What is knowledge management?

Rebecca O. Barclay
Managing Editor, Knowledge
Praxis
Philip C. Murray
Editor-in-Chief, Knowledge
Praxis

Business
Strategies | What
is Knowledge | Why do
we need..... | Roadblocks to
solutions
History of KM | KM.....cross
disciplinary | Categorization
| Conclusion

At Knowledge Praxis, we define knowledge management as a business
activity with two primary aspects:

Treating the knowledge component of business activities as an explicit
concern of business reflected in strategy, policy, and practice at all
levels of the organization.

Making a direct connection between an organization’s intellectual assets
— both explicit [recorded] and tacit [personal know-how] — and positive
business results.

In practice, knowledge management often encompasses identifying and mapping
intellectual assets within the organization, generating new knowledge for
competitive advantage within the organization, making vast amounts of corporate
information accessible, sharing of best practices, and technology that enables
all of the above — including groupware and intranets.

That covers a lot of ground. And it should, because applying knowledge to
work is integral to most business activities.

Knowledge management is hard to define precisely and simply. (The definition
also leapfrogs the task of defining "knowledge" itself. We’ll get to that
later.) That’s not surprising. How would a nurse or doctor define "health care"
succinctly? How would a CEO describe "management"? How would a CFO describe
"compensation"? Each of those domains is complex, with many sub-areas of
specialization. Nevertheless, we know "health care" and "management" when we see
them, and we understand the major goals and activities of those
domains.

Business strategies related to knowledge management

As you explore other explanations of knowledge management — Bo Newman’s Knowledge Management Forum is a good starting point — you’ll detect connections with
several well-known management strategies, practices, and business issues,
including

Change management

Best practices

Risk management

Benchmarking

A significant element of the business community also views knowledge
management as a natural extension of "business process reengineering," a fact
underscored by the recent announcement that John Wiley’s Business Change and
Reengineering will become Knowledge and Process Management in March,
1997. See (http://www.mgmt.utoronto.ca/~wensle/journal1.htm)

There is a common thread among these and many other recent business
strategies: A recognition that information and knowledge are corporate assets,
and that businesses need strategies, policies, and tools to manage those
assets.

The need to manage knowledge seems obvious, and discussions of intellectual
capital have proliferated, but few businesses have acted on that understanding.
Where companies have take action — and a growing number are doing so —
implementations of "knowledge management" may range from technology-driven
methods of accessing, controlling, and delivering information to massive efforts
to change corporate culture.

Opinions about the paths, methods, and even the objectives of knowledge
management abound. Some efforts focus on enhancing creativity — creating new
knowledge value — while other programs emphasize leveraging existing knowledge.
(See below, "Categorization of
knowledge management approaches.")

What is "knowledge"?

Aren’t we managing knowledge already? Well, no. In fact, most of the
time we’re making a really ugly mess of managing information. In
practice, the terms information and knowledge are often used
interchangeably by business writers.

Let’s choose a simple working definition and get on with it:

Knowledge has two basic definitions of interest. The first pertains to a
defined body of information. Depending on the definition, the body of
information might consist of facts, opinions, ideas, theories, principles, and
models (or other frameworks). Clearly, other categories are possible, too.
Subject matter (e.g., chemistry, mathematics, etc.) is just one possibility.

Knowledge also refers to a person’s state of being with respect to some body
of information. These states include ignorance, awareness, familiarity,
understanding, facility, and so on.

Email from Fred Nickols, Executive Director — Strategic Planning &
Management, Educational Testing Service.

There are many thoughtful and thought-provoking definitions of "knowledge" —
including the important distinctions Gene Bellinger et al. make in "Data,
Information, Knowledge, and Wisdom". Nevertheless, Nickols
provides a good, sensible, functional definition, and it is sufficient for our
purposes.

Nickols’ two kinds of knowledge parallel Michael Polanyi’s often-quoted
distinction between explicit knowledge (sometimes referred to as
formal knowledge), which can be articulated in language and transmitted
among individuals, and tacit knowledge (also, informal knowledge),
personal knowledge rooted in individual experience and involving personal
belief, perspective, and values. (Polanyi, Michael. The Tacit Dimension.
London: Routledge & Kegan Paul. See also Karl E. Sveiby’s online
description, "Tacit
Knowledge."

