Knowledge Management describes an organization strategy to get the knowledge of its workers out of their heads and into an information storage and retrieval system where it can be used and reused.

When workers leave an enterprise, their knowledge (information in their heads) goes with them. KM captures their knowledge in a form that can be shared with other workers and especially future workers. It externalizes Institutional Memory? and it aims to optimize Knowledge Transfer?, which means passing along skills.

Knowledge Management as a term was coined by management consultancies who wanted to differentiate it from Data or Information Management, the sphere of Management Information Systems (MIS) and the IT (InformationTechnology?) department. It has proved a popular concept in business schools.

Karl-Erik Sveiby, author of the first book on knowledge management (1990), distinguishes KM that is primarily Information Management, from KM that is People Management.

Information KM uses tools similar to Content Management (creation, acquisition, aggregation, data repository, metadata, version control, workflow, search), but the essential content is knowledge about business processes, best practices, expert systems, and controlled vocabularies, not mere content like brochures, articles, white papers, and website pages.

The knowledge collected in the data repository is called the knowledge base, or body of knowledge (BOK).

KM goes beyond Content Management with a strong emphasis on collaborative use of the base of knowledge. CM uses a Search Engine and occasionally indexing to facilitate navigation of content. But for KM, Search and Indexing are vital tools for their audience, the Knowledge Worker?.

KM can be the major source of content for a strong eLearning program implementing a Learning Management System.

Excitement about KM has waned as the difficulty of extracting worker knowledge (KnowledgeCapture?) has been understood. Moreover, when knowledge has been obtained, edited, and stored, it has proven very difficult for other workers to retrieve and use effectively, even when it is made easily accessible in online user manuals. Data Mining? of existing enterprise documents offered an automated way to collect knowledge. But the sheer quantity of such data is daunting, despite Auto Categorization and Auto Classification tools that add the metadata needed for Advanced Search? and Information Retrieval?.

Like many of the management buzzwords promoted as tools to increase enterprise productivity and increase competitiveness (ManagementByObjectives?, Enterprise Resource Planning, Business Process Management, Total Quality Management?, Business Intelligence), KM has had more failures than successes, especially at the enterprise level.

Nevertheless, there are many KM community organizations, some with impressive success stories to report, mostly case studies within departments that collaborate with modern groupware tools.

Knowledge mapping (see Mind Map?) diagrams the connections between knowledge resources.

The most useful form of Knowledge Mapping for an organization starts by modelling its core business processes. Once the sequence of activities in a process has been modelled, the model is synthesized with the results of a knowledge audit to show what knowledge, information (explicit knowledge) and skill are required in order to undertake each activity effectively. While explicit knowledge resources (information) may be mapped to activities fairly easily, mapping tacit knowledge requires a number of specialized techniques. The most prominent techniques include knowledge elicitation, knowledge codification and organizational network analysis.



References:
Karl-Erik Sveiby, What Is Knowledge Management?
Wikipedia
WWW Virtual Library on KM
KM World
KM Magazine
KM Pro
KM Resource Center
The nonsense of KM
Lynda Moulton on KM