Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organizational objectives by making the best use of knowledge.
An established discipline since 1991,KM includes courses taught in the fields of business administration, information systems, management, library, and information science. Other fields may contribute to KM research, including information and media, computer science, public health and public policy. Several universities offer dedicated master's degrees in knowledge management.
Many large companies, public institutions, and non-profit organisations have resources dedicated to internal KM efforts, often as a part of their business strategy, IT, or human resource management departments. Several consulting companies provide advice regarding KM to these organizations.
Knowledge management 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. These 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 on encouraging the sharing of knowledge. KM is an enabler of organizational learning.
The most complex scenario for knowledge management may be found in the context of supply chain as it involves multiple companies without an ownership relationship or hierarchy between them, being called by some authors as transorganizational or interorganizational knowledge. That complexity is additionally increased by industry 4.0 (or 4th industrial revolution) and digital transformation, as new challenges emerge from both the volume and speed of information flows and knowledge generation.
Different frameworks for distinguishing between different 'types of' knowledge exist. One proposed framework for categorizing the dimensions of knowledge distinguishes tacit knowledge and explicit knowledge. Tacit knowledge represents internalised knowledge that an individual may not be consciously aware of, such as to accomplish 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.
Ikujiro Nonaka proposed a model (SECI, for Socialization, Externalization, Combination, Internalization) which considers a spiraling interaction between explicit knowledge and tacit knowledge. 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. Early research suggested that KM needs to convert internalised tacit knowledge into explicit knowledge to share it, and the same effort must permit individuals to internalise and make personally meaningful any codified knowledge retrieved from the KM effort.
Subsequent research 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 our heads). More recently, together with Georg von Krogh and Sven Voelpel, Nonaka returned to his earlier work in an attempt to move the debate about knowledge conversion forward.