In traditional perceptions of the role of knowledge in business
organizations, tacit knowledge is often viewed as the real key to getting
things done and creating new value. Not explicit knowledge. Thus we often
encounter an emphasis on the "learning organization" and other approaches that
stress internalization of information (through experience and action) and
generation of new knowledge through managed interaction.

In the opinion of the editors of Knowledge Praxis, quibbles about fine
distinctions in the meaning of knowledge are just not very important. (See Rant #1: Thinking objectively
about subjective knowing) It doesn’t matter whether a written procedure or a
subject matter expert provides a solution to a particular problem, as long as a
positive result is achieved. However, observing how knowledge is acquired and
how we can apply knowledge — whether tacit or explicit — in order to achieve a
positive result that meets business requirements … that’s a different and very
important issue.

Why we need knowledge management now

Why do we need to manage knowledge? Ann Macintosh of the Artificial
Intelligence Applications Institute (University of Edinburgh) has written a "Position Paper on Knowledge Asset
Management" that identifies some of the specific business factors,
including:

Marketplaces are increasingly competitive and the rate of innovation is
rising.

Reductions in staffing create a need to replace informal knowledge with
formal methods.

Competitive pressures reduce the size of the work force that holds
valuable business knowledge.

The amount of time available to experience and acquire knowledge has
diminished.

Early retirements and increasing mobility of the work force lead to loss
of knowledge.

There is a need to manage increasing complexity as small operating
companies are trans-national sourcing operations.

Changes in strategic direction may result in the loss of knowledge in a
specific area.

To these paraphrases of Ms. Macintosh’s observations we would add:

Most of our work is information based.

Organizations compete on the basis of knowledge.

Products and services are increasingly complex, endowing them with a
significant information component.

The need for life-long learning is an inescapable reality.

In brief, knowledge and information have become the medium in which business
problems occur. As a result, managing knowledge represents the primary
opportunity for achieving substantial savings, significant improvements in human
performance, and competitive advantage.

It’s not just a Fortune 500 business problem. Small companies need formal
approaches to knowledge management even more, because they don’t have the market
leverage, inertia, and resources that big companies do. They have to be much
more flexible, more responsive, and more "right" (make better decisions) —
because even small mistakes can be fatal to them.

Roadblocks to adoption of knowledge management solutions

There have been many roadblocks to adoption of formal knowledge management
activities. In general, managing knowledge has been perceived as an
unmanageable kind of problem — an implicitly human, individual activity —
that was intractable with traditional management methods and technology.

We tend to treat the activities of knowledge work as necessary, but
ill-defined, costs of human resources, and we treat the explicit manifestations
of knowledge work as forms of publishing — as byproducts of "real" work.

As a result, the metrics associated with knowledge resources — and our
ability to manage those resources in meaningful ways — have not become part of
business infrastructure.

But it isn’t necessary to throw up one’s hands in despair. We do know
a lot about how people learn. We know more and more about how organizations
develop and use knowledge. The body of literature about managing intellectual
capital is growing. We have new insights and solutions from a variety of domains
and disciplines that can be applied to making knowledge work manageable and
measurable. And computer technology — itself a cause of the problem — can
provide new tools to make it all work.

We don’t need another "paradigm shift" (Please!), but we do have to accept
that the nature of business itself has changed, in at least two important
ways:

Knowledge work is fundamentally different in character from physical
labor.

The knowledge worker is almost completely immersed in a computing
environment. This new reality dramatically alters the methods by which we
must manage, learn, represent knowledge, interact, solve problems, and act.

You can’t solve the problems of Information Age business or gain a
competitive advantage simply by throwing more information and people at the
problems. And you can’t solve knowledge-based problems with approaches borrowed
from the product-oriented, print-based economy. Those solutions are
reactive and inappropriate.

Applying technology blindly to knowledge-related business problems is a
mistake, too, but the computerized business environment provides opportunities
and new methods for representing "knowledge" and leveraging its value. It’s not
an issue of finding the right computer interface — although that would help,
too. We simply have not defined in a rigorous, clear, widely accepted way the
fundamental characteristics of "knowledge" in the computing environment. (See "Cooperative development
of a classification of knowledge management functions.")

