicit knowledge
Properties of tacit knowledge
Properties of explicit knowledge
Ability to adapt, to deal with new and
exceptional situations
Ability to disseminate, to reproduce, to access
and re-apply throughout the organization
Expertise, know-how, know-why, and
care-why
Ability to teach, to train
Ability to collaborate, to share a vision, to
transmit a culture
Ability to organize, to systematize, to
translate a vision into a mission statement,
into operational guidelines
Coaching and mentoring to transfer
experiential knowledge on a one-to-one,
face-to-face basis
Transfer knowledge via products, services,
and documented processes
tangible form such as words, audio recordings, or images. Tacit knowledge tends to
reside within the heads of knowers, whereas explicit knowledge is usually contained
within tangible or concrete media. However, it should be noted that this is a rather
simplistic dichotomy. In fact, the property of tacitness is a property of the knower:
that which is easily articulated by one person may be very difficult to externalize by
another. The same content may be explicit for one person and tacit for another.
There is also somewhat of a paradox at play here: highly skilled, experienced, and
expert individuals may find it harder to articulate their know-how. Novices, on the
other hand, are more apt to easily verbalize what they are attempting to do because
they are typically following a manual or how-to process. Table 1.1 summarizes some
of the major properties of tacit and explicit knowledge.
Typically, the more tacit knowledge is, the more valuable it tends to be. The
paradox lies in the fact that the more difficult it is to articulate a concept such as story,
the more valuable that knowledge may be. This is often witnessed when people make
reference to knowledge versus know-how, or knowing something versus knowing how
to do something. Valuable tacit knowledge often results in some observable action
when individuals understand and subsequently make use of knowledge. Another
perspective is that explicit knowledge tends to represent the final end product whereas
tacit knowledge is the know-how or all of the processes that were required in order
to produce that final product.
We have a habit of writing articles published in scientific journals to make the work as finished
as possible, to cover up all the tracks, to not worry about the blind alleys or how you had the
wrong idea at first, and so on. So there isn’t any place to publish, in a dignified manner, what
you actually did in order to do the work. (Feynman 1966).
Introduction to Knowledge Management
11
A popular misconception is that KM focuses on rendering that which is tacit into
more explicit or tangible forms, then storing or archiving these forms somewhere,
usually some form of intranet or knowledge portal. The “build it and they will come”
expectation typifies this approach: Organizations take an exhaustive inventory of
tangible knowledge (i.e., documents, digital records) and make them accessible to all
employees. Senior management is then mystified as to why employees are not using
this wonderful new resource. In fact, knowledge management is broader and includes
leveraging the value of the organizational knowledge and know-how that accumulates
over time. This approach is a much more holistic and user-centered approach that
begins not with an audit of existing documents but with a needs analysis to better
understand how improved knowledge sharing may benefit specific individuals, groups,
and the organization as a whole. Successful knowledge-sharing examples are gathered
and documented in the form of lessons learned and best practices and these then form
the kernel of organizational stories.
There are a number of other attributes that together make up a set of what KM
should be all about. One good technique for identifying these attributes is the concept
analysis technique.
The Concept Analysis Technique
Concept analysis is an established technique used in the social sciences (i.e., philosophy and education) in order to derive a formula that in turn can be used to generate
definitions and descriptive phrases for highly complex terms. We still lack a consensus
on knowledge management–related terms, and these concepts do appear to be complex
enough to merit the concept analysis approach. A great deal of conceptual complexity
derives from the fact that a word such as knowledge is necessarily subjective in nature,
not to mention value laden in interpretation.
The concept analysis approach rests on the obtaining consensus around three major
dimensions of a given concept (shown in figure 1.2).
1. A list of key attributes that must be present in the definition, vision, or mission
statement
2. A list of illustrative examples
3. A list of illustrative nonexamples
This approach is particularly useful in tackling multidisciplinary domains such
as intellectual capital, because clear criteria can be developed to enable sorting
into categories such as knowledge versus information, document management versus
knowledge management, and tangible versus intangible assets. In addition, valuable
12
Chapter 1
Concept Name
Key Attributes
Examples
Nonexamples
1.
1.
1.
2.
2.
2.
3.
3.
3.
4.
4.
4.
5.
5.
5.
6.
6.
6.
7.
7.
7.
Figure 1.2
Illustration of the Concept Analysis Technique
contributions to the organization’s intellectual capital are derived through the production of ontologies (semantic maps of key concepts), identification of core competencies, and identification of knowledge, know-how, and know-why at risk of being lost
through human capital attrition.
Concept analysis is a technique used to visually map out conceptual information
in the process of defining a word (Novak 1990, 1991). This is a technique derived from
the fields of philosophy and science education (Bareholz and Tamir 1992; Lawson
1994) and is typically used in clearly defining complex, value-laden terms such as
democracy or religion. It is a graphical approach to help develop a rich, in-depth understanding of a concept. Figure 1.2 outlines the major components of this approach.
Davenport and Prusak (1998) decry the ability to provide a definitive account of
knowledge management since “epistemologists have spent their lives trying to understand what it means to know something.” In his 2008 keynote address, Michael
Stankosky reiterated this disappointment that we still “don’t know what to call it!” If
Introduction to Knowledge Management
13
you can’t manage what you cannot measure, then you can’t measure what you cannot
name. Knowledge management, due to this still ongoing lack of clarity and lack of
consensus on a definition, presents itself as a good candidate for this approach. In
visioning workshops, this is the first activity that participants are asked to undertake.
