Knowledge Management Research Library

Knowledge Management
Definition & Overview

Overview - Six Characteristics

Definition 1

Definition 2

Why Important?

KM Benefits

Knowledge Management

Capturing & Structuring

The After Action Review

Leadership Behavior

The People Factor

An Integrated Strategy

Learning From Lessons -
Ten Steps

Eighteen Steps To Networking

Developing An In-House Network

Knowledge Management
Case Studies

#1 - Federal Highways

#2 - U.S. Navy

Knowledge Management
Magazine Rack

Knowledge Management

Knowledge Management Bookstore

Knowledge Management

Knowledge Management - Definition Two

What is Knowledge Management?

The term knowledge management was first introduced in a 1986 keynote address to a European management conference (American Productivity and Quality Center 1996).

This term had immediate and vast appeal and, at the same time, spawned strongly felt criticism.

The key to the knowledge-based economy is not knowledge-infused products but tacit knowledge that provides the capacity for these knowledge-infused products and for non-codified knowledge services (Sveiby 1997).

The major criticisms of knowledge management are that:

  • It has traditionally conjured up too close an association with information management and information technology (IT).

  • It implies that knowledge can be managed.

  • It tends to be so broad and vague as to have little meaning.

  • It tends to focus on the nuts and bolts of knowledge creation, capture, sharing, use and reuse, rather than providing a true vision and strategy that conveys how knowledge-based enterprises will function and succeed in the new knowledge-based economy.

In addition, more specific criticisms have been leveled at particular views of knowledge management.

The most common type of definition describes knowledge management as a set of processes directed at “creating-capturing-storing-sharing-applying-reusing” knowledge (Sydanmaanlakka 2000).

This type of definition is criticized for making knowledge management appear to involve somewhat mechanistic and sequential process steps and for focusing attention on explicit knowledge artifacts as opposed to tacit knowledge.

Knowledge engineering reflects this view of knowledge management. A definition with similar problems sees knowledge management as “delivering the right knowledge to the right persons at the right time.”

This definition emphasizes explicit knowledge artifacts over tacit knowledge and ignores knowledge creation.

Alternative definitions have been proffered that attempt to better capture the complexities of knowledge and knowledge management.

For example, Snowden (2000) defines knowledge management as: The identification, optimization, and active management of intellectual assets, either in the form of explicit knowledge held in artifacts or as tacit knowledge possessed by individuals or communities.

The optimization of explicit knowledge is achieved by the consolidating and making available of artifacts. The optimization of tacit knowledge is achieved through the creation of communities to hold, share, and grow the tacit knowledge.

The active management of intellectual assets is the creation of management processes and infrastructure to bring together artifacts and communities in a common ecology that will sustain the creation, utilization and retention of intellectual capital.

This definition, though a bit cumbersome, recognizes that knowledge management must address both explicit and tacit knowledge, as well as the interaction between the two, and begins to address some of the mechanisms for doing this.

It does not, however, capture all aspects of knowledge management, nor does it address how knowledge will be used or how a knowledge-based enterprise will ultimately function and/or look.

The problems with the term knowledge management can be overcome if one thinks of knowledge management as building and enhancing knowledge systems and embedding work systems within these knowledge systems, rather than managing something as nebulous as knowledge per se.

Thus, an appropriate definition of knowledge management would be creating knowledge-rich environments and knowledge-rich interactions in the conduct of work.

More specifically, knowledge management is developing and managing integrated, well-configured knowledge systems and increasingly embedding work systems within these knowledge systems.

Defined in this way, knowledge management does not over-emphasize IT.

It is clear that both knowledge systems and the processes of embedding work systems within knowledge systems can be managed.

Finally, this definition is broad enough to capture all aspects of knowledge management but is not overly vague – one can define, with some precision, what a knowledge system is.

One can also articulate how work systems can become embedded within knowledge systems.

In addition, more specific knowledge systems and corresponding work systems can be specified for particular contexts.

While an organization may vary in the extent to which it develops full-fledged and integrated knowledge systems and embeds work systems within these knowledge systems, all organizations need to direct greater attention to assessing and improving their knowledge systems and linking work processes to these knowledge systems.

However, this definition does overly attend to the nuts and bolts of knowledge management to the point of ignoring the bigger picture.

It leads to an enterprise-wide vision – a view absent in the literature and in organizations, although there is a recognized need for both vision and strategy.

The vision of building knowledge systems and embedding work systems within them encourages the whole spectrum of on-going, dynamic, interrelated knowledge-oriented activities to be taken into consideration, while making it impossible to reduce knowledge management to a set of discrete, mechanistic knowledge management practices.

This view of knowledge management enables the organization to identify its critical knowledge domains, its most immediate and future knowledge priorities, goals and objectives, and to work toward building critical knowledge systems and embedding work systems within them.

Finally, it helps the organization identify the most appropriate set of knowledge management practices, determine how information technology (IT) and artificial intelligence (AI) can best enable these well-configured, integrated enterprisewide knowledge systems and embed work systems within them.

By Kathryn A. Baker and Ghuzal M. Badamshina

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