Returning to the wording in the definition of Knowledge Management (KM) offered earlier, it is important to note that the process is selective, in that only the important facts and contextual information is saved. Some sort of filter mechanism must be in place to avoid collecting a massive amount of information that is too expensive to store and can’t be easily searched or retrieved efficiently. Similarly, the KM process involves distillation of data to information and of information to knowledge. This step further clarifies and limits the amount of data that must be stored.
Before the information can be stored in some type of memory system, however, it has to be organized in a way that facilitates later retrieval. Organization usually involves deciding on a representation language and a vocabulary to identify concepts. For example, in the risk assignment for insurance policy prospects, does the designation “single” apply to recently divorce prospects as well? Furthermore, the concept of Low Risk (LR) can be represented mathematically, as in:
LR = AGE < 28 AND MS = SINGLE OR MS = MARRIED
Or in simple text prose:
Low Risk is assigned to prospective customers less than 28 years of age who are married or single.
Storage is most often accomplished using several forms of information technology, typically including PCs and servers running database management software. However, data sitting in a repository is of no value unless it’s put to use. As such, Knowledge Management is a two-way process, in that data are first captured, manipulated, and stored, and then the resulting information is packaged or reformatted to suit the needs of the user.