The objective is to agree upon a list of key attributes that are both necessary and sufficient in order for a definition of knowledge management to be acceptable. This is
completed by a list of examples and nonexamples, with justifications as to why a
particular item was included on the example or nonexample list. Semantic mapping
(Jonassen, Beissner, and Yacci 1993; Fisher 1990) is the visual technique used to extend
the definition by displaying words related to it. Popular terms to distinguish clearly
from knowledge management include document management, content management,
portal, knowledge repository, and others. Together, the concept and semantic maps
visually depict a model-based definition of knowledge management and its closely
related terms.
In some cases, participants are provided with lists of definitions of knowledge
management from a variety of sources can so they can try out their concept map of
knowledge management by analyzing these existing definitions. Definitions are typically drawn from the knowledge management literature as well as internally, from
their own organization. The use of concept definition through concept and semantic
mapping techniques can help participants rapidly reach a consensus on a formulaic
definition of knowledge management, that is, one that focuses less on the actual text
or words used but more on which key concepts need to be present, what comprises
a necessary and sufficient (complete) set of concepts, and rules of thumb to use in
discerning what is and what is not an illustrative example of knowledge
management.
Ruggles and Holtshouse (1999) identified the following key attributes of knowledge
management:
•
Generating new knowledge
•
Accessing valuable knowledge from outside sources
•
Using accessible knowledge in decision making
•
Embedding knowledge in processes, products and/or services
•
Representing knowledge in documents, databases, and software
•
Facilitating knowledge growth through culture and incentives
•
Transferring existing knowledge into other parts of the organization
•
Measuring the value of knowledge assets and/or impact of knowledge management
14
Chapter 1
Some key knowledge management attributes that continue to recur include:
•
Both tacit and explicit knowledge forms are addressed; tacit knowledge (Polanyi
1966) is knowledge that often resides only within individuals, knowledge that is difficult to articulate such as expertise, know-how, tricks of the trade, and so on.
•
There is a notion of added-value (the so what? of KM).
•
The notion of application or use of the knowledge captured, codified, and dissemi-
nated (the impact of KM).
It should be noted that a good enough or sufficient definition of knowledge has been
shown to be effective (i.e., settling for good enough as opposed to optimizing; when 80
percent is done because the incremental cost of completing the remaining 20 percent
is disproportionately expensive and/or time-consuming in relation to the expected
additional benefits). Norman (1988, 50–74) noted that knowledge might reside in two
places—in the minds of people and/or in the world. It is easy to show the faulty nature
of human knowledge and memory. For example, when typists were given caps for
typewriter keys, they could not arrange them in the proper configuration—yet all
those typists could type rapidly and accurately. Why the apparent discrepancy between
the precision of behavior and the imprecision of knowledge? Because not all of the
knowledge required for precise behavior has to be in the mind. It can be distributed—
partly in the mind, partly in the world, and partly in the constraints of the world.
Precise behavior can thus emerge from imprecise knowledge (Ambur 1996). It is for
this reason that once a satisfactory working or operational definition of knowledge
management has been arrived at, then a knowledge management strategy can be
confidently tackled.
It is highly recommended that each organization undertake a concept analysis
exercise to clarify their understanding of what KM means in their own context. The
best way to do this would be to work as a group in order to achieve a shared understanding at the same time that a clearer conceptualization of the KM concept is
developed. Each participant can take a turn to contribute one good example of what
KM is and another example of what KM is not. The entire group can then discuss this
example/nonexample pair in order to identify one (or several) key KM attributes.
Miller’s (1956) magic number can be used to define the optimal number of attributes
a given concept should have—namely, seven plus or minus two attributes. Once the
group feels they have covered as much ground as they are likely to, the key attributes
can be summarized in the form of a KM concept formula such as:
In our organization, knowledge management must include the following: both tacit
and explicit knowledge; a framework to measure the value of knowledge assets; a
process for managing knowledge assets . . .
Introduction to Knowledge Management
15
The lack of agreement on one universal formulation of a definition for knowledge
management makes it essential to develop one for each organization (at a very
minimum). This working or operational definition, derived through the concept analysis
technique, will render explicit the various perceptions people in that company may
have of KM and bring them together into a coherent framework. It may seem strange
that KM is almost always defined at the beginning of any talk or presentation on the
topic (imagine if other professionals such as doctors, lawyers, or engineers began every
talk with “here is a definition of what I do and why”) but this is the reality we must
deal with. Whether the lack of a definition is due to the interdisciplinary nature of
the field and/or because it is still an emerging discipline, it certainly appears to be
highly contextual. The concept analysis technique allows us to continue in both
research and practice while armed with a common, validated, and clear description
of KM that is useful and adapted to a particular organizational context.
History of Knowledge Management
Although the term knowledge management formally entered popular usage in the late
1980s (e.g., conferences in KM began appearing, books on KM were published, and
the term began to be seen in business journals), philosophers, teachers, and writers
have been making use of many of the same techniques for decades. Denning (2002)
related how from “time immemorial, the elder, the traditional healer, and the midwife
in the village have been the living repositories of distilled experience in the life of the
community”(http://www.stevedenning.com/ knowledge_management.html).