A brief history of knowledge management

An overarching theory of knowledge management has yet to emerge, perhaps
because the practices associated with managing knowledge have their roots in a
variety of disciplines and domains. Special thanks to Karl Wiig for supplying us
with a pre-publication copy of "Knowledge Management:Where Did It Come From and
Where Will It Go?" which will appear in The Journal of Expert Systems with
Applications. This section draws heavily on that work but supplies only a
small part of that value.

A number of management theorists have contributed to the evolution of
knowledge management, among them such notables as Peter Drucker, Paul
Strassmann, and Peter Senge in the United States. Drucker and Strassmann have
stressed the growing importance of information and explicit knowledge as
organizational resources, and Senge has focused on the "learning organization,"
a cultural dimension of managing knowledge. Chris Argyris, Christoper Bartlett,
and Dorothy Leonard-Barton of Harvard Business School have examined various
facets of managing knowledge. In fact, Leonard-Barton’s well-known case study of
Chaparral Steel, a company which has had an effective knowledge management
strategy in place since the mid-1970s, inspired the research documented in her
Wellsprings of Knowledge — Building and Sustaining Sources of Innovation
(Harvard Business School Press, 1995).

Everett Rogers’ work at Stanford in the diffusion of innovation and Thomas
Allen’s research at MIT in information and technology transfer, both of which
date from the late 1970s, have also contributed to our understanding of how
knowledge is produced, used, and diffused within organizations. By the
mid-1980s, the importance of knowledge (and its expression in professional
competence) as a competitive asset was apparent, even though classical economic
theory ignores (the value of) knowledge as an asset and most organizations still
lack strategies and methods for managing it.

Recognition of the growing importance of organizational knowledge was
accompanied by concern over how to deal with exponential increases in the amount
of available knowledge and increasingly complex products and processes. The
computer technology that contributed so heavily to superabundance of information
started to become part of the solution, in a variety of domains. Doug
Engelbart’s Augment (for "augmenting human intelligence"), which was introduced
in 1978, was an early hypertext/groupware application capable of interfacing
with other applications and systems. Rob Acksyn’s and Don McCracken’s Knowledge
Management System (KMS), an open distributed hypermedia tool, is another notable
example and one that predates the World Wide Web by a decade.

The 1980s also saw the development of systems for managing knowledge that
relied on work done in artificial intelligence and expert systems, giving us
such concepts as "knowledge acquisition," "knowledge engineering,"
"knowledge-base systems, and computer-based ontologies.

The phrase "knowledge management" entered the lexicon in earnest. To provide
a technological base for managing knowledge, a consortium of U.S. companies
started the Initiative for Managing Knowledge Assets in 1989. Knowledge
management-related articles began appearing in journals like Sloan Management
Review, Organizational Science, Harvard Business Review, and
others, and the first books on organizational learning and knowledge management
were published (for example, Senge’s The Fifth Discipline and Sakaiya’s
The Knowledge Value Revolution).

By 1990, a number of management consulting firms had begun in-house knowledge
management programs, and several well known U.S., European, and Japanese firms
had instituted focused knowledge management programs. Knowledge management was
introduced in the popular press in 1991, when Tom Stewart published "Brainpower"
in Fortune magazine. Perhaps the most widely read work to date is Ikujiro
Nonaka’s and Hirotaka Takeuchi’s The Knowledge-Creating Company: How Japanese
Companies Create the Dynamics of Innovation (1995).

By the mid-1990s, knowledge management initiatives were flourishing, thanks
in part to the Internet. The International Knowledge Management Network (IKMN),
begun in Europe in 1989, went online in 1994 and was soon joined by the
U.S.-based Knowledge Management Forum and other KM-related groups and
publications. The number of knowledge management conferences and seminars is
growing as organizations focus on managing and leveraging explicit and tacit
knowledge resources to achieve competitive advantage. In 1994 the IKMN published
the results of a knowledge management survey conducted among European firms, and
the European Community began offering funding for KM-related projects through
the ESPRIT program in 1995.

Knowledge management, which appears to offer a highly desirable alternative
to failed TQM and business process re-engineering initiatives, has become big
business for such major international consulting firms as Ernst & Young,
Arthur Andersen, and Booz-Allen & Hamilton. In addition, a number of
professional organizations interested in such related areas as benchmarking,
best practices, risk management, and change management are exploring the
relationship of knowledge management to their areas of special expertise (for
example, the APQC [American Productivity and Quality Council] and ASIS [American
Society for Information Science]).

