The Logic of Knowledge Management

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 achieving organisational 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 science, 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 organisational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration, and continuous improvement of the organization. These efforts overlap with organisational learning and may be distinguished from it 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 organisational learning. The most complex scenario for knowledge management may be found in the context of the supply chain, as it involves multiple companies without an ownership relationship or hierarchy between them, which is called by some authors "trans-organizational" or "inter-organizational" knowledge. That complexity is additionally increased by industry 4.0 (or the 4th industrial revolution) and digital transformation, as new challenges emerge from both the volume and speed of information flows and knowledge generation.

History

Knowledge management efforts have a long history, including on-the-job discussions, formal apprenticeships, discussion forums, corporate libraries, professional training, and mentoring programs. With increased use of computers in the second half of the 20th century, specific adaptations of technologies such as knowledge bases, expert systems, information repositories, group decision support systems, intranets, and computer-supported cooperative work have been introduced to further enhance such efforts.In 1999, the term "personal knowledge management" was introduced; it refers to the management of knowledge at the individual level. In the enterprise, early collections of case studies recognised the importance of knowledge management dimensions of strategy, process, and measurement. Key lessons learned include that people and the cultural norms that influence their behaviours are the most critical resources for successful knowledge creation, dissemination, and application; cognitive, social, and organisational learning processes are essential to the success of a knowledge management strategy; and measurement, benchmarking, and incentives are essential to accelerate the learning process and drive cultural change. In short, knowledge management programmes can yield impressive benefits to individuals and organisations if they are purposeful, concrete, and action-oriented.

Research

KM emerged as a scientific discipline in the early 1990s. It was initially supported by individual practitioners when Scandinavia hired Leif Edvinsson of Sweden as the world's first Chief Knowledge Officer (CKO). Hubert Saint-Onge (formerly of CIBC, Canada), started investigating KM long before that. The objective of CKOs is to manage and maximise the intangible assets of their organizations. Gradually, CKOs became interested in the practical and theoretical aspects of KM, and a new research field was formed. The KM idea has been taken up by academics such as Ikujiro Nonaka (Hitotsubashi University), Hirotaka Takeuchi (Hitotsubashi University), Thomas H. Davenport (Babson College), and Baruch Lev (New York University). In 2001, Thomas A. Stewart, former editor at Fortune magazine and subsequently the editor of Harvard Business Review, published a cover story highlighting the importance of intellectual capital in organizations. The KM discipline has been gradually moving towards academic maturity. First, there is a trend toward higher cooperation among academics; single-author publications are less common. Second, the role of practitioners has changed. Their contribution to academic research declined from 30% of overall contributions up until 2002 to only 10% by 2009. Third, the number of academic knowledge management journals has been steadily growing, currently reaching 27 outlets. Multiple KM disciplines exist; approaches vary by author and school. As the discipline matured, academic debates regarding theory and practice increased, including:

• Techno-centric with a focus on technology, ideally those that enhance knowledge sharing and creation.
• Organizational, with a focus on how an organisation can be designed to facilitate knowledge processes the best.

Ecological, with a focus on the interaction of people, identity, knowledge, and environmental factors as a complex adaptive system akin to a natural ecosystem. Regardless of the school of thought, core components of KM roughly include people (culture), processes (structure), and technology. The details depend on your perspective. KM perspectives include:

• Community of practise
• Social network analysis
• Intellectual capital
• Information theory
• Complexity science
• Constructivism

The practical relevance of academic research in knowledge management has been called into question, with action research being suggested as more relevant, as well as the need to translate the findings presented in academic journals to practice.

Dimensions

Different frameworks for distinguishing between different "types" of knowledge exist. One proposed framework for categorising the dimensions of knowledge distinguishes tacit and explicit knowledge. Tacit knowledge represents internalized knowledge that an individual may not be consciously aware of, such as how 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 be easily communicated to others.