Some form of narrative repository has been around for a long time, and people
have found a variety of ways to share knowledge in order to build on earlier experience, eliminate costly redundancies, and avoid making at least the same mistakes
again. For example, knowledge sharing often took the form of town meetings, workshops, seminars, and mentoring sessions. The primary vehicle for knowledge transfer
was people themselves—in fact, much of our cultural legacy stems from the migration
of different peoples across continents.
Wells (1938), while never using the actual term knowledge management, described
his vision of the World Brain that would allow the intellectual organization of the sum
total of our collective knowledge. The World Brain would represent “a universal organization and clarification of knowledge and ideas” (Wells 1938, xvi). Wells in fact
anticipated the World Wide Web, albeit in an idealized manner, when he spoke of
“this wide gap between . . . at present unassembled and unexploited best thought and
knowledge in the world . . . we live in a world of unused and misapplied knowledge
and skill” (p. 10). The World Brain encapsulates many of the desirable features of the
16
Chapter 1
intellectual capital approach to KM: selected, well-organized, and widely vetted
content that is maintained, kept up to date, and, above all, put to use to generate
value to users, the users’ community, and their organization.
What Wells envisioned for the entire world can easily be applied within an organization in the form of an intranet. What is new and termed knowledge management
is that we are now able to simulate rich, interactive, face-to-face knowledge encounters virtually through the use of new communication technologies. Information technologies such as an intranet and the Internet enable us to knit together the intellectual
assets of an organization and organize and manage this content through the lenses
of common interest, common language, and conscious cooperation. We are able to
extend the depth and breadth or reach of knowledge capture, sharing and dissemination activities, as we had not been able to do before and find ourselves one step
closer to Wells’ (1938) “perpetual digest . . . and a system of publication and distribution” (pp. 70–71) “to an intellectual unification . . . of human memory” (pp.
86–87).
Drucker was the first to coin the term knowledge worker in the early 1960s (Drucker
1964). Senge (1990) focused on the learning organization as one that can learn from
past experiences stored in corporate memory systems. Dorothy Barton-Leonard (1995)
documented the case of Chapparal Steel as a knowledge management success story.
Nonaka and Takeuchi (1995) studied how knowledge is produced, used, and diffused
within organizations and how this contributes to the diffusion of innovation.
The growing importance of organizational knowledge as a competitive asset was
recognized by a number of people who saw the value in being able to measure intellectual assets (see Kaplan and Norton; APQC 1996; Edvinsson and Malone 1997,
among others). A cross-industry benchmarking study was led by APQC’s president
Carla O’Dell and completed in 1996. It focused on the following KM needs:
• Knowledge management as a business strategy
• Transfer of knowledge and best practices
• Customer-focused knowledge
• Personal responsibility for knowledge
• Intellectual asset management
• Innovation and knowledge creation (APQC 1996)
The Entovation timeline (available at http://www.entovation.com/timeline/
timeline.htm) identifies a variety of disciplines and domains that have blended
together to emerge as knowledge management. A number of management theorists
have contributed significantly to the evolution of KM such as Peter Drucker, Peter
Introduction to Knowledge Management
Knowledge
Creating
Company
HBR Nonaka
ARPANET
1969
17
Emergence
of virtual
organizations
Organizational
Learning
Sloan Mgmt.
Measurement
of intellectual
assets
Community
of Practice
Brown
1988
1991
1994
1985
Proliferation
of information
technology
Fifth
Discipline
Senge
Knowledge
Management
Foundations
Wiig
Your Company’s
Most Valuable
Asset:
Intellectual
Capital
Certification
Stewart
of knowledge
innovation
standards
1997
The Balanced
Scorecard
Kaplan and Norton
First CKO
Edvinsson
Corporation
2000 +
First KM
programs in
universities
APQC
benchmarking
Figure 1.3
A summary timeline of knowledge management
Senge, Ikujiro Nonaka, Hirotaka Takeuchi, and Thomas Stewart. An extract of this
timeline is shown in figure 1.3.
The various eras we have lived through offer another perspective on the history of
KM. Starting with the industrial era in the 1800s, we focused on transportation technologies in 1850, communications in 1900, computerization beginning in the 1950s,
and virtualization in the early 1980s, and early efforts at personalization and profiling
technologies beginning in the year 2000 (Deloitte, Touche, Tohmatsu 1999). Figure
1.4 summarizes these developmental phases.
With the advent of the information or computer age, KM has come to mean the
systematic, deliberate leveraging of knowledge assets. Technologies enable valuable
knowledge to be remembered, via organizational learning and corporate memory; as
well as enabling valuable knowledge to be published, that is, widely disseminated to
all stakeholders. The evolution of knowledge management has occurred in parallel
with a shift from a retail model based on a catalog (e.g., Ford’s famous quote that you
can have a car in any color you like—as long as it is black) to an auction model (as
exemplified by eBay) to a personalization model where real-time matching of user
needs and services occur in a win-win exchange model.
In 1969, the launch of the ARPANET allowed scientists and researchers to communicate more easily with one another in addition to being able to exchange large
data sets they were working on. They came up with a network protocol or language
that would allow disparate computers and operating systems to network together
18
Chapter 1
Personalization
2000 ++
Virtualization
1980
Computerization
Communications
Transportation
Industrialization
1950*
1900
1850
1800
* Birth of the Internet, 1969
Figure 1.4
Developmental phases in KM history
across communication lines. Next, a messaging system was added to this data file
transfer network. In 1991, the nodes were transferred to the Internet and World Wide
Web. At the end of 1969, only four computers and about a dozen workers were
connected.
