Contents
Preface
9
How to Get the Most Out of
this Book
11
Knowledge Management:
An Introduction
13
Introduction
Background
Understanding Knowledge
Management
Data, Information and
Knowledge
Towards Sustainable
Competitive Advantage
Framing a Knowledge
Strategy
Making Strategic Choices
Building Dynamic Capabilities
Implementing Knowledge
Management
Evaluating the Strategy
The Road Ahead
Managing a Knowledge
Business
Introduction
Key Features of Knowledge
Businesses
Leveraging Knowledge
Managing Knowledge Workers
The Road Ahead
The Social Dimensions of
Knowledge Management
How Knowledge Markets
Function
Building Social Networks
Nurturing Communities of
Practice
Conclusion
13
14
16
17
20
21
23
25
26
27
28
29
29
29
33
35
39
42
42
45
46
50
A to Z
Advanced Knowledge
Agent
Agile Methodology
AI
Application Service
Provider (ASP)
Argyris, Chris
Articulation
Artificial Intelligence (AI)
ASP
Asynchronous Communication
Automated Decision Making
Autonomy
Ba
Benchlearning
Benchmarking
Best Practices
BI
Blog
Brand Knowledge
Browser
Bulletin Board
Business Intelligence (BI)
51
51
52
52
52
52
53
54
54
54
54
55
56
57
57
58
63
63
63
64
64
64
Case Based Reasoning (CBR) 65
Causal Knowledge
66
Caves and Commons
66
Channel Integration
66
Chief Knowledge Officer (CKO) 67
CKO
68
Clusters
68
Clustering
69
Codification
69
Cognition
70
Collaborative Filtering
70
Collaborative Platform
70
Collaboration Work
71
Combination
71
Community of Interest (CoI) 71
6
Knowledge Management from A to Z
Community of Practice (CoP)
Comprehension
Concept Mapping
Condensation
Constraint-Based Systems
Content Analysis
Content Management
System (CMS)
Context Sensitivity
Cookies
CoP
Core Capabilities
Core Knowledge
Core Rigidities
Corporate Amnesia
Corporate Culture
Creative Abrasion
Customer Capital
Customer Knowledge
72
74
75
75
76
76
Data
Data Marts
Data Mining
Data Slam
Data Warehousing
Davenport, Tom
Decision Diary
Decision Making
Decision Support
Systems (DSS)
Declarative Knowledge
Deep Smarts
Defensive Reasoning
Desktop Conferencing
Dialectics
Dialogue
Digital Rights
DIKAR Model
Discussion List
Document Management
Systems
Double-loop Learning
DSS
Dynamic Capability Building
83
83
84
84
85
85
86
86
E-learning
Earl, Michael
EIS
76
77
77
78
78
78
78
79
79
80
81
81
Enterprise Information
Systems (EIS)
Epistemology
Experiential Learning
Expertise Directory
Expert Systems
Expert Work
Explicit Knowledge
Externalization
Extensible Markup
Language (XML)
Extranet
Fuzzy Logic
Garbage In Garbage
Out (GIGO)
GDSS
Genetic Algorithm Tools
Gestalt
Group Decision Support
Systems (GDSS)
Groupware
94
94
94
95
95
96
97
97
98
98
99
100
100
100
100
101
101
Hansen, Morten
HTML (Hyper Text Markup
Language)
Human Capital
103
87
88
88
88
89
89
90
90
90
91
IC
Information
Innovative Knowledge
Insight
Instant Messaging
Integration Work
Intellectual Capital (IC)
Intelligent Routing
Intention
Internalization
Intranet
105
105
105
106
106
106
107
108
108
109
109
91
92
92
92
Just-in-Case Knowledge Management
110
Just-in-Time Knowledge Management
110
93
94
94
K-Spots
Knowledge
Knowledge Acquisition
103
103
111
111
112
Knowledge Activities
113
Knowledge Archaeology
113
Knowledge Asset
113
Knowledge Audit
113
Know-bot (Knowledge Robot) 115
Know-how
115
Know-what
115
Know-why
116
Knowing-Doing Gap
116
Knowledge Base
116
Knowledge Business
117
Knowledge Centre
117
Knowledge Champions
117
Knowledge Enablers
117
Knowledge Engineers
118
Knowledge Growth
Framework
118
Knowledge Harvesting
119
Knowledge Integration
119
Knowledge Interrogators
119
Knowledge Management
Projects
119
Knowledge Mapping
120
Knowledge Markets
121
Knowledge Metrics
124
Knowledge Networking
124
Knowledge Object
125
Knowledge Packaging
125
Knowledge Product
125
Knowledge Recipe
125
Knowledge Refining
125
Knowledge Repository
126
Knowledge
Representation (KR)
126
Knowledge Sharing
128
Knowledge Utilization
128
Knowledge Value Chain
128
Knowledge Work
Management
128
Knowledge Workers
129
Knowledge Wrapper
129
KR
129
Learning History
Learning Management
System (LMS)
Learning Organization
Leonard, Dorothy
130
130
131
133
Lessons Learned
LMS
Management Information
Systems (MIS)
Market-to-Book Ratio
Maturity of Knowledge
Management
Memory
Mental Models
Mentoring
Meta Information
Middleware
Migratory Knowledge
Mind
Mind Map
MIS
Multimedia
Neural Networks
NIH
Nohria, Nitin
Nonaka, Ikujiro
Not-Invented-Here (NIH)
Object Oriented Databases
(OODBs)
OLAP
Online Analytical Processing
(OLAP)
Ontology
OODBs
Organizational Knowledge
Awareness
Organizational Knowledge
Creation
Organizational Memory
Parsing
Peer Assist
Personal Mastery
Physical Environment
Practice
Procedural Knowledge
Process
Process Networks
Productive Friction
Professional Intellect
Prusak, Laurence
133
134
135
135
135
135
136
136
136
136
137
137
137
137
137
139
141
141
141
141
142
143
143
143
143
143
144
145
146
146
147
147
147
147
148
148
149
149
150
8
Knowledge Management from A to Z
Pull System
Push Systems
150
150
Transaction Work
172
Univocality
173
Radio Frequency
Identification (RFID)
Reciprocity
Redundancy
Report Generator
RFID
Roth, George
Rules of Thumb
151
151
152
152
152
152
153
Virtual Private Network
(VPN)
Visualizing Tools
Voiceover IP
VPN
174
174
174
174
Scalability
Schools of Knowledge
Management
Scripting
Search Engine
SECI Model
Semantics
Semantic Network
Semantic Web
Senge, Peter
Service Oriented
Architecture (SOA)
Single-Loop Learning
Skyrme, David J.
SOA
Socialization
Social Capital
Social Networks
Social Networking Analysis
Social Software
Spider’s Web
Storytelling
Structural Capital
Summarization
Systems Thinking
154
Tacit Knowledge
Tag
Takeuchi, Hirotaka
Taxonomy
Team Learning
Technology
Text Mining
167
167
168
168
169
169
172
154
156
156
157
158
158
159
159
160
160
161
161
161
162
162
164
164
165
166
166
166
166
Webinar (Web Seminar)
Web Server
Web Services
Wiig, Karl
Wiki
Willpower
Wisdom
Work Ambience
Workflow Management
Tools
175
175
175
175
176
176
176
177
178
XML (Extensible Markup
Language)
179
Yellow Pages
180
Zack, Michael
181
Case Studies: Knowledge
Management in Action
182
1. McKinsey & Co
2. Pfizer
3. Kao
4. Silicon Valley
5. Toyota
6. Partners HealthCare
7. NTT DoCoMo
8. Chaparral Steel
9. Canon
10. British Petroleum (BP)
11. Buckman Laboratories
12. Nucor Steel
182
185
187
190
193
196
198
200
202
205
208
210
Knowledge Management
Mantras
213
Bibliography
221
6
Knowledge Management from A to Z
Preface
Knowledge management is an area which has interested me since the
late 1990s. Having been in academics for a long time from 1996 to 2006,
I was a natural believer in knowledge creation and sharing. This belief
was reinforced by the strong intellectual leadership provided by Mr N.
J. Yasaswy when I used to work closely with him in ICFAI. Then in
2006, I got the opportunity to head the Knowledge Management division
of Satyam, one of India’s largest software companies and a consistent
winner of the MAKE (Most Admired Knowledge Enterprises) awards.
This marked a turning point for me.
While in Satyam, I became fascinated by the challenges involved in
knowledge sharing in a large, geographically dispersed organization.
Unlike academic institutions, knowledge sharing did not come naturally
to the busy software engineers and project managers. But the positive
side of the story was Satyam’s strengths in automation and virtualization, thanks to the vision of the company’s top management, especially
Mr Ramalinga Raju, its chairman. This made it possible to use technology to scale up any knowledge management initiative quickly. I was also
fortunate to work under the direct leadership of Mr Mohan Eddy, Director and Senior Vice President, and Mr Sanjiv Varma, Vice President.
Both of them were intellectuals in their own right and knowing my academic background strongly encouraged me to work on a compact but
useful book on knowledge management. That is how this book saw the
light of the day.
Working on this book was a great experience as I was a complete
novice in many of the technologies used in knowledge management. I
would like to thank Arun Khan who is currently with the Satyam School
of Leadership for supporting me with the research work involved in this
project. I would also like to thank all my erstwhile Satyam colleagues,
especially Vira Komarraju and Uma Thomas for their encouragement.
And last but not the least, Kapil Malhotra of Vision Books for all the
support in making this book a reality.
I dedicate this book to my mentor and PhD supervisor, Prof A. Vidyadhar Reddy, Dean, Osmania University, who is a great human being
and most passionate about learning . Prof Reddy is currently recuperating from a major surgery. I pray to God, along with his many well wishers, to help him recover quickly and keep guiding the academic community in its various endeavors.
A. V. VEDPURISWAR
8
Knowledge Management from A to Z
How to Get the Most Out of This
Book
Alphabetization:
All entries are alphabetized by letter rather than by
word so that multiple-word terms are treated as single words. In cases
where abbreviations or acronyms are more commonly used than full
terms, they are given as entries in the main text. For example, XML is
more commonly used than EXTENSIBLE MARKUP LANGUAGE, and so the
concept is explained under XML. Where a term has several meanings, the
various meanings are given.
Cross References:
To offer a fuller understanding of a concept, sometimes it is both necessary and useful to refer to some other related entries
in the book as well. Such cross references are printed in SMALL
CAPITALS.
Italics
have been used to indicate titles of publications, books, journals,
etc.
Parentheses:
Parentheses have sometimes been used in entry headings
to indicate that an abbreviation is as commonly used as the term itself;
for example, BUSINESS INTELLIGENCE (BI).
Examples, Illustrations and Tables:
This book contains numerous examples to help you better understand a concept, or to relate it to the real
business world. Illustrations and tables are also given at many places
along with their related entries.
Knowledge Management: An Introduction
Introduction
As the foundation of today’s global economy moves away from natural
resources to intellectual assets, knowledge has increasingly become the
only basis for a competitive advantage that can be sustained. Rather than
land, labor or capital it is knowledge that is the key factor of production
in many industries. In this “third wave,”1 the wealth system is increasingly based on thinking, knowing — and serving customers by way of
providing them a unique experience. Companies need superior
knowledge to leverage their traditional resources and capabilities in new
and distinctive ways to serve their customers. And they must do this
more effectively compared to competitors. As a result, knowledge management (KM) is being taken seriously by companies across industries.
Information technology (IT) has been a major driver of knowledge
management in recent times. But knowledge management should not be
equated with information technology. It is human beings who think,
experiment and learn to create knowledge. Much of the valuable
knowledge that lies in people’s brains and minds can be best shared
through human interaction. Information technology is only an enabler,
though in the words of famous journalist, Thomas A. Stewart, “It is one
hell of an enabler”. Without information technology, would be quite
difficult to replicate and distribute knowledge related documents in a
cost effective way across an organization that is largely geographically
dispersed. As Stewart mentions,2 “knowledge management is knowing
what we know, capturing and organizing it, and using it to produce re-
1
A term coined by Alvin Toffler.
Stewart, Thomas, A., The Wealth of Knowledge: Intellectual Capital and
the Twenty-first Century Organization, Currency Books, 2003.
2
10
Knowledge Management from A to Z
turns. Nothing in that definition says anything about computers but
modern knowledge management is inconceivable without using them
and in some sense they created it.”
A final point before we get into more details is that knowledge management should not be looked upon as a new mantra that can produce a
magical impact on the functioning of an organization. Organizations
need to take a practical, hard-nosed perspective when it comes to managing knowledge. Like any other initiative, knowledge management activities will build momentum only if they generate business value. That in
turn is possible only if knowledge management helps the organization to
cut costs by improving efficiency, or to innovate and come up with new
products / services.
Background
Development and sharing of knowledge started from the time God
brought man to this world. For millions of years, human beings had limited ways of passing knowledge to the next generation. Apart from oral
narratives, knowledge died with each dying person and each dying generation. Fortunately, the pace of change was so slow that it did not really
matter. As Alvin Toffler mentions in his book, Revolutionary Wealth, a
major breakthrough occurred about 35,000 years ago when someone
drew the first pictograph on a cave wall to mark an important event. The
next turning point in knowledge sharing came when man learnt to write,
enabling future generations to access the knowledge of earlier generations. The invention of the printing press, which allowed copies of a
document to be made and distributed cost-effectively, was another watershed event. And lately, information technology in general and the
Internet in particular have given a new momentum to knowledge management.
When we go through history books, we notice that knowledge as a
subject, including knowing and the reasons for knowing, was documented by Western philosophers for millennia, and undoubtedly, long before
that as well. Since ancient times, Eastern philosophers too have emphasized knowledge and understanding for conducting both spiritual and
material life. The Hindu religion, for example, has laid great emphasis
on gaining knowledge. Along with these efforts directed towards theoretical and abstract understanding of knowledge, practical needs for expertise and operational understanding have also been important since the
battle for survival first started.
Managing practical knowledge was implicit and unsystematic at first.
Later, it became more systematic. The craft-guilds and apprentice systems of the 13th century, were based on systematic and pragmatic
knowledge management considerations. So also was the way owners of
family businesses passed on their commercial acumen to their children.
Still, the practical concerns for knowledge and the theoretical and abstract perspectives were not integrated then.
There was little change in the need for putting knowledge to practical
use until the industrial revolution changed the economic landscape in the
17th century. The introduction of factories and the need for systematic
specialization, gave an impetus to knowledge. Still, knowledge management was largely based on traditional approaches such as a master
training an apprentice. Meanwhile, schools and universities mostly focused on providing education for the elite. Knowledge was approached
from a largely theoretical perspective with little effort directed at leveraging it for making products and services needed by society.
All this has changed in recent times. Today knowledge management
is increasingly being looked at from a business perspective. Many organizations have put in place systems and processes for managing
knowledge to cut costs or differentiate their products and services. At the
same time, there is a growing belief that intellectual development plays a
key role in motivating workers and making them more productive in the
workplace. As Peter Senge has mentioned, people in general have a natural desire to learn. Thus knowledge management can be seen as one
more step in the evolution of the move towards personal and intellectual
freedom that started with the age of enlightenment and reason a few centuries go.
In the years to come, knowledge management will increasingly be an
integral part of corporate strategy for the following reasons:
12




Knowledge Management from A to Z
Knowledge management helps avoid unnecessary work duplication,
expensive reinvention of the wheel and repetition of mistakes. In other words, knowledge management improves productivity.
Knowledge management softens the blow when talented people leave
the firms by ensuring that most, if not all, of their knowledge is captured in the company’s systems and processes.
Knowledge management improves the agility of the firm by helping
it to understand and react to the environment better.
Knowledge management can compress delivery schedules and reduce
cycle time through reuse of components.
Understanding Knowledge Management
What exactly do we mean by knowledge management? Knowledge
management does not have the same meaning across organizations.
Some companies focus on knowledge sharing among individuals or on
building elaborate educational and learning capabilities. Others emphasize the use of technology to locate, capture, manipulate and distribute
knowledge. A few others focus on knowledge utilization to improve the
enterprise’s operational and overall effectiveness. Still others pursue
building and exploiting intellectual capital (IC) to enhance the enterprise’s economic value and generate sustainable competitive advantage.
(See also: SCHOOLS OF KNOWLEDGE MANAGEMENT)
Notwithstanding such different approaches, in a broad sense
knowledge management is the systematic and explicit management of
knowledge-related activities, practices, programs, and policies within an
enterprise. The goal of knowledge management is to build and exploit
knowledge assets effectively and gainfully. The key challenge in
knowledge management is to leverage the knowledge of individuals for
the benefit of the organization. By systematically mapping, categorizing,
and benchmarking organizational knowledge, knowledge management
makes knowledge more accessible throughout an organization. A systematic approach to managing knowledge also helps a company prioritize knowledge and builds a “critical learning mass” around particular
strategic areas of knowledge. This enables the company to strengthen its
core capabilities and compete more effectively in the market place.
As Amrit Tiwana notes,3 “knowledge management enables the creation, distribution and exploitation of knowledge to create and retain
greater value from core businesses competencies. Knowledge management addresses business problems particular to your business — whether
it is creating and delivering innovative products or services, managing
and enhancing relationships with customers, partners and suppliers or
improving work processes. The primary goal of knowledge management
in a business context is to facilitate opportunistic application of fragmented knowledge through integration.”
Data, Information and Knowledge
“Data”, “information” and “knowledge” are three different terms. Understanding what they stand for, and how they differ, is the starting point
in knowledge management.
DATA
Data is a set of discrete, objective facts about events4. Data can be
viewed as structured records of transactions.
People gather data because it is factual and generates a feeling of
scientific accuracy. They think that if enough data is available, objectively correct decisions will automatically follow. But as Davenport and
Prusak have pointed out, this is false on two counts. First, too much data
can confuse us and make it harder to make sense of a situation. Second,
there is no inherent meaning in data. As it provides no judgment or interpretation, data cannot tell us what to do. Despite these limitations,
data is important for any organization because it is what gives rise to
information.
Data management is typically evaluated in terms of cost, speed, and
capacity. How much does it cost to store or retrieve data? How soon can
we get it into the system or retrieve it? How much is the storage capacity? Qualitative measurements are timeliness, relevance, and clarity. Do
3
In his book, The Knowledge Management Toolkit: Orchestrating IT,
Strategy, and Knowledge Platforms, Prentice Hall, 2002.
4
www.acm.org/ubiquity/book/t_davenport_1.html
14
Knowledge Management from A to Z
we have access to it when we need it? Is it what we need? Can we make
sense out of it?
INFORMATION
Information is a message meant to change the way the receiver perceives
something and have an impact on his judgment and behavior. Information is data that makes a difference .
We transform data into information by adding value in various ways5:

Contextualizing: Understanding for what purpose the data was gathered.

Categorizing:
Knowing the units of analysis or key components of the
data.



Calculating:
Analyzing the data mathematically or statistically.
Correcting: Removing errors from the data.
Condensing: To make the data available in a more concise, user
friendly form.
Information moves around organizations through hard and soft networks6. Hard networks refer to visible and definite infrastructure such as
electronic mailboxes. Soft networks are less formal and visible and more
ad hoc. When a colleague sends a note or a copy of an article marked
“FYI”, or when two people exchange notes at the water cooler or cafeteria, the soft network is in operation.
Quantitative measures of information management focus on the degree of connectivity and the number of transactions:





5
How many downloads are taking place daily?
How many messages do we send in a given period? 7
Qualitative measures focus on the depth and usefulness of information.
Does the message give us some new insight?
Does it help make sense of a situation and contribute to decision
making or problem solving?
See Working Knowledge, by Tom Davenport & Larry Prusak, HBS
Press, 1998.
6
www.acm.org/ubiquity/book/t_davenport_1.html
7
www.acm.org/ubiquity/book/t_davenport_1.html
KNOWLEDGE
It is important to understand what knowledge is and what it does because
too often organizations focus all their efforts on data and / or information
management alone. In the process, the unique dimensions of knowledge
are completely ignored. For example, an excessive focus on information
technology effectively converts knowledge management into information management. As we shall see later, the organizations that have
the most effective knowledge management processes, synergize information technology and human networks to give a boost to knowledge
creation and sharing.
Knowledge is broader, deeper and richer than data or information.
Information becomes knowledge, through1:




Comparison:
How does information about this situation compare with
other situations?
Consequences: What implications does the information have for
decisions and actions?
Connections: How does this bit of knowledge relate to others?
Conversation: What do other people think about this information?
Because knowledge is more actionable, it is more valuable than either
data or information. Better knowledge leads to improved productivity or
lower cost and facilitates better decisions.
Knowledge develops over time, through experience which provides a
historical perspective from which to view and understand new situations
and events. Experience helps us recognize familiar patterns and make
connections between what is happening now and what happened in the
past. Experience changes the focus from what should happen into what
does happen. Knowledge is much more than a recipe to deal with routine
situations. When we become knowledgeable people we see some patterns even in new situations and can respond appropriately. We don’t
have to start from scratch every time.
There are two kinds of knowledge — explicit and tacit. Explicit
knowledge can be codified and transmitted formally and systematically
8
In their well known book, Working Knowledge, Harvard Business
School Press, 1998.
16
Knowledge Management from A to Z
through documents, databases, intranet, email, etc. Tacit knowledge is
difficult to encode, formalize or articulate. It is personal and context specific. Tacit knowledge is shared and developed by observation and practice, through a process of trial and error.
Though, it may appear that data, information and knowledge lie on a
continuum, there are discontinuities that make knowledge fundamentally
different from information. The discontinuity between information and
knowledge is caused by how knowledge is created from newly received
information. New insights are typically internalized by establishing links
with already existing knowledge, which helps us make sense of received
information. Hence new knowledge is as much a function of prior
knowledge as it is of received inputs. In short, data can be “processed”
into information, say by using computers, but information cannot be
“processed” into knowledge in a similar manner. The human factor plays
a critical role in the conversion of information into knowledge.
Knowledge provides us with the ability to handle different situations
and to anticipate implications, judge their effects and improvise. Unlike
data and information, knowledge can judge new situations in light of
what is already known and also judge and refine itself in response to
new situations. Knowledge is like a living system that grows and changes as it interacts with the environment.
By helping us deal with complexity, knowledge provides value. As
Davenport and Prusak point out1, it is tempting to look for simple answers to complex problems and deal with uncertainties by pretending
they don’t exist. Knowing more usually leads to better decisions than
knowing less, even if the “less” seems clearer and more definite. Certainty and clarity may seem convenient but they often come at the price
of ignoring key factors.
Towards Sustainable Competitive Advantage
Knowledge is a particularly valuable asset. Among all assets, it is the
one most likely to lead to a sustainable competitive advantage. The economics of knowledge is different from that of other assets. The cost of
9 http://web.cba.neu.edu/~mzack/articles/kstrat/kstrat.htm
producing knowledge is little affected by how many people eventually
use it.
Knowledge also provides increasing returns. Unlike traditional physical goods that are consumed as they are used (providing decreasing returns over time), knowledge provides increasing returns as it is used. The
more it is used, the more valuable it becomes, creating a self reinforcing
cycle1.
Unlike other assets, knowledge is difficult to replicate. Knowledge,
especially context-specific, tacit knowledge, tends to be unique and difficult to imitate and cannot be easily purchased in the marketplace. To
get hold of such knowledge, competitors have to go through similar
experiences. This can take time. Merely making heavy investments in
technology, systems or processes may not accelerate the learning.
Knowledge-based competitive advantage is also sustainable because
a firm that already knows is better placed to learn1. As Michael Zack
has put it, learning opportunities for an organization that already has a
knowledge advantage may be more valuable than for competitors having
similar learning opportunities but which are starting off knowing less.
Sustainability also results when an organization already knows something that uniquely complements newly acquired knowledge. The new
knowledge can then be combined with existing knowledge to develop
unique insights and create even more valuable knowledge.
Framing a Knowledge Strategy1
The starting point in knowledge management is framing a knowledge
strategy. Knowledge strategy effectively means identifying and developing the knowledge required for providing products or services to customers more effectively than competitors do. Identifying which
knowledge based resources and capabilities are valuable, unique, and
10 http://web.cba.neu.edu/~mzack/articles/kstrat/kstrat.htm
11
This and the following sections drawn heavily from the article, “Developing a Knowledge Strategy” by Michael Zack, California Management
Review, Spring 1999, pp. 125-145.
12
Toffler, Alvin and Toffler, Heidi, Revolutionary Wealth, Knopf, 2006.
18
Knowledge Management from A to Z
inimitable as well as how those resources and capabilities support the
firm’s competitive position form the essence of a knowledge strategy.
The strategic choices that a company makes regarding technologies,
products, services, markets and processes determine what kind of
knowledge is required to compete and excel in an industry. On the other
hand, what a firm does know, limits the ways in which it can actually
compete.
A firm must realign its strategy with its capabilities. Alternatively, it
must make the necessary investments to acquire the capabilities to execute its strategy. Knowledge management initiatives should be directed
towards acquiring these capabilities. This alignment of business strategy
and knowledge lies at the heart of a firm’s knowledge strategy.
World class organizations such as the consulting firm, McKinsey
drive knowledge management by having what is called a knowledge
agenda which identifies knowledge gaps and how they must be dealt
with. But pinpointing the knowledge that an organization must build is
not easy. There are no simple answers regarding what a firm must know
to be competitive. Indeed, if the answers were so easy, knowledge would
not yield a sustainable advantage. The trick is to stay in touch with customers, understand what competitors are doing, develop a broad vision
of how the business environment is likely to evolve in the long run, and
the kind of knowledge capabilities that it might require.
Another point to be emphasized is that all pieces of knowledge may
not be equally valuable. Specifically, knowledge can be classified as
core, advanced, or innovative.
Core Knowledge refers to the essential, basic knowledge required to
compete in an industry. Such knowledge is held by all industry players
and therefore does not provide a sustainable competitive advantage.
Advanced Knowledge is more likely to generate sustainable competitive advantage. To take an example, there are many world class consumer electronics companies. But Sony is ahead of them because it has developed unique capabilities in miniaturization. Similarly, in the computer software industry, IBM has developed advanced knowledge of middleware.
Innovative Knowledge
is needed for a firm to significantly differentiate itself from its competitors and stay ahead of them. Innovative
knowledge often enables a firm to change the rules of the game itself. In
the automobile industry, Toyota has leapfrogged competitors with its
knowledge of just-in-time and lean production. In the PC industry, Dell
stands apart with its knowledge of the supply chain and in particular the
order fulfillment process.
Knowledge is not static. What is innovative knowledge today will
eventually become core knowledge tomorrow. Defending and strengthening a competitive position thus requires continual learning and
knowledge acquisition. It often involves unlearning as well as the situation changes. Technology may become obsolescent and customer tastes
may change. The ability of an organization to learn, accumulate
knowledge from its experiences, unlearn sometimes and reapply that
knowledge, are the building blocks of an effective knowledge strategy.
As Alvin Toffler puts it1, “Today, work-relevant knowledge changes so
rapidly that more and more new knowledge has to be learned both on
and off the job. Learning becomes a continuous flow process . . . every
chunk of knowledge has a limited shelf life. At some point, it becomes
obsolete knowledge.
Making Strategic Choices
Putting in place a well thought out knowledge strategy involves making
strategic choices.
A company must first identify the role of knowledge in its business.
How knowledge intensive is the business? What kind of knowledge is
important? Who is generating this knowledge? Who is using the
knowledge? Who is getting paid for the knowledge?
The overall approach of the organization to knowledge creation and
sharing must then be critically examined along two dimensions. The first
addresses the degree to which an organization needs to increase its
knowledge in a particular area as opposed to exploiting its existing
knowledge resources. The second dimension is whether the knowledge
13
http://web.cba.neu.edu/~mzack/articles/kstrat/kstrat.htm
20
Knowledge Management from A to Z
management initiatives are predominantly information technologycentric or people-centric.
EXPLORATION VERSUS EXPLOITATION
When knowledge is in short supply, the focus must be on exploration.
When an organization has less knowledge than is needed to execute its
strategy or to defend its position, it must develop or acquire knowledge.
Then, too, when competitors know more, the focus must be on
knowledge acquisition. If knowledge in the industry is changing rapidly,
and companies are rapidly innovating, creating new knowledge becomes
the priority. On the other hand, when available knowledge resources and
capabilities are more than adequate, the organization can further exploit
the available knowledge, possibly within or across business units and
sometimes even by entering new businesses.
Exploration creates the knowledge needed to exploit new opportunities while maintaining the viability of existing ones. Exploitation provides the financial capital to fuel successive rounds of exploration. Exploration without exploitation is not economically viable in the long run.
At the same time, after a point, exploitation without exploration will be
like trying to pump water from a dry well. So companies must strive to
maintain a balance between exploration and exploitation.
The creation of unique, strategic knowledge takes time, forcing a
firm to balance short-and long-term resource commitments. The firm
therefore must determine whether its efforts are best focused on longerterm knowledge exploration, shorter-term exploitation, or both1. Exploration and exploitation activities must be linked and coordinated to reinforce one another in a virtuous circle. Balancing exploitation and exploration requires smooth knowledge transfer across functions and business
units. Time delays between developing and applying knowledge as well
as between applying and developing the next round of knowledge should
be minimized. This requires a culture, reward systems, and communication networks that support the smooth flow of knowledge.
14
Hansen, Morten T.; Nohria, Nitin and Tierney, Thomas, “What’s Your
Strategy for Managing Knowledge?” Harvard Business Review, MarchApril 1999, pp. 106-116.
CODIFICATION VERSUS
PERSONALIZATION
A second issue is whether a knowledge strategy should be centered on
information technology or person-to-person contacts. According to Hansen, Nohria and Tierney1, some companies focus on codification, i.e.,
codifying and storing knowledge in databases for easy access by people
across the organization. In other companies, the focus is on personalization, namely, building connections among people, the role of technology
being limited to facilitating such connections and to helping people
communicate this knowledge.
The choice between codification and personalization should be driven by a company’s business strategy. Codification is recommended
when the business needs to reuse knowledge assets effectively. For example, information technology consulting firms like Accenture use codification to provide high quality, reliable and fast information technology
solutions to their clients. In contrast, where customized solutions have to
be provided as in strategy consulting, personalization is preferable.
Mckinsey is a good example. As Hansen, Nohria and Tierney put it, “A
company’s knowledge management strategy should reflect its competitive strategy: how it creates value for customers, how that value supports
an economic model and how the company’s people deliver on the value
and the economics.” Thus companies that pursue an assemble-to-order
or service strategy may be better off with codification. Those that provide highly customized product / service offerings or a product innovation strategy may find it useful to pursue personalization. Companies
that have an effective knowledge management strategy predominantly
pursue one of the two strategies and use the second to support the first.
Hansen, Nohria and Tierney call it the 80-20 split. Companies should
not get stuck in the middle. Trying to do both in equal amounts will fail
to produce desired results. Just as a firm should either pursue cost leadership or differentiation, similarly it must make a strategic choice between codification and personalization.
15
http://hbswk.hbs.edu/archive/4778.html
22
Knowledge Management from A to Z
Firms focused on exploiting internal knowledge exhibit the most
conservative knowledge strategy. Those who closely integrate
knowledge exploration and exploitation without regard to organizational
boundaries represent the most aggressive strategy. In knowledgeintensive industries, in cases where a firm’s knowledge significantly lags
its competitors or where the firm is defending a knowledge position, an
aggressive knowledge strategy is needed. In mature industries where
technology is not changing much, a conservative strategy may make
sense.
Building Dynamic Capabilities
In their interesting book, The Only Sustainable Edge, John Hagel III and
John Seely Brown point out that the paradigm for knowledge creation
and sharing is undergoing major changes. Companies must not only be
able to exploit fully their internal capabilities to differentiate themselves
in the market place but also mobilize the resources of other companies to
deliver greater value to customers1. As customers become more demanding, the knowledge within the firm may not be adequate. At the
same time, if the company does not have unique specialized knowledge,
it will be difficult to mobilize knowledge from outside. As the authors
point out,1 “. . . distinct capabilities remain the basis of strategy but must
rapidly evolve among collaborators to remain a source of strategic advantage. The competitive edge ultimately depends on a firm’s institutional capacity to rapidly deepen its distinctive capabilities and to accelerate learning across enterprise boundaries, rather than simply mobilizing static resources.” Hagel III and Seely Brown emphasize that companies must look for areas with the greatest potential for specialization and
learning. They must closely watch the edges of business activity for this
kind of capability building. Edges refer to the interfaces between enterprises, between industries / markets, between nations and between gen16
Hagel, John III and Brown, John Seely, The Only Sustainable Edge —
Why Business Strategy Depends on Productive Friction and Dynamic Specialization, Harvard Business School Press, 2005.
17
This essay draws heavily from the article, “Knowledge-Intensive
Firms” by Raimo Nurmi, Business Horizons, May-June 1998.
erations of customers. Companies must strike a balance between their
core businesses and these edges which is where the potential to innovate
and create value is maximum. Resources and opportunities emerging on
the edge must be tapped to amplify the existing core capabilities.
Implementing Knowledge Management
It may be difficult to introduce knowledge management across the organization in one go. One way to kick-start knowledge management
activities in an organization is to launch short burst knowledge management initiatives. Typically, they may involve creating an intranet, creating knowledge repositories, setting up data warehouses, decision support
tools, implementing groupware, helping knowledge workers come together and mapping internal expertise. Successful knowledge management projects aim at solving a problem that is crying for a solution.
The right project to launch can be determined only after thoroughly
examining the key knowledge processes in a business. Some involve the
creation of knowledge; R&D is a good example. Others involve the
sharing of knowledge. Other processes may involve discovering / finding knowledge (market research), applying knowledge (after sales service), or reusing knowledge (a school teacher).
Broadly speaking, knowledge management initiatives can focus on
either knowledge creation, or knowledge sharing, or both. Knowledge
creation, is largely about innovation. There is plenty of literature on
managing the innovation process. We will not go into the details here
except for pointing out that innovation is as much about developing specialized expertise as about culture. If the culture does not encourage experimentation and risk taking, innovation will not really take off, even if
the organization has the most talented people.
Knowledge sharing initiatives must be tightly linked to the company’s business processes and what people need to know to do their jobs
effectively. The right questions to ask are: What are the jobs people are
trying to get done? What is the knowledge base required? Customers can
also be asked what they expect the company to know.
Knowledge sharing initiatives can take various shapes. A yellowpage may be a good starting point. A knowledge repository may house
24
Knowledge Management from A to Z
important documents that are frequently used. A help desk can play the
role of a librarian — guiding people around the repository, keeping the
databases up to date, etc. A bulletin board can help people place requests
so that others within the system can respond. To facilitate sharing of tacit
knowledge, a physical context may also be needed. That means providing meeting spaces and conference rooms. Suitable design of the work
place can also help by creating more opportunities for conversations on
corridors and near coffee vending machines.
Evaluating the Strategy
One problem with any strategy is that it takes time for results to come. A
knowledge strategy too might take years to implement and generate the
full benefits. In the interim, companies must use their common sense and
ask some basic questions to evaluate the strategy. Is the organization’s
intention clearly defined? Is the knowledge strategy built around the
company’s core competencies? Unless the knowledge management activities have been prioritized and the company is clear about what kind
of knowledge to go after, knowledge management will not take off. For
example, introducing the latest technology without identifying what
knowledge is beneficial to the organization is doomed to failure. Is
knowledge management tightly linked to potential improvements in the
way the company is adding value for customers? Are knowledge management activities focused on improving or streamlining the value
chain? Is the knowledge being captured or shared, helping people to do
their job more efficiently? If the company is going through a major
change initiative, can knowledge management help in revitalizing the
company? Yet, another issue is whether the culture exists for a full
blown knowledge management initiative. If cultural issues are not addressed, major knowledge management initiatives are unlikely to succeed.
The Road Ahead
Many developments are under way that will influence how knowledge
management will evolve in the coming years. These include:





Developments in information technology that allow knowledge management practices to be extended to new areas.
Greater understanding of how knowledge workers do their job.
Sharing of best practices across companies and industries.
Growing opportunities to create unique value for customers, using
knowledge.
Intensifying competition and the ongoing quest for sustainable competitive advantage.
Companies that understand the importance of knowledge and know
how to manage it systematically to improve their business performance
will emerge as market leaders of the future.
26
Knowledge Management from A to Z
Managing a Knowledge Business
Introduction
A knowledge business can be defined simply as one that leverages
knowledge to create value for its customers. Knowledge businesses convert what they know into products and services that customers find useful.
All work involves some amount of knowledge. But in a truly
knowledge business, the core activity is processing data into information
and knowledge that in turn creates value for its customers. Consulting,
training, education and research are classic examples of knowledge
businesses. But many other businesses also fall into this category, as we
shall see shortly. Indeed, it is dangerous to classify businesses as
knowledge or non-knowledge based, going by conventional stereotypes.
Even what looks like commodity businesses can be transformed into
knowledge intensive businesses with the right mindset and perspective.
Key Features of Knowledge Businesses
Knowledge businesses are different from other businesses in some important ways. Knowledge businesses are usually less capital intensive.
The interaction between the customer and the producer assumes more
importance in knowledge businesses. These businesses also tend to have
fewer layers within the organization which promotes freer flow of information between management and operations. Horizontal barriers are
also low in order to promote easier interaction and exchange of ideas
among knowledge workers. Loosely structured knowledge teams are
quite common. Such teams are formed and disbanded, based on the
needs of the situation. People in knowledge businesses tend to be highly
independent. So a high level of communication is needed to ensure the
18
Zack, Michael H., “Rethinking the Knowledge Based Organization”,
Sloan Management Review, Summer 2003, pp. 67-71.
minimum amount of coordination needed for maintaining the firm as an
integrated entity.
In capital intensive firms, strategy is often controlled and driven by
the top management and corporate headquarters. But knowledge businesses are driven by human capital and customer relationships. So the
line between strategy and operations is blurred. Market research may be
less useful in a knowledge business as customers may not be able to visualize and appreciate all the potential value adding features. So
knowledge businesses must innovate and develop products and services
in anticipation of customer needs. Products of knowledge businesses
tend to have typically shorter life cycles. Knowledge is not subject to
wear and tear. But it is vulnerable to obsolescence. So knowledge firms
must come out with better versions of existing products or radically new
products, often cannibalizing current offerings.
According to Michael Zack1, the degree to which knowledge is an
integral part of a company is defined by not what the company sells, but
by how it does so — and how it is organized. There is a common misunderstanding that some businesses are inherently more knowledge based
than others. So a research unit or a consulting firm is considered very
knowledge intensive whereas a cement manufacturer is ranked very low
on knowledge intensity: “That is a dangerous assumption . . . the focus
on products or services as a means of categorizing companies or defining the knowledge-based organization leads to a distorted image. Products or services are only what are visible or tangible to customers . . .
most of what enables a company to produce anything lies below the surface, hidden within the so-called invisible assets of the organization —
its knowledge about what it does, how it does and why.” According to
Zack, a knowledge-based organization has four characteristics — process, place, purpose and perspective.
Most organizations are focused on the day-to-day, visible operational
activities. To be considered knowledge-based, an organization must
spend enough time on applying existing knowledge and creating new
19 Zack, Michael H., “Rethinking the Knowledge Based Organization”, Sloan
Management Review, Summer 2003, pp. 67-71.
28
Knowledge Management from A to Z
knowledge. These processes are needed to ensure that knowledge from
one part of a company is applied to activities in other parts, past
knowledge is leveraged, people can locate each other and collaborate
and
experimentation and learning are actively encouraged.
Knowledge is often generated and shared as a by product of daily
interactions with customers, vendors, and other external partners. So the
boundaries of knowledge-based organizations are not only blurred, but
also keep shifting. Such organizations seek knowledge where it exists
and strike alliances with whoever can provide knowledge.
Knowledge based organizations view knowledge as a key strategic
resource and keep asking: What knowledge is needed to execute our
strategy? How much knowledge do we have? How much knowledge do
competitors have? Accordingly, such organizations make deliberate,
conscious efforts to close these knowledge gaps.
Perspective is another key attribute of knowledge based organizations. They take into account knowledge in every aspect of their operations and treat every activity as a potentially knowledge enhancing act.
Knowledge and learning became the primary criteria for evaluating how
the company is organizing itself, what it is making, who it is hiring, how
it is managing its relations with customers and so on.
Zack argues that to become a knowledge based organization, the following steps are involved1:





20
Define the organization’s mission and purpose in terms of
knowledge.
Define the organization’s industry and position within it in terms of
knowledge.
Formulate strategy with knowledge in mind.
Implement knowledge management processes and structures that
directly support the company’s key knowledge requirements.
Transform the company into a learning organization.
Davis, Stan and Botkin, Jim. “The Coming of Knowledge-based Business”, Harvard Business Review, September-October 1994, pp. 165-170.