Ikujiro Nonaka proposed a model (SECI, which stands for socialisation, externalisation, combination, and internalisation) that takes into account the spiralling interaction between explicit 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. Hayes and Walsham (2003) describe knowledge and knowledge management as two different perspectives. The content perspective suggests that knowledge is easily stored because it may be codified, while the relational perspective recognises the contextual and relational aspects of knowledge that can make knowledge difficult to share outside the specific context in which it is developed. 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. A second proposed framework for categorising knowledge dimensions distinguishes embedded knowledge of a system outside a human individual (e.g., an information system may have knowledge embedded into its design) from embodied knowledge, which represents a learned capability of a human body's nervous and endocrine systems. A third proposed framework distinguishes between the exploratory creation of "new knowledge" (i.e., innovation) and the transfer or exploitation of "established knowledge" within a group, organization, or community. Collaborative environments, such as communities of practise 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. Organizations have tried knowledge capture incentives, including making content submission mandatory and incorporating rewards into performance measurement plans. Considerable controversy exists over whether such incentives work, and no consensus has emerged. One strategy for 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 retrieve knowledge they need that other individuals have provided (codification). Another strategy involves individuals making knowledge requests of experts associated with a particular subject on an ad hoc basis (the pull strategy). In such cases, an expert or experts provide insights to the requestor (personalization).When talking about strategic knowledge management, the form of the knowledge and the activities to share it define the concepts of codification and personalization. The form of the knowledge means that it’s either tacit or explicit. Data and information can be considered explicit, and know-how can be considered tacit. Hansen et al. defined the two strategies (codification and personalization). Codification means a system-oriented method in KM strategy for managing explicit knowledge with organisational objectives. The coding strategy is a document-centered strategy in which knowledge is primarily codified through the "people-to-document" method. Codification relies on an information infrastructure where explicit knowledge is carefully codified and stored. Codification focuses on collecting and storing codified knowledge in electronic databases to make it accessible. Codification can therefore refer to both tacit and explicit knowledge. In contrast, personalization encourages individuals to share their knowledge directly. Personification means a human-oriented KM strategy where the target is to improve knowledge flows through networking and integrations related to tacit knowledge with knowledge sharing and creation. Information technology plays a less important role, as it only facilitates communication and knowledge sharing.

Other knowledge management strategies and instruments for companies include:

• Knowledge sharing (fostering a culture that encourages the sharing of information based on the concept that knowledge is not irrevocable and should be shared and updated to remain relevant).
• Make knowledge-sharing a key role in employees' job descriptions.
• Inter-project knowledge transfer.
• Knowledge sharing within an organisation.
• Knowledge sharing across organisations.
• Knowledge retention, also known as "knowledge continuation," is the process of addressing the challenge of knowledge loss as a result of people leaving.
• Mapping knowledge competencies and roles and identifying current or future predicted gaps.
• defining the main knowledge that should be retained for each chosen role and developing rituals for documenting or passing on knowledge from the day they start their job.
• transfer of knowledge and information prior to employee departure by means of document sharing, shadowing, mentoring, and more.
• Proximity and architecture (the physical situation of employees can be either conducive or obstructive to knowledge sharing).
• Storytelling (as a means of transferring tacit knowledge).
• Cross-project learning.

After-action reviews

Knowledge mapping requires the organisation to know what kind of knowledge it has, how it is distributed throughout the company, and how to efficiently use and repurpose that knowledge. (a map of knowledge repositories within a company accessible by all)

Communities of practise

1. Expert directories (to enable knowledge seekers to reach the experts).
2. Expert systems (a knowledge seeker responds to one or more specific questions to reach knowledge in a repository).
3. transfer of best practises.
4. Knowledge fairs.
5. Competency-based management (systematic assessment and planning of individual organisational members' knowledge-related competencies).
6. Master–apprentice relationships, mentor-mentee relationships, and job shadowing.
7. Collaborative software technologies (wikis, shared bookmarking, blogs, social software, etc.).
8. Knowledge repositories (databases, bookmarking engines, etc.).
9. Measuring and reporting intellectual capital (a way of making explicit knowledge for companies).
10. Knowledge brokers (some organisational members who take on responsibility for a specific "field" and act as first references on a specific subject).
11. Knowledge farming (using note-taking software to cultivate a knowledge graph, part of knowledge agriculture).
12. Knowledge capture refers to a process where trained people extract valuable or otherwise desired knowledge from experts and embed it in databases.