In parallel, there were many key developments in information technologies devoted
to knowledge-based systems: expert systems that aimed at capturing experts on a diskette, intelligent tutoring systems aimed at capturing teachers on a diskette and artificial
intelligence approaches that gave rise to knowledge engineering, someone tasked with
acquiring knowledge from subject matter experts, conceptually modeling this content,
and then translating it into machine-executable code (McGraw and Harrison-Briggs
1989). They describe knowledge engineering as “involving information gathering,
domain familiarization, analysisand design efforts. In addition, accumulated knowledge must be translated into code, tested and refined” (McGraw and Harrison Briggs,
5). A knowledge engineer is “the individual responsible for structuring and/or constructing an expert system” (5). The design and development of such knowledge-based
systems have much to offer knowledge management that also aims at the capture,
validation, and subsequent technology-mediated dissemination of valuable knowledge from experts.
Introduction to Knowledge Management
19
Table 1.2
Knowledge management milestones
Year
Entity
Event
1980
DEC, CMU
XCON Expert System
1986
Dr. K. Wiig
Coined KM concept at UN
1989
Consulting Firms
Start internal KM projects
1991
HBR article
Nonaka and Takeuchi
1993
Dr. K. Wiig
First KM book published
1994
KM Network
First KM conference
Mid 1990s
Consulting Firms
Start offering KM services
Late 1990s
Key vertical industries
Implement KM and start seeing benefits
2000–2003
Academia
KM courses/programs in universities with
KM texts
2003 to present
Professional and Academic
Certification
KM degrees offered by universities, by
professional institutions such as KMCI
(Knowledge Management Consortium
International; information available at:
http://www.kmci.org/) and PhD students
completing KM dissertations
By the early 1990s, books on knowledge management began to appear and the field
picked up momentum in the mid 1990s with a number of large international KM
conferences and consortia being developed. In 1999, Boisot summarized some of these
milestones. Table 1.2 shows an updated summary.
At the 24th World Congress on Intellectual Capital Management in January 2003,
a number of KM gurus united in sending out a request to academia to pick up the KM
torch. Among those attending the conference were Karl Sveiby, Leif Edvinsson, Debra
Amidon, Hubert Saint-Onge, and Verna Allee. They made a strong case that KM had
up until now been led by practitioners who were problem-solving by the seat of their
pants and that it was now time to focus on transforming KM into an academic discipline, promoting doctoral research in the discipline, and providing a more formalized
training for future practitioners. Today, over a hundred universities around the world
offer courses in KM, and quite a few business and library schools offer degree programs
in KM (Petrides and Nodine 2003).
From Physical Assets to Knowledge Assets
Knowledge has increasingly become more valuable than the more traditional physical
or tangible assets. For example, traditionally, an airline organization’s assets included
the physical inventory of airplanes. Today, however, the greatest asset possessed by
20
Chapter 1
an airline is the SABRE reservation system, software that enables the airline to not
only manage the logistics of its passenger reservations but also to implement a seatyield management system. The latter refers to an optimization program that is used
to ensure maximum revenue is generated from each seat sold—even if each and every
seat carried a distinct price. Similarly, in the manufacturing sector, the value of nonphysical assets such as just-in-time (JIT) inventory systems is rapidly proving to
provide more value. These are examples of intellectual assets, which generally refer to
an organization’s recorded information, and human talent where such information is
typically either inefficiently warehoused or simply lost, especially in large, physically
dispersed organizations (Stewart 1991).
This has led to a change in focus to the useful lifespan of a valuable piece of
knowledge—when is some knowledge of no use? What about knowledge that never
loses its value? The notion of knowledge obsolescence and archiving needs to be
approached with a fresh lens. It is no longer advisable to simply discard items that
are past their due date. Instead, content analysis and a cost-benefit analysis are needed
in order to manage each piece of valuable knowledge in the best possible way.
Intellectual capital is often made visible by the difference between the book value
and the market value of an organization (often referred to as goodwill). Intellectual
assets are represented by the sum total of what employees of the organization know
and know how to do. The value of these knowledge assets is at least equal to the cost
of recreating this knowledge. The accounting profession still has considerable difficulty in accommodating these new forms of assets. Some progress has been made (e.g.,
Skandia was the first organization to report intellectual capital as part of its yearly
financial report), but there is much more work to be done in this area. As shown in
figure 1.5, intellectual assets may be found at the strategic, tactical, and operational
levels of an organization.
Some examples of intellectual capital include:
Competence The skills necessary to achieve a certain (high) level of performance
Capability
Strategic skills necessary to integrate and apply competencies
Technologies Tools and methods required to produce certain physical results
Core competencies are the things that an organization knows how to do well, that
provide a competitive advantage. These are situated at a tactical level. Some examples
would be a process, a specialized type of knowledge, or a particular kind of expertise
that is rare or unique to the organization. Capabilities are found at a more strategic
level. Capabilities are those things that an individual knows how to do well, which,
under appropriate conditions, may be aggregated to organizational competencies.