Segment the company’s customers and markets, not only on the basis
of products and services but also according to how much can be
learned from them.
View learning as an investment, not as an expense.
Rethink the business model.
Take human resource management seriously.
Reinforce the organization’s mission through internal and external
communication.
Any business has the potential to become highly knowledge intensive. The scope to enrich products and services with knowledge is only
limited by one’s imagination. A hamburger looks like a commodity. But
there is a whole lot of information involved in the production and consumption of hamburgers. Ultimately, a hamburger is a source of nutrition. If nutrition data are presented creatively to customers, there is
scope to transform the business. For example, the calorie and fat content
can be included in the menu. Then customers can make more informed
decisions while placing orders. Soon, the company can set new benchmarks in nutrition, differentiate its products on the nutrition plank and
steal a march on competitors.
According to David Skyrme, a well known knowledge management
expert, knowledge can be embedded as a part of the product or be used
to surround the core product with complementary services. “Smart”
products have embedded knowledge that gives them a great deal of intelligence, enabling them to sense and integrate information from multiple
sources and act accordingly. A refrigerator, for instance, may send out
an alarm when the level of vegetables falls below a certain amount. Stan
Davis and Jim Botkin1 have given some more examples of smart products which filter and interpret information to enable the user to act more
effectively. A smart tire can notify a driver about the air pressure. An
intelligent garment can heat or cool in response to the temperature outside. Knowledge can also surround a product. Thus a vendor can offer
21
http://web.cba.neu.edu/~mzack/articles/kstrat/kstrat.htm
30
Knowledge Management from A to Z
consultancy services along with the basic product. Alternatively, the firm
can provide training to help customers use the product more effectively.
Davis and Botkin have identified six characteristics of knowledge
businesses:






The more knowledge-based offerings are used, the smarter they get.
The more they use knowledge-based offerings, the smarter people
get.
Knowledge based offerings adjust to changing circumstances.
Knowledge based offerings can be customized.
The offerings of these businesses have relatively short lifecycles.
These businesses enable customers to act in real time.
The Mexican cement company Cemex is a good example of how a
commodity can be converted into an information product. When Lorenzo Zambrano took over as CEO in 1968, he realized that his company
was making a perishable product, ready mix concrete for a market where
demand was far from predictable due to uncertainties in labor supply,
traffic, weather and financing. Often Cemex found itself trying to deliver
concrete to customers not yet ready to use it, even as others who desperately needed the product were starved of supply. Zambrano decided to
change the focus of the business from selling concrete to delivering concrete just-in-time to customers. Cemex committed to deliver concrete to
customers at 3 hours notice. Later, it reduced this to 20 minutes. In return, customers had to pay a small premium. Cemex put in place a mobile communications network to coordinate deliveries by trucks and production at different plants. A central scheduling and communications
centre in each region allowed Cemex to re-route trucks in real time.
Over the years, Cemex has strengthened its technology infrastructure to
deliver concrete within 20 minutes with 98% reliability. The company
even gives a discount of 5% to customers for a delay of every 5 minutes.
The knowledge Cemex has developed in Mexico in scheduling and coping with uncertain demand, has been leveraged to support the company
in several other emerging markets which have similar scheduling challenges, as in Mexico.
Leveraging Knowledge
A knowledge business has to keep tapping various knowledge sources
which may exist within or outside the firm:



Internal knowledge may be lying within individuals; embedded in
behaviors, procedures, software and equipment;
Recorded in various documents; or
Stored in databases and online repositories.
External knowledge can be accessed through publications, universities, government agencies, professional associations, personal connections,
consultants, vendors, knowledge brokers, customers and strategic alliances1.
Knowledge generated within a firm and embedded within its systems
and processes, tends to be unique, specific, and tacitly held. It is therefore more difficult for competitors to imitate*. Toyota’s just-in-time
(JIT) production is a good example. Even though so much has been written about it and so many executives from all over the world have visited
Toyota, replicating Toyota’s JIT system represents a major challenge for
rivals.
External knowledge, though more general and more widely available
to competitors, can simulate fresh thinking, generate new ideas and facilitate benchmarking, especially when combined with unique internal
knowledge.
Customer knowledge is a particularly valuable form of knowledge
gathered from outside the company. This is different from other forms of
external knowledge in that it may not be available to others. Customer
knowledge is generated in the process of engaging with customers, in
various ways. These include beta-testing, web sites, electronic mail, tollfree numbers, customer care centers, conferences, and social gatherings.
Customer knowledge is often the difference between success and
failure in many businesses. In very simple terms, if companies know
more about their customers, they can sell more to them. If customers
know more about the sellers, they would buy more. According to a lead22
Stewart, Thomas A., The Wealth of Knowledge: Intellectual Capital
and the Twenty-first Century Organization, Currency Books, 2003.
32
Knowledge Management from A to Z
ing researcher, Nick Bontis, customer capital, the knowledge buyers and
sellers have of each other, is the single most important influence on revenue per employee and profit per employee in many organizations.
Without customer capital, human capital (the expertise and competencies of people) and structural capital (expertise embedded in systems and
processes) would be highly ineffective.
Unfortunately, customer capital is handled mechanically and in
piecemeal fashion in most organizations. According to Thomas Stewart1,
different agencies are involved but they do not talk to each other. Many
companies have introduced CRM initiatives some of which go under the
high sounding name of 3600 customer view. But these approaches, relying heavily on automation, lead to a company centric view of customers.
The focus is not on creating value, but on cutting costs. Companies need
to change their mindset. Value creation must be viewed as the process of
collaboration between a buyer and a seller. According to Stewart, a fully
developed customer learning process will emphasize communication
over information mining. It will encourage a process of mutual learning.
CRM must be cross functional, cutting across various departments of the
organization and should lead to strong relationships with customers.
Managing Knowledge Workers
Ultimately, knowledge is created and shared by knowledge workers. So
knowledge based organizations should understand the nuances, subtleties and challenges involved while dealing with knowledge workers.
Despite the acknowledged importance of knowledge workers, not
enough attention has been paid to improving their performance and
productivity. In his fascinating book, Thinking For a Living, Thomas
Davenport, probably the leading knowledge management expert in the
world, has discussed at length the key challenges faced by organizations
in improving the productivity and effectiveness of knowledge workers.
Way back in 1988, Davenport’s points were covered to some extent
by Peter Drucker. Writing in the Harvard Business Review, Drucker had
23
Drucker, Peter F., “The Coming of the New Organization”, Harvard
Business Review, January-February 1988.
mentioned1: “The typical large business 20 years hence will have fewer
than half the levels of management of its counterpart today and no more
than a third the managers. So the typical business will be knowledgebased, an organization composed largely of specialists who direct and
discipline their own performance through organized feedback from colleagues, customers and headquarters”.
Drucker pointed out that as manual and clerical workers were replaced by knowledge workers, the command-and-control model would
become increasingly irrelevant. Drucker mentioned how knowledge
workers would have to be handled differently. As these workers have
specialized knowledge, they tend to be independent and cannot be told
how to do their work. Such workers tend to operate by a system of self
control according to clearly laid down expectations and feedback. Without actually saying in so many words, Drucker also explained how social
networks and informal communities of practice would play a key role in
knowledge work, “The key to such a system is that everyone asks: Who
in this organization depends on me for what information? And on whom
in turn do I depend? Each person’s list will always include superiors and
subordinates. But the most important names on it will be those of colleagues, people with whom one’s primary relationship is coordination”.
Drucker highlighted the following key management problems in information-based organizations1:




Developing rewards, recognition and career opportunities for specialists.
Creating a unified vision.
Devising the management structure for an organization of task forces.
Building a cadre of top management personnel.
Managing knowledge work is a challenge for various reasons. The
problems knowledge workers solve are novel and rarely become routine.
As just mentioned, knowledge workers don’t like to be directed. Much
of their work is difficult to structure and predict. Usually, they are better
led by example than by command and control. It is difficult to give ex24
Drucker, Peter F., “The Coming of the New Organization”, Harvard
Business Review, January-February 1988.
25
21 January 2006.
34
Knowledge Management from A to Z
plicit instructions to knowledge workers. In short, knowledge workers
cannot be managed in the traditional way.
Among knowledge workers, there are differences in the kinds of jobs
they handle. According to Davenport, there are two dimensions along
which knowledge intensive processes can be characterized — level of
interdependence, and complexity of work:




Complex work with a high degree of interdependence can be called
the collaboration model;
That with a low level of interdependence can be called the expert
model;
Routine work with a low level of interdependence can be called the
transaction model; and
That with a high degree of interdependence can be called the integration model.
Transaction work can be executed according to clearly laid down
rules. A good example is a call centre. Integration work is relatively
structured, with scope for the reuse of knowledge assets. The work of
software services companies falls in this category.
Expert work is largely done by individuals. A good example is a
doctor.
Collaboration work which involves both teamwork and individual
expertise is the most difficult to improve in a structured way, e.g. investment banking.
Like any organizational activity, knowledge work needs to be evaluated and controlled. Knowledge workers can be evaluated on the basis of
the volume of the knowledge produced, the quality of the decisions or
actions taken on the basis of their knowledge, and the impact of their
produced knowledge. The output of knowledge workers has to be measured in terms of both volume and quality. One way to measure the quality of knowledge work is to get feedback from a peer group or an expert.
Knowledge workers also do not form one homogenous group. They
cannot be controlled in the same way. Scripting may work for call centre
workers but not for others. Similarly, computer aided decision making
may be useful for physicians in some health care settings but not for
those in others. Top down reengineering may be worth trying, if at all,
only in case of lower level or relatively docile knowledge workers.
The ease of structuring, i.e. breaking down into activities and monitoring knowledge work also varies from activity to activity. In general,
knowledge creation is difficult to structure. Thus, the early stages of
product development are quite fuzzy compared to later stages where
more discipline can be imposed.
Most knowledge workers do not want to be constrained by formal,
rigid processes. But the fact is knowledge workers can benefit from the
discipline and structure that a process brings, while remaining free to be
creative and improvise when the situation demands. That is why Microsoft insists on daily builds. Each coder must submit the work done for
the day by a specified time so that it can be integrated with the work
done by the others. And many leading Indian software companies, despite giving so much freedom to their employees, insist on time sheets,
where employees indicate how they spend each day in office. The idea is
to give people freedom but within a framework. The degree of process
orientation possible depends on the nature of the work. A high degree of
structuring is possible in the case of transaction workers. Here the job
can be routinised. In case of integration workers, the process can be laid
down in documents which the workers can consult when needed. In case
of expert workers, specifying the work flow in detail may be difficult. A
better approach would be to provide templates, sample output and high
level guidelines. In case of collaboration workers, specifying and measuring output, instilling a customer orientation and fostering a sense of
urgency may be more effective than imposing process flow charts. External knowledge and information, if necessary, can be made available
through repositories and documents.
The process side to knowledge work must be balanced with the practice perspective. Process is essentially about how work should be done.
Practice is how individual workers actually accomplish their assigned
tasks. A good understanding of work practice requires detailed observation and a good appreciation of why knowledge workers do their work in
a particular way. To combine the best of process and practice,
knowledge workers must be involved in the design of the new process.
36
Knowledge Management from A to Z
The most effective forms of process intervention tend to be participative,
incremental and continuous. They are more people oriented, less focused
on the specific steps to be followed in a process, but more oriented towards the managerial and cultural context surrounding the process.
Technology has been the single most important intervention in the
performance of knowledge worker in the past two decades. Technology
does not automatically enhance the productivity of knowledge workers.
But when applied carefully, technology can give an impetus to
knowledge management. Technology can operate at two levels — organizational and individual.
The type of technology used would vary from job to job:




In transaction work, not much collaboration or judgment is involved.
So automation is possible using technology.
In integration work, technology can help structure both the process
and flow of work.
In expert work, technology can embed knowledge into the business
processes
In collaboration work, which is usually iterative and unstructured, the
types of tools that are likely to be the most effective are knowledge
repositories and aids that enable people to come together and collaborate with each other.
The physical ambience also affects knowledge work productivity.
Knowledge workers prefer closed offices but seem to communicate better in open ones. To collaborate effectively, they need meeting spaces
and conference rooms. To be able to concentrate, they require quiet settings with few distractions. Knowledge workers like to work from home
occasionally. But they don’t want to work from home all the time. They
want to come together from time to time and exchange notes about their
work.
The emergence of knowledge workers has profound implications for
management. Because knowledge work can be and is done by managers
and workers, the line dividing the two is getting increasingly blurred. As
knowledge becomes central to organizations, management will undergo
various changes in the coming years. Some of these are:

From supervising work to doing it too.



From organizing a hierarchally defined structure to organizing communities.
From hiring and firing workers to recruitment and training.
From evaluating tangible performance on the job to assessing “invisible” knowledge achievements.
Knowledge workers must be allowed to express dissent and indulge
in constructive criticism. Decision making processes must be highly participative. Knowledge workers must be encouraged to cut across organizational boundaries. Social networks must be nurtured. These are challenging tasks for which there is no prescribed recipe.
The Road Ahead
Fifty years ago, when William Whyte wrote his celebrated book, The
Organization Man, the prevailing norms in companies were long service, obedience and loyalty. As the Economist1 recently reported1: “Organization man . . . found comfort in hierarchy, which obviated the need
to be self-motivating and take risks. He lived in a highly structured
world where lines of authority were clearly drawn on charts . . . and
knowledge resided in manuals.”
Today the scenario is vastly different. Life time employment / loyalty
doesn’t exist any more. People keep switching jobs at regular intervals.
Improvements in communication technology, globalization and largescale outsourcing of various functions have changed the way organizations are managed. Many companies are moving towards less hierarchical organizations, with loosely defined organizational boundaries. At
the same time, advances in technology facilitate effective coordination,
even if people are geographically apart.
But much more can be done to make organizations conducive to
knowledge work. According to Lowell Bryan and Claudia Joyce: “Today’s large companies do very little to enhance the productivity of their
26
Hindle, Tim. “The New Organization-Survey: The Company”, The
Economist, 19 January 2006, pp. 3-5.
27
Bryan, Lowell L. and Joyce, Claudia. “The 21 st Century Organization:
Big Corporations Must Make Sweeping Organizational Changes to Get the
Best from Their Professionals”, Mckinsey Quarterly, 2005, Number 3, pp.
21- 29.
38
Knowledge Management from A to Z
professionals. In fact, their vertically oriented organizational structures,
retrofitted with ad hoc and matrix overlays, nearly always make professional work more complex and inefficient1.” These structures are not
very conducive to the flow of ideas and the spread of knowledge across
the organization.
But there are organizations which are setting a new direction. Take
the global oil company, BP. At one point BP had a centralized, hierarchical structure. BP then cut its head-office staff drastically and pushed
decision making down to 90 newly established, empowered separate
business units, reporting directly to BP’s apex executive committee. BP
also strengthened horizontal linkages across the business units and divided its assets into four groups, roughly reflecting the same stage of
their lifecycle. These groups grapple with similar commercial and technical issues and are encouraged to support each other and help solve
each other’s problems when required. As a result, people now trust each
other. They admit early when they are facing difficulties and are less
hesitant about seeking assistance. People have also started responding
positively to requests for help.
As knowledge work gains in importance and managing knowledge
workers becomes the key challenge in the coming years, innovations in
organizational design and work process will become the order of the
day. Those organizations that will be able to make knowledge and
knowledge workers central to their business strategy will generate a
sustainable competitive advantage. Others will be left behind.
28
Davidson, Carl and Voss, Philip, Knowledge Management: An Introduction to Creating Competitive Advantage from Intellectual Capital, Vision Books, 2003.
The Social Dimensions of
Knowledge Management
Building a conducive social environment in the organization is a crucial
requirement for effective knowledge creation and sharing. The social
environment shapes expectations, influences the patterns of interaction
within and outside the organization and risk taking by individual employees. Many organizations put too much emphasis on technology
while managing knowledge. Technology does have scale effects and can
expand connectivity across the organization rapidly in a cost effective
way. But without the necessary ecosystem, knowledge management may
degenerate into information management, i.e. exchange of documents
containing factual information, not deep insights. As Carl Davidson and
Philip Voss point out1, “Because the technology makes it so easy to access and share information, the amount of information the average information worker receives in a day is staggering and often distracting.
Think about the number of emails your staff receive each day, consider
what that does for the rhythm of their working day.” The right social
environment can minimize this problem and help people use their time
more productively. Shaping the social environment requires action on
several fronts — leadership, structure, processes, reward systems, cultural intervention. Social networks and communities of practice must be
carefully nurtured.
How Knowledge Markets Function
Knowledge is exchanged, bought and bartered. Like any other market,
the knowledge market too has buyers and sellers who arrive at a mutually acceptable price for the goods exchanged through a process of
negotiation. There are also brokers who bring buyers and sellers togeth29
Harvard Business Review, March 2005.
40
Knowledge Management from A to Z
er. Knowledge market transactions will occur efficiently when the
participants believe that they will benefit in some way. Tom Davenport
and Larry Prusak have given an excellent account of how knowledge
markets function in their book, Working Knowledge.
Knowledge buyers are usually people trying to solve unusual or
complex problems. They seek knowledge to make a sale, do a task more
efficiently; improve their skills, or make better decisions. In short, they
want knowledge to do their work more effectively.
Knowledge sellers are typically people with some specialized or
unique expertise. Although virtually everyone is a knowledge buyer at
one time or another, not everyone may be a seller. Some people are
skilled but unable to articulate their tacit knowledge. Others have
knowledge that is too specialized, personal, or limited to be of much
value to others. Some people may possess valuable knowledge, but may
be unwilling to share their knowledge. Knowledge sellers are typically
motivated by one or more of three factors: reciprocity, repute, and altruism.
Knowledge sharing will take place enthusiastically only if the sellers
expect the buyers to share their knowledge willingly at a future point in
time. Knowledge sellers usually want recognition from others. Having a
reputation for knowledge sharing makes achieving reciprocity more likely. Having a reputation as a valuable knowledge source can also lead to
job security, promotion, and all the rewards and trappings of an internal
guru.
Altruism may also motivate knowledge sharing. After a certain age,
some people have an urge to pass on what they have learned to the next
generation. Firms can encourage this tendency by formally recognizing
mentoring relationships and giving managers time to pass on their
knowledge to less experienced colleagues.
Knowledge markets are shaped by the social and political realities
prevailing in the organization. If the political reality of an organization
allows knowledge hoarders to thrive, there is no incentive for people to
share their expertise. If it is considered a sign of weakness or incompetence within the culture of an organization to admit one can’t solve a
problem, then the social cost of “buying” knowledge will be too high.
Once again, the knowledge market won’t operate well. The notinvented-here mentality is another barrier to knowledge sharing. A variation is the class barrier, an unwillingness to give knowledge to or accept
it from people in the organization who have relatively low status.
Three factors in particular can make knowledge markets inefficient:



Incompleteness of Information about the Knowledge Market:
People
may not know where to find their company’s own existing knowledge.
Asymmetry of Knowledge: One department of an organization may
have abundant knowledge even as another has shortages. This makes
reciprocity highly unlikely.
Localness of Knowledge:. People usually get knowledge from their
neighbors, as they know and trust them more. Face-to-face meetings
are often the best way to obtain knowledge. People often do not
know much about more distant knowledge sources. Also, mechanisms for getting access to distant knowledge tend to be weak or
nonexistent. People will rely more on whatever knowledge the person in the adjacent cubicle, may have, rather than try to discover who
in the company is really knowledgeable.
Trust is particularly important in knowledge exchange. Top management must consciously promote trust in various ways, such as:
1.
Visibility:
The members of the organization must actually see people
get credit for knowledge sharing.
2. Ubiquity: If part of the internal knowledge market is untrustworthy,
the market becomes asymmetric and less efficient.
3. Top down: Trust tends to flow downward through organizations. Only if top managers are trustworthy, will trust permeate the whole firm.
Informal markets play an important role in the buying and selling of
knowledge. Probably the best knowledge market signals flow through
the informal communities of practice that develop in organizations.
Within these webs, people ask each other who knows what and quickly
learn who has previously provided knowledge that turned out to be reliable and useful. If the person they approach doesn’t know an appropriate
seller, she might know someone else who does.
42
Knowledge Management from A to Z
Informal networks engender trust because they function through personal contact and word of mouth. A recommendation that comes from
someone we know and respect within the firm is more likely to lead us
to a trustworthy seller with appropriate knowledge than would a cold
call based on a reference to the organizational chart or corporate phone
directory. Such informal networks are also dynamic. Since people in the
network are more or less continually in communication with one another, they tend to update themselves as conditions change. People share
information about who has left the company or moved to new projects,
who has recently become a useful source of knowledge, and who has
become reticent or less accessible. Of course, informal networks are not
readily available to all those who need them. The functioning of informal networks depends on chance conversations and local interactions —
which sometimes do not work out well. So formal markets also have a
role to play in knowledge exchange. Which is why the intranet, forums
and seminars will continue to play an important role in facilitating
knowledge sharing.
Building Social Networks
In most organizations, work is accomplished through informal networks
of relationships. But the power of these networks is often underestimated. Most managers have the simplistic notion that more connectivity is
better. Managers need to determine exactly what they want to accomplish through informal networks and then decide on the appropriate level
of connectivity.
Networking is about building trust, strengthening human relationships and improving the richness of knowledge transferred. The starting
point is helping employees develop an awareness of who knows what in
the organization. Skill profiling systems and expertise locators can be a
great help here. Leadership and culture have a profound influence on
networks. Leaders must demonstrate by their actions that they support a
collaborative culture. Mentoring and encouraging learning from failure
should also be encouraged. A variety of social networking software is
also now available to form and nurture social networks.
According to Rob Cross, Jeanne Lieutka and Leigh Weirs1, informal
networks serve the twin purposes recognizing opportunities or challenges and coordinating appropriate responses. Using this broad framework,
we can classify social networks as follows:
CUSTOMIZED RESPONSE
In some situations, both problems and solutions are ambiguous. Good
examples are new product development teams, high-end investment
banks, early-stage drug development teams, and strategy consulting
firms. Here teams need to rapidly define a problem or an opportunity
and coordinate relevant expertise to make an effective response. The
problem must be framed and solved in an innovative way. The role of
technology here is primarily to bring experts together. The problems are
too unstructured for automation to be used in a meaningful way.
MODULAR RESPONSE
This kind of a response is appropriate where the components of a problem and solution are known but the combination or sequence of those
components is not yet known. Surgical teams, law firms, business-tobusiness sales, and mid-stage drug development teams are good examples. Depending on the expertise required these teams must be capable
of delivering a unique response. Technology can be used to facilitate the
use of reusable components.
ROUTINE RESPONSE
This kind of response makes sense when both problems and solutions
are well defined and predictable. This would be so in the case of call
centers, insurance claims-processing departments, and late-stage drug
development teams. These teams must be capable of delivering efficient
and consistent response to a set of established problems. Technology can
be used to automate these processes in a big way.
30
This part draws heavily from the article, “Communities of Practice: The
Structure of Knowledge Stewarding” by Etienne Wenger in Knowledge
Horizons: The Present and the Promise of Knowledge Management, edited by Charles Despres and Daniel, Chauvel, Butterworth Heinemann,
2001.
44
Knowledge Management from A to Z
Nurturing Communities of Practice 1
In many disciplines, knowledge is generated by groups of people who
come together based on one or more areas of common interest. Such
“communities of practice” (CoP) provide a forum in which existing
members learn from one another. A dynamic community also encourages others to join.
The three elements of CoP are:
1. A sense of joint enterprise,
2. Relationships of mutual engagement that promote bonding, and
3. Shared expertise developed through engagement over time.
Communities can be formed within business units, across business
units, and across organizations. A CoP does not involve any reporting
relationships. Respect and power within the community depend essentially on individual knowledge and expertise.
Many organizations focus on knowledge that can be captured through
information technology intervention. In the process, the context gets
diluted. Context gives a knowledge asset its richness. Context includes
detailed background information, alternatives that were tried but discarded, experiments that didn’t work, the thinking behind a solution, and
the reasons for the success or failure of an approach. Context is a part of
that bulk of knowledge which never gets captured in a database.
Communities facilitate the sharing of contextual tacit knowledge.
Since rich tacit knowledge resides in people and in their interactions, not
just in databases, people-to-people connections are critical in sharing
such knowledge. Communities are a natural place to make connections
between the knowledge seekers and the knowledge givers. Within a
community, members are interested in the same issues or topic. They
have developed relationships and built trust, and already practice the
behaviors of helping and sharing with each other.
CoPs have different categories of members:
31
Davidson, Carl and Voss, Philip, Knowledge Management: An Introduction to Creating Competitive Advantage from Intellectual Capital, Vision Books, 2003.

Core Group:

Full Membership:
These are the passionate and actively engaged members.
These are the practitioners who make up the com-
munity.



Peripheral Membership:
These people too belong to the CoP but have
lesser involvement and authority.
Transactional Participation: These are outsiders who interact with the
CoP occasionally, either to receive or provide service.
Passive Access: Then there is a large number of people who do not
take part in community activities but have some access to the documents produced by the community.
A well functioning community must be able to take all these members along. While nurturing a core group, it must attract new members
and have a large number of people taking an active interest in the community’s activities even if they are not directly involved.
CoPs do not appear on any organization chart. Indeed, they fill the
white spaces inherent in any organizational context. CoPs provide a stable form of membership that enables people to move from one task to
the next while maintaining continuity in terms of professional trajectory
and identity.
A CoP usually starts as a loose network with latent needs and opportunities. As the community matures and grows, members assume greater
responsibility for establishing a shared practice, a learning agenda and a
group identity. CoPs evolve over time. Some CoPs are short-lived; others last for centuries. CoPs lose their relevance as knowledge needs shift.
Each stage in a community’s development has its own challenges or
questions. In the early phase, there is a need for an inspiring vision to
advance the state of a practice or to achieve a challenging organizational
objective. The challenge at the next stage is to make the intimate community scalable so that it can handle larger numbers of people who may
want to join. When it reaches maturity, a community must take steps to
avoid complacency. When a community loses its vitality, it should be
reinvigorated.
Traditional organizational units have daily routines, like coffee and
lunch breaks. A community won’t have this routine, especially if members are geographically dispersed as can be expected, for example, in
46
Knowledge Management from A to Z
Indian information technology services companies. Mechanisms have to
be put in place to give it that rhythm and pace. For example, members
can check in at regular intervals, or schedule virtual conference sessions.
Similarly, events can be arranged to celebrate community milestones or
accomplishments.
The community needs to determine how frequently it gets together. It
is important to get together for a face-to-face meeting early on to break
the ice and establish trust. Members need to know each other — what
their strengths and interests are, what they’re passionate about, the
knowledge they hold, their experience, etc. Subsequently too, face-toface meetings must be planned from time to time.
Collaborative and communication tools can support communities. In
their early days, communities need tools that help develop relationships
while enhancing divergent thinking. Chat rooms, brainstorming tools
and mechanisms to facilitate the sharing of member biographies and
pictures may be best for young communities.
During the growth stage, the community needs tools that enable convergent thinking to help it agree on a course of action, a best practice, a
recommended solution, or a decision about which product idea to pursue. It needs technologies that help it to find relevant knowledge assets
quickly. It needs the capability to vote on alternatives, and features that
help bring conflicts to the surface and resolve them quickly.
In its maturity stage, the community may need tools that balance
convergent and divergent thinking. When it is in decline, a community
needs tools that archive and preserve knowledge.
A community on the decline needs to be re-energized. More than
technological interventions, what is needed at this stage are movies, images and motivating stories or other ways to engage the community’s
emotions. Face-to-face meetings backed up by skilled facilitation can
help the community to start functioning effectively again.
Organizations must encourage CoPs but too much formal involvement may unwillingly kill an informal network. As Carl Davidson and
Philip Voss put it1:
“The aim is to create an organization with structured informality not
informal structures. . . . If you give the communities too many resources, this will increase the pressure on them for outputs and defeat
the whole point. The best way to fertilize the ground for CoP is to
recognize the important role they play in the organization and then
provide members the time and space they need to come together”.
The return on time invested by community members in community
activities can be evaluated using various metrics such as:







Business problems solved in the community.
New knowledge created in the community.
Joint learning occurring in the community.
Existing knowledge reused by the community.
Innovations (products, ideas, processes, etc).
Improvements in process performance metrics.
The community’s role in recruiting and retaining talent.
Conclusion
Companies cannot afford to ignore the social dimensions while implementing a system of knowledge management. Technology can be easily
replicated by competitors but a high performing eco-system cannot. In
Gupta and Govindarajan’s words1:
“It is relatively easy for a company to adopt a sophisticated information technology architecture but is even easier for competitors to
neutralize or even leap frog that architecture. Creating a social ecology that is free of pathologies, . . . is a much more difficult challenge.
It requires building a whole eco-system of complementary and mutu32
Gupta, Anil K. and Govindarajan, Vijay, ”Knowledge Management’s Social
Dimension: Lessons from Nucor Steel”, Sloan Management Review, Fall
2000, pp. 71-80.
33
Tiwana, Amrit, The Knowledge Management Toolkit: Orchestrating IT,
Strategy, and Knowledge Platforms, Prentice Hall, 2002.
48
Knowledge Management from A to Z
ally reinforcing organizational mechanisms. . . . Any company can
acquire a new piece of hardware but not every company can overcome the difficulties and build an effective social ecology.”
A
Advanced Knowledge
The type of knowledge that is more likely to generate sustainable competitive advantage. For instance, there are world class consumer electronics companies galore but Sony is ahead of them because it has developed unique capabilities in miniaturization. Similarly, in the software
industry IBM has developed an advanced knowledge of middleware.
(See also: CORE KNOWLEDGE, INNOVATIVE KNOWLEDGE)
Agent
Software programs that search for available information and filter incoming information based on specified characteristics. Intelligent agents
can work without direct human intervention to carry out specific, repetitive and predictable tasks. Agents support gathering, delivering, categorizing, profiling information, or notifying the knowledge seeker about
the existence of changes in an area of interest. Many agents can perceive, reason and act in the environments in which they operate. Some
agents can learn from past mistakes. Essentially, an agent uses a limited
built-in or learned knowledge base to execute tasks or take decisions.
Agents can be programmed to execute various tasks — delete junk email, schedule appointments or search for the lowest airfare.
Agents can be of three types — static in the client, static in the server
and mobile. The most useful are the mobile agents that can move from
one server to another to locate information. Such agents can either report
results periodically or if they find something relevant. According to Amrit Tiwana1, agents embody the push model. They can disseminate news,
bulletins, warnings and notifications. Agents operate in asynchronous
mode. They can monitor information at the source without being de34
Argyris, Chris. On Organizational Learning, Blackwell Publishers,
1999.
50
Knowledge Management from A to Z
pendent on the system from which they originate. Agent technology has
grown in sophistication and capabilities in recent years. In supply chain
management, agents can improve the coordination among different entities. For example, P&G has been using agents to cut logistics costs by
optimizing scheduling processes.
(See also: KNOWLEDGE BASE)
Agile Methodology
A useful compromise between no process and too much process. Processes are meant to impose discipline on the way people do their work in
an organization. The danger with such methodologies is that they may
stifle creativity. Agile methods are adaptive and thrive on change. They
are people oriented rather than process oriented. Agile methods take into
account that a process cannot compensate for the skills of team members. The role of a process is to support the team. While managing
knowledge, too much of a process orientation may sometimes backfire.
The “practice” of knowledge workers, i.e. how they actually do their
work, is as important as “process” which is about how they should be
doing their work. Agile methodology is a term associated with Martin
Fowler
(For
more
information,
visit
his
website:
www.martinfowler.com)
AI
See ARTIFICIAL INTELLIGENCE.
Application Service Provider (ASP)
A business that delivers and manages applications and computer services
from a few centers to multiple users using the Internet or a private network. Instead of buying software, customers can effectively rent the
same. The payment may be on subscription or transaction basis. The
customer typically interacts with a single entity, not an array of technologies and service vendors. ASP contracts usually guarantee a level of
service and support to ensure that the software is working and available
at all times.
Argyris, Chris
Behavioral issues play a key role in organizational learning. The work of
Chris Argyris has influenced thinking in this area. People have mental
maps with regard to how to act in situations. It is these maps that guide
people’s actions rather than the theories they explicitly espouse. What is
more, few people are aware of the maps or theories they do use. Argyris
and Schön1 suggest that two theories of action are involved. There are
theories that are implicit in what we do as practitioners and managers,
and those which we use to explain our actions to others. The former can
be described as theories-in-use. They govern actual behavior and tend to
be tacit. The words we use to convey what we, do or what we would like
others to think we do, can be called espoused theory.
When people are asked how they would behave under certain circumstances, the answer they usually give is their espoused theory of
action for that situation. However, the theory that actually governs their
actions is the theory-in-use. For example, managers might mention that
they rushed out of the office because an urgent meeting with a client had
come up. Actually the managers may have become bored and tired by
the paper work and viewed the customer meeting as a welcome change.
A key role of reflection is to reveal the theory-in-use and to explore
the nature of the “fit”. Managers must identify the gulf between espoused theory and theory-in-use. This gulf is not bad by itself. Provided
the two remain connected, the gap facilitates reflection and dialogue. But
if it gets too wide, it can create problems.
A key aspect of learning is detecting and correcting errors. Where
something goes wrong, many people look for another strategy that will
work within the governing variables. In other words, the given goals,
values, plans and rules are operationalized rather than questioned. Argyris and Schon call this single-loop learning. An alternative response is
to subject the governing variables themselves to critical scrutiny. Called
35
O’Deli, Carla and Grayson, C. Jackson. “If Only We Knew What We
Know: Identification and Transfer of Internal Best Practices” California
Management Review, Spring 1998, pp. 154-174.
52
Knowledge Management from A to Z
double-loop learning, this may then lead to an alteration in the governing
variables and, thus, a shift in the way in which strategies are framed.
(See also: DEFENSIVE REASONING, ORGANIZATIONAL LEARNING,
SINGLE-LOOP LEARNING, DOUBLE-LOOP LEARNING)
Articulation
The process by which TACIT KNOWLEDGE is converted into EXPLICIT
KNOWLEDGE. Articulation, also called EXTERNALIZATION, is one of the
four components of the SOCIALIZATION, EXTERNALIZATION, COMBINATION
and INTERNALIZATION (SECI) MODEL developed by the Japanese scholars,
Hirotaka TAKEUCHI and Ikujiro NONAKA. Making tacit knowledge explicit
is one of the major challenges of knowledge management. Figurative
language and symbolism can greatly facilitate the process of articulation.
Artificial Intelligence (AI)
Involves the elimination or reduction of human involvement by extracting people’s knowledge and having the computer make or support important decisions. Much work has been done to make computers develop
the intelligence of human beings. Despite lacking the flexibility, breadth
and generality of human intelligence, AI can also be used to capture,
codify and extend organizational knowledge. AI can also be used to generate solutions to specific problems that are too complex to be analyzed
by human beings on their own. AI has, however, not taken off as rapidly
as expected for various reasons. It is not that easy to extract knowledge
from the brains of experts. Knowledge also changes more rapidly than
the design of such systems can cope with. So AI often complements,
rather than replaces human experts.
(See also: GENETIC ALGORITHMS, NEURAL NETWORKS, CASE BASED
REASONING, FUZZY LOGIC)
ASP
See APPLICATION SERVICE PROVIDER.
Asynchronous Communication
Asynchronous communication means the transmission and receipt of a
message not occurring simultaneously. A good example is e-mail. Blogging is also an example of asynchronous communication. While asynchronous communication is non-intrusive but it lacks interactivity. It is
often the interaction of messages and ideas that leads to rich knowledge
sharing and knowledge creation.
Automated Decision Making
Use of computers in decision making. These systems are taking over
previously human made decisions in various areas of management. Essentially, computers make decisions on the basis of pre-specified business rules. Yield management systems that automate pricing are common in the airline industry. In the financial services industry, program
trading of equities and currencies is taking off. Automated credit approval is quite common in case of banks and mortgage companies.
(See also: DECISION SUPPORT SYSTEMS)
Autonomy
Autonomy is a necessary condition for knowledge creation. Autonomy
encourages people to pursue new ideas, work on them and develop new
knowledge. When autonomy is limited, the culture can get stifling and
people will not take the initiative to share ideas, chase opportunities and
create knowledge. Workers in different departments will share
knowledge with each other in a seamless manner only when there is autonomy. Without autonomy, silos will be created within the organization.
54
Knowledge Management from A to Z
B
Ba
A concept developed by the famous Japanese management guru, Ikujiro
NONAKA, which denotes a shared context, in which knowledge is shared,
created and utilized, through human interactions. Knowledge cannot be
created in a vacuum. Knowledge needs a context to be created. It needs a
space where information is given meaning through interpretation. Ba is a
useful concept in this regard.
Ba provides the energy, quality and space to perform the individual
knowledge conversions and to move along the knowledge spiral.
Ba can be built by providing physical space such as meeting rooms,
cyberspace such as computer networks or mental space such as common
goals to foster interactions. A Ba must have the right mix of people with
different backgrounds and viewpoints to make the shared context a rich
one. The challenge for leaders is to locate the right people.
When participants come together in a Ba, they must suspend judgment of the objective meaning and see things as they are. This allows
tacit knowledge to be articulated without any pre-conceived notions.
Then, they must reflect on what the thing means to them and put the
meaning into words. Finally, they must reflect on whether this meaning
can be universally applied to other situations.
Love, care, trust and commitment form the foundation of knowledge
creation. A Ba needs all of these. A Ba needs to be a self-organizing
place with intention, direction and interest. Without intention, energy in
Ba cannot be directed effectively. Only chaos rules. The energy of Ba is
given by its self-organizing nature. To be effective, Ba requires creative
chaos and REDUNDANCY. Creative chaos results when challenging goals
are set and employees are forced to question conventional assumptions.
Redundancy results when people are given more information than they
need. This generates more ideas, leading to more alternatives.
Ba need not be limited to a single organization. It can cross the organizational boundary and exist in the form of a joint venture with a
supplier, as an alliance with a competitor, as a relationship with a customer, or as a tie-up with a local university.
(See also: REDUNDANCY)
Benchlearning
A structured approach to learning from others, and improving. Developed by Bengt Karlof and his colleagues, it goes beyond BENCHMARKING.
Focused on quantitative comparisons, benchmarking tends to downplay
the key role of knowledge transfer.
(See also: BENCHMARKING).
Benchmarking
The process of identifying who is the very best, who sets the standard
and what that standard is. Benchmarking is a systematic process for
comparing the performance of an activity or process across industries,
organizations or departments and then introducing necessary improvements.
Benchmarking starts with some fundamental questions:







Who has the best CRM?
Who has the highest quality levels?
Who has the most robust delivery process?
Who provides the best after sales practice?
Who has the most agile supply chain?
Who manages customer relationships best?
Who has the highest quality levels?
Much of the early work in benchmarking was done in the area of
manufacturing. Now benchmarking is applied almost anywhere.
Benchmarking can be both internal, i.e. within the organization, and
external, namely across organizations. External benchmarking can provide models of excellence. However, this may actually be quite little
compared with the vast amount of untapped knowledge already residing
inside organizations, which can be tapped through internal benchmark-
56
Knowledge Management from A to Z
ing. Vibrant mechanisms for internal benchmarking represent one of the
most tangible manifestations of knowledge management. They are also
tangible evidence of a learning organization — one that can analyze,
reflect, learn, and change, based on experience.
(See also: BEST PRACTICES, BENCHLEARNING)
Best Practices
The distillation of accumulated wisdom about the most effective way to
carry out a business activity or process. Arriving at a best practice involves comparison with other firms within the industry and sometimes
across industries. For example, Toyota has established best practices in
the area of lean manufacturing, Dell in supply chain management and
McKinsey in tacit knowledge sharing. Sharing of best practices within
an organization is also an important area of knowledge management.
Such knowledge sharing enables lagging departments to catch up with
leaders. For example, the Ispat group, global leaders in the steel industry,
has driven up productivity by systematic sharing of best practices in their
plants across the world.
What exactly constitutes a best practice? According to Carla O’Deli
and C. Jackson Grayson1, labeling any practice as best immediately raises a hue and cry in the organization. Not only is “best” a moving target
but it is also contextual. Arriving at a working definition of best practice
can help create a shared language across the organization. As the term
“best” is highly subjected and context dependent, it seems to imply that
no further improvements are possible. So, the term good practice is often preferred. Some companies have thought through carefully while
dealing with this definitional issue. The oil giant, Chevron has adopted a
simple definition of best practices: Any practice, knowledge, know-how,
or experience that has proven to be valuable or effective within one organization that may have applicability to other organizations.
Chevron views best practices at four levels:
36
In their book, Hitotsubhashi on Knowledge Management, John Wiley
and Sons, 2004.
1.
Good Idea:
Unproved ideas not yet substantiated by data but which
make a lot of sense intuitively and could have a positive impact on
business performance. They need further review / analysis. If substantiated by data, these ideas could be candidates for implementation
in one or more locations / sites.
2. Good Practice: A technique, methodology, procedure, or process that
has been implemented and has improved which business results for
an organization. This is substantiated by data collected at the
location. A limited amount of comparative data from other organizations exists. It is a candidate for application in one or more locations.
3. Local Best Practice: A good practice that has been determined to be
the best approach for all or a large part of an organization based on
an analysis of process performance data. The analysis includes some
review of similar practices outside Chevron.
4. Industry Best Practice: A practice that has been determined to be the
best approach for all or large parts of an organization. This is based
on both internal and external benchmarking work, including the analysis of performance data. External benchmarking is not confined to
the organization’s industry.
Research reveals that companies use different ways to share best
practices.
BUMBLE BEE APPROACH
High level managers can visit different plants / locations / sites / offices
to understand what is going on. These executives make personal judgments about what they are hearing and pass along the relevant information to other offices. This approach can create rivalry, holding up one
unit as better than another. But it does not provide enough information or
motivation to the weaker unit to adopt the practice. Moreover, this approach may facilitate sharing of “explicit” knowledge — but not tacit
knowledge. There is no direct interaction between the two groups. This
approach does help identify people who have set the standard. Transferring such people to another location is probably a more effective way of
transferring the best practice.
BENCHMARKING TEAMS
BENCHMARKING
teams can be formed to assess the current state of an organization on a particular process, identify gaps and problems, and then
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Knowledge Management from A to Z
search for best practices outside the company. Teams often start their
benchmarking efforts by trying to compare measures and results in order
to identify best practices. A comparison of financial and operating performance alone is not enough. Other factors can affect performance outcomes. Teams should spend less time arguing about “who is really
good” and more on looking for breakthroughs in practices.
BEST PRACTICE TEAMS
Unlike benchmarking teams which tend to have a short life span, best
practice teams tend to be more enduring. These teams usually consist of
managers or professionals with similar responsibilities but in different
divisions or plants in the company. The teams are usually led by functional experts who act as internal consultant assisting transfer. Best practice teams also often provide guidelines on what constitutes a bestpractice in their function. Teams meet from time to time to share practices and issues and also remain in touch through e-mail and electronic
conferences.
KNOWLEDGE AND PRACTICE
NETWORKS
Unlike benchmarking and best practice teams which are imposed from
the top, knowledge and practice networks emerge from below. The right
culture and necessary technological infrastructure play a key role in the
formation and functioning of these networks.
INTERNAL ASSESSMENT AND AUDITS
This fourth approach can range from formal technical assessments to
internal audit programs. Assessment activities may also include the identification and transfer of best practices.
Transfer of best practices across an organization continues to be a
major challenge. According to O’Deli and Jackson Grayson, the biggest
barrier is ignorance. In most companies, particularly large ones, people
do not know that someone else has the knowledge they require — or
conversely would be interested in knowledge that they have. Once they
recognize that a better practice exists, the second biggest barrier to transfer is the absorptive capacity of the recipient. Potential recipients may
have neither the resources nor enough practical details to implement it.
The third barrier is the lack of a relationship between the source and the
recipient. Personal ties must be strong enough and credible enough for
both listening and helping to be effective. Finally, even in the best of
firms, best practices take months to move from one part of the organization to another. This kind of a time lag is unacceptable in a fast changing
business environment.
TECHNOLOGY can help in sharing best practices. But technology has its
limitations. It should be remembered that all the important information
about a process is too complex and too experiential to be captured
electronically. Moreover, without the right organizational climate, technology will have little impact. But in many organizations, the instinctive
reaction is to create a technical solution, usually an online database of
best practices. Dozens of companies create internal electronic directories
and databases and launch massive internal corporate PR campaigns to
encourage the use of these databases. But few people enter information
about their practices and few access it. There are several reasons for this:




The really important and useful information for improvement is too
complex to put online.
There has to be a framework for classifying information. The framework must provide a common vocabulary for people from different
businesses and industries to identify similar or analogous processes.
This framework must enable diverse units to talk to each other more
effectively about their business problems.
Entering information into the system must be part of someone’s job.
Busy managers and professionals will rarely take the time to enter a
practice into a database unless it is part of their job.
Culture and behaviors are the key drivers and inhibitors of internal
sharing. Companies must address some fundamental questions: How
do you get people to contribute to and use the system? Are people
rewarded for taking the time to share or seek out best practices?
Satyam, one of India’s top IT services providers launched an organization wide initiative to facilitate sharing of best practices. The initiative
includes widespread e-mail communication across the organization and
interactive knowledge sharing sessions in which the best practices are
explained by the people who have implemented them.
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Knowledge Management from A to Z
According to O’Deli and Jackson Grayson, there are seven lessons
for firms about to embark on best-practice transfer:
1. Benchmarking must be used to create a sense of urgency or find a
compelling reason to change.
2. Initial efforts must focus on critical business issues that have high
payoff and are aligned with organizational values and strategy.
3. As resources are not infinite, an organization can only invest in and
support a finite amount of change at any one time.
4. Measurements should not be taken too far as they can be distorted due
to inconsistencies in data collection. They are also open to interpretation about local causes for the differences in performance. The debate
should shift from “who’s best” and why the measures are not fair, to
identifying dramatic differences in performance. Such differences
would establish beyond doubt a real underlying process difference.
5. Realign the reward system to encourage sharing and transfer. Leadership can help by promoting, recognizing, and rewarding people who
model sharing behavior, as well as those who adopt best practices.
Rewards must be given for collective improvement as well as individual contributions of time, talent and expertise.
6. Use technology as a catalyst to support networks and the internal
search for best practices, but don’t rely on it as a solution. A combination of new information technology tools such as e-mail, “best
practices databases,” internal directories, and groupware can be used
to support employees seeking knowledge and collaboration across
the organization. But technology by itself will not create a vibrant
market for sharing best practices.
7. Leaders must constantly spread the message of sharing and leveraging knowledge for the greater good. Leaders must encourage collaboration across boundaries of structure, time, and function. Some ways
to do this are to promulgate success stories, provide infrastructure
and support, and change the reward system to remove barriers.
According to O’Deli and Jackson Grayson, three themes seem to be
evident in all successful internal benchmarking and transfer efforts. First,
internal transfer is a people-to-people process. Relationships hold the
key to meaningful sharing and transfer. Second, learning and transfer is
an interactive, ongoing, and dynamic process that cannot rest on a static
body of knowledge. Employees are inventing, improvising, and learning
something new every day. New best practices keep emerging. Third,
specific skills and capabilities are needed as a foundation. These capabilities include: a process improvement orientation, a common methodology for improvement and change, the ability to work effectively in teams,
the ability to capture learning, and the technology to support cataloguing
and collaboration.
Ultimately, the key to successful transfer of best practices lies in a
personal and organizational willingness, and desire to learn. A vibrant
sense of curiosity and a deep respect and desire for learning from others
are the prerequisites for success.
(See also: BENCHMARKING, BENCHLEARNING)
BI
See BUSINESS INTELLIGENCE.
Blog
A user friendly website where individuals can express their thoughts,
feelings, ideas and opinions, often with hyperlinks to sources that have
stimulated their thinking. While some dismiss blogging as a gimmick,
others see it as grassroots knowledge management, somewhat similar to
STORYTELLING. Blogs can trigger the thinking of other people, especially
when they have a contrarian or unconventional view that provokes other
people to respond. This exchange of ideas facilitates knowledge sharing
and, in some cases, even knowledge creation. Blogs can also be viewed
as online personal diaries. Blogs provide a more personal way of showcasing a company’s products and eliciting feedback from customers. In
the software industry, blogs provide a forum where new products can be
introduced and developers educated on how to use the different features.
Within an organization, blogs can be used to exchange project related
and event related news.
Brand Knowledge
A brand, viewed from the right perspective, is a knowledge asset. It
packs a lot of insights about what benefits customers are looking for —
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Knowledge Management from A to Z
both functional and emotional. According to Satoshi Akutsu and Ikujiro
NONAKA1, brand knowledge includes brand meta knowledge, brand
knowledge vision, brand experience, and context creativity. Brand meta
knowledge serves as a mental model for thinking about what can create
valuable brand knowledge. It acts like a methodology for creating
knowledge about the brand. Brand knowledge vision determines the sort
of brand knowledge an organization should create to remain relevant and
what governs the brand, including its promises to customers. Vision
helps in creating a distinctive identity for the brand. Brand knowledge
gets enhanced by capturing the experiences of employees, customers,
associates, investors and the community.
The brand building process can be seen as a dynamic process of creating context. In some cases, differences in contexts need to be modified.
On other occasions, the differences become opportunities to create
something by making the best use of them. For example, the marketer
may want to change the consumer brand image and bring it closer to the
desired or ideal brand identity.
Browser
The Internet is the most ubiquitous source of knowledge today. Browser
software allows people to access documents on the Internet, typically
using the HTTP protocol. Browsers read HTML and convert the code
into web pages. Browsers serve as the primary front-end interface for
knowledge management systems that rely on intranet technology.
(See also: HTML)
Bulletin Board
An electronic public forum created with software that supports multiple
simultaneous callers. Participants can post their views and ideas. They
can also comment on messages from other participants. A bulletin board
facilitates exchange of ideas, announcement of events and collection of
feedback from people.
37
In his book The Knowledge Management Toolkit: Orchestrating IT,
Strategy, and Knowledge Platforms, Prentice Hall, 2002.
Business Intelligence (BI)
Helps in converting data into information and then into knowledge. Organizations collect huge amounts of data in their information systems
during the course of their day-to-day operations. Just as human intelligence enables us to combine existing knowledge with new information
and change our behavior in such a way that we succeed at our task, or
adapt to a new situation, BI enables firms to collect information, develop
knowledge about operations and change decision making behavior to
achieve various business objectives. BI software can be used to gather,
store, analyze and provide access to data and present that data in a simple, useful manner. Data warehousing is usually a part of this process. BI
involves sifting through large amounts of data, extracting pertinent information and turning that information into knowledge, using which
decisions can be taken.
(See also: DATA WAREHOUSING, DATA MINING)
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Knowledge Management from A to Z
C
Case Based Reasoning (CBR)
A branch of ARTIFICIAL INTELLIGENCE, CBR is the method of taking
advantage of previous problems or cases handled by people and attempts
to solve problems through analogies. Based on the attributes of the problem at hand, a search mechanism sifts through the cases available and
retrieves the closest matches. Many business problems can be solved by
identifying patterns.
The case-based approach is conceptual, not based on individual
words. So the traditional methods based on comparing strings of words
do not work well. Through categorization, CBR connects similar cases.
The search is on the basis of ideas and concepts, not key words.
The starting point in CBR is to input a series of “cases” which represent knowledge about a particular domain expressed as a set of problem
characteristics and solutions. When people are presented with a problem,
its characteristics can be compared with the set of cases in the application, and the closest match can be selected.
According to Amrit Tiwana1, CBR is a promising tool for any
knowledge management system. CBR is particularly useful when the
choice is between deciding on the basis of some data and no data at all.
CBR is most commonly found in the customer service and support processes in firms.
Take customer support or “help desk” applications, for example. The
customer is on the telephone in real time. In this situation, the users can
understand problems, but are not capable of solving some of them right
away. CBR may be the best bet under these circumstances. CBR has
also been successfully applied to planning, scheduling, design and legal
deliberation.
38
In their article, “What Do We Know About CKOs?”, Knowledge Horizons, 2001.
CBR systems need to be put in place after thorough initial planning.
All possible attributes that may be needed in future, must be identified.
If attributes are subsequently added, older cases that have those attributes will not show up in the search, unless more attributes are explicitly
added to the old cases as well.
(See also: NEURAL NETWORKS)
Causal Knowledge
The kind of knowledge which covers issues such as rationale for decisions, alternatives and eventual outcome of activities. Causal knowledge
is much richer, deeper and consequently more valuable than factual or
procedural knowledge. For example, when something goes wrong, managers can actually document the reasons and the circumstances underlying the failure. “Lessons learnt” databases contain some of the most valuable knowledge in organizations. Unfortunately, not many organizations invest sufficiently in storing and sharing causal knowledge. One of
the best ways to encourage the development of causal knowledge is to
encourage employees to ask why, when a problem is faced, something
goes wrong, there is an unexpected success, etc.
Caves and Commons
Proper design of the work space can significantly enhance the productivity of knowledge workers. Caves and commons denote two main types
of physical working area.
A cave is a private area for concentrated thinking. Microsoft is famous for providing individual cabins to most of its knowledge workers.
A common is an open area for socialization, meeting rooms for team
discussions and so on. Both caves and commons are needed to improve
the productivity of knowledge workers.
(See also: PHYSICAL ENVIRONMENT, WORK AMBIENCE)
Channel Integration
The integration of different channels to facilitate effective leveraging of
knowledge. In any business, there are several channels of communication that connect a company to its customers and partners. These include
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web browsers, voice, wireless hand held devices and computing devices
and direct contact with customers and retailers. Through channel integration, for example, customer knowledge can be integrated across all business processes including pre- and post-sale contacts, orders, delivery,
after sales service, complaint resolution, etc. Such knowledge can then
be updated and made available in real time. The ultimate objective of
channel integration is to exploit knowledge, lock in customers, and increase switching costs. This approach is often called “getting a 3600
view of customers.”
(See also: CUSTOMER KNOWLEDGE)
Chief Knowledge Officer (CKO)
Many organizations these days appoint chief knowledge officers explicitly mandated to lead the knowledge management function. Michael Earl
and Ian Scott1 have given an excellent account of the work of CKOs.
CKOs are usually appointed when top management realizes that inadequate attention is being paid to explicit or formal management of
knowledge in ongoing operations, and that hidden value of organizational knowledge is not being leveraged satisfactorily. Inability to learn from
past failures and experiences in strategic decision making, and difficulties in creating value or making money from knowledge embedded in
products (or held by employees) are other reasons that prompt the appointment of CKOs. The role of CKOs is still evolving in most organizations. Different corporations are likely to have different expectations
from the knowledge management function. So CKOs have often to work
out their agenda in consultation with key people in the organization.
In general, CKOs need to bring to the table multiple skills. CKOs
must be passionate about learning. They must act entrepreneurially.
They also need to be self starters. They must be flexible and able to carry
key people along with them as they implement projects. Typically, they
should have been around in the organization for long. This not only
39
Porter, Michael E., “Clusters and the New Economics of Competition”,
Harvard Business Review, November-December 1998, pp. 77-90.
gives them greater credibility but also a better understanding of cultural
and organizational issues that makes implementation easier.
As evangelists, CKOs have to influence minds and behaviors. They
have to get a buy-in from senior managers about the importance of
knowledge management. They have to create a vision, spot opportunities
and leverage existing initiatives.
As facilitators, CKOs act like consultants. They have to work with
and through people. They have to enlist the support of champions, sponsors and partners. Champions are people who are excited about
knowledge management. They need no further selling. Sponsors are senior executives who fully support knowledge management. Partners are
typically people from MANAGEMENT INFORMATION SYSTEMS (MIS) and
human resources (HR). They should be able to shape ideas, be good at
interventions and work with line managers in pain areas.
As designers, CKOs must analyze situations, ask good questions and
propose solutions. They may not actually deliver solutions but should
know who can do so and work with them. They must understand quickly
what is possible and what is not.
To kick start knowledge management, CKOs can focus on specific
themes, such as knowledge directories, knowledge repositories,
knowledge-intensive business and management processes, knowledge
exchange events and knowledge protection policies.
CKOs usually tend to have small budgets and small staff. They mobilize resources as the knowledge management initiative picks up, need for
investments in technology arises, and more line managers request advisory support. In general, CKOs are not “resource hungry” people.
Appointing a CKO is one way of giving momentum to a knowledge
management program. Over time, knowledge management may get embedded into organizational routines, making the role of a CKO less critical. But initially, a leader is needed to set the agenda and spread awareness across the organization about knowledge sharing and learning.
Chief information officers (CIOs) may not be able to take on the role of
CKO. CIOs may have good technological and consulting capabilities.
But they may not have the entrepreneurial mindset of CKOs. CIOs are
used to managing a core function and controlling resources, not handling
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transitory teams. In contrast to CIOs, CKOs are more concerned with
change and less with delivery. But CKOs often have to work closely
with CIOs when implementing knowledge management projects.
CKO
See CHIEF KNOWLEDGE OFFICER.
Clusters
An important concept in inter ORGANIZATIONAL KNOWLEDGE CREATION.
Michael Porter coined this term to describe geographical concentrations
of interconnected companies and institutions in a particular business.
Clusters1 include suppliers of components, machinery and services.
Institutions which provide specialized infrastructure and demanding customers also form part of a cluster. Other members of a cluster include
the local government, universities, research centers and think tanks who
facilitate learning. Clusters are important drivers of global competitiveness because they facilitate inter organizational learning and KNOWLEDGE
SHARING. Silicon valley in California, USA is probably the world’s best
known industrial cluster.
Clustering
The tendency to group objects, words, pictures or ideas into groups in
some subjective ways. Data clustering is a technique for data analysis by
partitioning a data set into subsets whose elements share common traits.
Thus, a data mining tool can discover different groupings within data.
For example, it can divide investors into groups based on their liquidity
preferences.
(See also: SEARCH STRATEGY).
Codification
Codification aims at putting knowledge that people have, into a form
that makes it easily accessible across the organization. It attempts to
40
In her article, “Communities of Practice: The Structure of Knowledge
Stewarding”, Knowledge Horizons, 2001.
make knowledge as organized, explicit and portable as possible. Codification allows knowledge to be shared, stored, combined and manipulated in various ways across the organization.
Some forms of knowledge, such as patents, are already codified and
explicit. Similarly, manuals and other structured documents are examples of codified knowledge. In other cases, reports can be generated. But
not all kinds of knowledge are amenable to codification. The rich, tacit,
intuitive knowledge of a seasoned expert, developed and internalized
over a long period of time is almost impossible to reproduce in a structured document or database.
The challenge for organizations is to codify knowledge and still leave
its distinctive attributes intact. The process of codification should not
severely dilute the richness and context. One way to deal with this problem is that instead of trying to turn knowledge into a “code”, or cram it
into a template, companies can often encode the stories themselves. That
way, the context can be preserved and meaning conveyed without losing
much of its value. For example, managers can prepare a video that can
narrate how a key sale was made.
(See also: CONTEXT SENSITIVITY)
Cognition
Refers to activities such as thinking and reasoning. For the cognitive
psychologist, behavior requires explanations at the level of mental
events, mental representations, beliefs, intentions, etc. Cognitive science
is the name given to academic disciplines that study the human mind.
Cognitive differences among people arise because of the different ways
in which they perceive and assimilate data, make decisions, solve problems and relate to other people. Some people, for example, may use a lot
of intuition while solving problems; others prefer a more analytical approach. People who use an analytical, logical, sequential approach to
solving problems are left-brained while those who use an intuitive, value-based and non-linear approach are right-brained. Some people like to
collaborate while solving problems, while others like to be on their own.
Cognitive unconscious is a general term that describes a variety of mental processes and functions that take place largely independent of con-
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Knowledge Management from A to Z
sciousness or awareness. Cognitive therapy is based on the assumption
that the way in which individuals structure and interpret their experiences determine their subsequent behavior.
Collaborative Filtering
Technology which automatically compares attributes of one set of customers with other sets and facilitates personalization of websites by anticipating customer needs. It relies on an extensive base of similar customers. The software makes recommendations to users based on their
presumed interests. Collaborate filtering requires scaleable personalization capabilities that can cope with increasing customer data volume.
Amazon website is a good example. The site recommends books to a
site visitor, based on purchases by other customers with similar interests.
Collaborative Platform
Refers to the network, hardware and software that allow knowledge
workers to perform tasks and work on projects together. Workers sitting
at geographically dispersed locations can collaborate using such a platform. The ideal collaborative platform is characterized by portability,
scalability, integration, customizability, security, flexibility, low implementation and training costs, minimum deployment time and open architecture.
Collaboration Work
A term coined by Tom Davenport to describe work involving a high
degree of improvisation that, in turn, demands deep cross-functional
expertise. Individual expertise and degree of interdependence among
workers are both high in such kind of work. Investment banking is a
good example. In the case of an M&A deal, experts in different functions like legal, human resources, valuation and accounting may have to
come together and collaborate. It is difficult to automate or create a process flow for such work. So, knowledge can be made available in repositories which people can access as and when needed.
Combination
A term coined by Hirotaka TAKEUCHI and Ikujiro NONAKA in their book,
The Knowledge Creating Company, as part of their SECI (SOCIALIZATION,
EXTERNALIZATION, COMBINATION, INTERNALIZATION) MODEL. This mode
of KNOWLEDGE conversion involves combining different bodies of
EXPLICIT knowledge. Combination is the process of creating new explicit
knowledge by sorting, adding, categorizing and combining existing explicit knowledge. Many software services companies store valuable documents in repositories, for easy access by employees. People refer to
these documents, offer comments and also contribute new documents.
This way, new knowledge is generated.
Community of Interest (CoI)
A group of people who share knowledge and experience around a common interest. These people are driven more by learning and less by outcomes, compared to a COMMUNITY OF PRACTICE. A good example could
be business school faculty having a common interest in a particular topic
of research. Peer reviews, seminars and collaborative paper writing are
some of the ways in which communities of interest are sustained.
Community of Practice (CoP)
A group of people who share and develop their knowledge and expertise. These people may not necessarily work in the same department or
organization.
In many disciplines, knowledge is generated not by individuals but by
a community of like-minded peers. So formation and nurturing of communities of practice is becoming a key challenge for many companies.
Etienne Wenger1 has given an excellent account of how CoPs function.
41
It is a database in which the operations carried out on information items
(data objects) are considered part of their definition. When database capabilities are integrated with object programming language capabilities,
the result is an object-oriented database management system or
ODBMS. An ODBMS makes database objects appear as programming
language objects in one or more existing programming languages. ODBMSs extend the object programming language with transparently per-
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Knowledge Management from A to Z
Most knowledge management initiatives lay emphasis on making
codified knowledge available in databases / portals. But important
knowledge is often difficult to codify. Only a small fraction of the
knowledge in an organization is ever captured in CONTENT MANAGEMENT
SYSTEMS, knowledge repositories and portals. Moreover, context is missing in such knowledge. It is context which gives a knowledge asset its
richness. Context includes background information, alternatives that
were tried but discarded, experiments that did not work the thinking behind a solution and reasons for the success or failure of an approach.
Communities provide this context by facilitating connections between
knowledge seekers and the knowledge source. Within a community,
members are likely to have common interests. They’ve developed relationships and built trust, and are used to helping and sharing knowledge
with one another.
The common elements of CoP are a sense of joint enterprise, shared
identification, relationships of mutual engagement that promote bonding,
and shared repertoire of resources that members develop over time
through engagement. Communities can be formed within business units,
across business units, and across organizations.
A CoP is not entirely homogeneous. Indeed CoP often have different
categories of members:

Core Group:

Full Membership:
There are the passionate and actively engaged people.
These are the practitioners who make up the com-
munity.

Peripheral Membership:
They belong to the CoP but have less in-
volvement and authority.


Transactional Participation:
These are outsiders who interact with the
CoP occasionally to receive or provide service.
Passive Access: There may be many other people who have access to
artifacts produced by the community such as publications, website or
tools.
sistent data, concurrency control, data recovery, associative queries, and
other database capabilities.
A CoP is different from other forms of organizational structure. Rather, it does not involve reporting relationships. Rather, it is based on
collegiality. The power of its members comes from knowledge, not formal authority. Unlike a team which is defined by a task, a CoP is defined
by knowledge. A CoP is held together, not by a project but by the passion of its members. Unlike a cross functional team, a CoP does not
form when a project starts or disappears when a project gets over. A CoP
provides a stable form of membership that carries people from one task
to the next while allowing them to find continuity in terms of professional identity and development of expertise. A CoP provides a context
for the relevant exchange and local interpretation of information.
CoPs usually start as loose networks with latent needs and opportunities. As the community matures and grows, members gradually establish
a shared practice, a learning agenda and a group identity. CoPs evolve
over time. Some CoPs are short-lived; others last for centuries.
Communities have to be nurtured carefully. They need activities to
remain vibrant and get people involved. Meetings play a key role in
many communities. A face-to-face meeting is often desirable early on, to
socialize, build relationships and trust. Members can get to know one
another — what their strengths and interests are, what they’re passionate
about, the knowledge they hold, their experience, etc.
At each stage in the life cycle of a CoP, there are specific challenges
or questions. In the early days, there is a need for an inspiring vision or a
difficult task to advance the state of a practice or to achieve a challenging organizational objective. The challenge at the next stage, where more
people want to participate, is scaling up, so that the community can handle larger numbers. When it reaches maturity, the problems faced by a
CoP include complacency and loss of vitality. People participate less and
less. The key challenge then is to reinvigorate the community.
Collaborative and communication tools can support communities. In
their early days, communities need tools that help develop relationships
while enhancing divergent thinking. Collaborative environments like
chat rooms, brainstorming tools and mechanisms to facilitate the sharing
of member biographies and pictures, and simple portals with various
features for collaboration may be ideally suited for young communities.
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During the growth stage, a community needs tools that enable convergent thinking to help it agree on a course of action, a best practice, a
recommended solution, or a decision about which product idea to pursue. It needs technologies that help it to find relevant knowledge assets
quickly, and engage internal and external customers in dialogue. It needs
the capability to vote on alternatives, and features that help surface and
resolve inter-community conflicts. It also needs to integrate new members quickly.
During the maturity stage, the community may need tools that balance convergent and divergent thinking. Finally, when it is in decline, a
community needs tools that archive and preserve knowledge.
Communities on the decline need to be re-energized. Movies, images
and motivating stories can be used to revitalize the community. Face-toface meetings, as well as skilled facilitation, may once again become
essential.
The return on time invested in community activities can be evaluated
using various metrics:





Business problems solved in the community.
New knowledge created in the community.
Joint learning occurring in the community.
Existing knowledge reused by the community innovations.
The community’s role in recruiting and retaining talent.
Comprehension
Information overload is increasingly a problem today. The ability to distil out key messages when there is abundance of information has become
crucial. The quality of decision making deteriorates when decision makers spend time going through more information than what is needed.
That time might be better spent on comprehending, reflecting, analyzing
and making decisions. Comprehension can be improved by eliminating
duplicate or overlapping messages. Messages can also be filtered or prioritized. Visualizing techniques can be applied to help the user understand the available information more easily. Various knowledge tools
like concept mapping are available to facilitate comprehension.
Concept Mapping
A visual representation of core concepts showing the relationships between them. A typical concept map has nodes (the concepts) with arrowed links between them (the causal relationships).
Concept mapping helps in visualizing the relationships between different concepts. These relationships are articulated in linking phrases,
e.g. “gives rise to”, “results in”, “is required by,” or “contributes to”.
Concept mapping helps to represent the mental models, i.e. the cognitive
map of individuals, teams and organizations and also the structure of
knowledge extracted from written documents. The addition of
knowledge resources, such as diagrams, reports, other concept maps,
spreadsheets, etc., to the concept nodes can further facilitate meaningful
learning.
Concept maps are used to stimulate idea generation and to communicate complex ideas. Teachers can use them in the classroom to make
learning more interesting and to reinforce key concepts. Formalized concept maps are used in software design.
In short, concept maps are used for:







Taking notes and summarizing.
Communicating complex ideas and arguments.
Detailing the entire structure of an idea, train of thought, or line of
argument for the scrutiny of others.
Capturing key concepts, their relationships and hierarchy from documents
Transforming tacit knowledge into an organizational resource.
Enabling knowledge retention by eliciting and mapping expert
knowledge of employees prior to retirement.
Facilitating the creation of shared vision and shared understanding
within a team or organization.
Condensation
The summarizing of data into a more manageable, concise form. For
example, a series of data can be summarized into a table. Condensation
is one of the ways by which we can convert data into information.
(See also: DATA, INFORMATION)
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Constraint-Based Systems
Constraint-based systems are suited for situations where data is available, but normally in a less quantitative from than that required by neural
networks. Like expert systems, they are suited for relatively narrow
problem domains, such as product configuration or pricing. Constraintbased systems capture and model the constraints that govern complex
decision making. These systems are usually object-oriented1, not rulebased. So they are easier to modify than expert systems. There are no
complex interactions to understand and modify.
(See also: EXPERT SYSTEM, NEURAL NETWORKS, OBJECT ORIENTED
DATABASES).
Content Analysis
Analysis of a body of content (text) into its key concepts to identify
trends, to generate keywords and thesaurus terms to improve subsequent
text search and retrieval.
(See also: CONTENT MANAGEMENT SYSTEM)
Content Management System (CMS)
A system makes it easier to develop enterprise portals and websites, by
separating the management of content from its presentation (display).
CMS facilitates collaborative creation of documents and other content.
Blocks of content are tagged with metadata and other attributes and held
in a database.
There are various kinds of CMS:



42
Web content management systems can automate various aspects of
web publishing.
Transactional CMS assist in managing e-commerce transactions.
An integrated CMS helps in managing enterprise documents and content.
“Knowledge Sharing is a Human Behavior”, in Knowledge Management — Classic and Contemporary Works, edited by Daryl Morey, Mark
Maybury and Bhavani Thuraisingham, University Press, 2001.


