Chapter 7: KnowledgeManagement in Practice

FINDING INFORMATION AND KNOWLEDGE

Knowledge exists in all organizations, but all knowledge may not be explicit.Knowledge objects or artifacts are entities that represent knowledge existing within organizational members [McInerney, C., 2002]. A long-time employee may have a deep understanding of processes and guidelines, but he or she may never have written them down or compiled them in a document like a procedural manual. As a gatekeeper of know-how about “how things are done,” this worker has the power of knowing, but may also find that it is tedious and annoying having to answer the same questions over and over again. Codifying his or her knowledge in a manual would allow others to read and understand how tasks and projects can proceed to completion.

SHARINGINFORMATIONANDKNOWLEDGE

Teaching and learning activities, such as online universities in industry, mentoring programs, apprenticeships, and training programs all serve as opportunities for individuals to share knowledge. The live interactions that occur in lectures and other kinds of learning sessions can now be captured fairly easily with digital video or audio equipment. Even mobile devices have these capabilities.They can then be indexed and placed on a shared file platform or in an intranet. If indexed appropriately, knowledge workers can find the audio and video and use these things over and over again.

DEVELOPMENTOF KNOWLEDGE

Although individuals can intentionally develop their own knowledge through seeking opportunities to be creative and learn, the development of knowledge is often a social process. Meetings, teleconferences, planning sessions, knowledge cafes, and team think tank sessions all serve to help workers develop knowledge together. The synergies brought about by effective meetings can encourage the development of new knowledge. Allowing individuals to take risks and occasionally make mistakes (and learn from them) can also develop a culture of innovation that fosters the creation of new knowledge through research and experimentation.

KNOWLEDGE AUDIT

The idea of an information auditory much predates KM as we have defined KM here. Accompanying, or more accurately a component of, the Information Resources Management (IRM) movement of the 1970’s was a strong emphasis upon the information or knowledge audit. The foremost exponent of the information or knowledge audit was Forrest (Woody) Horton. He and Burk developed a program called ‘InfoMapper’ [Burk and Horton, 1988] precisely to facilitate the conduct of an information audit. With the development of KM, there ensued a shift to amuch greater emphasis upon knowledge embodied in people. Indeed, Moulton, L. [2008] advocates a three-stage process for a knowledge audit that starts with people and emphasizes knowledge embodied in people.The first stage focuses on people, “their knowledge and expertise and their connections to others” [Moulton, L., 2008, p. 80].The ideal result is a “map” of:

Who is connected to whom, formally and informally?

What are their formal roles and job descriptions, and informal relationships and roles?

Where do expertise, methods, differing views of the organization reside?

What are the successful knowledge sharing engagements and practices?

What are the barriers to information and knowledge transfer?

TAGS,TAXONOMIES,ANDCONTENTMANAGEMENT

The tag and taxonomy stage of KM consists primarily of assembling various information resources in some sort of portal-like environment and making them available to the organization. This can include internally generated information, including lessons learned databases and expertise locators, as well as external information, the open web and also deep web information subscribed to by the organization .With the arrival of extensive email use by virtually all organizations the extent of internal information to be managed has exploded. The obvious consequence of this plethora of data and information from multiple sources is great terminological inconsistency and confusion, and that, in turn, drives the appeal of syndetic data structures and taxonomies that can assist the user in locating information or knowledge and result in better and more effective searching.

LESSONS LEARNEDDATABASES

Lessons Learned databases are databases that attempt to capture and to make accessible knowledge that has been operationally obtained and typicallywould not have been captured in a fixedmedium(to use copyright terminology). In the KMcontext, the emphasis is typically upon capturing knowledge embedded in persons andmaking it explicit. The lessons learned concept or practice is one thatmight be described as having been birthed by KM, as there is very little in the way of a direct antecedent. Early in the KM movement, the phrase typically used was “best practices,” but that phrase was soon replaced with “lessons learned.” The reasons were that “lessons learned” was broader and more inclusive, and because “best practice” seemed too restrictive and could be interpreted as meaning there was only one best practice in a situation. The implementation of a lessons learned system is complex both politically and operationally. Many of the questions surrounding such a system are difficult to answer. Who is to decide what constitutes a worthwhile lesson learned? Are employees free to submit to the system unvetted?Most successful lessons learned implementations have concluded that such a systemneeds to bemonitored and that there needs to be a vetting and approval mechanism before items are mounted as lessons learned

EXPERTISE LOCATION

Expertise location systems are another aspect of KM that certainly predates KM thinking. TheMitre Corporation, for example, developed such a system in 1978. It was based upon creating a database developed from reformatted resumes retrieved from word-processing tapes, and upon the development of a competence area thesaurus to improve retrieval. There are nowthree areaswhich typically supply data for an expertise locator system, employee resumes, employee self identification of areas of expertise, typically by being requested to fill out a form online, or by algorithmic analysis of electronic communications from and to the employee. The latter approach is typically based on email traffic, but it can include other social networking  electronic communications such as Twitter and Facebook.

COMMUNITIESOF PRACTICE (COPS)

Communities of Practice (CoPs) are groups of individuals with shared interests that come together in person or virtually to tell stories, discuss best practices, and talk over lessons learned [Wenger, E., 1998a,Wenger and Snyder, 1999].Communities of practice emphasize the social nature of learning within or across organizations. In the context of KM, CoPs are generally understood to mean electronically linked communities. Electronic linkage is not essential of course, but since KMarose in the consulting community from the awareness of the potential of Intranets to link geographically dispersed organizations, this orientation is understandable and inevitable.