Introduction to Knowledge Management
21
Intellectual capital
Increasing complexity
Political negotiation
Mainly subjective
Strategic
Tactical
Technical integration
Mainly objective
Operational
Figure 1.5
Three levels of intellectual capital
Capabilities are potential core competencies and sound KM practices are required
in order for that potential to be realized. A number of business management texts
discuss these concepts in greater detail (e.g., Hamel and Prahalad 1990). It should be
noted that the more valuable a capability is, and the less it is shared among many
employees, then the more vulnerable the organization becomes should that employee
leave.
Organizational Perspectives on Knowledge Management
Wiig (1993) considers knowledge management in organizations from three perspectives, each with different horizons and purposes:
Business perspective Focusing on why, where, and to what extent the organization
must invest in or exploit knowledge. Strategies, products and services, alliances, acquisitions, or divestments should be considered from knowledge-related points of view.
Management perspective
Focusing on determining, organizing, directing, facilitating,
and monitoring knowledge-related practices and activities required to achieve the
desired business strategies and objectives
Hands-on perspective Focusing on applying the expertise to conduct explicit knowledge-related work and tasks
22
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The business perspective easily maps onto the strategic nature of knowledge management, the management perspective to the tactical layer, and the hands-on perspective may be equated with the operational level.
Library and Information Science (LIS) Perspectives on KM
Although not everyone in the LIS community is positively inclined toward KM
(tending to fall back on arguments that IM is enough and that KM is encroaching
upon this territory, as shown in some of the earlier definitions), others see KM as a
means of enlarging the scope of activities that information professionals can participate in. Gandhi (2004) notes that knowledge organization has always been part of the
core curriculum and the professional toolkit of LIS; and Martin et al. (2006, 15) point
out that LIS professionals are also expert in content management. The authors go on
to state that
Libraries and information centers will continue to perform access and intermediary roles which
embrace not just information but also knowledge management (Henczel 2004). The difference
today is that these traditional roles could be expanded if not transformed . . . through activities
aimed at helping to capture tacit knowledge and by turning personal knowledge into corporate
knowledge that can be widely shared through the library and applied appropriately.
Blair (2002) notes that the primary differences between traditional information
management practiced by LIS professional and knowledge management consist of
collaborative learning, the transformation of tacit knowledge into explicit forms, and
the documentation of best practices (and presumably their counterpart, lessons
learned). The author often uses the phrase “connecting people to content and connecting people to people” to highlight the addition of non-document-based resources
that play a critical role in KM.
As with KM itself, there is no best or better perspective; instead, the potential added
value is to combine the two perspectives in order to get the most out of KM. One of
the easiest ways of doing so would be to ensure that both perspectives—and both
types of skill sets—are represented on your KM team.
Why Is KM Important Today?
The major business drivers behind today’s increased interest and application of KM
lie in four key areas:
1. Globalization of business Organizations today are more global—multisite, multilingual, and multicultural in nature.
Introduction to Knowledge Management
2. Leaner organizations
23
We are doing more and we are doing it faster, but we also
need to work smarter as knowledge workers—increased pace and workload.
3. Corporate amnesia
We are more mobile as a workforce, which creates problems of
knowledge continuity for the organization, and places continuous learning demands
on the knowledge worker—we no longer expect to work for the same organization for
our entire career.
4. Technological advances
We are more connected—information technology advances
have made connectivity not only ubiquitous but has radically changed expectations:
we are expected to be on at all times and the turnaround time in responding is now
measured in minutes, not weeks.
Today’s work environment is more complex due to the increase in the number of
subjective knowledge items we need to attend to every day. Filtering over two hundred
e-mails, faxes, and voice mail messages on a daily basis should be done according to
good time management practices and filtering rules, but more often than not, workers
tend to exhibit a Pavlovian reflex to beeps announcing the arrival of new mail or the
ringing of the phone that demands immediate attention. Knowledge workers are
increasingly being asked to think on their feet with little time to digest and analyze
incoming data and information, let alone time to retrieve, access, and apply relevant
experiential knowledge. This is due both to the sheer volume of tasks to attend to, as
well as the greatly diminished turnaround time. Today’s expectation is that everyone
is on all the time—as evidenced by the various messages embodying annoyance at not
having connected, such as voice mails asking why you have not responded to an
e-mail, and e-mails asking why you have not returned a call!
Knowledge management represents one response to the challenge of trying to
manage this complex, information overloaded work environment. As such, KM is
perhaps best categorized as a science of complexity. One of the largest contributors to
the complexity is that information overload represents only the tip of the iceberg—
only that information that has been rendered explicit. KM must also deal with the
yet to be articulated or tacit knowledge. To further complicate matters, we may not
even be aware of all the tacit knowledge that exists—we may not know that we don’t
know. Maynard Keynes (in Wells 1938, 6) hit upon a truism when he stated “these
. . . directive people who are in authority over us, know scarcely anything about the
business they have in hand. Nobody knows very much, but the important thing to
realize is that they do not even know what is to be known.” Though he was addressing politics and the economic consequences of peace, today’s organizational leaders
have echoed his words countless times.
24
Chapter 1
In fact, we are now entering the third generation of knowledge management, one
devoted to content management. In the first generation, the emphasis was placed on
containers of knowledge or information technologies in order to help us with the
dilemma exemplified by the much quoted phrase “if only we knew what we know”
(O’Dell and Grayson 1998). The early adopters of KM, large consulting companies that
realized that their primary product was knowledge and that they needed to inventory
their knowledge stock more effectively, exemplified this phase. A great many intranets
and internal knowledge management systems were implemented during the first KM
generation. This was the generation devoted to finding all the information that had
up until then been buried in the organization with commonly produced by-products
encapsulated as reusable best practices and lessons learned.