Digital asset management systems help in managing the lifecycle of
digital media.
Similarly there are publications management, learning management
and document imaging systems.
(See also: DOCUMENT MANAGEMENT SYSTEMS)
Context Sensitivity
Rich knowledge tends to be highly contextual. Separating the context
from the knowledge tends to take away much of its value. So it is important to understand for what purpose the data has been collected or a
report prepared. This ensures that the right interpretation is made of any
document available in a knowledge repository. Equally important, this
knowledge must be applied carefully with necessary modification and
customization in a different context. To take an example, the challenges
involved in implementing an enterprise resources planning (ERP) system for an oil company may be quite different from those for a pharmaceutical company.
(See also: CODIFICATION)
Cookies
A general mechanism in which server side connections can be used
to store and retrieve information on the client side of the connection.
The main purpose of cookies is to identify users, prepare customized
web pages and make the site more personalized and user friendly. For
example, the client is freed from retyping a user ID, every time. Sites
can also store user preferences on the client. Every time connection is
established with the site, those preferences can be supplied by the client.
To facilitate this process, customers entering a website are usually
asked to fill out a form. This information is packaged into a cookie and
sent to the web browser which stores it for later use. The next time the
customer visits the site, it will be customized. For example, the welcome
page may have the user’s name on it.
Cookies can be of different types. A session cookie, also called a
transient cookie is erased when the user closes the web browser. Session
cookies do not collect information from the person’s computer. They are
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based on session identification, not personal identification. A permanent
cookie or a stored cookie, is stored on a user’s hard drive until it expires
or until the user deletes the cookie. Permanent cookies are used to collect
unique information about the user such as web surfing behavior.
CoP
See COMMUNITY OF PRACTICE.
Core Capabilities
Also called core competencies, core capabilities constitute a bundle of
skills that together represent valuable knowledge which cannot be easily
replicated. They form the basis for the competitive advantage of a firm.
A firm’s knowledge strategy must be built around its core capabilities. The firm must develop knowledge in such a way that its core capabilities are strengthened. However, when there is a radical change in the
industry or a new paradigm emerges, new kinds of knowledge with no
link to the existing core capabilities may have to be developed. Core
capabilities may, otherwise, become CORE RIGIDITIES.
Core Knowledge
The minimum scope and level of knowledge required for a firm to compete. While core knowledge may act as a basic barrier to entry, since
such knowledge is held by all players it therefore does not provide a sustainable competitive advantage.
(See also: ADVANCED KNOWLEDGE, INNOVATIVE KNOWLEDGE)
Core Rigidities
Erstwhile CORE CAPABILITIES which are no longer of value due to emergence or radical change or new paradigm in an industry. Thus, an organization’s strengths can also be its weaknesses.
Over time, as organizations develop these strengths, they tend to focus on one kind of knowledge at the expense of others. If the existing
strengths are not able to deliver value to customers, they may turn out to
be a handicap. For example, Motorola’s strengths in analog technology
became a core rigidity when digital technology took off. So core capabil-
ities must be examined on an ongoing basis, to see how useful they are,
in relation to current market needs. When the existing core capabilities
have outlived their relevance, the focus must shift to building new core
capabilities.
Corporate Amnesia
The loss of collective experience, embedded tacit knowledge, and accumulated skills, when many people leave a firm, for example due to
down-sizing and layoffs. In India, this has happened in some public sector units because of voluntary retirement schemes.
Corporate Culture
Culture refers to the beliefs and values held by a group of people. The
culture of the organization plays a key role in managing knowledge. In a
positive knowledge sharing culture, problems, errors, omissions, and
failures are shared; not penalized or hidden. Debate and healthy conflicts
are encouraged as legitimate means of solving problems. Consequently,
people are open to learning and applying new ways of solving problems.
In dysfunctional cultures, people have a closed mindset. They tend to
become defensive when mistakes are pointed out or the scope for improvement is identified. As a result, people in such organizations find it
difficult to learn and change their behavior.
The Gartner group has identified three types of cultures in the context
of KNOWLEDGE SHARING.
The first category includes balkanized organizations where people
compete against each other in an atmosphere of mutual suspicion and
information hoarding. The potential for knowledge sharing is low here in
such cases.
The second category consists of “monarchies” with top-down authoritarian rule. The potential for knowledge sharing is higher here.
The third category consists of federations with local autonomy and
democratic means of dispute resolution. Cooperation is based on enlightened self-interest. The potential for knowledge sharing is high here
in such organizations.
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According to William Ives, Ben Torrey and Cindy Gordon1, various
steps are involved in shaping a right culture for knowledge sharing. The
first step is to identify knowledge sharing as a priority and then provide
strong leadership and investment support. Leaders must display a strong
sense of trust and integrity. Once trust is established, knowledge sharing
must be embedded into the way of working. All project reviews should
cover knowledge sharing and reuse of knowledge. Performance appraisals must take into account knowledge sharing. All newsletters and communications should provide links, where appropriate, to the knowledge
management system. Equally, all training courses should leverage the
knowledge management system. The company must also encourage collective inquiry into everyday experiences and sensitivity to the environment and willingness to change. Communities of practice must be actively encouraged and nurtured.
(See also: DEFENSIVE REASONING, LEARNING ORGANIZATION)
Creative Abrasion
A term coined by Gerald Hirshberg, director of Nissan Design International. The concept has been further developed by Dorothy Leonard in
her well known book, Wellsprings of Knowledge.
Creative abrasion focuses on knowledge building at the work-group
level within an enterprise as a result of arguments that occur when people with diverse backgrounds, experiences and skill sets come together
to work on real business problems. A similar idea has been described by
Richard T. Pascale in his book, Managing on the Edge: How the smartest companies use conflict to stay ahead.
Innovation, as Dorothy Leonard and Susan Straus1 mention, takes
place when different ideas, perceptions and ways of processing and
judging information collide. That is possible only when people who see
the world in inherently different ways come together. But often, the con43
Harvard Business Review, July-August, 1997.
Bassie, Laurie J. and Buren, Mark E. Van, "New Measures for a New
Era” in Knowledge Management — Classic and Contemporary Works,
edited by Daryl Morey, Mark Maybury and Bhavani Thuraisingham, University Press, 2001.
44
structive conflicts that should take place, do not happen. Some managers
avoid clashes by keeping in their team people who think as they themselves do. So nothing radically different or new emerges. In the rare cases where managers are bold enough to bring diversity into the team, not
much is done to encourage constructive conflicts. Only a few managers
know how to promote creative abrasion. They do so by actively considering various approaches and taking different perspectives and by encouraging people to respect the thinking styles of other team members.
These managers lay down necessary ground rules to discipline the creative process.
(See also: PRODUCTIVE FRICTION)
Customer Capital
The value of an organization’s relationships with its customers. Often, it
is these relationships that fetch business, not just the quality of the products or services offered by the company. This is also the reason why
there is so much emphasis on Customer Relationship Management.
(See also: CUSTOMER KNOWLEDGE)
Customer Knowledge
Customer knowledge consists of the insights collected while dealing
with customers. Customer knowledge is useful in understanding customer needs, including those which are unmet and unarticulated. Various
sources of customer knowledge can be integrated and analyzed both to
serve customers better and to generate ideas for new products and services. Customer knowledge facilitates customer relationship management (CRM). Many IT services companies offer CRM solutions that
help their clients in getting 360 degree views of the customers. Information technology (IT) can support ongoing efforts to improve customer
identification, conversion, acquisition and retention and to deliver personalized services. IT facilitates high levels of personalization and decision support in a cost effective manner. But customer knowledge initiatives should not be driven by IT alone. Close personal interaction with
customers is needed to get deep insights about what customers are really
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looking for. This is because customers sometimes find it difficult to articulate their needs.
Customer knowledge should lead to the following1:






45
Customer Satisfaction:
This can be measured as the percentage of
customers completely satisfied with existing products / services.
Customer Retention: The metric here can be the percentage of customers still with the company compared with the previous year.
Product / Service Quality: This can be tracked by computing the percentage of customers complaining about product quality.
Average duration of Customer Relationship: This can be measured as
the number of months for which an average relationship with customers continues.
Repeat Orders: The metric here can be the ratio of volume of business generated by repeat orders to the total business.
Growth in Sales of Key Accounts: Both sales and profit growth can be
tracked.
Harvard Business Review, September 2004.
D
Data
A set of particular and objective facts about an event or a transaction; for
example, the number of customers arriving at a restaurant every hour. Or
the total amount of purchases made at a departmental store during the
day.
We often have a very simplistic notion that the more the data we
have, the better we are equipped to take the right decision. But data collection is the easier part. Indeed, too much data may be collected and
distract our attention. And data by itself does not have any meaning.
Moreover data can be cumbersome and voluminous to handle. Unless
data is processed into information and subsequently converted into
knowledge, it adds little value to the business.
Data Marts
Scaled down version of a data warehouse that is tailored to contain information for use by a department.
Data marts are also known as local data warehouses. A data mart has
the same characteristics as a data warehouse, but is usually smaller and
is focused on the data for one division or one workgroup within an enterprise. Whereas a data warehouse combines databases across an entire
enterprise, data marts focus on a particular subject or department. For
example, marketing data marts may be constructed to capture customer
related information.
There are three different ways of building data marts:

The data warehouse can be first created, combining the information
from the various databases which already exist. Specialized data
marts can then created not only to serve the unique needs of different
departments but also to allow the querying load to be spread among
several different computers. This can smoothen network traffic.
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
Knowledge Management from A to Z
The data mart can be viewed as the prototype of a data warehouse.
The division or group that would most benefit from data-based
knowledge is first selected. A data mart is built with that group’s data. Other information is added to the data mart over time till it becomes a data warehouse.
Data marts can be built independent of a data warehouse. It is usually
quicker and cheaper to build a separate data mart instead of building
an enterprise-wide data warehouse and then data marts from within it.
The problem here is that the company’s data will not be integrated.
There will quite likely be some duplication and inconsistency of data.
If there are too many data marts, complexity and costs will increase.
(See also: DATA WAREHOUSING)
Data Mining
The process of identifying commercially useful patterns or relationships
in databases through the use of information technology. Analyzing data
involves the recognition of significant patterns. Human analysts can see
patterns in small data sets. But large amounts of data need specialized
mining tools. These tools can perform high level analyses of patterns and
trends but also drill down to provide more detail when needed.
Data mining can be used to identify the attributes that characterize
the customers who account for a bulk of a business. Thus, a consumer
goods company may track hundreds of variables about each consumer
segment, with scores of possible relationships among the variables. Similarly, data mining software can help retail companies find customers
with common interests.
Data mining is often misused to describe software that presents data
in new ways. The focus of data mining is not to change the presentation
of the data, but discover previously unknown relationships among the
data.
(See also: DATA WAREHOUSING)
Data Slam
Refers to meaningless pieces of data which can clog corporate intranet
sites and databases. They make systems slow, unwieldy and difficult to
navigate. In the process, they slow down decision making.
Data Warehousing
A data warehouse facilitates integrated access to a company’s information. A data warehouse stores both current and historical data that are
of interest to managers across the organization. The data may originate
in different operational systems and external sources. They may be in
different forms. These data are standardized and consolidated so that
they are accessible to users through simple commands. A data warehouse provides data to decision makers without interfering with the
transaction processing operations. Selected items are regularly pulled
from transaction data files and stored in a central location. This may be
done on an hourly, daily, weekly or monthly basis.
What makes a data warehouse different from other databases is its
purpose. Most data are collected to manage day-to-day business activities. The systems used to collect such operational data are referred to as
OLTP (Online Transaction Processing). On the other hand, the distinguishing feature of a data warehouse is analysis. A data warehouse
makes data available for the purpose of analysis.
The main aim of a data warehouse is to hold in one place all the data
needed for managerial decision making. So the starting point is determining the data needs. Indeed, the success of a data warehouse largely
depends on how well the needs of managers have been identified. The
next step is to establish the sources of data. Then the data must be transformed and integrated so that it can be searched and analyzed efficiently
by decision makers. Instead of building a link to the original data files, it
is easier to copy the data into new files. Once the data warehouse has
been defined, programs are written to transfer the data from the legacy
systems into the data warehouse.
One problem with a data warehouse is that managers will not always
have the most current data. Often data is stored as collections of files and
data items and not in relational database management systems
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(RDBMS). So, the system is relatively easy to use but is less flexible
compared to RDBMS.
(See also: DATA MINING, DATA MARTS)
Davenport, Tom
One of the leading knowledge management gurus in the world, Davenport has been associated with Ernst & Young, McKinsey & Company,
and Accenture. He has written, co-authored or edited several books on
business process reengineering, knowledge management, and the business use of enterprise systems. Working Knowledge: How Organizations
Manage What They Know, coauthored with, Laurence PRUSAK (2000) is
one of the most popular books ever written on knowledge management.
His book, What’s the Big Idea: Creating and Capitalizing on the Best
Management Thinking, was named one of the three best books of the
Spring 2003 season by Fortune magazine. His most recent book, Thinking for a Living, has also received highly favorable reviews. Davenport
has also written hundreds of articles and columns for such publications
as Harvard Business Review, Sloan Management Review, California
Management Review, Financial Times, Information Week, CIO and
many others. His other books include: The Attention Economy: Understanding the New Currency of Business coauthored with, John C. Beck
(2002); Mastering Information Management coauthored with, Donald A.
Marchand (2000); Mission Critical: Realizing the Promise of Enterprise
Systems (2000); Information Ecology: Mastering the Information &
Knowledge Environment coauthored with, Laurence Prusak (1997) and
Process Innovation: Reengineering Work Through Information Technology (1992).
Decision Diary
A diary which gives an account of decisions taken, along with the assumptions and reasoning behind them. This kind of knowledge facilitates experiential learning and future decision-making.
(See also: LEARNING HISTORY, CAUSAL KNOWLEDGE)
Decision Making
Knowledge is of little use if it is not used to make decisions. Knowledge
management systems are increasingly being applied to decision making.
Such systems should take into account how people take decisions in real
life.
According to Nobel prize winner Herbert Simon, decision making
takes place in four stages:




“Intelligence” involves discovering, identifying and understanding
the problem.
“Design” includes identifying and exploring solutions to the problem.
“Choice” consists of choosing among solution alternatives.
“Implementation” means making the chosen alternative work.
These stages explain how decision making should take place logically. In practice, the influence of various behavioral issues cannot be overlooked. Moreover, the four steps may not happen sequentially; they may
overlap to some extent. And in many cases, decision making takes place
in an iterative fashion, accepting things that work and rejecting those
that do not.
Three key factors that are an impediment to good decisions are information quality, human filters and resistance to change:



Information may not be accurate, complete, consistent or available on
a timely basis.
Managers have selective attention, various biases and focus on some
dimensions of the problem while ignoring others.
Last, but not the least, people are resistant to change.
So, decisions often tend to be a balancing of the firm’s various interest groups rather than the most optimal solution. A knowledge management system should take into account all these factors if it is to become
an effective aid to managerial decision taking.
Decision Support Systems (DSS)
Decision support systems support managers in data collection, analysis
and presentation of output. Such systems help managers in retrieving,
summarizing and analyzing data for the purpose of decision making.
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Knowledge Management from A to Z
DSS may support a large group of managers in a networked environment
with a data warehouse or a single user, desktop application. A computer
program churns through data and with human interpretation, reveals previously hidden trends and patterns, allowing managers to make smarter
and faster decisions. Data collection is typically performed by a transaction processing system. This data is transferred to a model for analysis
using the appropriate software. Finally, the DSS presents the results in a
format that is easy to understand. Graphs are often a useful way of presenting the result. Often, the reports generated by the DSS are used to
build a business case or to persuade other people. So the reports must be
concise, accurate and visually appealing.
DSS must be designed carefully based on customer requirement. Even
the best DSS will not eliminate bad decisions. It goes without saying that
if managers ask the wrong questions or draw the wrong conclusion, DSS
will be ineffective.
DSS have not taken off as rapidly as expected because of the difficulties involved in laying down decision rules, or algorithms, from human
experts. Moreover, many managers, have a mental block about the ability of a computer to take decisions on their behalf.
Declarative Knowledge
Declarative knowledge consists of meaningful concepts, categories, definitions and assumptions.
Deep Smarts
The ability some people can possess to see the whole picture and zoom
in on a problem that others have not identified. Almost intuitively, they
make the right decision. They combine expertise in individual areas with
a systems view. According to Dorothy LEONARD and Walter Swap1, these
are people with deep smarts. Their judgment and knowledge are stored
in their heads and hands. They bring very important knowledge to the
table, so much so that, organizations cannot do without them. These
In his article, “Teaching smart people how to learn,” Harvard Business
Review, May-June, 1991.
46
people know the business, customers and product lines overall and in
depth but their insight is neither documented nor evaluated. When such
people leave their jobs or move on to a new role, their absence is keenly
felt. Experience is the obvious reason that these deeply knowledgeable
people make swift, smart decisions. Having encountered a wide range of
situations over the years, they become a storehouse of knowledge and
can reason swiftly and without a lot of conscious effort. They can identify patterns, trends and anomalies effortlessly.
Defensive Reasoning
A concept introduced by Chris ARGYRIS, a former professor of Harvard
Business School. As expounded by Argyris1, defensive reasoning encourages individuals to keep private the assumptions, inferences and
conclusions that shape their behavior and to avoid testing them in a truly,
independent, objective fashion. When asked to examine their own role in
an organization’s problems, most people become defensive. They put the
blame on someone else. DEFENSIVE REASONING keeps people from identifying and admitting openly what has gone wrong. Companies need to
help managers understand, analyze and reason about their behavior in
more effective ways. Only then can the defenses that block organizational learning be broken.
(See also: CHRIS ARGYRIS, ORGANIZATIONAL LEARNING)
Desktop Conferencing
Videoconferencing using a desktop PC. A small camera (webcam) is
usually mounted on top of the user’s display screen. As communication
technology improves, greater bandwidth becomes available and costs
come down, desktop conferencing can be expected to take off, especially
as it is a more effective way of transferring knowledge than simply using
e-mail or searching through a repository. Where bandwidth availability
is an impediment to transmitting video documents, audio can be used.
In his article, “Designing for Business Benefits form Knowledge Management,” Knowledge Horizon, 2001.
47
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Dialectics
A form of thinking process that emphasizes managing change and transcending opposites. Dialectics goes back to ancient Greece. It is a method
of discovering the truth of ideas by discussion and logical argument and
by considering ideas that are opposed to each other. The starting point of
the dialectical movement is a thesis. In the next stage, comes anti-thesis,
when the thesis is shown to be inadequate and inconsistent. In the third
stage, synthesis, the previous thesis and anti-thesis are reconciled and
transcended. The new thesis then becomes the basis for another dialectical movement.
According to TAKEUCHI and NONAKA, knowledge is created by synthesizing what appears to be opposites and contradictions. It goes through
seemingly opposing concepts such as tacit and explicit, chaos and order,
micro and macro, self and other, mind and body, part and whole, deduction and induction, creativity and control, top-down and bottom-up, etc.
Dialectical thinking can facilitate knowledge creation by transcending
and synthesizing such opposites. For example, tacit and explicit
knowledge are portrayed as polar ends. But they are complementary to
each other, and also inter dependent. The exercise of one form of
knowledge requires the presence and utilization of the other form. There
is some TACIT KNOWLEDGE in every piece of EXPLICIT KNOWLEDGE and
some explicit knowledge in every piece of tacit knowledge. Takeuchi
and Nonaka pointed out that organizations do not merely use information to solve problems. Organizations create and define problems,
develop and apply knowledge to solve the problems, and then further
develop new knowledge through problem solving. In short, an organization is far more than an information processing machine. It is an entity
that creates knowledge through action and interaction. Dialectic
knowledge creation occurs as people in an organization synthesize tacit
and explicit knowledge through interactions with others and the environment.
Dialogue
The role of conversations in creating knowledge is often underestimated.
Through dialogue, differences in perspectives can function as a “think-
ing device,” creating new meaning. According to NONAKA and TAKEUCHI,
the TACIT KNOWLEDGE of an individual or group can be articulated into
explicit knowledge through dialogue. Healthy dialogues share some
common attributes. They allow room for revision or negation. Participants can express their views freely and candidly. Disagreement for the
sake of disagreement is not allowed. There is some degree of information redundancy. Dialogues play a key role in ORGANIZATIONAL
KNOWLEDGE CREATION. Yet their role in knowledge creation and sharing
is often underestimated.
Digital Rights
The rights and conditions of use for a piece of digital content. These
rights may be part of the product’s wrapper, or may be embedded in the
product. Digital rights are used to prevent illegal copying.
DIKAR Model
An approach that seeks to define the discrete components of the
knowledge value chain.
Data, information, knowledge, actions and results (DIKAR) make up
the knowledge value chain.
Data
Information
Knowledge
Actions
Results
The conventional approach starts with data, which through a series of
value adding steps, becomes knowledge. Peter Murray1 however, suggests that in a more dynamic environment, it may be better to work
backwards. Given the desired results, what actions are needed? What
knowledge is needed to perform these actions? What information is
needed to create this knowledge? What is the data to be collected for
generating the necessary information? The role of knowledge manage-
48
Hagel, John III and Brown, John Sleely, The Only Sustainable Edge:
Why Business Strategy Depends on Productive Friction and Dynamic Specialization, Harvard Business School Press, 2005.
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Knowledge Management from A to Z
ment is to marshal knowledge and experience and to integrate them and
develop new capabilities that the market will value.
Discussion List
Sharing information and knowledge among a group of people, using a
single e-mail address. Thus all messages generated during each day can
be grouped together and sent as a single e-mail in a “digest”. More
commonly, it saves the time of having to individually send the e-mail to
each person in the selected group.
Document Management Systems
System that ensures that the hundreds of documents generated each day
in any organization are stored properly for easy retrieval. These systems
make vast amounts of documents easily accessible and adaptable
through the web. Often, such systems incorporate workflow functionality that allows documents to be intelligently routed to select, relevant
people.
A useful document management tool is Microsoft SharePoint. SharePoint allows people to share Microsoft office documents with others
through web pages. SharePoint sites are highly dynamic, unlike usual
websites. Uploading of documents is a simple process. SharePoint also
facilitates meetings, making public announcements, sending alerts and
tracking work items. Instead of routing documents by e-mail, people can
set up a workspace on a SharePoint site. E-mail alerts notify reviewers
when files are uploaded or modified. Reviewers can discuss changes
online. Comments can be tracked and all the changes can be recorded in
version history. Document workspaces are provided to store work-inprogress. A workspace often contains only one document that a team is
working on. A document library is typically used to store multiple documents within a site.
Double-loop Learning
Single-loop learning involves using knowledge to solve specific problems based on existing assumptions and is often based on what has
worked in the past. But double-loop learning — also called generative
learning — goes a step further and questions existing assumptions in
order to create new insights.
(See also: SINGLE-LOOP LEARNING, LEARNING ORGANIZATION)
DSS
See DECISION SUPPORT SYSTEM.
Dynamic Capability Building
In their book, The Only Sustainable Edge, John Hagel III and John Seely
Brown define capability as the recurring mobilization of tangible and
intangible resources for the delivery of distinctive value in excess of
cost. They emphasize that companies must take a more dynamic view of
capabilities. Otherwise, they will find themselves outflanked by more
aggressive competitors. Sustainable competitive advantage will ultimately come from a firm’s institutional capacity to rapidly strengthen its distinctive capabilities and to accelerate learning across enterprise boundaries. As Hagel and Brown mention, “. . . . the primary role of the firm
should be to accelerate the knowledge and capability building of its
members so that all can create even more value. This perspective broadens managerial attention from the tasks of allocating existing resources
to the tasks of deepening knowledge and capability in an increasingly
uncertain environment”. Hagel and Brown suggest three mechanisms to
accelerate capability building:
1. Processes can be outsourced and in combination with offshoring can
give the firm access to specialized capabilities.
2. Distributed networks of specialized companies can also help in mobilizing resources.
3. By bringing together people with diverse backgrounds and skills to
solve business problems, capability building can again be accelerated.
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E
E-learning
Unlike in the past, when people were brought together to one place for
training, e-learning allows learning material and faculty expertise to be
distributed to desktops. With the availability of various technologies,
learning in organizations is undergoing a sea change. E-learning is leading to a fundamental rethinking of the learning process in business environments. E-learning is moving training away from a push-model to a
pull-model. Employees determine what is useful to them. They can learn
as per their convenience and customize training according to their specific needs and circumstances.
According to John Hagel III and John Seely Brown1, e-learning not
only imparts training inputs but also helps shape common points of view
and vocabularies across a distributed and diverse work force. E-learning
can facilitate innovation by enabling people from very different backgrounds to collaborate effectively, using common frameworks and vocabularies. Cisco is one company which has deployed learning portals to
serve the learning needs of its direct sales force, its system engineers as
well as its channel partners. People can easily locate learning modules
that are of the greatest relevance to them. Cisco has also been attempting
to make the whole process more proactive by recommending to employees what kind of learning they must engage in, to be more effective in
the work place. Thus, before a sales person meets a customer in a financial services company, the e-learning system might send a trigger suggesting that he may go through a new learning module that covers features of special interest to financial services companies.
“Building Intangible Assets: A Strategic Framework for investing in
Intellectual Capital”, in Knowledge Management — Classic and Contemporary Works, Edited by Daryl Morey, Mark Maybury and Bhavani
Thuraisingham, University Press, 2001
49
Earl, Michael
Previously professor of Information Management at London Business
School, Michael Earl works at the intersection of business strategy and
IT. Earl has published widely in reputed journals like Harvard Business
Review, Sloan Management Review, MIS Quarterly, and the Journal of
Management Information Systems. His book Management Strategies for
Information Technology became a best seller.
EIS
See ENTERPRISE INFORMATION SYSTEMS.
Enterprise Information Systems (EIS)
A system that attempts to use the existing transaction data and display it
in a form that is easy for top level executives to access. An EIS models
the entire company. The landing page of an EIS is typically a graphical
representation of the company. A CEO can drill down into required areas and ascertain relevant particulars. If there is a specific problem area,
the CEO can do a more focused investigation and pinpoint responsibilities. The primary aim of an EIS is to provide easy access to data for senior executives. Instead of waiting for the information, they can retrieve it
as soon as it is available. An EIS is expensive to create and maintain.
Integrating the data and formatting it to make it user friendly requires
programmers and analysts to anticipate management needs and keep the
system up-to-date. Another issue is that senior managers often find it
more convenient to ask lower level managers for reports instead of trying to retrieve the information themselves.
Epistemology
Framework for categorizing knowledge. There are two kinds of
knowledge — tacit and explicit. TACIT KNOWLEDGE is personal, contextspecific and difficult to formalize, document and articulate. EXPLICIT
KNOWLEDGE can be transmitted in formal, systematic language.
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Experiential Learning
Learning gathered and internalized by experience. Experience is considered life’s greatest teacher. In any company, people learn through experience. Experiential learning can be facilitated in various ways. One way
is to institutionalize the “after action review” throughout the
organization. Essentially, this is a structured approach to reviewing the
learning from an initiative immediately after it is concluded. Another
useful technique is LEARNING HISTORY, a detailed account of what happened during an important event, with accompanying analysis.
MENTORING can also encourage experiential learning. Behavioral issues
play a major role in experiential learning. Allowing learning from failure
must be an integral part of a company’s culture. Otherwise, people will
be reluctant to admit mistakes and share with their colleagues what went
wrong.
Expertise Directory
A database of people and their skills to help users locate experts easily.
An expertise directory is often referred to as “Yellow Pages”. When
combined with a SEARCH ENGINE, it becomes an expert locator. The effective functioning of expertise location systems depends on the quality
of expert profiles uploaded on the database. Expert profiles are often up
to date. Moreover, they may be incomplete and sometimes may also not
tell the full story. Often, people do not articulate clearly what they know.
So in many cases, expertise may have to be identified in other indirect
ways. Expertise can sometimes be inferred from the contents of the documents with which a person’s name is associated. Authorship of a document indicates some familiarity with the subjects it discusses. Activities
such as reading indicate some interest in the subject matter. The e-mails
a person sends out can also be analyzed to write a profile of the person’s
experience. Expertise can also be gauged by asking people whom they
consult on specific issues.
Expert Systems
In case of straightforward business problems, we can create a set of rules
or procedures to follow. A computer can be programmed to follow these
rules/procedures. But the situation becomes more complex when the
problems are less structured and the data is not well defined. Experts are
needed to solve problems involving non-numeric data and complex inter
relationships among the various factors. Special software programs
called Expert Systems are an attempt to simulate these experts.
Expert systems can analyze symptoms and identify the cause. Even
when decisions are less complex, expert systems can speed up the decision making process and thereby improve customer satisfaction. Expert
systems can also facilitate consistent decision making, i.e. reaching the
same conclusion for the same basic situations.
There are three types of expert systems:
1. A rule based expert system has a set of logical rules. The difficulty of
course lies in establishing these rules. Experts do not always find it
easy to express their thoughts in the form of rules. A rule based expert system essentially attempts to connect relatively small chunks of
data based on numbers and key words.
2. A frame based expert system deals with entire frames of data at one
time. A frame consists of related sets of information that people
group together.
3. CASE BASED REASONING is similar to frames. The only difference is
that entire cases are described in one frame. As people face problems
and develop solutions, they write a small case. These cases come in
handy while solving future problems. When a problem is encountered, the expert system searches the recorded cases for similar situations and then retries the solution.
There are some important drawbacks with expert systems. For one,
they can be created only for specific and narrowly defined problems.
When the problem is too complex with too many interactions and too
many rules, it becomes difficult to explicitly express all the interrelationships. It is also not very easy to modify the knowledge base in an expert
system. As the environment changes, the system has to be updated. If
there are many rules in the system with various interrelationships, the
system may have to be designed from scratch, resulting in heavy expenditure. Last but not the least, determining the rules can itself be a
complicated process. To set up an expert system, people are needed who
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understand the process and can express the rules in a form that can be
used by the system. Such people may not be all that easy to locate.
(See also: CASE BASED REASONING)
Expert Work
A term coined by Tom DAVENPORT while categorizing different kinds of
knowledge work. Expert work refers to knowledge work that is largely
individually done by experts. It is highly judgment oriented and dependent on individual expertise. Such work is difficult to structure. It is also
difficult to get experts to use the knowledge of others. Yet, over time, it
has been found that there is scope to use information technology to inject
relevant knowledge into the work process as and when needed by the an
expert. For example, a medical diagnostics system can provide relevant
information, just before the physician is going to write the prescription.
Explicit Knowledge
Knowledge that is documented in books, binders, databases, manuals
and repositories. This type of knowledge can be articulated, codified and
transmitted formally, in a systematic way. Explicit knowledge can be
expressed in numbers, words or sound and shared in the form of data,
scientific formulas, visuals, audio tapes, product specifications or manuals.
For example, an SEI CMM V software company can lay down clearly how software development processes must be carried out. Similarly, a
quality manual can indicate how food must be prepared and served in a
fast food restaurant. New employees can visit the company’s intranet
and familiarize themselves with the organization chart, performance appraisal system, profiles of different business units and their activities.
Explicit knowledge is amenable to the use of information technology.
(See also: CODIFICATION)
Externalization
A term coined by TAKEUCHI and NONAKA, as part of their SECI
(SOCIALIZATION, EXTERNALIZATION, COMBINATION, INTERNALIZATION)
MODEL of knowledge creation. This is the process of converting tacit
knowledge into explicit concepts through metaphors, analogies, hypothesis or models.
Metaphor can be viewed as a way of intuitively understanding one
thing by imaging another thing symbolically. Metaphors help us to see
one thing in terms of something else. Metaphors help in relating concepts that are far apart in our mind or even relate abstract concepts to
concrete ones. As Takeuchi and Nonaka put it, “This creative, cognitive
process continues as we think of the similarities among concepts and
feel an imbalance, inconsistency or contradiction in their associations,
thus often leading to the discovery of new meaning or even to the formation of a new paradigm.”
Contradictions inherent in a metaphor can be harmonized by analogy.
Association through metaphor is driven mostly by intuition and imagery
and does not aim to find the differences between them. On the other
hand, analogy works by rational thinking and focuses on structural /
functional similarities between two things, along with their differences.
(See also: SECI MODEL)
Extensible Markup Language (XML)
See XML.
Extranet
A portion of an organization’s intranet that is opened up for external
Internet access on a selective basis, e.g. for customers or suppliers to
access certain information. Extranets can help in tapping knowledge that
lies outside the organization.
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F
Fuzzy Logic
Fuzzy logic provides solutions to problems requiring expertise that is
difficult to represent in the form of crisp if-then rules. Fuzzy logic recognizes more than simple true and false values. With fuzzy logic, propositions can be represented as partially true or partially false. For example, the statement, today is sunny, might be 100% true if there are no
clouds, 80% true if there are a few clouds, 50% true if it is hazy and 0%
true if it rains all day. The same logic applies to a dirty cloth. Fuzzy logic systems cope with uncertainty to some extent, the way people manage
uncertainty in their day-to-day life. One way people do this is to use subjective, incomplete descriptions. When people say it is hot outside, it is
understood even though the term is subjective. Fuzzy logic systems need
to be trained by experts. Such experts may not be available. And even if
they are available, these experts might not articulate their knowledge
effectively. Fuzzy logic is used in applications such as washing machine
settings, elevator control and some spell checkers (to suggest a list of
probable words to replace a misspelled one).
(See also: ARTIFICIAL INTELLIGENCE)
G
Garbage In Garbage Out (GIGO)
Information technology is only as good as the quality of data and information fed into the system. If the data being fed in, is incomplete or has
errors, the output will be of poor quality.
GDSS
See GROUP DECISION SUPPORT SYSTEMS.
Genetic Algorithm Tools
Tools that help arrive at an optimal solution by examining a very large
number of possible solutions for that problem. The underlying principle
is similar to the way living organisms adapt to their environments. Genetic algorithms facilitate the evolution of solutions to particular problems, controlling the generation, variation, adaptation and selection of
possible solutions, using genetically based processes. As solutions alter
and combine, the worst ones are discarded, while the best ones survive.
Genetic algorithms are useful when decision makers do not know
how to solve the problem but are likely to know the solution when they
see it. Genetic algorithms can considerably simplify the amount of work
required to solve a complex, decision related problem. They are useful
while making decisions where standard rules of thumb are difficult or
impossible to use. These tools tend to be heavily dependent on software
and the nature of the problem. As a result, their usability in other problem domains is somewhat limited.
GE has used genetic algorithms to optimize the design for jet turbine
aircraft engines where each design change may involve changes in up to
100 variables. Genetic algorithms can also be used to optimize production scheduling models.
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Gestalt
Theory which holds that a psychological phenomenon can only be understood if it is viewed as organized, structured wholes. Learning is
regarded by Gestaltists not as associations between stimuli and responses but as a restructuring or reorganizing of the whole situation. In short,
Gestalt emphasizes unity and wholeness. For example, we tend to complete an incomplete picture mentally using our imagination. Gestalt theory explains how people actually absorb and interpret information.
Group Decision Support Systems (GDSS)
System that enables a group of people to work on unstructured problems.
Unlike GROUPWARE and video conferencing which focus primarily on
communication GDSS provides tools and technologies that facilitate
group decision making. GDSS helps make meetings more effective.
GDSS tools also facilitate planning, generating, organizing and evaluating ideas, establishing priorities and documentation of meeting proceedings.
Some of the commonly used GDSS tools are electronic questionnaires, electronic brainstorming tools, tools for voting or setting priorities and policy formulation tools. In traditional decision making meetings, having more than 4-5 people may make the process ineffective and
indeed disruptive in some cases. When GDSS is used, the number of
people taking part in a meeting can increase while productivity also goes
up. Since people can contribute simultaneously, the meeting time can be
used efficiently. Of course, GDSS will not be effective if the composition of the group is not right, the problem is not properly presented, or
facilitation is not effective.
Groupware
The PROCESS of creating and sharing knowledge in any organization
involves collaboration. People come together for complaint resolution,
problem solving, brainstorming, idea generation, etc. These interactions
may occur among people from different departments, spread across geographical locations. Groupware supports such collaboration. The software enables a group of users on a network to collaborate on a particular
project in groups or teams. Groupware provides a virtual space, within
which people can share experiences, conduct meetings, listen to presentations, hold discussions and share documents. Some applications support real time online meetings including video and text based conferencing, synchronous communication and chat. Other applications enable
location of persons with common interests who are candidates to join a
community.
There are three key components in groupware:
1. Communication,
2. Compound documents, and
3. Databases.
To share data effectively, people should be connected to each other
through a network, which must be able to handle large data transfer efficiently. E-mail and scheduling are common applications.
Groupware helps to extend e-mail in various ways. For example, it
helps in sorting and organizing and retrieving e-mails more effectively.
Compound documents are a key focus area for groupware tools.
These documents can contain text, images, graphs, sound and video
clips. Each document can be revised and shared with other members of
the team.
Databases which form another crucial component, enable workers to
share access to the same documents simultaneously. Each member of the
team can work on the same document. Contributions from individuals
are immediately available to the rest of the team. Comments and changes
can be added at any time by team members. These changes are automatically recorded and made immediately available to other team members.
There are security features to decide who can make changes and who
can see documents. Groupware tools are especially useful in automating
the workflow in service-based organizations.
By storing observations, insights and comments by various members
of the team, workers are better equipped to deal with problems in the
future. Groupware minimizes the adverse impact when a knowledgeable
worker leaves the organization. By standardizing on hardware, software
and communication protocols, groupware tools make it possible to create
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ad hoc problem solving teams consisting of workers from different departments.
H
Hansen, Morten
A former professor of Harvard Business School, Morten T. Hansen is
currently Professor of Entrepreneurship at INSEAD. Hansen has done
extensive research on knowledge-based competition, corporate transformation, and building great companies. He has published articles in
leading international academic journals including Harvard Business Review. His research work has been featured in the New York Times, Business Week, The Wall Street Journal, The Economist and Financial
Times, among others. His article “How to Build Collaborative Advantage” received the Sloan Management Review / Pricewaterhouse
Coopers Award for the article that has contributed most significantly to
the enhancement of management practice. Hansen is also the co-author
of an influential article, “What is your strategy for managing
knowledge?” (Harvard Business Review, April 1999).
HTML (Hyper Text Markup Language)
HTML is the language used to format documents for viewing with a
browser on the user’s machine or on a network. HTML tells browsers
how to display type and images to the user and describes responses to
user actions such as the activation of a link by a mouse click. HTML
defines the structure and layout of a Web document by using a variety of
TAGS and attributes. There are hundreds of other tags used to format and
lay out the information in a Web page. Tags are also used to specify hypertext links. These allow Web developers to direct users to other Web
pages with the click of the mouse.
Human Capital
Knowledge, skills and experiences possessed by individual employees.
Human capital includes both explicit conceptual knowledge such as how
to create a budget or how to use an e-mail system as well as more TACIT
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KNOWLEDGE
like how to negotiate a sale or interpret a market trend. A
company’s stock of human capital tells us about the current level of individual skills. By comparing the skill level with that of competition and
what customers demand, gaps can be identified and necessary corrective
steps can be taken.
I
IC
See INTELLECTUAL CAPITAL.
Information
Information is processed data. Data becomes information when it is
summarized, tabulated, processed and checked for errors. It is easier to
make sense out of information than from unprocessed data. Thus the
heights of students in a class may represent data. But if we can tabulate,
summarize and categorize this data, it becomes information. For example, we can consolidate this data into a frequency table consisting of two
columns. The first column can indicate the range of heights (150-160
cm., etc.) while the second may indicate the number of students falling
in the range. Alternatively, a histogram can be plotted that geographically depicts the frequency distribution. Information is something the human mind finds much easier to handle, than raw data. Information is less
cluttered, better arranged and easier to grasp, than data.
(See also: DATA)
Innovative Knowledge
The most valuable knowledge is that which other companies do not
have. Or even if they have, they are not able to leverage as effectively.
Innovative knowledge is needed for a firm to lead its industry and competitors and to significantly differentiate itself from its competitors. Innovative knowledge often enables a firm to change the rules of the game
itself. In the automobile industry, Toyota has leapfrogged competitors
with its knowledge of just-in-time and lean production. In the PC industry, Dell stands apart with its knowledge of the supply chain and in particular the order fulfillment process.
(See also: CORE KNOWLEDGE, ADVANCED KNOWLEDGE)
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Insight
Can be viewed as an act of intuitively sensing the inner nature of something. Insight can also be described as a novel, clear, compelling, understanding of something occurring without direct recourse to memories of
past experiences. In GESTALT psychology, insight characterizes a sudden
reorganization or restructuring of the pattern or significance of events
allowing one to grasp relationships relevant to the solution. In simple
terms, insight is the ability to see and understand the truth about people
or situations. Developing insight involves going below the surface and
arriving at a well thought out explanation for a phenomenon. This involves careful observation and reflection. For example, the insight that
customer demand should pull inventory, has been the guiding principle
of Toyota’s Just-in-Time production system.
(See also: KNOWLEDGE, WISDOM)
Instant Messaging
An increasingly popular way of communication in many organizations.
While commonly associated with informal social groups, the tool is a
useful complement to synchronous communication, for example to interact with peers during a virtual seminar. Unlike e-mails, instant messaging can help in resolving issues and closing action items faster. At the
same time, an instant message is less intrusive than a phone call. One
can keep responding to a message at an acceptable pace, with time lags,
unlike a phone which interrupts the current work.
Integration Work
A kind of knowledge work which is systematic, repeatable and depends
on integration across functional boundaries. In such work, there is scope
for reuse of knowledge. For example, software companies keep libraries
of reusable code. Similarly, automobile companies keep reusable component designs. A term coined by Tom DAVENPORT.
Intellectual Capital (IC)
According to Patricia Seemann, David De Long, Susan Stucky and Edward Guthrie1, intellectual capital has three elements:
1.
2.
3.
HUMAN CAPITAL,
STRUCTURAL CAPITAL, and
SOCIAL CAPITAL.
HUMAN CAPITAL refers to the knowledge, skills and experiences possessed by individual employees. Without human capital, no company
can compete effectively in the market place.
Structural CAPITAL refers to the explicit, rule based knowledge embedded in the company’s work processes, systems, policies, training
documentation or best practices repository. Structural capital also includes patents and copyrights.
Social capital refers to the ability of groups of employees to collaborate and work together. Effective networks of relationships constitute an
extremely valuable, intangible asset that is often overlooked.
Seemann, De long, Stucky and Guthrie have explained the relationship between intellectual capital and knowledge management.
Knowledge management is all about ensuring that intellectual capital is
constantly enhanced, shared, sold or used to generate value. Knowledge
management can be viewed as the deliberate design of processes, tools
and structures to increase and improve the use of knowledge contained
in the three kinds of intellectual capital. Many companies make the mistake of equating knowledge management with structural capital, i.e. implementing shared databases or document repositories. Effective
knowledge management is all about managing, human, structural and
social capital in an integrated way. According to Laurie J. Bassie and
Mark E. Van Buren, managing intellectual capital involves1:
Bassie, Laurie J. and Buren, Mark E. Van. “New Measures for a New
Era”, in Knowledge Management — Classic and Contemporary Works,
Edited by Daryl Morey, Mark Maybury and Bhavani Thuraisingham, University Press, 2001.
51
Knowledge Management — An Introduction to Creating Competitive
Advantage from Intellectual Capital, published by Vision Books, 2003.
50
110
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
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

