Knowledge category

The Knowledge category object type, represented by an oval thought bubble (see figure Knowledge structure diagram), illustrates an object with content referring to specific knowledge. Examples of knowledge categories include project management knowledge, specific industry knowledge, specific technology knowledge, customer and competitor knowledge, etc. These categories assist in classifying a company's existing or required knowledge.

Knowledge assigned to a particular knowledge category can be either implicit knowledge, that is, knowledge that cannot be fully documented as it is available in the form of employee or group skills, or explicit knowledge that can be documented in the form of descriptions or technical drawings. Knowledge categories often contain both. For example, project management knowledge can include project managers' experiences on the one hand and information provided in a project management manual on the other.

In addition to general attributes like Description, Remark, Source, etc., the following specific attributes serve to describe knowledge categories in more detail:

Attribute name

Value range

Description/Example

Updating frequency

Enumeration type: hourly, daily, weekly, monthly, annually, seldom, never

The updating frequency describes how often the knowledge of the relevant category must be refreshed to be up-to-date. For example, basic trigonometry knowledge needs to be updated rarely or, for practical purposes, never, whereas knowledge of certain stock prices must be updated daily or even hourly.

Significance

Percentage: 0..100

The significance of the knowledge category for the company can range from 0% (totally unimportant) to 100% (extremely important).

Degree of coverage

Percentage: 0..100

The current degree of coverage for the relevant knowledge in the company can range from 0% (not covered at all) to 100% (maximum possible coverage).

If the degree of coverage of a knowledge category is to be represented by a particular organizational unit or person, the corresponding attribute of the has at disposal connection type can be used to specify this in a knowledge map.

Knowlegde advantage

Percentage: 0..100

The relative advantage of your company over the competition in terms of knowledge can range from 0% (the competition has the greatest possible advantage over your company) to 100% (your company has the greatest possible advantage over the competition).

Knowledge usage

Percentage: 0..100

The degree of utilization of a particular knowledge category can range from 0% (relevant knowledge is not utilized at all) to 100% (optimal utilization of relevant knowledge).

Desired degree of coverage

Percentage: 0..100

The desired degree of coverage for relevant knowledge can range from 0% (not covered at all) to 100% (maximum possible degree of coverage).

Future significance

Enumeration type: sharply falling, falling, stable, rising, sharply rising

Future significance depicts the expected tendency of a knowledge category to change in significance for the company.

Structural

change speed

Percentage: 0..100

The structural change speed is a measure of how fast the methods applied to acquire relevant knowledge must change (0%: no change, 100% maximum change speed).

These attributes are used to assess the significance of the relevant knowledge category for the company. They can therefore serve as the basis for identifying important or urgent measures aimed at improving the company's knowledge management. It is often helpful to display such values graphically. Copying and pasting the values from the Attributes window into a table calculation program that can create the desired models is a simple way to do so. For example, it is possible to compare the current and desired degree of coverage in a bar chart for the knowledge categories under consideration.