Reeling from information overload, the second generation swung to the opposite
end of the spectrum, to focus on people; this could be phrased as “if only we knew
who knows about.” There was growing awareness of the importance of human and
cultural dimensions of knowledge management as organizations pondered why the
new digital libraries were entirely devoid of content (i.e., information junkyards) and
why the usage rate was so low. In fact, the information technology approach of the
first KM generation leaned heavily toward a top-down, organization-wide monolithic
KM system. In the second generation, it became quite apparent that a bottom-up or
grassroots adoption of KM led to much greater success and that there were many
grassroots movements—which were later dubbed communities of practice. Communities
of practice are good vehicles to study knowledge sharing or the movement of knowledge throughout the organization to spark not only reuse for greater efficiency but
knowledge creation for greater innovation.
The third stage of KM brought about an awareness of the importance of content—
how to describe and organize content so that intended end users are aware it exists,
and can easily access and apply this content. This phase is characterized by the advent
of metadata to describe the content in addition to the format of content, content
management, and knowledge taxonomies. After all, if knowledge is not put to use to
benefit the individual, the community of practice, and/or the organization, then
knowledge management has failed. Bright ideas in the form of light bulbs in the pocket
are not enough—they must be plugged in and this can only be possible if people know
what there is to be known, can find it when they need, can understand it, and, perhaps
most important, are convinced that this knowledge should be put to work. A
slogan for this phase might be something like: “taxonomy before technology” (Koenig
2002, 3).
Introduction to Knowledge Management
25
KM for Individuals, Communities, and Organizations
Knowledge management provides benefits to individual employees, to communities
of practice, and to the organization itself. This three-tiered view of KM helps emphasize why KM is important today (see figure 1.6).
For the individual, KM:
•
Helps people do their jobs and save time through better decision making and
problem solving
•
Builds a sense of community bonds within the organization
•
Helps people to keep up to date
•
Provides challenges and opportunities to contribute
For the community of practice, KM:
•
Develops professional skills
•
Promotes peer-to-peer mentoring
•
Facilitates more effective networking and collaboration
•
Develops a professional code of ethics that members can adhere to
•
Develops a common language
For the organization, KM:
•
Helps drive strategy
•
Solves problems quickly
•
Diffuses best practices
•
Improves knowledge embedded in products and services
•
Cross-fertilizes ideas and increases opportunities for innovation
•
Enables organizations to better stay ahead of the competition
•
Builds organizational memory
Communities
Containers
Content
Figure 1.6
Summary of the three major components of KM
26
Chapter 1
Some critical KM challenges are to manage content effectively, facilitate collaboration, help knowledge workers connect, find experts, and help the organization to learn
to make decisions based on complete, valid, and well-interpreted data, information,
and knowledge.
In order for knowledge management to succeed, it has to tap into what is important
to knowledge workers, what is of value to them and to their professional practice as
well as what the organization stands to gain. It is important to get the balance right.
If the KM initiative is too big, it risks being too general, too abstract, too top-down,
and far too remote to catalyze the requisite level of buy-in from individuals. If the KM
initiative is too small, however, then it may not be enough to provide sufficient interaction between knowledge workers to generate synergy. The KM technology must be
supportive and management must commit itself to putting into place the appropriate
rewards and incentives for knowledge management activities. Last but not least, participants need to develop KM skills in order to participate effectively. These KM skills
and competencies are quite diverse and varied, given the multidisciplinary nature of
the field, but one particular link is often neglected, and that is the link between KM
skills and information professionals’ skills. KM has resulted in the emergence of new
roles and responsibilities. Many of these new roles can benefit from a healthy foundation from not only information technology (IT) but also information science. In fact,
KM professionals have a crucial role to play in all processes of the KM cycle, which is
described in more detail in chapter 2.
Key Points
•
KM is not necessarily something completely new but has been practiced in a wide
variety of settings for some time now, albeit under different monikers.
•
Knowledge is more complex than data or information; it is subjective, often based
on experience, and highly contextual.
•
There is no generally accepted definition of KM, but most practitioners and profes-
sionals concur that KM treats both tacit and explicit knowledge with the objective of
adding value to the organization.
•
Each organization should define KM in terms of the business objective; concept
analysis is one way of accomplishing this.
•
KM is all about applying knowledge in new, previously unencumbered or novel
situations.
•
KM has its roots in a variety of different disciplines.
Introduction to Knowledge Management
•
27
The KM generations to date have focused first on containers, next on communities,
and finally on the content itself.
Discussion Points
1. Use concept analysis to clarify the following terms:
a. Intellectual capital versus physical assets
b. Tacit knowledge versus explicit knowledge
c. Community of practice versus community of interest
2. “Knowledge management is not anything new.” Would you argue that this
statement is largely true? Why or why not? Use historical antecedents to justify your
arguments.
3. What are the three generations of knowledge management to date? What was the
primary focus of each?
4. What are the different types of roles required for each of the above three
generations?
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2 The Knowledge Management Cycle
A little knowledge that acts is worth infinitely more than much knowledge that is idle.