Knowledge Management from A to Z
Identifying intellectual capital types, needs and requirements.
Creating new intellectual capital and uncovering existing intellectual
capital.
Compiling, gathering, representing, codifying and reorganizing intellectual capital.
Disseminating, distributing and transferring intellectual capital.
Applying, incorporating, reusing, exploiting and leveraging intellectual capital.
Intellectual capital is not the same as intellectual property (IP). The
latter is that part of intellectual capital that is protected by law. Intellectual property includes patents, copyrights and trademarks. Intellectual
property must be unique and not too obvious. Otherwise, it would be
difficult to get a patent or copyright. As Carl Davidson and Philip Voss
put it so well,1 the distinction between intellectual capital and intellectual
property is important. Knowledge does not have to be invented to be
useful to an organization. “Originality is much less important than usefulness.”
Intelligent Routing
Responding to queries is an integral part of any business. Information
technology facilitates intelligent routing of incoming queries. Filtering
can be done on the basis of customer profile, customer requirements,
past history and skills of the customer service agent.
Intention
A concept coined by NONAKA and TAKEUCHI. Intention is an important
enabler of knowledge creation. There should be a clear intention on the
part of the organization about what knowledge is important and the
commitment of resources to developing that knowledge. Without a clear
vision of where it is heading and what kind of knowledge needs to be
developed, an organization will find it difficult to implement knowledge
management. As Nonaka and Takeuchi put it, intention provides the
52
“Tiwana, Amrit, The Knowledge Management Toolkit: Orchestrating IT,
Strategy, and Knowledge Platforms, Prentice Hall, 2002.
most important criterion for judging the “truthfulness of knowledge”.
Without intention, it would be difficult to judge the value of information
or knowledge perceived and created.
Internalization
A term coined by TAKEUCHI and NONAKA, as part of their SECI MODEL to
describe the process of converting explicit knowledge into tacit
knowledge. In this stage, knowledge is applied and used in practical situations and becomes the basis for new routines. Action, practice and
reflection are the building blocks of the internalization process. Internalization essentially converts externalized explicit knowledge back into an
individual’s tacit knowledge.
Thus a Business School professor after reading a book may reflect on
the various concepts covered in the book. He may then attempt to understand whether the examples given in the book will work in a different
context. He may also examine whether the principles mentioned are universally applicable. In the process of reading the book and reflecting on
its contents, knowledge gets internalized. Here, internalization is taking
place not by re-experiencing other people’s experiences but by relating
to those experiences.
(See also: SECI MODEL)
Intranet
A network designed to organize and share information — and carry out
digital business transactions — within a company, using web pages,
browsers, e-mail, news groups and mailing lists. An intranet is accessible
only to those within the organization. Human resource policies, code of
conduct, address book, travel rules, reimbursement of expenses, payroll,
leave applications, etc. are usually available for easy access to employees on an intranet.
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J
Just-in-Case Knowledge Management
Making knowledge available to users just-in-case it is needed. This
saves users the trouble and time of having to search for knowledge. But
users may not perceive much value if the knowledge is not immediately
relevant to the task at hand.
(See also: JUST-IN-TIME KNOWLEDGE MANAGEMENT)
Just-in-Time Knowledge Management
Knowledge is often more valuable when it is delivered when it is needed, rather than being available at all times. It is the dream of all
knowledge management practitioners to make knowledge flow into
work processes as and when it is needed to solve business problems or
facilitate decision making. It is under these circumstances that the full
value of knowledge can be leveraged.
K
K-Spots
The knowledge areas on which a company can concentrate its
knowledge management efforts. These are promising areas which stand
to gain the most through knowledge management. By concentrating on
these areas, business benefits can be reaped fast. In the case of Indian IT
companies, software project management is a good example.
Knowledge
Understanding clarity and insights that we gain through education, practical experience, reflection and observing others. Knowledge goes far
beyond data and information. According to DAVENPORT and PRUSAK, it is
the fluid mix of experiences, values, contextual information, insights and
intuition. It originates in individual minds but over time, gets embedded
in organizational routines, processes, practices, systems, software and
norms.
Information becomes knowledge through:
1.
Comparison:
How does information about this situation compare with
other situations?
2. Consequences: What implications does the information have for decisions and actions?
3. Connections: How does this bit of knowledge relate to others?
4. Conversation: What do other people think about this information?
Though data, information and knowledge may appear to lie on a continuum, there are major discontinuities. Knowledge is fundamentally
different from information. The discontinuity is caused by how new
knowledge is created from received information. To become knowledge,
new insights are internalized by establishing links with already existing
knowledge. Prior knowledge helps us make sense of received information. Once accepted for inclusion, people will internalize new insights
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by linking these with prior knowledge. Hence, new knowledge is as
much a function of prior knowledge as it is of received inputs.
Knowledge helps us to understand phenomena, make predictions and
deal with situations we may not have encountered before. Knowledge is
actionable information. It facilitates decision making, problem solving
and developing new concepts or processes. Much of valuable knowledge
is difficult to document or capture in databases. It remains in the minds
of the people. This is called TACIT KNOWLEDGE. Such knowledge is best
transferred through human interaction. Knowledge which can be
codified is called EXPLICIT KNOWLEDGE. Technology is a major enabler
in the dissemination of explicit knowledge. Knowledge can also be categorized in other ways: Technological business / environmental, operational / strategic, low perishability, high perishability. intuition, ground
truth (whether it works or not), judgments, experience, values, assumptions, beliefs and intelligence are the various components of knowledge.
Unlike information, knowledge has a component of judgment
attached to it. We use knowledge to make decisions. In making decisions, we use our judgment. Knowledge is largely derived from experience. Experience helps people develop rules of thumb and respond to
new problems more effectively. Usually, business processes are based
on deeply ingrained, unarticulated assumptions and values. These
beliefs, values and assumptions are integral components of knowledge.
Knowledge also contributes to corporate intelligence. As Amrit Tiwana
mentions1:
“When knowledge can be applied, acted on when and where needed,
and brought to bear on present decisions and when these lead to better performance or results, knowledge qualifies as intelligence. When
it flows freely throughout a company, is exchanged, grows and is validated, it transforms an informated company into an intelligent
enterprise.”
(See also:
DATA, INFORMATION, EXPLICIT KNOWLEDGE and TACIT
KNOWLEDGE).
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Zack, Michael H., “Managing Codified Knowledge”, Sloan Management Review, Summer 1999, pp. 45-58.
Knowledge Acquisition
The process of eliciting and formally coding tacit knowledge into facts
and rules and entering them in a knowledge base. Knowledge acquisition
is the process of developing insights and skills. Intelligent databases,
electronic whiteboards, artificial intelligence tools and data warehousing
are some of the technologies that can support knowledge acquisition.
Knowledge Activities
Refers to the various kinds of tasks done by knowledge workers: finding
existing knowledge, creating new knowledge, packaging knowledge,
distributing knowledge and applying knowledge. The common thread
running through these activities is that they primarily involve thinking
and information processing as opposed to physical work.
Knowledge Archaeology
The process of retrieving an organization’s historical knowledge that has
become lost or inaccessible.
Knowledge Asset
A piece of knowledge that has some intrinsic or extrinsic value. A proprietary methodology, a patent or a copyright fall into this category.
Knowledge Audit
Determining what knowledge an organization has, who has it and how it
flows through the enterprise. A knowledge audit can show what changes
are needed in organizational and personal behavior, business processes
and enabling technologies so that knowledge can be applied to strengthen the competitive position of the firm. A successful knowledge audit
can identify intellectual assets of value to the company. It can point out
improvements to existing processes for knowledge creation and sharing.
An audit can also identify people who have been acting as barriers to
knowledge proliferation, whether inadvertently or on purpose. Thus a
knowledge audit not only helps to determine where knowledge exists
within organizations, but may also be seen as a type of roadmap for pro-
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cess improvement. A knowledge audit can cover various aspects of
knowledge management:






Acquisition and Learning,
Storage and Maintenance,
Application and Exploitation,
Dissemination and Transfer,
Knowledge Creation, and
Performance Measurement.
In general, a knowledge audit would proceed systematically along the
following lines:




the identification of knowledge needs through the use of questionnaires, interviews and focus groups;
the development of a knowledge inventory mainly focusing on the
types of knowledge available; where this knowledge is located; how
it is maintained and stored, what it is used for and how relevant it is;
analysis of knowledge flows in terms of people, processes and systems; and
the creation of a knowledge map.
Knowledge audit, if done properly, can facilitate the following:








identifying the knowledge needed to support overall organizational
goals and individual and team activities;
understanding the extent to which knowledge is being effectively
managed and where improvements are needed;
understanding the knowledge that exists in the organization and how
that knowledge moves around, across the organization;
understanding knowledge gaps and duplication;
identifying pockets of knowledge that are not currently being used
effectively;
identifying BEST PRACTICES and barriers to knowledge sharing;
preparing an inventory of knowledge assets, making them more visible and more measurable and accountable and giving a clearer understanding of the contribution of knowledge to organizational performance; and
providing vital information for the development of effective
knowledge management programs and initiatives that are directly rel-
evant to the organization’s specific knowledge needs and current situation.
Usually, organizations are unaware that they require an audit at all.
Wiig (1993) has identified several signs that an organization requires a
knowledge audit:





Information overload or lack of information.
Lack of awareness of knowledge or information available in the organization.
Knowledge duplication through different departments; reinventing
the wheel.
Common use of out of date knowledge or knowledge with no quality
or value.
Not knowing where to find appropriate knowledge or expertise.
Know-bot (Knowledge Robot)
An intelligent agent that gathers or exchanges knowledge from other
agents or computer systems based on the user’s criteria. A Know bot is a
kind of Bot. A Bot interacts with other network services intended for
people, just like a real person. A typical use of Bots is in gathering information. It can also dynamically interact with a site. Some Bots can
respond to questions asked in English and report the weather, sports
score, etc. Bots can also be used maliciously, for example, to attack a
website.
Know-how
The ability to go beyond factual information and leverage knowledge to
deal with unexpected situations that ordinary people would find difficult
to deal with. In cricket, for example, a great fast bowler knows when to
fool the batsman by bowling a slower delivery. An experienced driver
knows when not to overtake a vehicle ahead. An expert negotiator
knows when to maintain silence and let the other party talk. A good
teacher can understand a question which a student is finding it difficult
to articulate. Know-how is gained through learning by doing. Know-how
is context dependent and difficult to codify and is usually embedded as
organizational routines in the organization’s structure, communication
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channels, problem-solving methods and planning and management systems. Know-how is so innately routinized that it tends to be difficult to
transfer across companies.
(See also: KNOW WHAT, KNOW WHY).
Know-what
The level of learning representing cognitive knowledge. It is basic
knowledge that does not give a competitive edge. A good example
would be reading a book on negotiation. Unless the principles mentioned
in the book are actually applied in practice, the knowledge may have
little value. One cannot become a good negotiator merely by reading a
book.
Know-why
A system of knowledge about a causal relationship formulated using a
certain number of variables, developing a good understanding of how
they work and what impact they have. Know-why is shaped through
learning-by-studying, with repeated experiments and simulations controlling various sources of influence.
(See also: CAUSAL KNOWLEDGE)
Knowing-Doing Gap
The gap between knowledge and acting on it. Knowledge is of little use
unless we do something with it. According to Stanford professors, Jeffrey Pfeffer and Robert Sutton, the gap between knowing and doing is
more important than the gap between ignorance and knowing. Today,
knowledge is easily available. There are knowledge brokers like consulting firms who specialize in collecting knowledge about management
practices, storing it and then transferring the information to those who
need it. Better ways of doing things cannot remain secret for long. In
most cases, however, the knowledge that is successfully transferred
through seminars, training programs and consulting, is not implemented.
Talking dominates action in many companies. It is the companies which
can bridge the knowing-doing gap that emerge winners in the market
place.
Knowledge Base
A knowledge base consists of basic data and a set of rules. In most situations, an inference engine applies new observations to the knowledge
base and analyses the rules to reach a conclusion. A knowledge base
consists of data along with the rules, logic and links among data elements.
Usually, it contains less structured and more descriptive data. For example, in medicine, a knowledge base might include terms like “severe
headache” or “severe abdominal pain”.
Knowledge Business
Business which leverages knowledge to create value for customers. All
work involves some amount of knowledge. But in truly knowledge
businesses, the core activity is processing data into information and
knowledge that in turn creates value for customers. According to
Michael Zack, knowledge based organizations have four characteristics.
Such organizations spend substantial time on application of existing
knowledge and creation of new knowledge. The boundaries of
knowledge based organizations are blurred. They seek knowledge from
customers, vendors, alliance partners and even competitors. Knowledge
based organizations view knowledge as a key resource and keep asking
what knowledge is needed to execute the company’s strategy. These
companies make conscious attempts to bridge knowledge gaps. Last but
not the least, knowledge based organizations take a different perspective
compared to other equivalent organizations. They take into account
knowledge in every aspect of their operations and treat every activity as
a potentially knowledge enhancing act.
Knowledge Centre
A central function created by a company for managing knowledge resources. A typical knowledge centre will manage various knowledge
resources — documents, databases, intranet content, expertise directories, etc. McKinsey, the consulting company, has a large knowledge
centre in Gurgaon. This centre supports McKinsey consultants all over
the world by providing them industry and company related information.
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Knowledge Champions
People in different business units, divisions and functions, who support
the central knowledge management team in implementing various
knowledge management initiatives.
Knowledge Enablers
Knowledge creation and sharing are enabled under certain conditions:






A high level of trust prevails in the company.
Team based collaborative work is encouraged.
Individuals enjoy considerable autonomy.
Accountability exists at the group, not individual level.
Co-operation is rewarded.
There is a strong focus on customer satisfaction.
Culture is clearly one of the most important conditions for the success of a knowledge management project. It is the hardest factor to build
from scratch. An enabling culture has several different components.
Employees must be bright and intellectually curious. They must be willing and free to explore. Knowledge-creating activities should be encouraged by the top management. Failure during experimentation should not
be penalized heavily.
Knowledge Engineers
Professionals who play a key role in converting the TACIT KNOWLEDGE
of experts into EXPLICIT KNOWLEDGE. Knowledge engineers are trained
to deal with experts to derive the rules needed to create an expert system.
These engineers also convert the data and rules into the format needed
by the expert system. In some systems, there are if-then rules, others use
decision trees, yet others link frames. Knowledge engineers are recommended when several experts are involved and it is expected that a lot of
time will be taken to develop the system.
Knowledge Growth Framework
Bohn has identified eight stages of knowledge growth.

Knowledge does not exist.

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




Knowledge is primarily tacit.
Knowledge is mostly written.
Knowledge is contained in methodologies. Records of processes and
outcomes are maintained.
Knowledge is embodied in operating manuals.
Knowledge is found in empirical equations.
Procedures and algorithms exist. There is codification in computer
software and process manuals.
Knowledge management becomes a natural part of work processes.
This stage represents the ideal.
Indeed, in companies with the most mature knowledge management
practices, each business process would be entrusted with managing
knowledge. There would be no need for a separate knowledge management function.
Knowledge Harvesting
The process of making TACIT KNOWLEDGE more explicit, by capturing
people’s knowledge in documents.
Knowledge Integration
Combining separate knowledge management programs into a more
complete whole. This is a challenge that most organizations face.
Knowledge management programs are more often than not, piecemeal
and fragmented.
Knowledge Interrogators
Persons responsible for managing the content of organizational
knowledge as well as its technology. Knowledge interrogators maintain
the database, remove obsolete documents and connect the users with the
information they seek.
Knowledge Management Projects
It is often difficult to launch a full blown knowledge management initiative across an organization. A better way might be to introduce a series
of short burst knowledge management projects that can yield quick results. Knowledge management projects must be planned and executed
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carefully. Managing knowledge management projects is quite different
from managing other projects such as software development. Knowledge
is naturally fluid and closely linked to the people who hold it. This means
knowledge projects cannot be structured as tightly as other projects.
Success in the initial projects taken up is important to build the required momentum for knowledge management. Knowledge management projects are more likely to succeed if they start with a recognized
business problem that relates to knowledge. That is what industry people
call the “pain areas”. Customer defections, poorly designed products,
loss of key personnel, or a lower “win rate” for service engagements are
all business problems that might be traced to poor knowledge management. Attacking these problems and using the business value of solving
them as justification for knowledge management initiatives are all good
ways to build momentum.
It is often non-core or feeder processes that benefit from knowledge
management most according to a survey done by the Cranfield School of
Management. These feeder processes do not generate income but
provide significant inputs to the main processes. Such processes often
involve a wide range of knowledge and expertise that must be mobilized
in a short time span. In these processes, documents and workflow are
usually important.
The following factors can contribute to the success of a knowledge
management project:





A knowledge-oriented culture;
Technical and organizational infrastructure;
Senior management support;
Clarity of vision and language; and
Suitable metrics.
Knowledge projects need the requisite technology and organization
infrastructure. Technological infrastructure is easier to put in place.
Building an organizational infrastructure means establishing a set of
roles and structures from which individual projects can benefit. Many
companies find this difficult to do. Some firms have been able to establish multiple levels of new roles, from chief knowledge officers to
knowledge project managers to knowledge reporters, editors, and
knowledge network facilitators.
(See also: CHIEF KNOWLEDGE OFFICER)
Knowledge Mapping
The process of identifying where knowledge lies in an organization. A
map may be portrayed in many visual formats, such as a hierarchical tree
or a node and link diagram. Knowledge mapping is usually carried out
as part of a KNOWLEDGE AUDIT.
A knowledge map plays a crucial role in identifying where
knowledge resides in the organization. Developing a knowledge map
involves locating important knowledge in the organization and then publishing a list or picture that shows where to find it, including both people
as well as documents and databases.
The main benefit of a knowledge map is to indicate whom to contact
when some expertise is needed. Rather than managing with imperfect
answers by contacting people who are the most accessible, the employee
with a good knowledge map has relatively easy and quick access to the
most appropriate knowledge sources in the organization. Without a
knowledge map, it would be difficult or impossible to find such persons.
A firm’s organizational chart cannot substitute a knowledge map.
Most organizational charts are hierarchical, describing formal reporting
structures and usually with far more detail at the top than at the bottom.
But key knowledge may exist anywhere in the company. Indeed, cutting
edge technical knowledge is more likely to be found at the lower levels.
Also the most avid knowledge seekers almost always need to cross departmental boundaries and ignore reporting structures to get what they
need.
Technology can play a major role in constructing knowledge maps.
Online YELLOW PAGES can allow users to search by topic or key word,
making it easy to locate and compare potential knowledge sources across
the organization. Moreover, an electronic map can be revised frequently
unlike a printed one. This is a huge advantage in a rapidly growing organization. Since successful knowledge transactions depend so heavily
on trust and compatibility, personalizing the entries can make the map
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more effective. In many companies, Knowledge Yellow Pages show a
photograph of the person listed. A few organizations include a brief video clip.
Organizational knowledge maps are political documents as well. If
knowledge is genuinely important to an organization and those who
have it are recognized and rewarded, then the knowledge map will be a
picture of status and success as well as a knowledge locator. So, political
issues cannot be skirted. Indeed, if politics plays no part in a knowledge
mapping exercise, it is an indication that people are not taking the exercise seriously.
(See also: KNOWLEDGE AUDIT, SOCIAL NETWORKS).
Knowledge Markets
Markets where knowledge is exchanged, bought and bartered like any
other commodity. Like markets for goods and services, the knowledge
market has buyers and sellers who negotiate to reach a mutually satisfactory price for the goods exchanged. There are also brokers who bring
buyers and sellers together. Knowledge market transactions will occur
when the participants believe that they will benefit in some way. Tom
Davenport and Larry Prusak have given an excellent account of how
knowledge markets function in their book, Working Knowledge.
Knowledge buyers are usually people trying to solve unusual or
complex problems. They seek knowledge to make a sale, do a task more
efficiently; improve their skills or make better decisions. In short, they
want knowledge to do their work more effectively.
Knowledge sellers are people with a reputation for having substantial
knowledge about a process or subject. Although virtually everyone is a
knowledge buyer at one time or another, not everyone may be a seller.
Some people are skilled but unable to articulate their tacit knowledge.
Others have knowledge that is too specialized, personal, or limited to be
of much value to others. Some people may possess valuable knowledge,
but may be unwilling to share their knowledge. A knowledge seller is
typically motivated by one or more of three factors: reciprocity, repute,
and altruism.
Knowledge sellers will share knowledge enthusiastically if they expect the buyers to be willing sellers at a future point of time. Knowledge
sellers usually want recognition from others. Having a reputation for
knowledge sharing makes achieving reciprocity more likely. Having a
reputation as a valuable knowledge source can also lead to job security,
career advancement, visibility within the organization and all the rewards and trappings of an internal guru.
Altruism may also motivate knowledge sharing. After a certain age,
some people have an urge to pass on what they have learned to others.
Firms can encourage this tendency by formally recognizing mentoring
relationships and giving managers time to pass on their knowledge.
Knowledge markets are shaped by the social and political realities
prevailing in the organization. If the political reality of an organization
allows knowledge hoarders to thrive, there is no incentive for people to
share their expertise. If it is considered a sign of weakness or incompetence within the culture of an organization to admit one cannot solve a
problem, then the social cost of “buying” knowledge will be too high.
Once again, the knowledge market won’t operate well. The notinvented-here mentality, i.e. the willingness to accept an idea or innovation from another department is another barrier to knowledge sharing. A
variation is the class barrier, an unwillingness to give knowledge to or
accept it from people in the organization who have relatively low status.
Three factors in particular can cause knowledge markets to operate
inefficiently in organizations:



Incompleteness:
People may not know where to find their own company’s existing knowledge.
Asymmetry: Abundant knowledge on a subject in one department of
an organization, may coexist with a shortage somewhere else. This
makes reciprocity based knowledge sharing difficult.
Localness of Knowledge: People usually get knowledge from their
neighbors, as they know and trust them more. Face-to-face meetings
are often the best way to get knowledge. Reliable information about
more distant knowledge sources is usually not available. Also, mechanisms for getting access to distant knowledge tend to be weak or
non-existent. People will be happy with whatever knowledge the person in the adjacent cubicle may have, rather than try to discover who
in the company may know more.
Trust is particularly important in knowledge exchange. Top management must consciously promote trust in various ways:
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1. Trust must be visible: Members of the organization must actually see
people get credit for knowledge sharing.
2. Trust must be ubiquitous: Trust should pervade the organization. If
part of the internal knowledge market is untrustworthy, the market
becomes asymmetric and less efficient.
3. Trustworthiness must start at the top: Trust tends to flow downward
through organizations. Only if top managers are trustworthy, will
trust permeate the whole firm.
Informal markets play an important role in the buying and selling of
knowledge. Probably the best knowledge market signals flow through
the informal communities of professionals that develop in organizations.
Within these webs, people ask each other who knows what and who has
previously provided knowledge that turned out to be reliable and useful.
If the person they approach doesn’t know an appropriate seller, it is quite
likely that she might know someone else who does.
Informal networks engender trust because they function through personal contact and word of mouth. A recommendation that comes from
someone we know and respect within the firm is more likely to lead us
to a trustworthy seller with appropriate knowledge than would a cold
call based on the organizational chart or corporate phone directory. Such
informal networks are also dynamic. Since people in the network communicate regularly with one another, they tend to update themselves as
conditions change. People share information about who has left the
company or moved to new projects, who has recently become a useful
source of knowledge, and who has become reticent or less accessible. Of
course, informal networks are not readily available to all those who need
them. Their viability depends on chance conversations and local connections that sometimes work well but may not as well on other occasions.
So formal markets also have a role to play in knowledge exchange.
Which is why the intranet, forums and seminars will continue to play an
important role in facilitating knowledge creation and sharing.
Knowledge Metrics
Indicators to judge the impact of knowledge management initiative and
presentive. Like any initiative, knowledge management will make an
impact only if its benefits can be quantified.
What constitutes success in knowledge management? The impact of
knowledge management on financial performance is often indirect, rather than direct. Economic returns from knowledge may also not be easy
to quantify. So we must rely on more general indicators of success. Yet,
there should be some metrics to ensure that knowledge management
efforts are properly channelized. Some of the attributes that can be used
to define success in knowledge management are:

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


Comfort throughout the organization with the concept of knowledge
management.
Growth in the resources attached to the project, including staffing and
budgets.
Growth in the volume of knowledge content and usage (for example,
the number of documents in repositories and the number of downloads and number of participants in discussion forums).
The likelihood that the project will be sustaining beyond a particular
individual or two, that is, the project is an organizational initiative.
Some evidence of financial return, either for the knowledge management activity itself or for the larger organization. This linkage
need not be rigorously specified and may be only perceptual.
Knowledge Networking
The process of sharing and developing knowledge through technology
and human interaction. Exchange of e-mails, group discussions, seminars, online forums, wikis and even blogging facilitate knowledge networking. The philosophy here is that knowledge management is facilitated by the interaction of ideas and people, instead of depending totally
on passive forms of knowledge sharing such as downloading documents
from a repository.
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Knowledge Object
A piece of knowledge held in a well-defined and structured format, such
that it is easy to replicate and disseminate. A set of standard operating
procedures is a good example.
Knowledge Packaging
Filtering, editing, searching and organizing pieces of knowledge. Journalists and research analysts do this kind of work. The task involved in
knowledge packaging must not be underestimated. It usually involves
careful understanding of what has been already documented and representing it in a user friendly format.
Knowledge Product
A product which consists almost entirely of information or knowledge.
Imaginative thinking can make even commodities knowledge intensive,
if not knowledge products. By wrapping information around commodities, companies can create “intelligent products”. Thus, Cemex has converted cement into an information business while Fedex has done this in
case of document movement. These two companies have embedded IT
into various business processes especially logistics and tracking so that
the value comes not from the basic products / services but from the
knowledge surrounding them.
Knowledge Recipe
The process of using existing knowledge assets as inputs and combining
them in distinctive ways to create useful outputs and outcomes. Companies like IBM are good at creating and using reusable components.
Knowledge Refining
The process of filtering, aggregating and summarizing knowledge drawn
from various sources.
Knowledge Repository
A store of knowledge documents and artifacts. The term typically refers
to explicit forms of knowledge, such as documents and databases. The
attributes of a good repository are comprehensiveness, taxonomy (classification), structure and an efficient search facility.
Once TACIT KNOWLEDGE is conceptualized and articulated, it can be
converted into document form. These documents can be kept in a repository. The quality of documents can be assessed by the number of downloads, the number of times the document has been cited and judgments
by experts. Besides written documents, audio and video recordings are
also possible.
According to Michael ZACK1 repositories can support integrative and
interactive applications.
Integrative applications mean explicit knowledge flows into and out
of a repository. The repository is the prime medium for knowledge exchange.
Interactive applications mean producers and users come together.
The repository is a byproduct of interaction and collaboration rather than
the primary focus of the application.
At one extreme, users and producers do not belong to the same practice community. This can be called electronic publishing. At the other
extreme, users and producers belong to the same community and together work to integrate and build on their collective knowledge. This can be
called an integrated knowledge base. A good example is a best practices
database.
Electronic publishing can be highly cost effective. But an integrated
knowledge base provides better support for solving problems, innovating
and leveraging opportunities. The greatest impact may come from combining the two.
Knowledge Representation (KR)
A term commonly used to refer to representations intended for processing by modern computers. In the 1980s, work began on the development of formal KR languages and systems. The “Cye” project worked
on encoding the information a reader needed in order to understand an
encyclopedia. Prolog and KL-One programming languages facilitated
KR. Then came XML. Now the SEMANTIC WEB is growing in size. In
Davis, Randall; Shrobe, Howard and Szolovits, Peter. “What is a Knowledge
Representation?” Artificial Intelligence, Spring 1993.
54
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Knowledge Management from A to Z
SEMANTIC NETWORKS,
each node represents a concept and arcs are used
to define the relationships among the concepts
Efforts are on to represent knowledge in the same way that it is represented in the human mind and to represent knowledge in the form of
human language. But we still do not know how knowledge is represented in the human mind. We also do not know how to manipulate human
language in the same way the human mind does it.
According to Randal Davis, Howard Shrobe and Peter Szolovits of
MIT1, KR must be understood in terms of the five distinct roles it plays:





KR acts as a surrogate:
Reasoning goes on internally but the things
we wish to reason about lie externally. The representation is of things
that exist in the external world. The correspondence between the surrogate and the intended referent is the semantics for the representation. The surrogate must be close to the real thing.
KR is an approximation of reality: Each representation attends to
some things and ignores others. Essentially we decide how and what
to see in the world. This helps us to bring some parts of the world into sharp focus while blurring others.
KR is a fragmentary theory of intelligent reasoning: The representation typically incorporates only a part of the insight or belief that motivated it. The insight or belief is in turn only a part of the complex
and multi faceted phenomenon of intelligent reasoning.
KR is a medium for efficient computation: Reasoning in machines is a
computational process. In other words, to use a representation, we
must compute with it.
KR is the means by which we express things about the world, the
medium of expression and communication in which we tell the machine about the world:
So the questions to be raised here are: How
well does the representation function as a medium of expression?
How general is it? How precise? How easy is it for us to talk or think
in that language? What kinds of things can be easily communicated
in the language? What things are difficult to communicate?
55
Davenport, Thomas H., Thinking For a Living, Harvard Business School
Press, 2005.
All the roles mentioned above are important. Ignoring any one of
them may lead to serious inadequacies.
(See also: SEMANTIC NETWORKS)
Knowledge Sharing
The process of disseminating and making available what is already
known. This is a major challenge in large organizations which often do
not know what they know. Knowledge sharing is largely a cultural issue.
The organization must encourage people to part with their knowledge
and reward them for doing so. Of course, efficient knowledge sharing
also needs the appropriate IT and communications infrastructure including e-mail, groupware and video conferencing. Without such infrastructure, knowledge sharing cannot be scaled up effectively in large, geographically dispersed organizations.
Knowledge Utilization
Using accumulated knowledge to tackle problems, develop new products
and deal with unfamiliar situations. Knowledge is of no use unless it is
applied to solve business problems. Thus the effectiveness of a
KNOWLEDGE REPOSITORY must be assessed less by the number of documents available and more by the number of downloads.
Knowledge Value Chain
A sequence of knowledge processes including creation, organizing, dissemination and use that create value from knowledge stocks.
Knowledge Work Management
Process of managing knowledge work to ensure its effectiveness. In the
knowledge economy, managing knowledge work is becoming a huge
challenge. Managing knowledge workers demands a change in paradigm. According to Tom DAVENPORT1, the specific changes required,
include moving from organizing hierarchies to organizing communities,
In his article, “Building a Learning Organization,” Harvard Business
Review, July-August 1993, pp. 78-93.
56
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Knowledge Management from A to Z
from evaluating visible job performance to assessing invisible
knowledge achievements, from supporting the bureaucracy to fending it
off and from relying on internal personnel to considering a variety of
sources. In many ways, managing knowledge work is more challenging
than doing knowledge work. Knowledge work management must strike
a fine balance between leaving knowledge workers free to do their work
and monitoring them to understand how they spend their time and how
they can be made more productive, by imposing some amount of discipline.
Knowledge Workers
People who have a high degree of expertise, education or experience.
The primary purpose of their jobs involves the creation, distribution or
application of knowledge. All jobs involve some amount of knowledge.
But this may not make everybody a knowledge worker. According to
Tom Davenport, people can be called knowledge workers when the role
of knowledge is central to their job. That means they must be spending
considerable amount of their time on thinking and information processing.
Knowledge Wrapper
A term coined by David Skyrme. A knowledge wrapper accurately
describes the contents within. It holds metadata in a standard format and
may hold encrypted digital rights information. Wrappers typically
include factual information, such as formats and size and subjective information such as reviews and quality rating, plus some elements of
promotion. A good wrapper must be attractive to entice buyers, but it
must also be informative and accurate. Unlike physical goods,
knowledge cannot be returned after the wrapper has been opened. So a
knowledge provider may offer a free trial period or a money back guarantee if the buyer is not satisfied. Online bookstores and databases are
often marketed this way.
KR
See KNOWLEDGE REPRESENTATION.
L
Learning History
A narrative which captures same important knowledge in the form of a
story. Sometimes knowledge is communicated more effectively through
a convincing narrative that is delivered with elegance and passion. In
such cases it may be better to capture the knowledge in the form of a
story, instead of trying to codify it in a rigidly defined structure / template.
A learning history is a written narrative of a company’s recent set of
critical episodes such as a major change initiative, a radical process innovation, or a successful product launch. The document is presented in
two columns. In the right hand column, relevant events are described by
people who took part in them, were affected by them or observed them
from close quarters. The left hand column contains analysis and commentary by learning historians, consisting of consultants, academics and
knowledgeable insiders.
Learning history can be used as the basis for group discussions,
which provide opportunities for collective reflection. They raise issues
that people would like to talk about but have not had the courage to discuss openly. These discussions facilitate knowledge sharing, helping
build a body of generalizable knowledge about what works and what
does not.
Learning Management System (LMS)
A system which provides tools for managing, delivering, tracking and
assessing various types of employee learning and training. LMS consolidates mixed-media training, automates the selection and administration
of courses, assembles and delivers learning content, and measures learning effectiveness. Sophisticated systems can correlate performance-onthe-job data with training data. An LMS is indispensable for a large,
geographically dispersed knowledge organization.
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Learning Organization
An organization that realizes its success depends on continuous learning
and modifying its behavior on an ongoing basis. According to David. A.
Garvin1, a learning organization works deliberately to become good at
creating, acquiring, interpreting and retaining knowledge and then modifying its behavior to reflect new knowledge and insights. The concept
originated from Peter SENGE’s 1990 book The Fifth Discipline: The Art
and Practice of the Learning Organization. A learning organization has
in place systems, mechanisms and processes that are used to continually
enhance its capabilities by picking up new knowledge and adapting to
the environment.
All organizations learn but the effectiveness of learning varies from
one to another. The key to effective learning lies in aligning individual
and collective learning with the strategic intent of the firm. Effective
organizational learning happens when explicit management efforts are
made to build knowledge assets that support the firm’s strategy.
According to Garvin, learning organizations are skilled at:
1.
2.
3.
4.
5.
Systematic problem solving;
Experimentation with new approaches;
Learning from own experience and past history;
Learning from the experiences and BEST PRACTICES of others; and
Transferring knowledge quickly and efficiently throughout the
organization.
As Garvin explains, organizational learning takes place in three overlapping stages:


57
The first step is cognitive. As they get exposed to new ideas, people
expand their knowledge and begin to think differently.
The second step is behavioral. Employees begin to internalize new
insights and alter their behavior.
Reinhardt, Rudiger. “Knowledge Management: Linking Theory With
Practice” in Knowledge Management — Classic and Contemporary
Works, edited by Daryl Morey, Mark Maybury and Bhavani Thuraisingham, University Press, 2001.

