Chapter 11: Managing Knowledge

Summary:

The last decade or so has been called the “information age” by many. In fact, we live in an information economy, where the majority of prosperity and wealth is based upon the production and distribution of knowledge and information. Therefore, Knowledge Management is key to any business firms overall business strategy. Now, there is an important difference in data, bits of information about a flow of events or transactions, and knowledge. Knowledge is the use of information, derived from data, which is discovered through the analyzation of patterns rules and contexts. Knowledge Management refers to the business processes of an organization that stores, creates, transfers, and applies knowledge.  A firm’s value is directly related to its ability to do so. The three types of Knowledge Management Systems (KMS) are: Enterprise-wide KMS, Knowledge work systems, and Intelligent techniques.

Enterprise-wide KMS are general purpose tools that manage knowledge organization-wide. They are capable of searching for information and storing both structured and unstructured data. Structured knowledge exists in formal documents and files that are explicitly gleaned. Un-structured data exists in memos, emails, graphics and proposals that are stored in many different locations, in many different formats. Enterprise-wide KMS provide great value to firms as long as they are well designed and accomplish their task efficiently.

Knowledge work systems (KWS) focus on the creation of new knowledge and its application to an existing organization. In essence, they enable the location of tacit knowledge and its transformation to explicit knowledge. KWS have pre-requisites that include easy access to an external knowledge base, computer hardware and support software that is graphics intensive, communication capabilities, and being user friendly. Computer-aided design (CAD) and virtual reality systems are major work applications that can be considered a KWS.

Intelligent Techniques are of great benefit to knowledge management. Expert systems, case-based reasoning, and Fuzzy Logic (a software technology for expressing knowledge in the form of rules with subjective values) are all used to capture tacit knowledge. The other intelligent techniques discussed in our textbook are based upon Artificial Intelligence (AI). These systems include neural networks, genetic algorithms, and intelligent agents (software programs that carry out specific, repetitive, and predictable tasks without direct human intervention). While AI is no substitute for the flexibility and creativity of human intelligence, it is very useful for capturing and codifying organizational knowledge.