Knowledge management: a cross-disciplinary domain

Knowledge management draws from a wide range of disciplines and
technologies.

Cognitive science. Insights from how we learn and know
will certainly improve tools and techniques for gathering and transferring
knowledge.

Expert systems, artificial intelligence and knowledge base management
systems (KBMS). AI and related technologies have acquired an undeserved
reputation of having failed to meet their own — and the marketplace’s — high
expectations. In fact, these technologies continue to be applied widely, and
the lessons practitioners have learned are directly applicable to knowledge
management.

Computer-supported collaborative work (groupware). In Europe,
knowledge management is almost synonymous with groupware … and
therefore with Lotus Notes. Sharing and collaboration are clearly vital to
organizational knowledge management — with or without supporting technology.

Library and information science. We take it for granted that card
catalogs in libraries will help us find the right book when we need it. The
body of research and practice in classification and knowledge organization
that makes libraries work will be even more vital as we are inundated by
information in business. Tools for thesaurus construction and controlled
vocabularies are already helping us manage knowledge.

Technical writing. Also under-appreciated — even sneered at — as
a professional activity, technical writing (often referred to by its
practitioners as technical communication) forms a body of theory and
practice that is directly relevant to effective representation and transfer
of knowledge.

Document management. Originally concerned primarily with managing
the accessibility of images, document management has moved on to making
content accessible and re-usable at the component level. Early recognition
of the need to associate "metainformation" with each document object
prefigures document management technology’s growing role in knowledge
management activities.

Decision support systems. According to Daniel J. Power,
"Researchers working on Decision Support Systems have brought together
insights from the fields of cognitive sciences, management sciences,
computer sciences, operations research, and systems engineering in order to
produce both computerised artifacts for helping knowledge workers in their
performance of cognitive tasks, and to integrate such artifacts within the
decision-making processes of modern organisations." [See Powers’ DSS Research Resources Home
page.] That already sounds a lot like knowledge management, but in
practice the emphasis has been on quantitative analysis rather than
qualitative analysis, and on tools for managers rather than everyone in the
organization.

Semantic networks. Semantic networks are formed from ideas and
typed relationships among them — sort of "hypertext without the content,"
but with far more systematic structure according to meaning. Often applied
in such arcane tasks as textual analysis, semantic nets are now in use in
mainstream professional applications, including medicine, to represent
domain knowledge in an explicit way that can be shared.

Relational and object databases. Although relational databases
are currently used primarily as tools for managing "structured" data — and
object-oriented databases are considered more appropriate for "unstructured"
content — we have only begun to apply the models on which they are founded
to representing and managing knowledge resources.

Simulation. Knowledge Management expert Karl-Erik Sveiby suggests
"simulation" as a component technology of knowledge management, referring to
"computer simulations, manual simulations as well as role plays and micro
arenas for testing out skills." (Source: Email from Karl-Erik Sveiby, July
29, 1996 )

Organizational science. The science of managing organizations
increasingly deals with the need to manage knowledge — often explicitly.
It’s not a surprise that the American Management Association’s APQC has
sponsored major knowledge management events.

That’s only a partial list. Other technologies include: object-oriented
information modeling; electronic publishing technology, hypertext, and the World
Wide Web; help-desk technology; full-text search and retrieval; and performance
support systems.

Categorization of knowledge management
approaches

The term "knowledge management" is now in widespread use, having appeared in
the titles of many new books about knowledge management as a business strategy,
as well as in articles in many business publications, including The Wall
Street Journal. There are, of course, many ways to slice up the
multi-faceted world of knowledge management. However, it’s often useful to
categorize them.

In a posting to the Knowledge Management Forum, Karl-Erik Sveiby identified
two "tracks" of knowledge management:

Management of Information. To researchers in this track, according
to Sveiby, "… knowledge = Objects that can be identified and handled in
information systems."

Management of People. For researchers and practitioners in this
field, knowledge consists of "… processes, a complex set of dynamic skills,
know-how, etc., that is constantly changing."

(From Sveiby, Karl-Erik, "What is
knowledge management" )

Sveiby’s characterization is on target, but it may not capture the full
flavor of the important distinctions in approaches to organizational knowledge
management. At Knowledge Praxis, we have adopted a three-part
categorization: (1) mechanistic approaches, (2) cultural/behavioristic
approaches, and (3) systematic approaches to knowledge
management.