Motivations

Multiple motivations lead organisations to undertake KM. Typical considerations include:

1. Making increased knowledge content available in the development and provision of products and services.
2. Achieving shorter development cycles.
3. Improving consistency of knowledge and standardising expert skills among staff.
4. Facilitating and managing innovation and organisational learning.
5. Leveraging expertise across the organisation.
6. Increasing network connectivity between internal and external individuals.
7. Managing business environments and providing employees with relevant insights and ideas for their work.
8. Solving intractable or wicked problems.
9. Managing intellectual capital and assets in the workforce (such as the expertise and know-how possessed by key individuals or stored in repositories).

KM technologies

Knowledge management (KM) technology is classified as follows:

1. Groupware is software that facilitates collaboration and the sharing of organisational information. Such applications provide tools for threaded discussions, document sharing, organization-wide uniform email, and other collaboration-related features.
2. Workflow systems—Systems that enable the representation of processes associated with the creation, use, and maintenance of organisational knowledge, such as the creation and use of forms and documents.
3. Content management and document management systems are software systems that automate the process of creating web content and/or documents. Roles such as editors, graphic designers, writers, and producers can be explicitly modelled along with the tasks in the process and validation criteria. Commercial vendors started either to support documents or to support web content, but as the Internet grew, these functions merged, and vendors now perform both functions.
4. Enterprise portals: software that aggregates information across the entire organisation or for groups such as project teams.
5. eLearning—Software that enables organisations to create customised training and education This can include lesson plans, monitoring progress, and online classes.
6. Planning and scheduling software: software that automates schedule creation and maintenance The planning aspect can be integrated with project management software.
7. Telepresence is software that enables individuals to have virtual "face-to-face" meetings without assembling at one location. Videoconferencing is the most obvious example.
8. Semantic technology such as ontologies—systems that encode meaning alongside data to give machines the ability to extract and infer information.

These categories overlap. Workflow, for example, is a significant aspect of content or document management systems, most of which have tools for developing enterprise portals. Proprietary KM technology products such as Lotus Notes define proprietary formats for email, documents, forms, etc. The Internet drove most vendors to adopt Internet formats. Open-source and freeware tools for the creation of blogs and wikis now enable capabilities that used to require expensive commercial tools. KM is driving the adoption of tools that enable organisations to work at the semantic level, as part of the Semantic Web. Some commentators have argued that after many years, the Semantic Web has failed to see widespread adoption, while other commentators have argued that it has been a success.

Knowledge barriers

Just like knowledge transfer and knowledge sharing, the term "knowledge barriers" is not a uniformly defined term and differs in its meaning depending on the author. Knowledge barriers can be associated with high costs for both companies and individuals.

Knowledge retention

Knowledge retention is part of knowledge management. It helps convert tacit knowledge into explicit knowledge. It is a complex process that aims to reduce knowledge loss in the organization. Knowledge retention is needed when expert knowledge workers leave the organisation after a long career. Retaining knowledge prevents losing intellectual capital. According to DeLong (2004), knowledge retention strategies are divided into four main categories:

• Human resources, processes, and practises
• Knowledge transfer practises
• Knowledge recovery practises

Information technologies are used to capture, store, and share knowledge. Knowledge retention projects are usually introduced in three stages: decision making, planning, and implementation. There are differences among researchers on the terms of the stages. For example, Dalkir talks about knowledge capture, sharing, and acquisition, and Doan et al. introduce initiation, implementation, and evaluation. Furthermore, Levy introduces three steps (scope, transfer, and integration), but also recognises a "zero stage" for the initiation of the project.