The third step is performance improvement with changes in behavior
leading to measurable improvements in results: superior quality, better delivery, increased market share and other tangible gains.
What NONAKA and TAKEUCHI call, “the knowledge creating company,” seems to be for all practical purposes, the learning organization. As
Nonaka has mentioned, in such a company, inventing new knowledge is
not a specialized activity. It is a way of behaving, a way of being.
Everyone in such a company is a knowledge worker and contributes to
the learning process.
Rudiger Reinhardt1 has identified different levels of organizational
learning (See Table given below):
Learning Levels
Individual learning
Team learning
Organizational learning
Inter organizational learning
Learning Types
Single loop learning
Double loop learning
Deutero learning
Learning Modes
Cognitive perspectives
Cultural perspectives
Action perspectives
Learning Process
Identification / creation
Diffusion
Integration
Modification
Action
ARGYRIS
and Schon describe three types of organizational learning:
Single-Loop Learning: Errors may be detected and corrected but firms
carry on with their present policies and goals. Single-loop learning is
58
In their article “Managing Professional Intellect,” in Harvard Business
Review, March-April, 1996.
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Knowledge Management from A to Z
essentially lower level learning which does not challenge conventional
wisdom or alter the fundamental nature of the organization’s activities.
Double-Loop Learning: Besides detecting and correcting errors, the
organization may question and modify existing norms, procedures, policies and objectives. So double-loop learning is also called higher-level
learning, generative learning (or learning to expand an organization’s
capabilities), and strategic learning. Strategic learning is “the process by
which an organization makes sense of its environment and exploits the
opportunities unfolding.
Deutero Learning: Deutero learning or secondary learning is learning
which results incidentally as a result of learning something else rather
than as the result of a conscious effort. In particular, this is one of the
aspects of enculturation, when values, norms and styles of learning are
absorbed without being taught and may be crucial in determining a person’s future behavior and learning patterns. Such learning includes
learning that results from the reflection of learning processes and usually
is a prerequisite for changing norms, values and assumptions.
Leonard, Dorothy
A well-known scholar in the area of knowledge management. Dorothy
Leonard has done considerable research on managing knowledge for
innovation and stimulating creativity in group settings. Her articles have
appeared in academic journals (e.g., “Core Capabilities and Core Rigidities in New Product Development” awarded Best Paper by Strategic
Management Journal for sustained impact on the profession), practitioner journals (e.g., “Deep Smarts” in Harvard Business Review) and books
on technology management (e.g., “Guiding Visions” in The Perpetual
Enterprise Machine). Her book, Wellsprings of Knowledge: Building
and Sustaining the Sources of Innovation, published in 1995, has been
widely acclaimed and translated into several languages. Her book, When
Sparks Fly: Igniting Group Creativity, (co-authored with Walter Swap)
published in 1999 has also been widely translated and awarded the Best
Book on Creativity by the European Association for Creativity and Innovation. Her latest book (with Walter Swap) is Deep Smarts: How to
Cultivate and Transfer Enduring Business Wisdom, published in January, 2005.
(See also: CREATIVE ABRASION, DEEP SMARTS)
Lessons Learned
Lessons learned are concise descriptions of knowledge derived from
experiences. These lessons often reflect on what went right, what went
wrong, and what can be done to make the products and processes of the
organization more appealing or effective in the future. These lessons can
be communicated through mechanisms such as storytelling, debriefing
etc, or summarized in databases.
(See also: LEARNING HISTORY)
LMS
See LEARNING MANAGEMENT SYSTEM.
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M
Management Information Systems (MIS)
Systems that help managers monitor and control the operations of a
business. MIS produce reports on a regular basis, based on data extracted and summarized from the company’s underlying transaction processing systems. For example, a report may show sales by region. Sometimes MIS reports are exception reports. Unlike DECISION SUPPORT
SYSTEMS (DSS) which support semi structured and unstructured problems, MIS primarily deal with structured problems.
Market-to-Book Ratio
A common method of valuing knowledge intensive companies. It is the
ratio of the market value of outstanding shares to their book value. The
ratio tends to be high for knowledge businesses, where intangibles account for much of the valuation.
Maturity of Knowledge Management
The level of adoption of knowledge management within an organization.
A knowledge management maturity model looks at stages of maturity
starting from ad hoc ways of managing knowledge to a stage when
knowledge is fully embedded and integrated into the organization’s core
activities and business processes. However, rigid application of process
maturity models like the ones used for software development by IT services companies is not advisable. Some important knowledge will always be shared directly through face-to-face informal and unstructured
interactions by people coming together. It is difficult to impose a rigidly
defined framework on such interactions.
(See also: AGILE METHODOLOGY, PROCESS, PRACTICE)
Memory
The mental function of retaining information about stimuli, events, images and ideas after the original stimuli are no longer present. Memorial
processes are extremely complex. Different memory tasks are handled
differently. Yet, what memory can do is incredible. Memory helps us to
deal with a problem with relative ease. But memory can also create difficulties while dealing with new problems that demand a new approach.
(See also: ORGANIZATIONAL MEMORY)
Mental Models
The thought process of human beings which visualizes how something
works in the real world. It is an internal representation of external reality.
Mental models are deeply ingrained assumptions, generalizations, or
images that influence how individuals understand the world and take
action. Mental models have a significant impact on the pace and effectiveness of individual and organizational learning.
Mentoring
One-to-one learning relationship in which a senior member of an organization is assigned to support the development of a newer or more junior
members by sharing knowledge, experience, insights and wisdom with
them. Mentoring relationships can be formal and informal. Well designed mentoring programs are guided by program goals, schedules,
training and ongoing evaluation. New recruits and high potential managers identified as having high potential are typical candidates for mentoring programs.
Meta Information
Information about information. Meta information assists in defining,
categorizing, and locating knowledge sources and resources.
Middleware
Businesses are often tied down by the IT investments which have already been made. These investments are heavy and often irreversible. So
there is need for seamless integration across the old and new systems.
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Middleware facilitates this integration. Middleware helps connect
islands of data, facilitating better information utilization, adaptability and
extensibility. Some middleware is simple, essentially meant to transport
information from one system to another to complete a business transaction. Other middleware is more complicated.
(See also: SERVICE ORIENTED ARCHITECTURE)
Migratory Knowledge
Knowledge that is independent of its owner or creator. The more the
codification, the more the possibility of sharing knowledge. In case of
migratory knowledge, it is possible to transfer knowledge across people
and organizations without losing context or meaning.
Mind
Can be seen as a totality of hypothesized mental processes and acts that
may serve as explanatory devices for psychological data. It can also be
seen as the sum of the conscious and unconscious mental experiences of
an individual. These processes largely consist of two categories: perception and cognition.
Mind Map
A diagram used for linking words and ideas to a central key word or
idea. It is used to visualize, classify, structure, generate ideas and facilitate problem solving and decision making. Mind maps are useful for
organizing individual or collective thought and representing it visually.
A mind map can present complex information in an organized, easyto-understand visual format. A mind map enables us to get the big picture through cascading connections between related topics and sub topics. It helps us to grasp the obstacles and paths so that we can quickly
choose the best course of action and assign and manage tasks, resources,
timelines and deliverables.
A mind map is similar to a SEMANTIC NETWORK or cognitive map but
there are no formal restrictions on the kinds of links used. Most often,
the map involves images, words and lines. The elements are arranged
intuitively according to the importance of the concepts and organized
into groups, branches, or areas. The uniform graphic formulation of the
semantic structure of information on the method of gathering knowledge
may aid recall of existing memories.
MIS
See MANAGEMENT INFORMATION SYSTEMS.
Multimedia
Technology that combines information available in various formats such
as text, audio and video. Multimedia facilitates seamless sharing of
knowledge through audio files, pictures and video clips that can be combined with other knowledge objects, records, transactions and discussions. Mind maps and visual thinking tools make extensive use of multimedia features to capture and organize independent or collaborative
thought processes.
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N
Neural Networks
A knowledge network that seeks to mimic how human brain functions.
One of the key issues in ARTIFICIAL INTELLIGENCE has been understanding how the human brain works and how to make computers function
like the human brain. The human brain is good at recognizing patterns.
Human beings can relate current problems to past problems. If computers can detect patterns, they would be extremely useful in solving business problems. Thus a manager in an insurance company would find it
useful to identify fraudulent patterns while his counterpart in a mutual
fund might be interested in patterns that help him understand how the
financial markets will move.
Neural networks are used for modeling complex, poorly understood
problems for which large amounts of DATA have been collected. They
are especially useful in finding patterns and relationships in massive
amounts of data that would be too complicated and difficult for a human
being to analyze. Neural networks develop this knowledge by emulating
the processing patterns of the biological brain.
The brain is a collection of cells called neurons that have many connections to each other. A neuron can be at rest or send a message. A neuron receives input from some cells and sends the output to other cells. A
neural network is nothing but a collection of such cells.
Units of neural networks can be described by a single number, their
“activation” values. Each unit generates an output signal based on its
activation. Units are connected to each other such that each connection
has an individual “weight”. Each unit sends its output value to all other
units to which they have an outgoing connection. Using these connections, the output of one unit can influence the activations of other units.
The unit receiving the connections calculates its activation by taking a
weighted sum of the input signals. The output is determined by the acti-
vation function based on this activation. Networks learn by changing the
weights of the connections.
Neural networks can identify patterns within data. Indeed, a well designed neural network can identify patterns, even if some data is missing.
A neural network has three layers. The input layer receives data from
external sources. The processing layer, which has already learned from
solving earlier problems, tries to apply more lessons to the new data sets
that are fed into the neural network. The output layer transmits the outputs or guesses to the user. Unlike expert systems, which may have to be
redesigned when there is a change in the business / domain, neural networks have some capability to learn on their own, as they deal with
newer and newer problems. Indeed, what is most exciting about neural
networks is the possibility of learning.
Neural networks are useful in classifying cases into one category or
another — say, whether a loan customer is likely to default or pay back
the loan. As they deal with more cases and learn, the classification becomes more accurate.
In medicine, neural network applications are used for screening patients for coronary artery disease, for diagnosing patients with epilepsy,
and for performing pattern recognition of pathology images. Neural networks can also be used to predict the performance of equities, corporate
bond ratings or corporate bankruptcies. In the field of artificial intelligence, neural networks have been applied successfully to speech recognition, image analysis and adaptive control, in order to construct software agents or autonomous robots.
Neural networks require a lot of data and a high-powered computing.
Considerable amount of time has to be spent in training the neural network, cleaning up the data and preprocessing for better comparison of
the data being fed in. Doing the analysis and interpreting results can be
very tricky. So these systems require a very knowledgeable user, at least
to set up the initial model. Subsequent data may be analyzed with the
same model.
Neural networks are also something of a “black box”. A particular
case will be classified in a particular fashion according to nodes and var-
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iable weightings, and is therefore difficult to interpret. Some new neural
networking tools hide the complexity from the user and are able to explain to some degree why the system behaves the way it does. Still,
many managers do not like them because of difficulties in interpretation.
NIH
See NOT-INVENTED-HERE.
Nohria, Nitin
A well known professor at the Harvard Business School, Nohria’s research centers on leadership, corporate accountability, and organizational change. His book, Building the Information Age Organization, examines the role of information technology in transforming organizations. In
Networks and Organizations: Structure, Form, and Action, an edited
volume of original articles, he explores the emergence of network-like
organizations. He is the author of over 75 journal articles, book chapters,
cases, working papers, and notes. His article “What’s Your Strategy for
Managing Knowledge?” Harvard Business Review 77, No. 2 (MarchApril 1999): pp. 106-116. co-written with Morten Hansen and Thomas
Tierney is a highly influential piece that explains how companies can
strike a balance between information technology and human intervention
while managing knowledge.
Nonaka, Ikujiro
One of the leading knowledge management gurus in the world, Ikujiro
Nonaka is a Professor at the Haas School of Business at the University
of California, Berkeley and the Founding Dean of the Graduate School
of Knowledge Science at the Japan Advanced Institute of Science and
Technology (JAIST). He has authored or coauthored several books, including the widely acclaimed, The Knowledge-Creating Company and
has written several articles in various international academic and managerial journals. He has also been the editor of several international journals and conducted international knowledge management seminars for
managers.
Not-Invented-Here (NIH)
Individuals, departments and organizations often have a mental block
about using an idea / technology developed by an outsider. NIH is a major barrier to organizational learning. Companies have tried to deal with
this syndrome in various ways such as by introducing “Steal Shamelessly” awards.
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O
Object Oriented Databases (OODBs)
The type of database application should dictate the choice of database
management technology, namely Relational databases and Object Oriented Databases. In general, database applications can be categorized
into data collection and information analysis:


Data collection
applications focus on entering data into a database
and providing queries to obtain information about the data. These applications contain relatively simple data relationships and schema design. So, relational database management systems (RDBMs) are better suited for these applications. Examples are accounts payable, accounts receivable, order processing, and inventory control.
Information analysis applications involve navigation through and
analysis of large volumes of data. Object oriented databases
(OODBs) are better suited for such applications. OODBs are also
used in applications handling BLOBs (binary large objects) such as
images, sound, video, and unformatted text. OODBs support diverse
data types rather than only the simple tables, columns and rows of relational databases. Examples of these applications are CAD / CAM /
CAE, production planning, network planning, and financial engineering.
OODBS facilitate the unification of the application and database development into a seamless data model and language environment. As a
result, applications require less code and use more natural data modeling. So code bases are easier to maintain. Object developers can write
complete database applications with a modest amount of additional effort.
In contrast to a relational DBMS where a complex data structure
must be flattened out to fit into tables or joined together from those
tables to form the in-memory structure, OODBs do not store or retrieve a
web or hierarchy of interrelated objects. The one-to-one mapping of object programming language objects to database objects provides higher
performance management of objects. It also enables better management
of the complex interrelationships between objects. So OODBs are better
suited for applications such as financial portfolio risk analysis systems,
telecommunications service applications, world wide web document
structures, design and manufacturing systems, and hospital patient record systems, which have complex relationships between data.
OLAP
See ONLINE ANALYTICAL PROCESSING.
Online Analytical Processing (OLAP)
OLAP is part of the broader category of software applications which go
by the name of business intelligence. The typical applications of OLAP
are in business reporting for sales, marketing, management reporting,
business performance management, budgeting and forecasting, financial
reporting and similar areas. OLAP is a slight modification of the traditional OLTP (Online Transaction Processing). OLAP databases are capable of handling queries which are more complex than those handled
by standard relational databases through the ability to view data by different criteria, advanced calculation capability and specialized indexing
techniques
Ontology
Refers to the levels of knowledge creation. At the lowest level, we have
the individual, then we have the organization and finally we have more
than one organization. In a strict sense, knowledge is created only by individuals. The organization can provide the context and the necessary
support but it is individuals who create knowledge. Knowledge management is all about amplifying this knowledge and crystallizing it as part of
the knowledge network of the organization. From the individual level, the
process moves to intra organizational and inter organizational levels.
OODBs
See OBJECT ORIENTED DATABASES.
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Organizational Knowledge Awareness
Awareness of both the existing knowledge and the knowledge gaps
which exist. Such knowledge is the starting point in knowledge management. Knowledge awareness can be analyzed in various ways. Elias
Carayannis has identified four states of knowledge awareness as deputed
in the matrix below:
Awareness
Ignorance
of awareness
of awareness
Awareness
Ignorance
of ignorance
of ignorance
Similarly, Michael Earl has also developed a 2 x 2 Matrix as depicted
below:
What you know
What you don’t
know
Knowing
State of
Knowing
Not Knowing
Explicit
Planned
Knowledge
Ignorance
Tacit
Innocent
Knowledge
Ignorance
State of Knowledge
Organizational Knowledge Creation
According to the well-known Japanese scholars, TEKEUCHI and NONAKA,
organizational knowledge creation takes place-in five phases:




Sharing tacit knowledge:
Rich untapped knowledge is shared by employees through socialization.
Creating concepts: TACIT KNOWLEDGE is converted into EXPLICIT
KNOWLEDGE, leading for creation of new concepts.
Justifying concepts: The organization must determine if a concept is
worthy of perusal.
Building an archetype: Concepts are converted into prototype, operating mechanism, a new system, or an innovative organizational structure.

Cross leveling knowledge:
The knowledge created in one division is
extended to other divisions and even to external stakeholders, such as
customers and dealers.
Organizational Memory
The core knowledge of an organization’s past, such as project histories,
important decisions and their rationale, key documents and customer
relationships. It is the knowledge and understanding embedded in an
organization’s people, PROCESSES and products or services, along with
the company’s traditions and values. ORGANIZATIONAL MEMORY can
either assist or inhibit the organization’s progress. Organizational
memory helps avoid “reinventing the wheel” and repeating past mistakes. It also facilitates decision making. At the same time, in a fast
changing environment, organizational memory can stand in the way of
unlearning, a critical success factor.
(See also: MEMORY)
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P
Parsing
An algorithm that translates syntax into meaningful machine instructions
also. Parsing determines the meaning of statements issued in the data
manipulation language. Parsing also analyzes an input sequence in order
to determine its grammatical structure with respect to a given formal
grammar. The term parseable is generally applied to text or DATA which
can be parsed. Parsing transforms input text into a data structure, usually
a tree, which is suitable for later processing and which captures the
implied hierarchy of the input.
Peer Assist
A process where a team of people working on a project or activity call a
meeting or workshop to seek knowledge and insights from people in
other teams. Seeking help from peers is not new. But the formal use of
this process as a knowledge management tool and the coining of the
term “peer assist” were pioneered by British Petroleum. Peer assists facilitate “learning before doing”, i.e. gathering knowledge before embarking on a project or piece of work, or when facing a specific problem or
challenge within a piece of work.
The benefits of peer assists are quickly realized. Learning is directly
focused on a specific task or problem, and so it can be applied immediately. A peer assist allows the team involved to gain input and insights
from people outside the team, and to identify possible new lines of enquiry or approach. Peer assists also facilitate the reuse of existing
knowledge and experience, promote sharing of learning between teams,
and strengthen social networks. Peer assists are relatively simple and
inexpensive to do. They do not require any special resources or any new,
unfamiliar processes. They are particularly useful when a team is facing
a challenge, where the knowledge and experience of others will really
help, and when the potential benefits outweigh the costs of bringing
people together.
Personal Mastery
A term coined by Peter SENGE, is the discipline of continually clarifying
and deepening personal vision, focusing energies, developing patience,
and trying to see reality objectively as individuals strive to fulfill their
highest aspirations.
Physical Environment
The way office spaces are designed. The physical environment can influence the effectiveness of knowledge sharing. Many employees gain
work related knowledge, not from manuals or formal training but from
informal conversations on the corridor, near the water cooler, at the coffee vending machine and in the cafeteria. Indeed, realizing the importance of physical communication, some companies are creating physical spaces to promote this. If network connections are provided in these
spaces, knowledge sharing can be further enhanced. The famous journalist, Tom Stewart, once mentioned that the best hardware device for
transferring knowledge is a coffee pot. But he added that coffee pots do
not scale. By this he meant that while face-to-face informal conversation
is the best way to share knowledge, leverage comes only with technology. Only if a large number of people have access to knowledge, will it
make a signified impact. And that kind of sharing on a large scale is possible only with technology. So workplaces should be designed both to
increase human interaction and leverage technology. (See: Spatial School
under SCHOOLS OF KNOWLEDGE MANAGEMENT and WORK AMBIENCE)
Practice
How knowledge workers actually accomplish their tasks. Understanding
work practice requires detailed observation and a philosophical acceptance that there must be some good reason for work being done in a
particular way. Practice differs from PROCESS. A process orientation
means laying down norms on how work should be done. Some jobs are
very difficult for outsiders to understand and require a high proportion of
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practice orientation. In such cases, attempts to impose a process, may
backfire.
Procedural Knowledge
Includes processes, sequences of events and activities and actions. Thus
a company can maintain a database of methodologies pertaining to key
areas such as project management and six sigma. But without the contextual understanding of how such knowledge can be applied, this may
remain largely theoretical.
Process
Essentially a description of how work must be done. A process design is
basically an abstraction of how work should be done in the future. A
process orientation can impose discipline. But it may also stifle creativity. Often the design is done by people who have only a superficial understanding of how work is actually being done today. That is why a
process orientation must be balanced by a certain degree of PRACTICE
orientation while dealing with knowledge workers. Practice refers to
how work actually gets done in an organization.
Process Networks
A useful mechanism for facilitating inter ORGANIZATIONAL KNOWLEDGE
CREATION. According to John Hagel III and John Seely Brown, a specific form of network is evolving among world class companies in their
endeavor to gain more flexible access to specialized capabilities on a
global scale. Process networks typically extend beyond the first tier of
business partners, and seek to coordinate activities across multiple tiers
of enterprises within a business process.
Process networks adopt a pull model where resources are flexibly
provided in response to specific market demand. Process networks
require formal orchestrators to function effectively. These networks are
characterized by loose coupling. Relatively independent modules of
activity are designated, with clear ownership and accountability for each
module. The performance levels that each module must meet at the interfaces connecting it with other modules are defined. Module owners can
improvise so long as they comply with the performance requirements.
This kind of approach is not only more scalable but is also more effective in tapping the knowledge of a large number of specialized participants. In short, process networks are a way to multiply the value of a
company’s capabilities. Relevant complimentary knowledge is tapped in
a flexible way to provide more value to the customer.
Productive Friction
A concept coined by John Hagel III and John Seely Brown in their book,
The Only Sustainable Edge. When people with diverse backgrounds,
experiences and skill sets engage with each other on real problems, there
is usually friction in the form of misunderstandings and arguments. Such
friction can get dysfunctional. If properly harnessed, however, this kind
of friction can become very productive, accelerate learning, encourage
innovation and foster trust across diverse participants. Productive friction can generate opportunities for capability building across specialized
players within process networks.
(See also: BA, CREATIVE ABRASION, PROCESS NETWORKS)
Professional Intellect
A term coined by James Brian Quinn, Philips Anderson and Sydney
Finkelstein1. The professional intellect of an organization operates at
four levels:



*
Cognitive knowledge
is the basic mastery of a discipline achieved
through training and certification.
Advanced skills translate theoretical knowledge into effective execution.
Systems understanding represents the deep knowledge of cause and
effect relationships underlying a discipline. This is the understanding
needed to solve large, complex problems, and anticipate and deal
Published in International Journal of Information Management (1995),
Sloan Management Review (Fall 1993), International Journal of Information Management (1993), California Management Review (Spring
1996), and California Management Review (Spring 1998), respectively.
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with unexpected scenarios. Systems understanding is reflected in
highly trained intuition — for example, whether the candidate who
has come for the interview must be selected, whether the new project
must be approved, etc.
Self-motivated creativity consists of will, motivation and adaptability
for success. Self motivated creativity is needed in abundant measure
to respond aggressively to changing external conditions.
Developing professional intellect calls for a systematic approach. The
best people must be recruited and trained effectively by being exposed to
real problems. Stretch goals must be set to make employees work hard
and to exploit their full potential. Internal competition, peer pressure and
timely performance appraisal and feedback are also important factors in
shaping the professional intellect.
Prusak, Laurence
A widely respected authority in knowledge management, Prusak has
written, published and consulted extensively. His book, Managing Information Strategically (1994), co-authored with James McGee, explains
the role of information in generating competitive advantage. He has coauthored with Tom DAVENPORT two popular books; Information Ecology
(1997), and Working Knowledge (1997), and has edited an anthology
Knowledge in Organizations (1997). Some of his important articles include “Myth of Information Overload”, “Information Politics”, “Blow
up the Corporate Library”, “Knowledge and Risk Management” and
“Eleven Sins of Knowledge Management”.*
Pull System
An approach to knowledge management which holds that people should
“pull” knowledge and use it as and when their work demands. Users get
exactly what they need to know. They are not distracted by unwanted
information or updates. The system depends on users taking the initiative to seek information.
Push Systems
Deliver knowledge to users after putting it through highly customized
filters. Push systems deliver information to desktops or e-mail accounts
and are more likely to get noticed. Users do not have to take the trouble
of going and looking for information. The danger is that people may be
swamped with information which they may not need at that point of
time.
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R
Radio Frequency Identification (RFID)
Systems that enable tracking the movement of goods throughout the
supply chain. These systems use tiny tags with embedded microchips
containing data about an item and its location to transmit radio signals
over a short distance to special RFID readers. These readers pass data
over a network to a computer for processing.
RFID tags do not need line of sight contact to be read. The RFID tag
is electronically programmed with information that can uniquely identify
an item along with other information like location, place of manufacture,
etc.
The real savings from RFID come from the way it can improve an
entire business process. RFID systems give suppliers, manufacturers,
distributors and retailers much more detailed and real time data that facilitate improved inventory capital, shipping, etc. RFID is also likely to
change the way invoices are settled by triggering an electronic payment
to the shipper once a tagged pallet enters a retailer’s warehouse. Major
enterprise vendors, including SAP and Oracle for example now offer
RFID: ready versions of their supply chain management applications.
Reciprocity
A key concept in knowledge sharing, reciprocity is what makes
knowledge markets work. People will typically share knowledge when
they know that others will reciprocate. People will contribute to a
knowledge repository only when they feel they are in return gaining
something which they value. Reciprocity may, however, stand in the
way of some people enjoying access to a social network, if they have
nothing to contribute for the moment. So many COMMUNITIES OF
PRACTICE allow legitimate “peripheral participation”. Employees can
“lurk” in electronic mailing lists and discussion groups and get a feel of
what is happening within a group.
Redundancy
According to NONAKA and TAKEUCHI, redundancy is the conscious overlapping of company information, business activities and managerial responsibilities. Knowledge creation is facilitated when a company makes
available information that goes beyond the immediate operational requirements of organizational members. Effectively, redundancy means
that concepts created by an individual or group are shared with other
individuals who may not need the concepts immediately. Redundancy
encourages dialogue and helps generate new ideas and consequently
knowledge creation. When members of an organization share overlapping information, they can sense what others are struggling to articulate.
Japanese companies like Canon organize product development teams
into competing groups that develop different approaches to the same
project and argue their case. This enables the project to be examined
from multiple perspectives. Ultimately, the best approach is chosen. Redundancy can be facilitated through cross functional job rotation of employees.
Report Generator
A system that generates responses to queries, provides automated status
reports, or reports on the contents of a database.
RFID
See RADIO FREQUENCY IDENTIFICATION.
Roth, George
A member of the research staff at the MIT 21st Century Initiative, Roth
directs the learning history project. Roth has done extensive research on
organizational learning and change. Roth’s current research interests
include the following:


Learning Histories:
The use of documentation to capture, assess,
facilitate, diffuse and sustain organizational improvement initiatives.
Large Scale System Change: Issues involved in moving from teambased change efforts to organizational or system level change.
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Technological Change:
Creating mechanisms for effective change
while implementing new technology.
Educational Interventions in Organizational Learning: Improving
individual learning processes taking place in organizational settings.
Business Process Learning: Building better business processes by
enabling people to think differently about their work and business
processes.
Rules of Thumb
Shortcuts to solutions for tackling new problems that resemble problems
previously solved by experienced workers. This kind of knowledge
facilitates quick decision making. But one must be on guard, for situations where there is a paradigm shift and the existing thumb rules may
no longer apply.
S
Scalability
The ability of the knowledge management system to support an increasing number of users and a growing volume of transactions. A system that
performs well within a work group of limited size might not perform well
when it is extended across the enterprise. Scalability is an important issue
in rapidly growing organizations. Indian IT services companies clearly
fall in this category. Scalability depends on a number of factors, including
the flexibility of the architecture and the capacity of the hardware.
Schools of Knowledge Management
Michael Earl, one of the well known knowledge management gurus, has
identified seven different schools of knowledge management:
The systems school is perhaps the longest established, formal approach to knowledge management. The school believes in capturing
specialist knowledge in databases and making it available across the
organization. The content is validated, through peer and superior review.
The systems school is not feasible without information technology (IT).
Computer systems which capture, store, organize, and display
knowledge are the key drivers in this school.
The cartographic school is concerned with mapping organizational
knowledge. By building knowledge directories, the aim is to make sure
knowledgeable people in the organization are accessible to others for
advice, consultation, or knowledge exchange. Knowledge directories are
gateways to knowledge. People are expected to provide accurate and
comprehensive profiles of their competencies and experience in the
directories. The key driver of the mapping school is people connectivity.
Consequently, the principal contribution of IT is to connect people via
intranets, extranets and the Internet.
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The process school believes the performance of business processes
can be enhanced by providing operating personnel with knowledge relevant to their tasks. The process school focuses on enhancing the firm’s
core capabilities with knowledge flows. IT can be used to provide shared
databases across tasks, levels, entities, and geographies to all knowledge
workers throughout a process.
The commercial school lays emphasis on both protecting and exploiting a firm’s knowledge or intellectual assets such as patents, trademarks,
copyrights, and KNOW-HOW to produce revenue streams. A specialist
team or function is used to aggressively manage knowledge and intellectual property. Techniques and procedures are put in place to manage
intellectual assets as a matter of routine. Many companies spend too
much time trying to measure INTELLECTUAL CAPITAL rather than actually
developing and exploiting it. The philosophy of the commercial school
is commercialization of intellectual property.
The organizational school describes the use of organizational structures, or networks, for sharing or pooling knowledge. It believes in promoting “knowledge communities” or groups of people with a common
interest, problem, or experience, within and across organizations. These
communities can be intra or inter-organizational. Communities exchange
and share knowledge interactively, often in non-routine personal and
unstructured ways, as an interdependent network. The emphasis is on
increasing connectivity among knowledge workers. IT, in the form of
intranets and groupware, which can help connect members and pool
their knowledge, both explicit and tacit.
Most people prefer conversation to documents or IT systems. TACIT
KNOWLEDGE is most likely to be discovered and exchanged through discussion. The spatial school centers on the use of spatial design — to
facilitate knowledge exchange. Typical examples are the water cooler as
a meeting place, the open-style coffee bar or kitchen as a “knowledge
cafe” and the open-plan office as a “knowledge building.” This school
could also be called the social school, because the intent is to encourage
socialization as a means of knowledge exchange. This school believes in
nurturing and utilization of SOCIAL CAPITAL that develops from people
interacting, formally or informally, repeatedly over time. However, the
label “spatial” is preferred because of the use of space to stimulate conversations and exchange.
The strategic school sees knowledge management as a dimension of
competitive strategy. Indeed, it may be seen as the essence of a firm’s
strategy. The aim is to build, nurture, and fully exploit knowledge assets
through systems, PROCESSES, and people and convert them into value as
knowledge-based products and services. The strategic school provides
an umbrella for the pursuit of all the other schools. This school views
knowledge and intellectual capital as the key resource. The firm consciously chooses to compete on knowledge. With the firm viewing itself
as a knowledge business, knowledge creation and sharing, drive rather
than just support competitive strategy. The strategic school is essentially
concerned with raising awareness of how value can be created by treating knowledge as a strategic resource. Corporate mission and purpose
statements are used to send out clear signals about the importance of
knowledge management.
Scripting
A popular technique to improve the productivity of people involved in
low-end knowledge work. An expert lays down a script that tells lowerlevel knowledge workers what to do under different circumstances.
Scripting can bring the lowest performers to a certain level of proficiency. But it is unlikely to create a high-performing knowledge work force.
Moreover, for jobs involving high levels of knowledge, scripting is unlikely to be effective. The trick may lie in identifying the parts of the job
that can be scripted. Thus, the power point slides for a B School course
can be standardized. But it could be quite difficult to script the actual
delivery of instruction in the class room. That depends critically on the
skills of the instructor.
Search Engine
The most important technology for manipulation of EXPLICIT
KNOWLEDGE. Without effective search facility, a repository will be
meaningless. Search engines contain software that looks for web pages
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containing one or more of the search terms. They then display matches
ranked by a method that usually involves the location and frequency of
search terms. Search engines create indexes of the web pages they visit.
The search engine software then locates web pages of interest by searching through these indexes. The program used to perform the indexing
function is called spider or crawler. Search queries are often ineffective
because they retrieve many irrelevant documents. Improvements are
possible through better understanding of the context of information
needs and more knowledge of the domain being searched. An efficient
taxonomy can help by arranging documents more systematically.
Search strategies can be of various types:

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Metasearching:
Based on meta categories and dependent on keywords and attribute tags. Metasearching minimizes the time spent in
locating the right category. This approach emphasizes clarifying the
context intended by the user through refinement and rejection.
Hierarchical: Knowledge is organized in a fixed hierarchy. Links can
be used to efficiently locate the knowledge needed. Hyperlinks are
provided to dig deeper.
Tagged Attribute: This approach matches user input attributes against
attributes or TAGS associated with documents and pointers. Ranking
of results is based on relevance.
Content: Search term, keyword or text string are matched to return
results with relevant scores based on the frequency of matches. This
strategy is slow and inefficient.
Combinatorial: It combines two or more of the approaches mentioned
above and executes them in parallel.
Various automated mechanisms are available for enhancing
knowledge search and retrieval capabilities. CLUSTERING automatically
finds groups of related documents such as technical reports. Categorization assigns new knowledge elements to one or more categories from a
user-defined taxonomy. There are tools available to generate taxonomy
as well. Then there are translation capabilities which recognize and
translate key concepts from one language to another. A thesaurus can be
a useful tool for connecting inconsistently defined concepts in search
queries.
SECI Model
Developed by
TAKEUCHI
SECI (SOCIALIZATION,
is probably
the best well known and the most comprehensive theory of
ORGANIZATIONAL KNOWLEDGE CREATION. The model views the process
of knowledge creation as taking place in four phases.
and
NONAKA,
EXTERNALIZATION, COMBINATION and INTERNALIZATION)