Mechanistic approaches to knowledge management

Mechanistic approaches to knowledge management are characterized by the
application of technology and resources to do more of the same better.
The main assumptions of the mechanistic approach include:

Better accessibility to information is a key, including enhanced methods
of access and reuse of documents (hypertext linking, databases, full-text
search, etc.)

Networking technology in general (especially intranets), and groupware
in particular, will be key solutions.

In general, technology and sheer volume of information will make it
work.

Assessment: Such approaches are relatively easy to implement for
corporate "political" reasons, because the technologies and techniques —
although sometimes advanced in particular areas — are familiar and easily
understood. There is a modicum of good sense here, because enhanced access to
corporate intellectual assets is vital. But it’s simply not clear whether access
itself will have a substantial impact on business performance, especially as
mountains of new information are placed on line. Unless the knowledge management
approach incorporates methods of leveraging cumulative experience, the net
result may not be positive, and the impact of implementation may be no more
measurable than in traditional paper models.

Cultural/behavioristic approaches to knowledge management

Cultural/behavioristic approaches, with substantial roots in process
re-engineering and change management, tend to view the "knowledge problem" as a
management issue. Technology — though ultimately essential for managing explicit
knowledge resources — is not the solution. These approaches tend to focus more
on innovation and creativity (the "learning organization") than on leveraging
existing explicit resources or making working knowledge explicit.

Assumptions of cultural/behavioristic approaches often include:

Organizational behaviors and culture need to be changed … dramatically.
In our information-intensive environments, organizations become
dysfunctional relative to business objectives.

Organizational behaviors and culture can be changed, but
traditional technology and methods of attempting to solve the "knowledge
problem" have reached their limits of effectiveness. A "holistic" view is
required. Theories of behavior of large-scale systems are often invoked.

It’s the processes that matter, not the technology.

Nothing happens or changes unless a manager makes it happen.

Assessment: The cultural factors affecting organizational change have
almost certainly been undervalued, and cultural/behavioristic
implementations have shown some benefits. But the cause-effect relationship
between cultural strategy and business benefits is not clear, because the
"Hawthorne Effect" may come into play, and because we still can’t make
dependable predictions about systems as complex as knowledge-based business
organizations. Positive results achieved by cultural/behavioristic strategies
may not be sustainable, measurable, cumulative, or replicable … and employees
thoroughly "Dilbertized" by yet another management strategy may roll their eyes.
Time will tell.

Systematic approaches to knowledge management

Systematic approaches to knowledge management retain the traditional faith in
rational analysis of the knowledge problem: the problem can be solved, but new
thinking of many kinds is required. Some basic assumptions:

It’s sustainable results that matter, not the processes or technology …
or your definition of "knowledge."

A resource cannot be managed unless it is modeled, and many aspects of
the organization’s knowledge can be modeled as an explicit resource.

Solutions can be found in a variety of disciplines and technologies, and
traditional methods of analysis can be used to re-examine the nature
of knowledge work and to solve the knowledge problem.

Cultural issues are important, but they too must be evaluated
systematically. Employees may or may not have to be "changed," but policies
and work practices must certainly be changed, and technology can be applied
successfully to business knowledge problems themselves.

Knowledge management has an important management component, but it is
not an activity or discipline that belongs exclusively to
managers.

Assessment: Unrepentant rationalists in the business world are taking a
systematic approach to solving the "knowledge problem." You’ll also find
evidence of such approaches — as well as a less formal use of the term
systematic knowledge management —Karl Wiig’s Knowledge Research Institute Web
site and Gene Bellinger’s Systems
Thinking Web pages. Systematic approaches show the most promise for positive
cumulative impact, measurability, and sustainability.

Conclusion

Where do we stand at the moment, and where do we go from here? We conclude
with a thought from Bo Newman, via email:

As attested to in numerous articles in the popular press, knowledge
management has already been embraced as a source of solutions to the problems of
today’s business. Still it has not been easy for this "science" to construct for
itself that royal road of self validation. On the contrary, I believe that it is
still, at least for the majority of the practitioners and their customers, in
the stage of blind groping after its true aims and
destination.

Enough said … for the moment. Let’s change the end of this
story.

Copyright 1997 Knowledge Management Associates

Top | Return To Knowledge
Praxis | Knowledge Praxis
Forum