Knowledge Discovery and Detection

In this subsection, I will examine the knowledge management (KM) initiatives involved in knowledge discovery & detection.

This step deals with discovering the knowledge that a firm possesses all over the organization, as well as the patterns in the information available that hide previously undetected pockets of knowledge.

Once knowledge is created, it exists within the organization. However, before it can be reused or shared it must be properly recognized and categorized. This subsection deals with the former aspect, while the following subsection deals with the latter.

  • Explicit Knowledge: This is largely a process of sorting through documents and other records, as well as discovering knowledge within existing data and knowledge repositories. For the latter, IT can be used to uncover hidden knowledge by looking at patterns and relationships within data and text. The main tools/practices in this case include intelligence gathering, data mining (finding patterns in large bodies of data and information), and text mining (text analysis to search for knowledge, insights, etc.). Intelligence gathering is closely linked to expert systems (Bali et al 2009) where the system tries to capture the knowledge of an expert, though the extent to which they are competent for this task is questionable (Botha et al 2008).
  • Tacit knowledge: Discovering and detecting tacit knowledge is a lot more complex and often it is up to the management in each firm to gain an understanding of what their company's experts actually know. Since tacit knowledge is considered as the most valuable in relation to sustained competitive advantage, this is a crucial step, a step that often simply involves observation and awareness. There are several qualitative and quantitative tools/practices that can help in the process; these include knowledge surveys, questionnaires, individual interviews, group interviews, focus groups, network analysis, and observation. IT can be used to help identify experts and communities. Groupware systems and other social/professional networks as well as expert finders can point to people who are considered experts, and may also give an indication of the knowledge these people/groups possess.
  • Embedded knowledge: This implies an examination and identification of the knowledge trapped inside organizational routines, processes, products etc, which has not already been made explicit. Management must essentially ask "why do we do something a certain way?" This type of knowledge discovery involves observation and analysis, and the use of reverse engineering and modeling tools.

It is important to note that the sources of knowledge that a firm has access to may extend well outside the organization. This type of knowledge, which was introduced in the previous subsection on "Understanding Organizational Knowledge" is called extra-organizational knowledge. This can exist in both formal and informal settings. The former refers to management driven initiatives like partnerships, while the latter refers to the informal networks of individual members. We are interested in the former, which can be located and managed at least to some degree. Gamble and Blackwell identify several such sources:

  • Alliances
  • Suppliers
  • Customers

At this stage, we are still only discussing knowledge discovery and detection, so these relationships will not be explored in detail (see knowledge acquisition and external knowledge networks for more). Knowledge from alliances and partners can exist in joint projects, shared knowledge/experts operational data and so on. Suppliers and customers can provide product feedback, trends, developments etc. Within their respective limitations, similar tools as above can be used to identify the knowledge and/or knowledge sources.

IT can be used in this context both as a means of feedback, communication, and cooperation between partners, and also as a way to gather, analyze, and "mine" data and information.


Facilitating Knowledge Discovery and Detection

Useful to this process is the adoption of practices that make knowledge easier to detect. For example, teams could be asked to document aspects of their work with a certain language and presentation standard. Generalists could be used to help organize this process, as well as to document the expertise of the individual team members (which can be used later to promote tacit knowledge socialization). A rundown of how management should prepare knowledge in specific situations is presented in the final segment of the Knowledge Reuse subsection.


Alan Frost M.Sc., 2010

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