Knowledge management

Knowledge management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice.

An established discipline since 1991 , KM includes courses taught in the fields of business administration, information systems, management, and library and information sciences (Alavi & Leidner 1999). More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy.

Many large companies and non-profit organizations have resources dedicated to internal KM efforts, often as a part of their ‘business strategy’, ‘information technology’, or ‘human resource management’ departments (Addicott, McGivern & Ferlie 2006). Several consulting companies also exist that provide strategy and advice regarding KM to these organizations.

KM efforts typically focus on organizational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration and continuous improvement of the organization. KM efforts overlap with organizational learning, and may be distinguished from that by a greater focus on the management of knowledge as a strategic asset and a focus on encouraging the sharing of knowledge. KM efforts can help individuals and groups to share valuable organizational insights, to reduce redundant work, to avoid reinventing the wheel per se, to reduce training time for new employees, to retain intellectual capitalas employees turnover in an organization, and to adapt to changing environments and markets (McAdam & McCreedy 2000) (Thompson & Walsham 2004).

Different frameworks for distinguishing between knowledge exist. One proposed framework for categorizing the dimensions of knowledge distinguishes between tacit knowledge and explicit knowledge. Tacit knowledge represents internalized knowledge that an individual may not be consciously aware of, such as how he or she accomplishes particular tasks. At the opposite end of the spectrum, explicit knowledge represents knowledge that the individual holds consciously in mental focus, in a form that can easily be communicated to others.(Alavi & Leidner 2001).

Early research suggested that a successful KM effort needs to convert internalized tacit knowledge into explicit knowledge in order to share it, but the same effort must also permit individuals to internalize and make personally meaningful any codified knowledge retrieved from the KM effort. Subsequent research into KM suggested that a distinction between tacit knowledge and explicit knowledge represented an oversimplification and that the notion of explicit knowledge is self-contradictory. Specifically, for knowledge to be made explicit, it must be translated into information (i.e., symbols outside of our heads) (Serenko & Bontis 2004). Later on, Ikujiro Nonaka proposed a model (SECI for Socialization, Externalization, Combination, Internalization) which considers a spiraling knowledge process interaction between explicit knowledge and tacit knowledge (Nonaka & Takeuchi 1995). In this model, knowledge follows a cycle in which implicit knowledge is ‘extracted’ to become explicit knowledge, and explicit knowledge is ‘re-internalized’ into implicit knowledge.

A second proposed framework for categorizing the dimensions of knowledge distinguishes between embedded knowledge of a system outside of a human individual (e.g., an information system may have knowledge embedded into its design) and embodied knowledge representing a learned capability of a human body’s nervous and endocrine systems (Sensky 2002).

A third proposed framework for categorizing the dimensions of knowledge distinguishes between the exploratory creation of “new knowledge” (i.e., innovation) vs. the transfer or exploitation of “established knowledge” within a group, organization, or community. Collaborative environments such as communities of practice or the use of social computing tools can be used for both knowledge creation and transfer .

Strategies

Knowledge may be accessed at three stages: before, during, or after KM-related activities. Different organizations have tried various knowledge capture incentives, including making content submission mandatory and incorporating rewards into performance measurement plans. Considerable controversy exists over whether incentives work or not in this field and no consensus has emerged.

One strategy to KM involves actively managing knowledge (push strategy). In such an instance, individuals strive to explicitly encode their knowledge into a shared knowledge repository, such as a database, as well as retrieving knowledge they need that other individuals have provided to the repository . This is also commonly known as the Codification approach to KM.

Another strategy to KM involves individuals making knowledge requests of experts associated with a particular subject on an ad hoc basis (pull strategy). In such an instance, expert individual(s) can provide theirinsights to the particular person or people needing this (Snowden 2002). This is also commonly known as the Personalization approach to KM.

Other knowledge management strategies for companies include:

• rewards (as a means of motivating for knowledge sharing)
• storytelling (as a means of transferring tacit knowledge)
• cross-project learning
• after action reviews
• knowledge mapping (a map of knowledge repositories within a company accessible by all)
• communities of practice
• expert directories (to enable knowledge seeker to reach to the experts)
• best practice transfer
• competence management (systematic evaluation and planning of competences of individual organization members)
• proximity & architecture (the physical situation of employees can be either conducive or obstructive to knowledge sharing)
• master-apprentice relationship
• collaborative technologies (groupware, etc)
• knowledge repositories (databases, bookmarking engines, etc)
• measuring and reporting intellectual capital (a way of making explicit knowledge for companies)
• knowledge brokers (some organizational members take on responsibility for a specific “field” and act as first reference on whom to talk about a specific subject)
• social software (wikis, social bookmarking, blogs, etc)

Source: Wiki