—Kahlil Gibran (1883–1931)
This chapter provides a description of the major phases involved in the knowledge
management cycle, encompassing the capture, creation, codification, sharing, accessing, applying, and reuse of knowledge within and between organizations. Four
major approaches to KM cycles are presented from Meyer and Zack (1996), Bukowitz
and Williams (2000), McElroy (1993, 2003), and Wiig (1993). A synthesis of these
approaches is then developed as a framework for following the path that information
takes to become a valuable knowledge asset for a given organization. This chapter
concludes with a discussion of the strategic and practical implications of managing
knowledge throughout the KM cycle.
Learning Objectives
1. Describe how valuable individual, group, and organizational knowledge is captured,
created, codified, shared, accessed, applied, and reused throughout the knowledge
management cycle.
2. Compare and contrast major KM life cycle models including the Meyer and Zack,
Bukowitz and Williams, McElroy, and Wiig life cycle models.
3. Define the key steps in each process of the KM cycle and provide concrete examples
of each.
4. Identify the major challenges and benefits of each phase of the KM cycle.
5. Describe how the integrated KM cycle combines the advantages of other KM life
cycle models.
32
Chapter 2
Introduction
Effective knowledge management requires an organization to identify, generate,
acquire, diffuse, and capture the benefits of knowledge that provide a strategic advantage to that organization. A clear distinction must be made between information—
which can be digitized—and true knowledge assets—which can only exist within the
context of an intelligent system. As we are still far from the creation of artificial intelligence systems, this means that knowledge assets reside within a human knower—not
the organization per se. A knowledge information cycle can be envisioned as the route
that information follows in order to become transformed into a valuable strategic asset
for the organization via a knowledge management cycle.
One of the major KM processes identifies and locates knowledge and knowledge
sources within the organization. Valuable knowledge is then translated into explicit
form, often referred to as codification of knowledge, in order to facilitate more widespread dissemination. Networks, practices, and incentives are instituted to facilitate
person-to-person knowledge transfer as well as person–knowledge content connections in order to solve problems, make decisions, or otherwise act based on the best
possible knowledge base. Once this valuable, field-tested knowledge and know-how is
transferred to an organizational knowledge repository, it is said to become part of
corporate memory. This is sometimes also referred to as ground truth.
As was the case with a generally accepted definition of KM, a similar lack of consensus exists with respect to the terms used to describe the major steps in the KM
cycle. Table 2.1 summarizes the major terms found in the KM literature.
However, upon closer inspection, the differences in term definitions are not really
that great. The terms used differ, but there does appear to be some overlap with regard
to the different types of steps involved in a KM cycle. To this end, four models were
selected as they met the following criteria:
•
Implemented and validated in real-world settings
•
Comprehensive with respect to the different types of steps found in the KM
literature
•
Included detailed descriptions of the KM processes involved in each of the steps
These four KM cycle approaches are from Meyer and Zack (1996), Bukowitz and
Williams (2000), McElroy (1999, 2003), and Wiig (1993).
The Knowledge Management Cycle
33
Table 2.1
A comparison of key KM cycle processes
Wiig (1993)
McElroy (1999)
Rollet (2003)
Bukowitz and
Williams (2000)
Meyer and
Zack (1996)
Creation
Individual and group
learning
Planning
Get
Acquisition
Sourcing
Knowledge claim
validation
Creating
Use
Refinement
Compilation
Information acquisition
Integrating
Learn
Store/retrieve
Transformation
Knowledge validation
Organizing
Contribute
Distribution
Dissemination
Knowledge integration
Transferring
Assess
Presentation
Application
Maintaining
Build/sustain
Value realization
Assessing
Divest
Major Approaches to the KM Cycle
The Meyer and Zack KM Cycle
The Meyer and Zack KM cycle is derived from work on the design and development
of information products (Meyer and Zack 1996). Lessons learned from the physical
products cycle can be applied to the management of knowledge assets. Information
products are broadly defined as any information sold to internal or external customers such as databases, news synopses, customer profiles, and so forth. Meyer and
Zack (1996) propose that research and knowledge about the design of physical
products can be extended into the intellectual realm to serve as the basis for a KM
cycle.
This approach provides a number of useful analogies such as the notion of a product
platform (the knowledge repository) and the information process platform (the knowledge refinery) to emphasize the notion of value-added processes required in order to
leverage the knowledge of an organization. The KM cycle consists primarily of creating
a higher value-added knowledge product at each stage of knowledge processing. For
example, a basic database may represent an example of knowledge that has been
created. Value can then be added by extracting trends from these data. The original
information has been repackaged to now provides trend analyses that can serve as the
basis for decision making within the organization. Similarly, competitive intelligence
can be gathered and synthesized in order to repackage raw data into meaningful,
interpreted, and validated knowledge that is of immediate value to users, that is, it
can be put into action directly. Yet another example is a news gathering service that
34
Chapter 2
summarizes or repackages information to meet the needs of distinct individuals
through profiling and personalization value-added activities.
Meyer and Zack echoed other authors in stressing “the importance of managing
the evolution and renewal of product architecture for sustained competitive success
. . . different architectures result in different product functionality, cost, quality and
performance. Architectures are . . . a basis for product innovation” (Meyer and Zack
1996, 44). Research and knowledge about the design of physical information products
can inform the design of a KM cycle. In Meyer and Zack’s approach, the interfaces
between each of the stages are designed to be seamless and standardized. Experience
suggests the critical importance of specifying internal and external user interfaces in
order to do so.