Socialization is the process of converting TACIT KNOWLEDGE into
EXPLICIT KNOWLEDGE by sharing experiences.
Externalization is the process of converting tacit knowledge into
explicit concepts.
Combination is the process of combining and systematizing explicit
concepts into a knowledge system.
Internalization is the process of converting explicit knowledge into
tacit knowledge through learning by doing or by relating to the
experiences of others.
The movement through the four modes of knowledge conversion is
represented not by a circle but by a spiral. Knowledge gets amplified as
it moves through the four stages of knowledge conversion. The SECI
model views knowledge creation and knowledge sharing, both tacit and
explicit knowledge holistically, rather than as watertight compartments.
Semantics
Formal rules and procedures for representing meaning. Semantic feature
is any defining characteristic of the meaning of a word which serves to
distinguish it from the meaning of other words. This is important
because words are often used loosely and interchangeably.
(See also: SEMANTIC NETWORK, SEMANTIC WEB).
Semantic Network
A method of representing structured knowledge using nodes and links.
The nodes are concepts or entities, while the links represent relationships
and associations among the concepts. A semantic network assumes
information is stored in the form of words, concepts or propositions as
independent units which are interconnected by links or relations.
Important semantic relations include:
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Meronymy (A is part of B)
Holonymy (B has A as a part of itself).
Hyponymy (A is subordinate of B; A is a kind of B).
Hypernymy (A is superordinate of B).
Synonymy (A denotes the same as B).
Antonymy (A denotes the opposite of B).
There are various types of semantic networks like the Semantic Network Processing System (SNePS) of Stuart C. Shapiro or the MultiNet
paradigm of Hermann Helbig (MultiNet is an acronym for “Multilayered
Extended Semantic Network”). MultiNet is well suited for the semantic
representation of natural language expressions.
A MIND MAP can be considered a very free form variant of a semantic
network. By using colors and pictures, the emphasis is on generating a
semantic net which evokes human creativity.
(See also: MIND MAP)
Semantic Web
Seen by some as the next evolution of the World Wide Web, the Semantic Web links up information in such a way as to be easily processable
by machines on a global scale. Much of the data on the Web is difficult
to use on a large scale because there is no global system for publishing
data. The Semantic Web, thought up by Tim Berners-Lee, is still very
much in its infancy. Although the future of the project appears to be
bright, there is little consensus about the likely direction and characteristics of the early semantic web. However, it is expected that as more and
more people want to publish data, semantic webs may take off. A large
number of semantic web applications may be used for a variety of different tasks, increasing the modularity of applications on the Web.
Senge, Peter
Founding Chair of the Society for Organizational Learning, a global
community of corporations, researchers, and consultants committed “to
increase our capacity to collectively realize our highest aspirations and
productively resolve our differences” through the mutual development of
people and institutions. The Journal of Business Strategy named Senge a
“Strategist of the (20th ) Century,” one of twenty-four men and women
who have “had the greatest impact on the way we conduct business today” (September / October 1999). Senge believes that vision, purpose,
reflectiveness, and systems thinking are essential for organizations to
realize their potential.
Senge is also the author of several books, including the widely acclaimed, The Fifth Discipline: The Art and Practice of the Learning Organization (1990). Since its publication, more than a million copies of
The Fifth Discipline have been sold. In 1997, Harvard Business Review
identified it as one of the seminal management books of the past 75
years. His most recent book, Presence: Human Purpose and the Field of
the Future, co-authored with C. Otto Scharmer, Joseph Jaworski and
Betty Sue Flowers, outlines a new theory about change and learning.
Service Oriented Architecture (SOA)
A modular approach that attempts to increase the flexibility of available
software resources. Existing application platforms make top executives
feel their hands are tied. The cost of switching to a platform can be
exceedingly high. SOA is an attempt to minimize these costs through the
use of a more modular approach. Software is typically designed to support a business context. Services are designed without advanced
knowledge of the tasks and uses they will be called upon to support.
SOA helps to establish loosely coupled connections across existing applications and databases quickly and cost effectively. IT services can be
accessed when needed from wherever they reside. Where the software is
located becomes irrelevant as far as users are concerned. As John Hagel
III and John Seely Brown mention in their book, The Only Sustainable
Edge, software will become increasingly commoditized and will be able
to switch from one module to another. Loosely coupled connections can
consume a lot of computing and network resources. So coordination of
distributed processing power is exceedingly important. For SOAs to
become economically applicable, computing power must be made flexibly available.
SOAs can leverage vast resources which are already available and
make them accessible as services. This is unlike previous generations of
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architectures that demanded removal of existing technology platforms
and heavy investments in new ones. SOA can enhance the potential of
social software by making it easier to connect social software tools with
existing software resources such as databases, electronic documents and
analytic tools. This can greatly enhance problem solving among the
people mobilized by the social software. However, many more obstacles
must be overcome before SOA becomes more popular. Businesses must
develop a shared meaning regarding the content of business tasks. Currently, such architecture is used more to publish and distribute business
information, not to automate business processes.
Single-Loop Learning
Learning which involves using knowledge to solve specific problems
based on existing assumptions, and based on what has worked in the
past. If a room is becoming too cool, one would adjust the thermostat
setting, not question whether the air-conditioning system is over
designed. In short, single-loop learning is limited in scope and does not
lead to challenging the accepted wisdom. So, this kind of learning is
lower level learning that takes many things as given.
Skyrme, David J.
A leading authority in knowledge management, Skyrme’s book Creating
the Knowledge-Based Business is described by many practitioners as
“the Bible of Knowledge Management”. His book Measuring the Value
of Knowledge is considered an outstanding contribution to the field of
INTELLECTUAL CAPITAL measurements. His other books include:
Knowledge Networking: Creating the Collaborative Enterprise and
Capitalizing on Knowledge: From e-business to k-business. Skyrme’s
website: www.skyrme.com provides valuable information for
knowledge management practitioners.
SOA
See SERVICE ORIENTED ARCHITECTURE.
Socialization
One of the four components of TAKEUCHI and NONAKA’S SECI MODEL. It
is the process of sharing experiences and thereby creating TACIT
KNOWLEDGE such as shared mental models and technical skills. In socialization, KNOWLEDGE SHARING takes place through observation, imitation and practice. A good example is how the organizational culture is
shared across employees in a company. Similarly, apprentices learn from
their masters through observation, imitation and practice. On-the-job
training and mentoring can also be viewed as forms of socialization. The
key to socialization is shared experience. As Takeuchi and Nonaka put
it60, “Without some form of shared experience, it is extremely difficult
for one person to project herself into another individual’s thinking process. The mere transfer of information will often make little sense if it is
abstracted from embedded emotions and nuanced contexts that are associated with shared experiences.”
BRAINSTORMING can facilitate socialization. So can interactions
between product development engineers and customers.
Social Capital
A kind of INTELLECTUAL CAPITAL, that can be a valuable intangible asset
if carefully nurtured. Social capital refers to the ability of groups to collaborate and work together. Well functioning human networks facilitate
exchange of ideas, problem solving and creation of new knowledge. Social capital is a function of trust. Trust enables decisions to be taken
more quickly and implemented more smoothly. So, social capital reduces transaction costs. The quality of knowledge is also high because when
there is trust, ideas can be debated in a transparent way, with less defensive reasoning and without hidden agendas dominating. Social capital is
an intangible asset that is highly contextual and strongly shaped by the
organizational culture. So it cannot be easily imitated by competitors.
60
Nonaka, Ikujiro and Takeuchi, Hirotaka, The Knowledge Creating
Company: How Japanese Companies Create the Dynamics of Innovation,
Oxford University Press, 1995.
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Social Networks
In most organizations, work gets done less through standardized processes and formal structures and more through informal networks of
relationships. These networks must be both actively encouraged and
carefully nurtured. Yet the power of these invisible groups is often underestimated by many organizations.
Improving the functioning of social networks is not merely about
increasing connectivity. While expanding network connectivity, companies need to determine exactly what they want to accomplish through
informal networks and, the kind of connectivity needed to help them
achieve their goals. Indiscriminate expansion of the network can take a
toll on employees. Connectivity must be promoted only where it benefits
an organization or individual. Connectivity that is not needed should be
reduced.
According to Rob Cross, Jeanne Liedtka and Leigh Weiss61, all informal networks help organizations do two things — recognize opportunities or challenges and coordinate appropriate responses. Based on their
unique value propositions, three different archetypes can be identified:
1.
Customized Response:
Sometimes both problems and solutions are
ambiguous. New-product-development teams, high-end investment
banks, early-stage drug-development teams, and strategy consulting
firms require networks that can rapidly define a problem or an opportunity and bring together relevant expertise. Here, people must quickly frame and solve a problem.
2. Modular Response: In other situations, the components of a problem
and solution are known but the combination or sequence of those
components is not yet known. Surgical teams, law firms, business-tobusiness sales, and mid-stage drug development teams require networks to identify problem components and address them with modularized expertise. Such jobs involve delivering a unique response depending on the various elements of expertise required by the problem.
3. Routine Response: In many other situations, work is standardized.
Problems and their solutions are well defined and predictable. In call
61
Harvard Business Review, March 2005.
centers and insurance claims-processing departments, efficient and
consistent response to a set of established problems holds the key to
success.
The essence of networking is building trust, strengthening human
relationships and improving the richness of knowledge transferred.
Much can be done by organizations to nurture social networks. Collaborative behavior should be an important criterion during recruitment.
Helping employees develop an awareness of who knows what in the
organization allows them to know whom to turn for help. Skill profiling
systems, expertise locators and COMMUNITIES OF PRACTICE can all go a
long way in strengthening relationships and improving collaboration.
Performance appraisal systems can also promote collaborative behaviour. Leadership and culture have a profound influence on social networks. Leaders must send out clear signals that they support a collaborative culture. EXPERIENTIAL LEARNING must be encouraged through
mechanisms such as “after action review”. Mentoring, coaching and
learning from failure should be actively encouraged across the organization.
High performing knowledge workers actively manage their networks.
They know they receive a lot of information through network contacts.
So they are careful to reciprocate with information and nourish network
relationships. A variety of social networking software is also now available to form and nurture social networks. But software can only complement, not replace people-to-people connections.
(See also: SOCIAL SOFTWARE)
Social Networking Analysis
A useful technique for understanding the informal networks which exist
outside the formal structure of an organization, or for diagnosing the
limitations of the existing formal structure. First, information is collected
on who communicates with whom. Specialized software is then used for
analysis. Typically, the interactions are plotted graphically. The graph
will indicate clearly whether the network is excessively dependent on
some people. In that case, the structure needs to be corrected to “democratise” the information flows.
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Social Software
Software that can help connect up people, provide them collaboration
tools and create various records of interactions. Though not completely
new, it is only now that social software is developing the robust capabilities needed. Social software includes traditional tools like e-mail and
bulletin boards, as well more recent innovations like instant messaging,
blogging, wikis and social network analysis tools. One area where social
software looks likely to play a crucial role is exception handling. Massive enterprise applications generate various exceptions that must be
handled by people. The right people to handle the exception must be
identified and brought together. These people have then to be provided
the relevant information and analytical tools to come up with an effective resolution. This also demands a good understanding of the context.
More often than not, exceptions are handled in ad hoc fashion. Once the
transaction is completed, records are not properly maintained. So the
next time the same exception arises, the entire resolution must be
repeated from scratch. As John Hagel III and John Seely Brown mention
in their book, The Only Sustainable Edge, exceptions can actually be a
major source of business innovation. Employees are forced to address
unexpected challenges. Consequently, they often make significant
refinements in the business processes involved. Social software can provide the tools that help reduce the cost of exception handling. It can also
create a repository that documents the exceptions, the people involved in
resolving the exceptions and the resolutions themselves. The repository
can play a key role in disseminating business innovations across the organization.
One company which has made good use of social software to improve its business processes is Xerox. Social software has helped service
engineers to tackle unexpected repair needs for printers and copiers. Till
a few years back, the company’s standardized procedures only explained
what happened when a single fault in the equipment occurred. But many
malfunctions involved two or more faults simultaneously. So Xerox introduced Eureka, a social network that mobilized tips contributed by the
service engineers as they reported on their experiences while handling
unexpected problems. Engineers who began to contribute tips became
highly respected among peers. Within years, Xerox captured 30,000 tips
resulting in savings of $100 million per year and Eureka rapidly
emerged as an important learning tool. Service engineers can use Eureka
to sharpen their trouble shooting skills. Product designers can consult
Eureka while trying to improve product performance. Experiences of
engineers were transformed into knowledge that could be shared across a
geographically distributed work force.
Spider’s Web
A term coined by James Brian Quinn, Philip Anderson and Sydney
Finkelstein62. When a company encounters complex, poorly defined
problems, no one person may know how to solve them. A self organizing network or spider’s web comes in handy in such cases. Such a web
quickly brings people together to solve a problem and then disbands just
as quickly once the job is done. Research reveals that even with 8-10
collaborating independent professionals, a spider’s web can leverage
knowledge capabilities by hundreds of times. Spider’s webs are particularly appropriate when knowledge is dispersed among many specialists
who must come together to solve a different problem. Consulting firms,
investment banks, research consortia and medical diagnostic teams have
been known to use spider’s webs.
(See also: COLLABORATION WORK)
Storytelling
The use of stories in organizations as a way of sharing knowledge and
helping learning. Stories can be very powerful communication tools, and
may be used to describe complex issues, explain events, communicate
lessons learned, or bring about cultural change. Stories preserve the rich
context that gets lost if attempts are made to cram information into rigidly defined templates. Unfortunately, many organizations do not pay adequate attention to this important method of knowledge sharing.
In their article “Managing Professional Intellect: Making the Most of the
Best”, Harvard Business Review, March-April 1996, pp. 71-80.
62
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Structural Capital
A form of INTELLECTUAL CAPITAL that remains with the firm, not individual employees. It includes the explicit rule-based knowledge embedded in the organization’s work processes and systems, or encoded in
written policies. It also includes training documentation or best practices
databases.
Summarization
PROCESS, and TECHNOLOGY for summarizing key points. Long documents are cumbersome and unwieldy. Fortunately, today, technology is
available for summarizing documents. Typically, all the key points in a
large document can be summarized in less than twenty per cent of its
original size using such technology. If not anything else, a summary enables users to avoid reading irrelevant documents. Commercially available summarizers use the sentence selection method, preparing a summary from what are judged to be the key sentences in a document.
Systems Thinking
A philosophy that emphasizes the importance of looking at a problem
holistically. It is a conceptual framework, a body of knowledge and tools
that have been developed over the past fifty years, to make the full patterns clearer, and to make it possible to bring about effective change
with the least amount of effort by finding the leverage points in a system.
(See also: LEARNING ORGANIZATION)
T
Tacit Knowledge
KNOWLEDGE or KNOW-HOW that people carry in their heads including
subjective intuitions and hunches. Such knowledge is not easily visible
and expressible. As it is highly personal and hard to formalize, tacit
knowledge is difficult to communicate or share with others. There are
two dimensions of tacit knowledge. The technical dimension refers to
the skills developed over time. The second dimension is cognitive, consisting of beliefs, perceptions, ideas, values, emotions and mental models
so ingrained in us that we take them for granted.
Personal, context specific knowledge is difficult to formalize, articulate or record. It is developed through trial and error and best transferred
through doing and observing. Observation, MENTORING, STORYTELLING,
discussions, dialogues and project based learning are some of the tools
available to transfer tacit knowledge. Such knowledge is difficult to pass
on through the use of information technology. Because tacit knowledge
is difficult to document and replicate, it is often the most valuable form
of knowledge.
Some authors draw a distinction between tacit and implicit
knowledge, defining tacit knowledge as that which cannot be written
down, and implicit knowledge as that which can be written down but has
not been written down yet. In this context, explicit knowledge refers to
knowledge which has already been written down.
(See also: SOCIALIZATION, SECI MODEL)
Tag
A keyword which acts like a subject or category, to organize webpages
and objects on the Internet. Tags are used to find or organize objects
with similar properties. Each user “tags” a webpage or image using his
or her own unique tag.
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Tags can also be used to specify properties of an object that are not
obvious to the object itself. Attribute tag searching works by using tags
that define concepts not inherently captured in the content of the
document. A tag can have a brief description of the business activity, the
domain, the formal / physical representation of the knowledge, type of
document, product / service to which it relates, time of creation of the
document and the location of the knowledge element.
An image or webpage may have multiple tags that identify it.
Webpages and images with identical tags are then linked together. Users
may use the tag to search for similar webpages and images. Tags are
used in markup languages (HTML and XML). Tagging content is an
integral part of CONTENT MANAGEMENT SYSTEMS.
Takeuchi, Hirotaka
Dean of the Graduate School of International Corporate Strategy at Hitotsubashi University in Tokyo and a visiting professor at Harvard Business School, Takeuchi has done extensive research on the knowledge
creation process within organizations, competitiveness of Japanese firms
in global industries, new product development, and international corporate strategy. An April 1996 Fortune article introduced him as “among
the intellectual leaders of the younger, globally-minded generation that
is coming to power in Japan.” His book, The Knowledge-Creating
Company, coauthored with Ikujiro NONAKA, is probably the most acclaimed book on knowledge management.
Taxonomy
A classification system, which serves as the table of contents for an organization’s knowledge capital. Taxonomy allows an understanding of
how that body of knowledge can be broken down into parts, and how its
various parts relate to each other. Taxonomies are used to organize information and help users find it easily. Taxonomy provides the structure
governing the way information, documents and libraries are constructed.
This structure helps people in navigating, storing and retrieving needed
information. Taxonomy can also provide pointers to human expertise or
KNOWLEDGE. Taxonomy is useful in breaking down silos and building a
shared language across the organization. Taxonomy serves as a defacto
communication tool that connects people together on a common platform so that they can contribute and share knowledge easily.
(See also: SEARCH ENGINE)
Team Learning
Teams, not individuals, are the fundamental unit of work in modern organizations. Unless teams learn, the organization cannot learn. Teams
play a central role in knowledge creation. They provide a shared context
where individuals can interact with each other and engage in meaningful
conversations. Team learning depends on the ability to engage in “dialogue” and the capacity of the members to suspend assumptions and
enter into a genuine “thinking together” mode. Constructive dialogues
lead to new points of view. DEFENSIVE REASONING is a major impediment to team learning. When there is defensive reasoning and people are
not open, it is difficult for new perspectives to emerge.
Technology
Information technology has a key role to play in knowledge management. Technologies used in knowledge management are different from
those used for handling data. Technologies designed for managing data
are structured, numerically oriented, and address large volumes of observations, and do processing without substantial human intervention.
On the other hand, technologies used in knowledge management must
deal frequently with text rather than numbers. These technologies are
also more likely to be employed in an interactive and iterative manner by
their users.
There are various types of knowledge management technologies.
Some involve participation by large groups of people; others involve
only a few individuals. In case of some technologies, the user must be
something of an expert. Others assume that the user plays a more passive
role. Some knowledge-work environments allow time for search, synthesis, and reflection. A good example is an academic researcher. Others
require real-time or near real-time performance. A good example is a
doctor or call center worker.
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According to Tom DAVENPORT63, technology can support knowledge
work in different ways depending on the nature of the work: Transaction, Integration, Collaboration, and Expert:

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Transaction work involves low amounts of collaboration and judgment. Here, technology can automate structured transactions.
Integration work involves a low level of judgment but a high level of
interdependence. In this case, technology can structure the process
and the flow of work and also facilitate the reuse of knowledge.
Expert work calls for a high level of judgment but a low level of collaboration. Technology must embed knowledge into the flow of the
work process.
In collaboration work, there are high levels of judgment and collaboration. Work is usually iterative and unstructured. Repositories can be
useful here.
Repositories,
GROUPWARE
technologies,
DECISION
SUPPORT
SYSTEMS, EXPERT SYSTEMS, SOCIAL SOFTWARE
and the Internet are
some of the commonly used tools in knowledge management. Groupware, probably the most commonly used technology in knowledge management, supports collaboration. Groupware provides a virtual space in
which people can share experiences, conduct meetings, listen to presentations, hold discussions and share documents.
The Web is ideal for publishing information across different computer platforms. Since it is good at displaying knowledge that is linked to
other knowledge through hyper text links. The Web deals easily with
audio, graphic, and video representations of knowledge. The hyper text
structure of the Web facilitates easy navigation. Intranet Webs are often
the easiest way to get knowledge management started in an organization.
HYPER TEXT MARKUP LANGUAGE (HTML) publishing tools for producing
Web documents, a relational database system for storing them, text
search-and-retrieval engines, and some approach to managing the “metaknowledge” that describes and facilitates access to the knowledge
available, are some of the tools which can be used.
63
Davenport, Thomas H. Thinking For a Living, Harvard Business School
Press, 2005.
Early on in the life of knowledge management initiatives, a “let a
thousand flowers bloom” technology strategy may be helpful. Later on,
however, the sharing of knowledge across organizational boundaries will
be easier with a single, broadly deployed platform.
A good deal of new technology attends primarily to individuals and
the explicit information that passes between them. But the social dimension must not be ignored. Indeed, technology will be effective only when
it can build a community around it. When we go back in time, we notice
that information sharing devices such as the telephone and the fax, like
the book and newspaper before them, became popular not simply
because they carried information to individuals, but because they were
easily embedded in communities.
In the early days, the Internet was designed primarily so that computers could exchange information electronically and computer users could
exchange files. But some insightful programmers decided to introduce email for transferring files. E-mail which helped transform a scientific
network into a social network, still accounts for the bulk of Internet traffic. Similarly, Tim Berners-Lee realized that the World Wide Web
would be much more interesting if it was used not simply for exchanging
information between individuals, but to support collaborators. That is
what has driven the Web’s extraordinary evolution.
IT facilitates capturing knowledge; defining, storing, categorizing,
indexing and linking digital objects, searching for and subscribing to
relevant content. Yet, many people are reluctant to use IT or they use it
only when they are forced to. So IT strategy must begin by thinking
about how people use information.
One important issue in technology involves the way the local informality found within communities is protected. Technologies vary in
terms of formality and trust. At one end are systems that prevent people
from behaving in ways other than those clearly defined and constrained
by the technology. For high-security demands, such technologies will be
increasingly important and indeed may appeal to people. A good example is ATM machines. But if new technologies ask people to negotiate
all their social interrelations this way, the informal, the tacit, and the socially embedded dimensions will be completely ignored. The demands
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for formality demanded by technologies can disrupt informal relations.
For instance, in many situations, asking for explicit permission changes
social dynamics quite dramatically — and receiving a direct rejection
can change them even further. Consequently, people negotiate many
permissions tacitly. A great deal of trust grows up around the ability to
work with this sort of implicit negotiation. Direct requests and insistence
of rights and duties only serve to lower trust and heighten tension.
The limitations of technology should not be overlooked. Many important jobs in organizations get done through social networks. Informal
water cooler and coffee vending machine conversation and impromptu
unstructured meetings will continue to have a role to play in encouraging
informal KNOWLEDGE SHARING.
Technology is not ideally suited for handling TACIT KNOWLEDGE.
Also, technology cannot create new knowledge. Technology by itself
cannot also be a change agent. Changing a company’s knowledge culture requires altering basic behaviors, attitudes, values, management
expectations and incentives. But technology can expand access and ease
the problem of getting the right knowledge to the right person at the right
time. Technology can also raise the motivation to share knowledge.
When people see their company investing time and money on its Web
site or intranet for example, they may take knowledge management more
seriously.
Text Mining
Refers generally to the process of extracting interesting and important
information and knowledge from large amounts of unstructured text.
Text mining combines information retrieval, DATA MINING, machine
learning, statistics and computational linguistics. Several research groups
around the world, as well as R&D departments of big companies, are
doing research on TEXT MINING. One of the largest TEXT MINING applications that exist is the classified ECHELON surveillance system. Until
recently, websites mostly used text based lexical searches. Text mining
will allow more “SEMANTIC” searches. For example, searching for a “car
company” may yield the home page of an automobile manufacturer even
if the page does not contain the words “car company” explicitly.
(See also: SUMMARIZATION)
Transaction Work
A term coined by Tom DAVENPORT to describe essentially routine work
involving low discretion. Formal rules, procedures and training can be
used to structure this kind of work. Technology can facilitate automation
in a big way. Thus, call center workers can be asked to do their jobs according to a clearly laid down script.
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U
Univocality
The extent to which communication is dominated by one perspective.
Univocal communication functions as an information-transmission device. Utterances made by religious leaders, political leaders, moral authorities and teachers are examples of univocality. Such utterances are
not challenged. They are accepted as gospel truth. By itself, univocality
is not bad. Indeed, univocality is desirable in some situations where multiple perspectives are not desirable. Thus an organization’s shared values
or corporate identity must be communicated without any ambiguity. But
in many other situations, divergent thinking and multiple perspectives
must be encouraged. New product development is a good example.
V
Virtual Private Network (VPN)
A technology to create a secure private network using the Internet, without actually having to build a network. Effectively, a private pipeline is
created for exchanging data using the Internet infrastructure. VPNs are
designed in such a way that the security is as strong as in leased, private
lines.
Visualizing Tools
When ideas and concepts are depicted pictorially, they are easy to understand. Powerful visualization tools are available to investigate the structure of knowledge domains and knowledge within domains.
(See also: CONCEPT MAPPING and MIND MAP)
Voiceover IP
An Internet protocol that facilitates real-time voice communications over
the Internet. Voice is converted into information packets that are sent as
streamed data and reconverted into voice at the receiving end. In some
cases, the customers can talk through the BROWSER itself. The integration of the browser and voice allows support staff to pick up from where
a customer left rather than have the customer describe the problem
again.
VPN
See VIRTUAL PRIVATE NETWORK.
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W
Webinar (Web Seminar)
A presentation delivered over the Web using videoconferencing. A
Webinar is a useful KNOWLEDGE SHARING tool in the sense that people
can learn from an expert without leaving their desk. A webinar also facilitates peer group learning. In combination with facilities such as chat,
spontaneous discussions can also take place, leading to a rich exchange
of ideas among people attending a seminar.
Web Server
Software for locating and managing stored web pages. It locates the web
pages requested by a user client on the computer where they are stored
and delivers the web pages to the user’s computer. Web servers can also
work with application servers to access information from a company’s
internal information systems applications and their associated databases.
Web Services
Loosely coupled software components that exchange information with
each other using standard web communication standards and languages.
They can exchange information between two different platforms regardless of the operating systems or programming languages on which the
platforms are based. Different applications can use web services to
communicate with each other in a standard way without custom coding
which is time consuming. Web services can be used to link systems of
two different organizations, or to link disparate systems within a single
company. The collection of web services used to build a firm’s software
systems constitutes what is known as SERVICE ORIENTED
ARCHITECTURE.
Wiig, Karl
A leading expert in knowledge management, Wiig has authored four
books and over 40 articles on knowledge management. A co-founder of
the International Knowledge Management Network, he has helped various
organizations in helping them build their internal knowledge management capabilities. Wiig’s website www.krii.com / who_we_are.htm is
full of useful resources for knowledge management practitioners.
Wiki
A collaboration tool that allows multiple authors to join hands in creating and updating documents. A wiki allows users to easily add, remove,
or otherwise edit all content, very quickly and easily. The ease of interaction and operation makes a wiki an effective tool for collaborative
writing. A wiki records each individual change that occurs over time, so
that at any time, a page can be reverted to any of its previous states. A
wiki may also include various tools, designed to provide users with an
easy way to monitor the constantly changing state of the wiki as well as
a place to discuss and resolve the various disputes that can arise over the
content.
Willpower
A human quality that enables managers to take action even when they
are not inclined to do something. KNOWLEDGE is actionable information.
Unless managers get into action mode, knowledge is of little use. Heike
Bruch and Sumantra Ghoshal, mention in their book, A Bias for Action,
that despite all their knowledge and competence, their influence and resources at their disposal, managers do not grab the opportunities to
achieve something significant. Purposeful action requires energy and
focus. More than motivation is needed to spur people to purposeful action. What is needed is willpower.
Managers with willpower overcome barriers, deal with setbacks and
persevere to the end. Just as DEFENSIVE REASONING can block learning,
lack of will power can block action.
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Wisdom
Understanding clearly which knowledge to use for what purpose and
wisdom is the ability to make correct judgments and decisions. Wisdom
goes beyond knowledge. Many people think it is an intangible quality
gained through experience. According to Encarta, wisdom is the accumulated knowledge of life, or of a sphere of activity that has been gained
through experience. Wisdom is often determined in a pragmatic sense by
popularity, longevity and the ability to predict future events. Wisdom is
also accepted from cultural, philosophical and religious sources. Some
think of wisdom as foreseeing consequences and acting in a manner that
maximizes beneficial results. For many, wisdom connotes an enlightened perspective, something used for the long-term common good; recall King Solomon in the Bible. According to Andrew Hargaddon, a
well known researcher in the area of innovation, if knowledge is the
grasp we have over a subject, wisdom is the grip. A wise person is not
only knowledgeable but is also prepared to give up existing knowledge
for new knowledge when the situation demands.
Work Ambience
The physical work environment. Work ambience has an impact on
knowledge work productivity. KNOWLEDGE WORKERS prefer to work in
closed offices but seem to communicate better in open ones. Since
knowledge workers like to collaborate, there must be meeting spaces and
conference rooms. But when concentration is necessary, knowledge
workers require quiet settings with few distractions. Knowledge workers
like flexibility and occasionally they like to work at home. But they
don’t want their homes to be their only offices. They want to come together from time to time and exchange notes about their work.
Knowledge workers vary in their tasks and needs. So the most optimal physical work environment may well vary across workers. Transaction workers need work environments in which they can concentrate on
their transactions, while sitting at their desk. Expert workers also want to
concentrate while doing their work, but they may need more space to
keep books, journals, etc. which they may refer from time to time. Inte-
gration workers need an environment in which they can easily communicate with coworkers.
The right approach to workplace design depends on various factors:



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How homogeneous is the organization?
How important is it for the organization to align knowledge workers’
needs and their work settings?
How much freedom does the management want to give knowledge
workers in designing their work space?
How much is the company willing to invest?
Firms predominantly engaged in one type of work can provide one
standard work setting for all employees. Those with a moderate degree
of segmentation can group their employees into a limited number of categories and assign pre-defined work settings to each. Yet other firms
need to have different work settings for different groups of employees.
(See also: CAVES AND COMMONS)
Workflow Management Tools
Tools which facilitate PROCESS management in information intensive
organizations. Essentially an offshoot of traditional flowcharting tools,
workflow tools help specify the movement of documents and facilitate a
better understanding of information processes. Workflow software can
be used to remake and streamline business processes. It focuses on the
steps that make up processes and redesigns these steps. Work is routed
automatically from employee to employee. Workflow software effectively helps in eliminating paperwork and bureaucracy. Such software
also makes the management of projects and activities more transparent.
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X
XML (Extensible Markup Language)
A programming language that allows for the creation of customized
TAGS for individual information fields. XML is essentially a Web-based
markup language that allows a wide range of user-defined tags. XML is
an updated version of HTML. XML not only describes the way to lay
out content on a web page for display or printing, but also describes the
nature of the content. XML provides a simple way to handle data exchange over the Internet. Whereas HTML is limited to describing how
data should be presented in the form of web pages, XML can present,
communicate and store data. An XML file can contain the data too, as in
a database.
HTML has an inflexible, single-purpose vocabulary of elements and
attributes. XML makes it easier to write software that accesses the document’s information, since the data structures are expressed in a formal,
relatively simple way.
The easy availability of word processors facilitates rapid XML document authoring and maintenance. Before the arrival of XML, there
were very few data description languages that were general-purpose,
Internet protocol-friendly, and easy to learn and author. In fact, most
data interchange formats were proprietary, special-purpose, “binary”
formats that could not be easily shared by different software applications
or computing platforms.
XML makes it possible for computers to manipulate and interpret
their data automatically and perform operations on the data, without any
human intervention. Programmed rules can be used for applying and
displaying data. XML provides a standard format for data exchange,
enabling web services to pass data from one process to another. XML
database management systems are commonly used in B2B e-commerce.
Because they use documents and not tables, they can perform much faster than conventional database systems. It is much easier for people to
exchange data without getting involved in the underlying database
design.
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Y
Yellow Pages
A colloquial term for an expertise directory. It provides a list of experts,
a brief account of their expertise and their contact details.
(See also: EXPERTISE DIRECTORY)
Z
Zack, Michael
A reputed scholar in the area of knowledge management. Zack’s research and publications have focused on the use of information and
knowledge to improve organizational performance effectiveness. His
publications have appeared in a number of leading journals including
Organization Science, Sloan Management Review, California Management Review, Information Systems Research, and Information & Management. Some of his important articles include: “Managing Codified
Knowledge”, Sloan Management Review, Summer, 1999; “Developing a
knowledge Strategy”, California Management Review, Spring, 1999 and
“The Design and Development of Information Products”, Sloan Management Review, Spring, 1996.
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Case Studies
Knowledge Management in Action
1. McKinsey & Co
INTRODUCTION
Mckinsey64 was founded in 1926, by Professor James Mckinsey of the
University of Chicago. Mckinsey laid the foundation for a world class
organization by recruiting experienced executives and training them in
systematic business analysis using a framework built around goals, strategy, policies, organization, facilities, procedures and personnel. The
turning point came in 1932, when a bright young lawyer and a Harvard
MBA, Marvin Bower, joined the firm. Bower injected a strong element
of professionalism into his people. He believed in the highest standards
of integrity, professional ethics, technical excellence and client focus.
Bower emphasized that every assignment should bring the firm experience and prestige besides money. By the time Bower retired in 1967,
Mckinsey had gained widespread acceptance throughout Europe and
North America as a leading consulting firm.
It was in the early 1970s, in the wake of the oil crisis, appearance of
new competitors and growing expectations of clients, that Mckinsey
realized the need to develop new capabilities and equip its consultants
adequately. Ron Daniel, who took charge in 1976, was appointed
McKinsey’s first full time director of training. Daniel not only established industry based sectors but also gave a new thrust to the development of functional expertise. He set up two working groups to accumulate more expertise in the firm’s core areas of strategy and organization.
64
This caselet draws heavily from Sumantra Ghoshal and Christopher
Bartlett’s fascinating book The Individualized Corporation and the case,
Mckinsey & Company: Knowledge & Learning, Harvard Business School,
1996.
The knowledge building initiatives of Mckinsey gathered momentum
in the early 1980s. The top management made it clear that knowledge
development had to be a core, not a peripheral firm activity, that it needed to be ongoing and institutionalized, not temporary and project based
and had to be the responsibility of everyone, not just a few people. The
firm set up 15 centers of competence around different areas of
expertise like strategy, organization, marketing, change management and
systems.
Mckinsey consultants started pursuing thought leadership in a big
way by publishing books based on their expertise and consulting experience. Articles were also published in top management journals, such as
Harvard Business Review. To improve knowledge sharing within the
firm, Practice Bulletin, a two page summary of important new ideas was
introduced. In 1987, a knowledge management project was launched. As
part of efforts to build a common database of knowledge, each practice
area appointed a coordinator, who was responsible for the quality of the
documents that went into the database. Consultants were begged, cajoled
and challenged to contribute documents to the Practice Development
Network (PDNet). A list of experts was compiled along with key document titles by practice area and published in a small book, called the
Knowledge Resource Directory.
Meanwhile, Mckinsey realized that it was neglecting the development of the technical and professional skills of its consultants. The company’s partners decided to invest heavily in the development of its
bright, young people and make them T shaped consultants, i.e. people
who combined specialized industry knowledge / functional experience,
with generalist problem solving skills and client development capabilities. The top management realized that while the former could be acquired through formal training and focused experience, the latter needed
intensive counseling and mentoring relationships that Mckinsey people
called the “apprenticeship process”. To send out a clear signal that the
consulting firm was serious about people development, Fred Gluck, the
managing director at the time, announced, “There are two ways to look
at Mckinsey. The most common way is that we are a client service firm
whose primary focus is to serve the companies seeking our help. That is
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legitimate, but I believe there is an even more powerful way for us to see
ourselves. We should begin to view our primary purpose as building a
great institution that becomes an engine for producing highly motivated,
world class people who in turn, will serve our clients extraordinarily
well.”
Unlike many rivals who invested in developing tools and techniques
and then training consultants in the use of these tools, Mckinsey remained somewhat weary of packaged management concepts. This belief
in the craft of consulting, as opposed to the science, led to significant
investments in personal coaching and mentoring. Rajat Gupta, Gluck’s
successor, set an example by spending a substantial amount of his time,
coaching young partners. He introduced a firm wide event called “The
Practice Olympics”. Teams of young associates from all over the world,
presented new ideas and concepts they had developed. Finalists were
judged by a panel that included Gupta himself.
An estimated 10-20% of the average partner’s time began to be spent
in coaching and mentoring. Through the mentoring process, not only
problem solving skills but also the firm’s values and aspirations were
transmitted. Because of the support from their mentors, mentees were
able to operate confidently, often going beyond their comfort zone.
Today, McKinsey is acknowledged as a global leader in managing
knowledge. Many companies view McKinsey as the benchmark. But it
is clear that, though books and cases have been written about McKinsey,
replicating McKinsey’s culture that lays a premium on knowledge creation and sharing, will be difficult for most companies.
2. Pfizer65
A global pharmaceutical company which takes knowledge management
very seriously is Pfizer. The company has integrated knowledge management with its succession planning mechanisms. Pfizer has a well defined process for knowledge transfer from the incumbent to the successor in case of key strategic positions. The company carefully determines
what knowledge must be transferred and pairs the incumbent and successor together to facilitate the knowledge transfer. The transfer is implemented by combining documented content in various forms with
face-to-face meetings and discussions. Follow up reviews are held to see
how the successor is faring.
The aim is to make a newcomer competent in the shortest possible
time by focusing on the relevant areas of knowledge. Pfizer considers
task, process, behavioral system and environmental model as the building blocks. The environmental model explains how things get done. It is
about connecting vital things to get an effect. At the next level, come the
behavioral issues. Then comes the process, how things ought to get
done. Finally, there are the tasks that have to be done as part of the process. By breaking down knowledge into these four levels, Pfizer is able
to prioritize what knowledge the incumbent should be transferring to the
successor.
Pfizer believes that this kind of knowledge transfer is necessary to
reduce the risk of “decision black spot”. New people often have difficulty in understanding where an important decision is required. The process
also identifies the areas of self-study needed and when experts must
spend time with the successor.
In short, Pfizer employs a six-step knowledge retention process:


65
Identify the people in transition in a key strategic role.
Determine the knowledge that has to be transferred.
This caselet draws heavily from the interview with Victor Newman,
Chief Learning officer, Pfizer Research University, KM Review, January /
February 2002.
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Examine the significant work patterns that the successor needs to
understand.
Put together a knowledge succession plan that includes printed documents and face-to- face interaction.
Implement the plan, combining documented content and a schedule
of discussions.
Use follow up discussions to monitor the knowledge transfer process.
Pfizer also attaches great importance to tacit knowledge. The company attempts to systematically identify and capture tacit knowledge in
various ways by addressing some basic questions:




What kind of individual expertise have people added to documented
processes?
How are people prioritizing their daily tasks?
What are the factors that determine success on the job?
If they are based on connections in the organization, effective prioritization or a process orientation, how can these skills be developed in
others?
In short, Pfizer has brought a strong practice orientation (as opposed
to process orientation) to its knowledge management initiatives.
3. Kao66
The Japanese company, Kao is a six-time MAKE Japan Winner, widely
respected for its enterprise-wide knowledge sharing and collaboration,
and organizational learning. Kao is a four-time Asian MAKE Winner
(2002-2005), and a six-time Global MAKE Finalist (1999, 2001-2005).
Kao’s major product lines include Personal Care, Home and Fabric
Care, and Feminine and Baby Care. Kao’s Prestige Cosmetics line (Kao
Sofina) is marketed in Mainland China, Hong Kong and Taiwan. In the
field of chemical products, Kao has established production bases in Asia,
North America and Europe.
Kao illustrates the role of leadership in building a learning organization. Founded in 1890, Kao initially produced soaps. In the post-War
era, Kao started offering laundry detergents. Subsequently, the company
moved into dishwashing detergents and household cleaners. It was in the
1970s and 1980s, under the leadership of Yoshiro Maruta that learning
became an integral part of the company’s corporate philosophy.
For Maruta, leveraging knowledge went far beyond improving processes and products. He wanted his people to come up with new ideas
and products. He made it clear that teaching and learning were core responsibilities of employees. Maruta give managers easy access to the
data they needed.
Maruta concentrated on developing an organization designed to run
as a “flowing system”, where ideas, abilities and resources flowed freely
to where they were most needed. He once remarked: “Just as the body
reacts to pain or to injury by sending relief or support to the affected
area, so too must the organization respond. If anything should go wrong
in one department, others should sense the problem and help without
being asked”.
Through such statements, metaphors and analogies, Maruta shaped
an environment that became receptive to cross-unit initiatives.
66
This caselet draws heavily from the book The Individualized Corporation by Sumantra Ghoshal and Christopher Bartlett
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By encouraging redundancy of information, individuals became exposed to a wide range of ideas and perspectives in the normal course of
the day’s work. Employees could find out as much as they wanted to
know and understand how their job fit into the larger picture. They could
easily access information, such as the sales record of any product, the
performance of any unit, new product development activities and happenings in the company’s research laboratories.
Maruta also realized the importance of Ba, or context, for knowledge
sharing. He designed “decision spaces” for creative ideas and healthy
debate to flourish. These were large open areas at the centre of an office
floor or research lab, with a conference table, overhead projectors and
whiteboards where people gathered to discuss and decide on critical issues. The agenda was widely publicized and people from different departments could join the discussion.
Maruta encouraged the practice of tataki-dai. Individuals were asked
to present their ideas to their colleagues at 80% completion stage so that
they could be evaluated by others before the decisions became irreversible.
Kao’s espoused belief of being an “educational institution” encouraged people to work collectively towards shared goals and values, rather
than restrictively, within their narrow self interests. Employees began to
share knowledge with the firm conviction that such sharing would benefit the organization as a whole.
According to Teleos, the knowledge management consulting firm,
Kao has succeeded because of a highly flexible and flat organizational
structure — referred to by Kao as a “bio-function” — which mimics a
living organism and various enabling mechanisms known by such terms
as “free access to information,” “open floor allocation,” “open meetings”
and “fluid personnel change”. These approaches greatly facilitate tacit
knowledge sharing and the conversion of tacit knowledge into explicit
enterprise knowledge. Staff are regularly rotated among job functions
and business units. Typically, employees will serve in at least three different positions in their first 10 years with the company. The company’s
ECHO (Echo of Consumer’s Helpful Opinions) system processes and
analyzes customers’ product questions and complaints. Kao receives
more than 50,000 queries and comments each year. Information that
may be useful in solving problems is often compiled into reports and
sent to the appropriate departments, including R&D, production, marketing and sales.
The lesson from Kao is that learning organizations do not evolve on
their own. They have to be shaped consciously and deliberately by top
management. Clear signals from the top and actions which demonstrate
that intentions are genuine can go a long way in shaping a learning organization.
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4. Silicon Valley67
Knowledge creation is not limited to a single organization. Sometimes,
knowledge creation can span organizations. Silicon Valley in California,
USA, widely considered to be the world’s leading high tech cluster is a
good example.
Silicon Valley’s origins go back to Hewlett Packard (HP) which was
founded in 1937 by William Hewlett and David Packard with the encouragement of their professor, Frederick Terman. HP took off during
World War II. A small cluster of technology firms grew up alongside HP
and laid the foundation for the electronics industry in the region.
A visionary in every sense of the word, Terman did a lot to strengthen ties between Stanford where he became the dean in 1946 and the local industry. He set up Stanford Research Institute to conduct defenserelated research and to assist west coast businesses and opened the university’s classrooms to local companies through the Honors Cooperative
Program. Terman also promoted the Stanford Industrial Park which further strengthened the linkages between the university and local industry.
Several companies were attached to the Valley. Shockley Transistor
was set up in Palo Alto in 1955. By 1970, it was the largest and most
dynamic company in the region. A group of people broke off from
Shockley and set up Fairchild semiconductor. Fairchild itself spawned
10 spin-offs in its first eight years, the most celebrated one being Intel
set up by Robert Noyce, Gordon Moore and Andy Grove. By 1975, Silicon Valley’s technology enterprises employed well over 1,00,000 workers.
Even as the number of tech companies in the Valley increased, a
network of suppliers also emerged. By the early 1970s, venture capital
replaced the military as the main source of financing for start ups in the
valley. Successful entrepreneurs chose to invest their earnings in
promising new companies. The Valley’s relatively young companies and
the distance from Washington facilitated experimentation with technolo67
This caselet draws heavily from Annalee Saxenian’s Fascinating book,
Regional Advantage.
gy and business models. The culture of Silicon Valley encouraged risk
taking and accepted failure. Entrepreneurs created firms that were organized as loosely linked configurations of engineering teams. The result
was a flexible industrial system organized around professional and technical networks rather than around the individual firm.
Informal collaboration became common in the Valley. Informal conversations kept people informed about competitors, customers, markets
and technologies. Competitors consulted one another, with a frequency
unheard of in other parts of the US. Mobility across firms not only became acceptable but also quickly turned into a norm. Headhunters arrived in the 1970s, as the war for talent hotted up. Signing bonuses,
stock options, high salaries and interesting projects, were used to attract
smart people. As the firms were located geographically close to one another, people could change jobs with minimal dislocation. Loyalty to
one’s craft superseded loyalty to one’s company. When engineers
moved from one company to another, they took with them the
knowledge, skills and experience acquired in their previous jobs. A distinct technical language evolved in the region.
By the early 1970s, Silicon Valley had developed a solid reputation
for the speed with which technical skills and know-how diffused within
the local industrial community. The region’s social and professional
networks effectively functioned as a kind of large extended organization.
The region and its networks, rather than individual firms, became the
focus of economic activity. Service providers like lawyers, market research firms, consulting companies, public relations companies and electronic distributors facilitated the growth of the region. Berkley, California State University and various community colleges supplemented
Stanford in supporting Silicon Valley’s technical infrastructure. The proliferation of firms did not lead to destructive competition. Instead, the
Valley’s supportive social structures, institutions and collaborative practices encouraged mutual learning and adjustment. Firms cooperated in
various ways — cross-licensing, second sourcing arrangements, technology agreements and joint ventures. Competition demanded innovation, which in turn called for inter-firm cooperation.
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The Valley’s companies played a significant role in fostering and
reinforcing the region’s culture. Firms downplayed hierarchy and gave
individuals considerable autonomy and responsibility. Intel set an example by encouraging openness and confrontation. HP used a decentralized
structure that attempted to eliminate hierarchy and status and emphasized teamwork.
Essentially, the Valley’s industrial system blurred the boundaries
between social life and work, between firms, between firms and local
institutions, and between managers and workers. In a few decades, the
Valley became one of the most prosperous regions in the world, creating
wealth at a rate few could have imagined in their wildest dreams a few
decades earlier. Looking back it is clear that inter-organizational
knowledge creation has played a key role in the emergence of Silicon
Valley as the world’s best known industrial cluster.
San Jose, located in the heart of California’s Silicon Valley topped
the WKCI (World Knowledge Competitiveness Index) 2005 list. The
WKCI is an integrated and overall benchmark of the knowledge capacity, capability and sustainability of 125 regions across the globe, and the
extent to which this knowledge is translated into economic value, and
wealth. WKCI is based on 19 knowledge economy benchmarks, including employment levels in the knowledge economy, patent registrations,
R&D investment by the private and public sector, education expenditure,
information and communication technology infrastructure, and access to
private equity. San Jose is followed by Boston, San Francisco, Hartford
and Seattle. The highest ranked non-US region was Stockholm in Sweden. Tokyo was the highest ranked region outside North America and
Europe. Incidentally, the 2005 WKCI rankings highlight the gap in
competitiveness between the US, which has 41 of the top 50 regions in
the index, and the rest of the world.
5. Toyota68
Toyota holds a unique place in the global automobile industry.The way
Toyota designs and manufactures cars has led to an unbelievable consistency in its processes and products. Toyota designs cars faster than
global manufacturers. Toyota’s cars are among the most reliable and
extremely cost competitive. While many American and European car
manufacturers have continued to struggle in recent years, Toyota has
gone from strength to strength. Soon, Toyota will be the largest car maker in the world in terms of revenues. Many attribute Toyota’s success to
just-in-time and manufacturing excellence. But what is less appreciated
is the role played by knowledge creation and sharing in building the
company’s strong competitive position.
Toyota has attempted to encourage employees to learn in various
ways. The company motivates employees to grow in their jobs by constantly identifying, analyzing and solving problems. Managers deal with
problems by going to the source and personally observing and verifying
data rather than theorizing on the basis of what other people tell them.
Even senior executives are expected to have an in-depth understanding
of the situation. This is called genchi genbutsu. That means studying the
problem first hand and having a thorough grasp of the situation before
actually solving the problem.
Toyota believes in standardized tasks and processes. The company
deploys stable, repeatable methods everywhere to maintain predictability. Toyota standardizes existing best practices. It then encourages individual initiative and creativity to improve the standard. Innovative ideas
that work are then incorporated into a new standard. Continuous improvement initiatives result in standards being redefined from time to
time.
Individual employees do come up with innovative ideas in many organizations.Where Toyota scores is in its ability to standardize and practice the new idea across the organization until a better way is discovered.
This caselet draws heavily from Jeffrey K. Liker’s book, The Toyota
Way.
68
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The Toyota way of learning is all about standardization punctuated by
innovation which then gets translated into new standards.
Toyota emphasizes hansei or reflection at key milestones. After a
project is finished, employees identify all the mistakes made. Then steps
are taken to prevent the same mistakes from happening again.
Toyota does not believe in flamboyance. Indeed, many observers
dismiss the company as boring. But Toyota could not care less. Toyota
believes that learning is all about having the capacity to build on the past
and move forward incrementally, rather than start over and reinvent the
wheel with new personnel in each project. So the company believes in
stability of personnel, slow promotion and very careful succession planning to protect the organizational knowledge base.
At Toyota, Kaizen or continuous improvement is an important tool
for learning. The essence of Kaizen is an attitude of self reflection and
self-criticism, accompanied by a burning desire to improve. Employees
can openly address things that did not go right, take responsibility and
propose suitable measures to ensure that the mistakes do not happen
again.
One technique Toyota uses effectively is to ask “why” five times
when dealing with a problem. By doing so, Toyota employees go beyond the symptoms to the root cause of the problem. The aim is to take
counter measures at the deepest level of cause that is feasible and at the
level that will prevent recurrence of the problem.
Toyota understands that the key to organizational learning is to align
the objectives of all its employees with common goals. Toyota believes
that simply setting specific, measurable, challenging goals and then
measuring progress, is highly motivating, even when there is no tangible
reward associated with success. Toyota sets challenging goals and is
passionate about measurement and feedback. Toyota uses Hoshin Konri,
the process of cascading objectives from the top to the work group level.
Every team member knows his or her small number of specific objectives and works on them through the year. During formal review sessions, the progress towards achieving Hoshin Konri objectives is monitored.
Many companies waste their time on fire fighting and introducing
quick fix improvements. What Toyota does is to focus on long term improvements through Hansei and Kaizen. Reflection and a relentless focus on making further improvements have helped Toyota in creating and
applying knowledge almost as a matter of routine. The transformation of
Toyota into a learning organization has not happened overnight. It has
taken decades. But it is precisely because of its superior ability to learn
that today Toyota is far ahead of others in the global car industry. The
task of building a truly learning organization is daunting but so too are
the rewards. That is the message we get from Toyota.
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6. Partners HealthCare 69
Partners HealthCare (Partners), a group of Harvard-affiliated hospitals in
Boston, illustrates how experts can be supported by a well designed
knowledge management system. Partners has attempted to embed
knowledge throughout the information systems used by its physicians.
While prescribing a drug, ordering a test, referring a patient to another
physician or calling up the patient’s medical record, the knowledge base
can be accessed. For example, when a doctor calls up a medical record,
the system may recommend that some follow-up tests are desirable.
At the core of the knowledge management system at Partners lies a
computerized physician order entry system which packs a lot of
knowledge. For example, the system may inform the doctor that the drug
being prescribed may not be advisable as it may interact with a drug the
patient is already taking. Ordering is where physicians take decisions
about patient care. It is the point at which knowledge is most valuable.
There are also occasions when physicians need knowledge when they
are not face to face with a patient. For example, there is a system of
alerts to physicians when a hospitalized patient’s monitored health indicators significantly depart from the norms. In that case, the physician can
immediately visit the patient or advise a nurse to change the treatment.
A physician may use different systems for different transactions. But
all these systems are integrated and leverage a common database of patient clinical information and a common logic engine. Partners has also
assembled various other sources of knowledge that are provided through
online knowledge repositories in an integrated intranet portal.
There is clear evidence that the system is having a major impact on
the way health care is being offered by Partners. According to some estimates, serious medication errors have been reduced by 55%. The quality of prescription has also improved, with cheaper and more effective
drugs being used more often.
69
This caselet draws heavily from the book Thinking For A Living by Tom
Davenport.
The tracking mechanisms within the system can detect whether the
physicians use the embedded knowledge and change their treatment
decisions. This serves as a useful measure and helps understand how
effectively the knowledge management system is working. The system
facilitates measurement of key processes. The measures serve as the basis for ongoing efforts to further improve healthcare processes.
It has not been easy to put in place such a sophisticated system. Partners had to pull together the knowledge base and logic modules with an
integrated patient recording system, a clinical decision support system,
event management systems for alerts, an intranet portal and several other
system capabilities. Off the shelf packages were not available. But Partners was motivated to go ahead with the knowledge management system
in view of the high levels of medical errors.
Having decided to go ahead, Partners planned the project carefully.
Partners realized that the knowledge being embedded into critical processes, had to be of a high quality and also current and up-to-date.
Committees were set up to identify, refine and update the knowledge in
each domain. Participation in these committees became a matter of prestige. Physicians became willing to devote time to codifying knowledge
within their fields.
The people for implementing the system were selected carefully. Instead of a back-room IT group, Partners used people skilled in medical
informatics, for implementation. Partners leveraged the several medical
informatics departments in Partners, headed by people with a good understanding of patient care as well as information technology.
As the initiative was difficult and expensive, Partners decided to focus on truly critical knowledge work processes. Decisions were made
about which disease domains and which medical sub processes to address and in what order. Partners also identified fields with many disease
variants and multiple alternative treatments and protocols that were more
difficult to include in the knowledge management system.
Partners has attempted to combine the best of information technology
and human intervention. The system only provides a recommendation to
the physician. There is no pretension that technology will replace ex-
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perts. It is expected that the physicians will combine their knowledge
with that of the system, to make the right decision.
7. NTT DoCoMo70
The Japanese company, DoCoMo is one of the world’s most well known
Internet service providers. DoCoMo’s i-mode service allows subscribers
to remain connected to the internet via their cell phones. Subscribers can
enjoy a range of services like checking stock prices, conducting bank
transactions, reading news and horoscopes and playing games.
DoCoMo was spun off from its parent company, the large and bureaucratic NTT in 1992. Koji Oboshi, CEO of DoCoMo chose Keiichi
Enoki as the project leader. Enoki was not only in touch with the market
trends but was also not afraid to speak out freely. Oboshi felt that a leader who could think independently, was necessary to create the right context. Enoki was selected for the role, though he did not have any specialized knowledge of wireless technology.
Realizing the need for creativity and out-of-the-box thinking, Enoki
built his team carefully. Mari Matsunaga, the editor of a women’s magazine was recruited to work on the content. Tsuyoshi Natsuno, an Internet
entrepreneur was also appointed. Enoki sheltered the project team from
outside influences. He acted as an interface between the project and other departments so that project members were kept out of avoidable conflicts.
The new team came together and started sharing ideas and opinions.
They were guided by Oboshi’s knowledge vision “From volume to value”, which reflected his belief that DoCoMo had to go beyond voice
communication into data communication. Matsunaga had good
knowledge of young consumers based on her experience as a magazine
editor. Her lack of awareness of technology brought the much needed
diversity to the team.
Matsunaga wanted the service to be fun, holding appeal to even ordinary technology ignorant people, like herself. She felt the content should
be something “you can enjoy when you have a bit of time, not just useful
contents such as news and banking service”. Matsunaga used “my conThis caselet draws heavily from the article, “Knowledge Creation as a
Synthesizing Process” by Ikujiro Nonaka and Ryono Toyama.
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cierge” as a metaphor to explain the concept of i-mode service as someone to help people find what they wanted quickly. This metaphor made
more sense to ordinary customers, compared to other equivalent terms
like “secretary” or “agent”.
On the other hand, Natsuno had a good understanding of the Internet
and came up with an innovative business model. Natsuno sensed that
Japanese consumers would access the internet via the cell phone, not
PCs. Instead of buying content, the team decided to work collaboratively
with content providers. DoCoMo collected fees on behalf of content
providers as part of its monthly billing and took a 9% commission. Content providers liked the arrangement because they could reach out to a
large number of subscribers. It was a win-win arrangement. Both DoCoMo and the content providers could make money. Natsuno leveraged
his experience to cultivate the content providers.
DoCoMo decided not to use the existing Wireless Application Protocol (WAP). By using compact HTML, the team was able to take advantage of the vast amounts of content available in the Internet world.
Soon i-mode became popular across Japan and attracted attention
across the world.
8. Chaparral Steel71
Chaparral Steel, a leading steel manufacturer in North America, started
its operations at its Texas plant in July 1973 as a mini-mill producering
steel bar products with an annual capacity of 0.25 million tons. In 1999,
the company completed construction of its modern, low-cost structural
steel plant in Virginia, which nearly doubled its structural steel capacity
and expanded its product line. Over the years, as it grew in size, Chaparral demonstrated how knowledge can be used to generate a sustainable
competitive advantage in a low margin business.
Chaparral utilizes mini-mill technology. Recycled scrap steel is melted in electric arc furnaces, and continuous casting systems convert the
molten steel into a broad range of products. The company manufactures
hundreds of different types, sizes and grades of structural steel and bar
products.
Chaparral markets its products throughout the United States, Canada
and Mexico, and to a limited extent in Europe. The company sells its
products to steel service centers and steel fabricators for use in the construction industry, as well as to cold finishers, forgers and original
equipment manufacturers for use in the railroad, defense, automotive,
manufactured housing and energy industries.
To stay ahead in the steel industry, Chaparral must be able to produce
high quality steel at the lowest cost, without diluting safety norms.
Knowledge management requires knowledge. Knowledge management
at Chaparral is driven by shared-values, creative problem solving, implementing and integrating new methodologies and tools, formal and
informal experimentation and drawing expertise from outside.
For knowledge management to be effective, knowledge must flow in
all directions. Chaparral encourages all employees to contribute ideas.
The company has taken various steps to minimize both vertical and horizontal barriers to knowledge sharing. There are few layers and plant operators can easily approach the top management. Horizontal boundaries
This caselet draws heavily from Dorothy Leonard’s article, “An Organic
Learning System at Chaparral Steel”, Knowledge Management Review,
July-August, 1998.
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are also minimal. Multi tasking is quite common. Production workers do
quite a bit of the maintenance work. All people consider themselves to
be sales people. Security guards enter data while on night duty. They are
trained to function as paramedics too.
Decisions about process improvements are taken at the lowest levels.
These improvements are immediately implemented without waiting for
management approval or standardization of best practices. If a process
modification works, it becomes the de facto standard and other departments embrace it.
Work is structured keeping in view the ease of knowledge dissemination. Workers involved in commissioning a new plant or process are
dispersed among the other crew to diffuse the knowledge they have created, in particular the unique features of the new process.
There is no separate R&D facility at Chaparral. Indeed, it is often
difficult to identify the source of innovation. People share in the pride of
doing and if the experiment fails, everyone shares in the failure. Unlike
most companies, where a few people take responsibility for innovation,
Chaparral believes that when many people contribute in small amounts,
the total adds up to something significant.
9. Canon72
Canon is one of the most admired companies in the world. Canon is a
four-time MAKE Japan Winner (2002-2005), widely recognized for
developing knowledge workers through senior management leadership,
maximizing the value of enterprise intellectual capital, and delivering
value based on customer knowledge. Canon is a two-time Asian MAKE
Winner (2003-2004), and 2003 Global MAKE Winner.
Over the years, the company has developed new capabilities and entered new areas. Today, the company has three main product lines: office equipment (photocopiers, facsimile machines and printers for computers), cameras and optical and digital equipment. The company employs over 1,00,000 people and has marketing and sales operations in
over 100 countries. It maintains major research centers in Asia, Europe
and North America.
The company’s transformation into a world class corporation started
under the leadership of Fujio Mitarai, who became president in 1995.
Mitarai attempted to combine the aggressive bottom line orientation of
American managers and the strong people orientation of Japanese leaders.
In informal “asakai” or morning sessions, Mitarai involved his people
in discussions where many ideas began to emerge. These meetings also
helped identify problems and debate issues from various angles,
effectively providing a shared context or Ba where market opportunities
could be identified and pursued in line with the company’s capabilities.
Canon provides a good example of knowledge creation using metaphors and analogy. As Nonaka has put it73, “Metaphor is mostly driven
by intuition and links images that at first glance seem remote from each
other… analogy is a more structured process of reconciling contradictions and making distinctions… the contradictions incorporated into
72
This caselet draws heavily from the book The Knowledge Creating
Company by Nonaka and Takeuchi.
73
Nonaka, Ikujiro. “The Knowledge Creating Company”, Harvard Business Review, Nov. / Dec. 1991, pp. 96-104.
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metaphors are harmonized by analogy. In this respect, analogy is an
intermediate step between pure imagination and logical thinking”.
Metaphor and analogy lead to concepts which can be embodied in a
model which makes the knowledge available to the rest of the company.
Canon made full use of analogy while designing its personal copier.
Intended for family / individual use, the personal copier needed to have
high reliability and low maintenance costs. Canon’s market research
revealed that 90% of the maintenance problems came from the drum and
its surrounding parts. So the company’s product development engineers
came up with the concept of a disposable cartridge system in which the
drum was replaced after a certain amount of usage.
The next challenge was to figure out how to produce the drum at a
low cost, in line with the low selling price of the copier. The task force
set up in this regard discussed the possibility of making conventional
photosensitive drum cylinders with a base material of aluminum drawn
tube at a low cost. But the team could not make much progress. The
breakthrough came only when the team leader asked the question,
“How much does it cost to manufacture a beer can?” Soon the team
started discussing how to apply the basic principles underlying the
manufacture of the beer can to making the copier’s drum cylinder. The
team analyzed the situation, examined the similarities and differences
and came up with a process technology to manufacture the aluminum
drum at a low cost.
The development of Canon’s mini copier explains how externalization, the process of converting tacit knowledge to explicit knowledge,
works. Tacit knowledge becomes explicit knowledge through metaphors, analogies, concepts, hypotheses or models. While metaphors create a network of new concepts mostly through iteration, analogies focus
on the structural / functional similarities and differences through rational
thinking. Analogies help in bridging the gap between an image and a
logical model or prototype.
According to the knowledge management consulting firm Teleos,
there are several useful lessons to be picked up from Canon’s approach
to knowledge management. Canon views itself as a knowledge-creating
organization. Innovation is embedded in the company’s overall business
strategy. Canon spends over 7% of its annual sales on research and de-
velopment. The company has a global network of R&D facilities to tap
expertise available in each region. Virtual product development teams
and advanced electronic collaboration technologies support Canon’s
R&D efforts. The organizational culture encourages individual and
group learning. Canon has also established best practices in managing its
intellectual property.
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10. British Petroleum (BP)74
BP is one of the largest oil companies in the world. For many, the oil
industry is a commodity business. But BP has demonstrated that there is
scope to leverage knowledge even in such a business. BP’s transformation into a learning organization began under the leadership of John
Browne who became CEO in 1995. Browne realized that learning lay at
the heart of a company’s ability to adapt to a changing environment. To
generate value for shareholders, Browne understood BP had to be a better learner than its competitors and apply knowledge throughout its business faster and more widely than they did. As he put it, “… anyone in
the organization who is not directly accountable for making a profit,
should be involved in creating and distributing knowledge that the company can use to make a profit”. Browne’s message to his people was that
every time BP did something, it should do it better than the last time. If
BP would drill each well more efficiently than the previous one, profits
would increase substantially. Each time an oil well was drilled, employees were asked to reflect on what went right and what went wrong and
how the learning could be applied to future projects.
Browne encouraged employees to learn from contractors, suppliers,
partners, customers and the company’s own experiences. Browne defined the purpose of his business clearly, so that people could understand
what kind of knowledge was critical and what they had to learn in order
to improve performance. He made it clear that BP had to achieve cost
leadership, generate acceptable returns for shareholders and conform to
high standards of ethics, health, safety and environment. After serious
introspection, specific areas came for more attention. One was replacing
the falling oil reserves. BP was exploring in many countries. The management realized that advances in technology and the new markets opening up in various parts of the world were creating opportunities to find
and develop big new oil and gas fields where the costs would be lower
74
This caselet draws heavily from the interview with John Browne, former
CEO of BP, Harvard Business Review, September-October 1997.
and the growth potential was higher. BP decided to concentrate on some
20 countries.
Browne made it clear that BP would have a sustainable competitive
advantage in the businesses it operated, only if it had the culture and
processes to manage these businesses better than anyone else. People in
the company had to learn from one another and do things better over
time. It was important for people to feel that individually and collectively, they were in control of their businesses. Browne emphasized the concept of self-help, encouraging people to think about how to control the
cost structure, get more returns for investments made, upgrade the quality of products and services and improve relationships with suppliers and
customers. Stretch targets and ongoing benchmarking of key
parameters became key enablers of learning. Browne also asked employees to challenge conventional wisdom and pursue “breakthrough
thinking”, a new way of looking at things and challenging existing
boundaries.
Senior leaders in BP led from the front. The process of setting policies, standards, targets and creating processes was viewed as an opportunity to stimulate learning. As Browne put it, “It is while those processes are being carried out that learning should take place. What determines
whether it does is the questions leaders ask and the way they approach
what is going on”. During the quarterly reviews, Browne would personally review the performance by exception and facilitate learning by asking what went right and what went wrong.
Browne encouraged the formation of learning communities, each
essentially consisting of people grappling with common problems. This
kind of peer group learning made a tremendous impact on BP. As
Browne put it, “People are much more open with their peers, they are
much more willing to share and to listen and are much less likely to take
umbrage when someone disagrees with them”. Browne also set up a
virtual network, to bring people together and share knowledge quickly
regardless of time and distance. On BP’s intranet, employees were encouraged to create their home pages. These pages started providing a
range of information from functional expertise to technical data. BP
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started experimenting with a variety of approaches — making videos
that could be seen on the network, creating electronic yellow pages that
could be searched in a number of ways and encouraging people to list
expertise and experiences they were willing to share with others.
Today, BP is one of the leaders in knowledge sharing. BP has also
launched new initiatives to link knowledge management with strategic
planning. Senior managers meet regularly to identify technology and
business trends and deliberate on the kind of knowledge BP needs to
acquire for leveraging these trends effectively in the coming months.
11. Buckman Laboratories75
Buckman Laboratories (Buckman) is a specialty chemicals company
with operations and marketing activities across the world. Buckman’s
value proposition consists of the products it makes and the way it uses
them to solve the chemical treatment problems of customers. Selling
Buckman’s products not only involves knowledge of chemistry and other related disciplines but also practical experience in handling problems
faced by customers. This practical knowledge is tacit. Buckman knows
that it is this knowledge which gives it a competitive edge in the market
place.
Buckman’s Knowledge Network facilitates sharing of knowledge
among employees irrespective of time zone, geography or language. The
network helps in capturing conversations, interactions, contributions and
exchanges.
Buckman has attempted to combine the best of integrative and interactive knowledge sharing. Much of the explicit knowledge about Buckman’s customers, products and technologies is available in online repositories. This integrative application involves the flow of knowledge into
and out of the repository. But Buckman has also set up an online Tech
Forum to facilitate interactive knowledge management applications. The
forum has a standard structure. Comments are threaded in conversational
sequence and indexed by topic, author and date. The content includes
questions, responses and field observations.
There are several subject experts in Buckman for guiding discussions
about their areas of expertise and validating the advice given by others.
They periodically review the Tech Forum to identify useful threads for
storage in an online repository. Technically qualified persons in different
units share their knowledge through the forum. Product development
managers offer online technical advice to field personnel. Research
librarians collect information about different industries. People are actively encouraged to participate in the forum.
This case draws heavily from the article, “Managing Codified
Knowledge” by Michael Zack, Sloan Management Review, Summer 1999.
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Buckman’s knowledge management initiatives have played a key
role in developing relationships with customers and in clinching business deals. What has made knowledge management so successful in
Buckman is not the technology or the process, but culture and the clear
organizational intent to create, share and reapply knowledge. The Tech
Forum has become a way of life in Buckman. People are expected to
access the forum regularly, post problems, replies and observations and
to contribute wherever possible. The forum has gained wide acceptance
as a reliable and efficient means of sharing knowledge and solving problems.
What Buckman’s success demonstrates is that a combination of culture, roles, habits, norms and practices is needed to make knowledge
management initiatives successful. And such a combination is not easy
for competitors to replicate. More generally, as Zack puts it, “. . . . Organizations that are managing knowledge effectively understand their
strategic knowledge requirements, devise a knowledge strategy appropriate to the firm’s business strategy and implement an organizational
and technical architecture appropriate to the organization’s knowledge
processing needs.”
12. Nucor Steel76
The well known American steel company, Nucor is a good example of
why the right social environment is a crucial requirement for effective
knowledge management.
Anil Gupta and Viay Govindarajan use the term social ecology to
describe the social system in which people operate. As they mention, “It
(social ecology) drives an organization’s formal and informal expectations of individuals, defines the types of people who will fit into the organization, shapes individuals’ freedom to pursue actions without prior
approval and affects how people interact with others both within and
outside the organization”. Social ecology spans culture, structure, information systems, reward systems, processes, people and leadership. IT
platforms are not proprietary. Sustainable advantage depends on how
smartly the company can use the technology. This in turn depends on the
social ecology. Nucor is an excellent example of a company which has
shaped its social ecology to promote creation and sharing of knowledge.
Nucor’s end product is steel, generally recognized as a commodity
with little scope for differentiation. So cost leadership is a critical success factor. Nucor has focused on developing knowledge that can help it
to retain its status as one of the most efficient steel producers in the
world. More specifically, Nucor has focused on three competencies:
plant construction and startup know-how, manufacturing process expertise, and the ability to embrace breakthrough technologies faster than
competitors. Nucor’s knowledge management initiatives have focused
on creating knowledge from direct experimentation, acquiring external
knowledge and retaining internally created or externally acquired
knowledge.
To give a boost to knowledge creation, Nucor has focused on superior human capital, high powered incentives, and a high degree of empowerment. By locating plants in rural areas, Nucor has been able to
attract hardworking, mechanically inclined people. The company has
This caselet draws heavily from the article, “Knowledge Management’s
Social Dimension: Lessons from Nucor Steel” by Anil Gupta and Vijay
Govindarajan, Sloan Management Review, Fall 2000.
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also invested in continuous, on-the-job, multifunctional training. A high
powered incentive system has helped in cultivating hunger for new
knowledge. Since the incentives are linked to output, workers have continued to look for ways to improve productivity. Since incentives are
also linked to quality standards, employees are motivated to do things
right the first time. At the same time, employees are encouraged to experiment, even if it leads to failures occasionally. As Ken Iverson, former chairman of Nucor once remarked: “We believe that if you take an
average person and put him in a management position, he’ll make (or
take) 50% good decisions and 50% bad decisions. A good manager
makes 60% good decisions. That means 40% of these decisions could
have been better. The only other point I’d like to make about decision
making is ‘Don’t keep making the same bad decisions’. Every Nucor
plant has its little store house of equipment that was bought, tried and
discarded.”
Nucor encourages risk taking among its employees while embracing
new technologies despite the risk involved. Because of their ongoing
efforts to run their plants more efficiently, managers, engineers and operators have developed deep mastery of the manufacturing processes.
This mastery has given them the confidence in their ability to resolve
unknown bugs that tend to crop up in the case of new technologies. That
is why Nucor employees are able to take more risk, compared to their
counterparts in other steel companies.
Nucor has also been far more successful in retaining knowledge. That
is mainly because of its people-oriented policies that have helped in cultivating a high degree of commitment and loyalty amongst its employees. For example, Nucor has not sacked employees during recessions.
During tough times, the company’s strategy has been to shorten the work
week and lower the compensation.
Nucor has also been highly proactive in encouraging individuals to
share their knowledge, building efficient transmission channels and convincing individuals to accept and use the knowledge they receive. By
making the performance data of different departments visible across the
company, best practice dissemination has been greatly facilitated. Group
incentives have also encouraged individuals to share expertise with their
peers. Nucor has used IT to transmit explicit knowledge. But Nucor has
also been good at sharing unstructured knowledge. Plant managers, supervisors and machine operators periodically visit other plants to understand first hand, superior practices followed there. Nucor has also
systematically recycled process innovations from existing plants to start
up plants. Nucor has discouraged the Not-Invented-Here syndrome in
two ways. The incentive system has sent clear signals to employees that
staying focused on increasing output is important and trying to create all
the knowledge required may be too expensive. At the same time, by
building peer pressure, the weaker performing units have been motivated
to learn from the high performers.
As Gupta and Govindarajan conclude, the ability of a company to
function as a knowledge machine depends more on social ecology than
the IT infrastructure. Creating the right social ecology is a huge challenge. Building a social ecology involves putting in place “a whole ecosystem of complementary and mutually reinforcing organizational
mechanisms”. So it cannot be easily replicated.
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Knowledge Management Mantras
“Most people define learning too narrowly as mere “problem solving” so
they focus on identifying and correcting errors in the external environment. Solving problems is important. But if learning is to persist, managers and employees must also look inward. They need to reflect critically on their own behavior, identify the ways they often inadvertently
contribute to the organization’s problems and then change how they act.
In particular, they must learn how the very way they go about defining
and solving problems can be a source of problems in its own right.”
Chris Argyris
Harvard Business Review, May-June, 1991.
“The preservation of the means of knowledge among the lowest ranks is
of more importance to the public than all the property of the rich men in
the country.” — John Adams
“The problem with data is that it’s dead. We should bring it to life by
thinking through all its relationships — both with other data and with the
circumstances in the world that it’s supposed to represent.” — Phil Agre
“Living Data”, Wired Magazine,
November 1994, vol 2.11, p.94
“If the greatest database in the company is housed in the individual
minds or four associates, then that is where the knowledge of the organization resides. These individual knowledge bases are constantly changing and adapting to the real world. We have to connect these knowledge
bases together so that they can do whatever they do best in the shortest
possible time.” — Bob Buckman, Buckman Laboratories
“The way we see it, anyone in the organization who is not directly accountable for making a profit, should be involved in creating and distributing knowledge that the company can use to make a profit.”
John Browne, former CEO of BP
Harvard Business Review, Sep-Oct 1997
“If facts are the seeds that later produce knowledge and wisdom, then
the emotions and the impressions of the senses are the fertile soil in
which the seeds must grow.” — Rachel Carson
“The only irreplaceable capital an organization possesses is the
knowledge and ability of its people. The productivity of that capital depends on how effectively people share their competence with those who
can use it.” — Andrew Carnegie
“The first step towards knowledge is to know that we are ignorant”.
Richard Cecil
“These days people seek knowledge, not wisdom. Knowledge is of the
past, wisdom is of the future.” — Vernon Cooper
“Knowledge dwells in heads replete with thoughts of other men; Wisdom in minds attentive to their own.” — William Cowper
“Knowledge is proud that he has learned so much; Wisdom is humble
that he knows no more.” — William Cowper
“It is important to remember that there is also a practice side to
knowledge work, which has to be balanced with the process perspective.
. . . Every effort to change how work is done needs a dose of both process, the design for how work is to be done and practice, an understanding of how individual workers respond to the real world of work and
accomplish their assigned tasks. . . . A process design is fundamentally
an abstraction of how work should be done in the future. . . . Practice
analysis is more like anthropology — it is a well informed description of
how work is done today by those actually do it.” — Tom Davenport
“Thinking for a Living” 2005.
“The basic economic resource — the means of production — is no longer capital, nor natural resources, nor labor. It is and will be knowledge.”
— Peter F. Drucker
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“More and more, the productivity of knowledge is going to become, for
a country, an industry, or a company, the determining competitiveness
factor. In the matter of knowledge, no one country, no one industry, no
one company has a natural advantage or disadvantage. The only advantage that it can ensure to itself is to be able to draw more from the
knowledge available to all than others are able to do.”
Peter F. Drucker
Post Capitalist Society, 1993.
“There’s no such thing as knowledge management; there are only
knowledgeable people. Information only becomes knowledge in the
hands of someone who knows what to do with it.” — Peter F. Drucker
Industry Week, 24th January 2000.
“Of central importance is the changing nature of competitive advantage
— not based on market position, size and power as in times past, but on
the incorporation of knowledge into all of an organization’s activities”
Leif Edvinsson
Swedish Intellectual Capital guru in Corporate Longitude (2002)
“Knowledge is a process of piling up facts; wisdom lies in their simplification”. — Martin Fischer
“A learning organization is an organization skilled at creating, acquiring
and transferring knowledge and at modifying its behavior to reflect new
knowledge and insights.” — David Garvin
Harvard Business Review, July-August 1993.
“Knowledge management is a means, not an end. The end is to increase
institutional intelligence or corporate IQ. . . .Corporate IQ is a measure
of how easily your company can share information broadly and how
well people within your organization can build on each other’s ideas. . . .
Contributions to corporate IQ come from individual learning and from
cross-pollination of different people’s ideas.” — Bill Gates
“Business @ The Speed of Thought” 1999.
“Power comes not from knowledge kept but from knowledge shared. A
company’s values and reward systems should reflect that idea.”
Bill Gates
“Business @ The Speed of Thought” 1999.
“A little knowledge that acts is worth infinitely more than much
knowledge that is idle.” — Kahlil Gibran
“When people with diverse backgrounds, experiences, and skill sets engage with each other on real problems, the exchange usually generates
friction, that is misunderstandings and arguments — before resolution
and learning occur. Often, this friction becomes dysfunctional, misunderstanding dissolves into mistrust and opposing sides fixate on the distance between them rather than their common challenges. Yet, properly
harnessed, friction can become very productive, accelerating learning,
generating innovation and fostering trust across diverse participants.”
John Hagell III & John Seely Brown
The Only Sustainable Edge
“Learning is not finding out what other people already know, but is solving our own problems for our own purposes by questioning, thinking
and testing until the solution is a new part of our life.” — Charles Handy
The Age of Unreason, Arrow Books, 1990.
“Competitive strategy must drive knowledge management strategy. Executives must be able to articulate why customers buy a company’s
products or services rather than those of its competitors. What value do
customers expect from the company? How does knowledge that resides
in the company add value for customers?”
Morten. T. Hansen, Nitin Nohria, Thomas Tierney
Harvard Business Review, March-April 1999.
“In an industry with its entire foundation built upon R&D, I can’t think
of anything more compelling than a solid knowledge management strategy. It’s what will differentiate the winners from the losers in both the
short-term and the long-term.” — Claire Hogikyan
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Knowledge Management from A to Z
“The great end of life is not knowledge but action.” — Thomas H. Huxley
“Sit down before fact as a little child, be prepared to give up every preconceived notion, follow humbly wherever or whatever abysses nature
leads, or you will learn nothing.” — Thomas H. Huxley
“We try to impress upon our employees that we are not king Solomon.
We use an expression that I really like: Good managers make bad
decisions. We believe that if you take an average person and put him in a
management position, he’ll make 50% good decisions and 50% bad
decisions. A good manager makes 60% good decisions. That means 40%
of these decisions would have been better.… Every Nucor plant has its
little storehouse of equipment that was bought, tried and discarded.”
Ken Iverson, former chairman. Nucor
Sloan Management Review, Fall 2000
“A great many people think they are thinking when they are merely rearranging their prejudices.” — William James
“Knowledge is of two kinds: we know a subject ourselves, or we know
where we can find information upon it.” — Samuel Johnson
“The difference between data and knowledge is like the difference between raw food and the nourishment we obtain by eating it. An intermediate step, like information, is the meal we prepare from the raw ingredients and serve on the plate.” — Charles Jonscher
Wired Life: Who are we in the digital Age Anchor, 2000.
“It is and will be much more difficult to automate what we do with our
minds that it was to automate what we do with our hands.”
Charles Jonscher
“Science is organized knowledge. Wisdom is organized life.”
Immanual Kant
“Creating and sharing knowledge are activities that can neither be supervised nor forced out of people. They happen only when people cooperate
willingly. . . getting that active cooperation may well turn out to be one
of the key managerial issues of the next few decades.”
Chan Kim & Rence Mauborgne
Harvard Business Review, July-August 1997.
“In corporate life, even when experience is a good teacher, it’s still only
a private tutor. People in organizations act collectively, but they learn
individually. That is the central tenet and frustration of organizational
learning today.” — Art Kleiner & George Roth
Harvard Business Review, September-October 1997
“Relaxed in a comfortable place, one can hardly think sharply. Wisdom
is squeezed out of someone who is standing on the cliff and is struggling
to survive. . . without such struggles, we would never have been able to
catch up with IBM.” — Taiyu Kobayashi former chairman, Fujitsu, 1985
Knowledge management is obsoleting what you know before others obsolete it and profit by creating the challenges and opportunities others
haven’t even thought about.” — Yogesh Malhotra
Inc.Technology — US Defense
Information Systems Agency Interoperability Directorate
“Bentov’s Law — When one acquires a bit of new information, there are
many new questions that are generated by it, and each new piece of information breeds five-to-ten new questions. These questions pile up at a
much faster rate than does accumulated knowledge.”
Daryl Morey and Tim Frangioso
Knowledge Management Systems
On-line presentation: www.mitre.org, 20th July 1997
“The secret of business is to know something that nobody else knows.”
Aristotle Onassis
“The store of wisdom does not consist of hard coins which keep their
shape as they change from hand to hand; it consists of ideas and doctrines whose meanings change with the minds that entertain them.”
John Plamenatz
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“We have transformed information into a form of garbage.”
Neil Postman
“We cannot be taught wisdom, we have to discover it for ourselves by a
journey which no one can undertake for us.” — Marcel Proust
“What was the means has become the ends. . . instead of helping us organize data, computers are drowning us in it.” — Ricardo Semler
“Human beings are designed for learning. No one has to teach an infant
to work, or talk, or master the special relationships needed to stack eight
building blocks that do not topple. Children come fully equipped with an
insatiable drive to explore and experiment. Unfortunately, the primary
institutions of our society are oriented predominantly toward controlling
rather than learning, rewarding individuals for performing for others
rather than for cultivating their natural curiosity and impulse to learn.”
Peter Senge, Sloan Management Review, Fall 1990.
“Sharing knowledge is not about giving people something, or getting
something from them. That is only valid for information sharing. Sharing knowledge occurs when people are genuinely interested in helping
one another develop new capacities for action; it is about creating learning processes.” — Peter Senge
“Once we realize that information technology truly cannot replace human experience that is as it increases the available information, it also
helps devalue the meaning of each piece of information, we will be on
the road to reasserting our dominance over technology.” — David Shenk
“Unlike information, knowledge is less tangible and depends on human
cognition and awareness. There are several types of knowledge —
‘knowing’ a fact is little different from ‘information’, but ‘knowing’ a
skill, or ‘knowing’ that something might affect market conditions is
something, that despite attempts of knowledge engineers to codify such
knowledge, has an important human dimension…. Measuring the
knowledge asset, therefore, means putting a value on people, both as
individuals and more importantly on their collective capability, and other
factors such as the embedded intelligence in an organisation’s computer
systems.” — David Skyrme, Management Insight
No. 11, I3, on-line: www.skyrme.com, 1994
“While westerners tend to emphasize explicit knowledge, the Japanese
tend to stress tacit knowledge. In our view, however, tacit knowledge
and explicit knowledge are not totally separate but mutually complementary entities. They interact with and inter-change into each other in the
creative activities of human beings.”
Hirotaka Takeuchi & Ikujiro Nonaka
The Knowledge Creating Company
“The Japanese approach to knowledge differs from the west in a number
of ways. Knowledge is not viewed simply as data or information that can
be stored in a computer in Japan, it also involves emotions, values,
hunches, … companies do not merely manage knowledge but ‘create’ it
as well. . . everyone in the organization is involved in creating organizational knowledge, with middle managers serving as key knowledge engineers.” — Hirotaka Takeuchi & Ikujiro Nonaka
Knowledge Management: Classic & Contemporary Works, 2001
“Much of the excitement around knowledge management has been propelled by advances in information technology. However, information
transfer is not knowledge transfer and information management is not
knowledge management, although the former can certainly assist the
latter. …knowledge is not primarily about facts and what we refer to as
content. Rather, it is more about context…. Information technology assists in the storage, retrieval and transfer of codified knowledge, but unassisted by other organizational processes, the productivity benefit from
information technology is generally quite limited.”
David J. Teece in Knowledge Horizons, 2001.
“Although we recognize knowledge as a key source of competitive advantage in business, we still have little understanding of how to create
and leverage knowledge in practice. Traditional knowledge management
approaches attempt to capture existing knowledge within formal sys-
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tems, such as databases or websites. It may be good to capture information this way but it is only half of the task and I would argue, the second half. The first half is to foster the communities that can take the responsibility for stewarding knowledge.”
Etienne Wenger in Knowledge Horizons, 2001.
“Knowledge management will never work until corporations realize it’s
not about how you capture knowledge but how you create and leverage
it.” — Etienne Wenger
“It takes a clever question to turn data into information, but it takes intelligence to use the result. Intelligence can create systems of enormous
complexity, but it takes wisdom to determine which ones are worth the
trouble.” — Lauren Ruth Wiener,
Digital Woes: why we should not depend on software
Addison Wesley, 1993-4, p.209
“We must adopt greater people-centric perspectives of knowledge. To be
viable, we need constant learning, led by constant innovation. Technology goes only so far. It can provide us with only a rudimentary reasoning
devoid of innovation and with concrete analysis of the past through approaches such as knowledge discovery in databases. People are the intelligent agents that create and act on new opportunities.”
Karl M. Wiig, Knowledge Horizons, 2001.
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