In his piece for KMWorld, What is KM? Knowledge Management Explained, Dr. Michael Koenig provides an excellent overview of the origins, goals and fundamentals of knowledge management. The article is useful for those new to KM, and also reminds seasoned practitioners of the discipline’s principles, stages of development and current status.
Per Dr. Koenig, “… Knowledge Management can best and most quickly be explained by recapping its origins.” In his article, he provides an overview of the discipline’s original principles and techniques, as well as describing its two major goals of:
- “Rich, Deep, and Open Communication
- Situational Awareness”
In additional to describing the goals of knowledge management, Dr. Koenig summarizes the operational components of knowledge management as:
- Content Management
- Expertise Location
- Lessons Learned
- Communities of Practice (CoPs)
He then describes the stages of KM’s development, including:
- First Stage of KM: Information Technology
- Second Stage of KM: HR and Corporate Culture
- Third Stage of KM: Taxonomy and Content Management
Explicit, Tacit and Implicit Knowledge
In a section on current KM issues including “tacit knowledge,” Dr. Koenig expands its classic definition (“knowledge in people’s heads”) into a “more nuanced categorization …explicit, implicit and tacit.” He asserts that implicit knowledge is more important within a KM environment than tacit: “What is often very extensive is the amount of implicit information that could have been made explicit, but has not been. That it has not been is usually not a failure, but usually simply a cost-effective decision, usually taken unconsciously, that it is not worth the effort. The danger lies in assuming that explicit information is addressed by “collecting” and tacit information by “connecting,” and not examining whether there is potentially important implicit information that could and should be made explicit.”
Knowledge in Interaction
Another important issue the world of KM faces is that of “Knowledge Retention and Retirees” as baby boomers reach retirement age. Dr. Koenig asserts that an exit interview “data dump” is insufficient for continued access to the knowledge created and held by departing employees. He suggests, “Much more likely to be useful is to keep the retiree involved, maintaining him or her in the [Communities of Practice], involved in the discussions concerning current issues, and findable through expertise locator systems.”
Per Dr. Koenig, “The real utility is likely to be found not directly in the information that the retiree leaves behind, but in new knowledge created by the interaction of the retiree with current employees.”
Powerful Partnership – Librarians & Knowledge Management Software
Certainly, that vision of how knowledge is created (through human interaction) is inspiring, but it’s only through enabling KM technologies that knowledge becomes widely accessible by those who need it. Dr. Koenig writes, “Increasingly KM is seen as ideally encompassing the whole bandwidth of information and knowledge likely to be useful to an organization, including knowledge external to the organization—knowledge emanating from vendors, suppliers, customers, etc., and knowledge originating in the scientific and scholarly community, the traditional domain of the library world.”
We at Lucidea suggest that a powerful knowledge management application in the capable hands of a special librarian—in an environment that values continual knowledge creation—approaches that ideal.
Read more on Lucidea’s solutions for Knowledge Management, including Inmagic Presto. Read more posts on knowledge management best practices on Think Clearly .
Best practices for KM helping users easily find the right content, spend less time searching, more time doing, efficient access and discovery methods.
The user interface is the knowledge management system point of entry providing navigation, search, communications, an index, a knowledge map, and links.
Best KM search engines enable searching for sites, documents, files, lists, content, and answers to questions, plus ability to search on text or metadata
Knowledge managers use taxonomy, folksonomy, metadata and tags to classify content so it’s easily discoverable through navigation, search and links.