The Meyer and Zack KM cycle processes are composed of the technologies, facilities,
and processes for manufacturing products and services. He suggests that information
products are best viewed as a repository comprising information content and structure.
Information content is the data held in the repository that provides the building
blocks for the resulting information products. The content is unique for each type of
business or organization. For example, banks have content relating to personal and
commercial accounts, insurance companies hold information on policies and claims,
and pharmaceutical companies have a large body of scientific and marketing knowledge around each product under design or currently sold.
In addition to the actual content, the other important elements to consider are the
overall structure and approach as to how the content is stored, manipulated, and
retrieved. The information unit is singled out as the formally defined atom of information to be stored, retrieved, and manipulated. This notion of a unit of information is
a critical concept that should be applied to knowledge items as well. A focus at the
level of a knowledge object distinguishes KM from document management. While a
document management system (DMS) stores, manipulates, and retrieves documents
as integral wholes, KM can easily identify, extract, and manage a number of different
knowledge items (sometimes referred to as “knowledge objects”) within the same
document. The unit under study is thus quite different—both in nature and scale. This
again links us back to the notion that KM is not about the exhaustive collection of
voluminous content but rather more selective sifting and modification of existing
captured content. The term often used today is “content management systems.”
Different businesses once again make use of unique meaningful information units.
For example, a repository of financial statements is held in Mead’s Data System Lexis/
Nexis and the footnotes can be defined as information units. A user is able to select
a particular financial statement for analysis based on key attributes of the footnotes.
The Knowledge Management Cycle
35
An expertise location system may have, as knowledge objects, the different categories
of expertise that exist within that organization (e.g., financial analysis) and these
attributes are used to search for, select, and retrieve specific knowledgeable individuals
within the company.
A well-designed repository will include schemes for labeling, indexing, linking, and
cross-referencing the information units that together comprise its content. Although
Meyer and Zack (1996) specifically address information products, their work is more
broadly applicable to knowledge products as well . Whereas knowledge does indeed
possess unique attributes not found in information (as discussed in chapter 1), this
does not necessitate adopting a tabula rasa approach and reinventing decades of tried,
tested, and true methods. This is especially true when managing explicit knowledge
(formal, codified), which has the greatest similarity to information management. In
the case of tacit knowledge, new management approaches need to be used, but these
should, once. again, build on solid content management processes.
The repository becomes the foundation upon which a firm creates its family of
information and knowledge products. This means that the greater the scope, depth,
and complexity, the greater the flexibility for deriving products and thus the greater
the potential variety within the product family. Such repositories often form the first
kernel of an organizational memory or corporate memory for the company. A sample
repository for a railway administration organization is shown in figure 2.1.
Meyer and Zack analyzed the major developmental stages of a knowledge repository
and these stages were mapped on to a KM cycle consisting of acquisition, refinement,
storage/retrieval, distribution, and presentation/use. Meyer and Zack refer to this as
the “refinery.” Figures 2.2 and 2.3 summarize the major stages in the Meyer and Zack
cycle.
Acquisition of data or information addresses the issues regarding sources of raw
materials such as scope, breadth, depth, credibility, accuracy, timeliness, relevance,
cost, control, exclusivity, and so on. The guiding principle is the well-known adage
of “garbage in garbage out,” that is, source data must be of the highest quality, otherwise the intellectual products produced downstream will be inferior.
Refinement is the primary source of added value. This refinement may be physical
(e.g., migrating form one medium to another) or logical (restructuring, relabeling,
indexing, and integrating). Refining also refers to cleaning up (e.g., sanitizing content
so as to ensure complete anonymity of sources and key players involved) or standardizing (e.g., conforming to templates of best practice or lessons learned as used within
that particular organization). Statistical analyses can be performed on content at this
stage to conduct a meta-analysis (e.g., a high-level summary of key themes, or patterns
36
Chapter 2
What’s new
Actions
Repository
administration
Head office
Regions
Links
Reports
Upcoming events
Safety related news
Simple search
One critical, 96 hurt as Amtrak train derails in…
Advanced search
Latest accident reports
New publications
Help
New members
Glossary
Figure 2.1
Example screen for a repository
Product family
Content
Packaging format
Access distribution
Interactivity
Repository
Content
Structure
Acquisition
Refinement
Storage
retrieval
Figure 2.2
High-level view of the Zack Information Cycle
Distribution
Users
Sources
Product platform
Presentation
37
Repository
of research
results
Acquire
Refine
Calls and
surveys
Analyze,
interpret, report
Reports
newsletters
bulletins
Users
Sources
The Knowledge Management Cycle
Store
Distribute
Present
Indexed and
linked
knowledge units
Online via Web
and groupware
Interactive
selection of
knowledge units
Edit and format
Decompose into
k units, index,
and link
Figure 2.3
Detailed view of the Zack Information Cycle
found in a collection of knowledge objects). This stage of the Meyer and Zack cycle
adds value by creating more readily usable knowledge objects and by storing the
content more flexibly for future use.
Storage/retrieval forms a bridge between the upstream acquisition and refinement
stages that feed the repository and downstream stages of product generation. Storage
may be physical (file folders, prin…