Knowledge management (KM) is the process of creating, sharing, using and managing the "knowledge and information of an organisation. 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, and "information sciences. 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 organisations.
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 organisation. These efforts overlap with "organisational 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 organisational learning.
Knowledge management efforts have a long history, including on-the-job discussions, formal "apprenticeship, "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 people and the cultural norms which influence their behaviors 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 to drive cultural change. In short, knowledge management programs can yield impressive benefits to individuals and organisations if they are purposeful, concrete and action-orientated.
KM emerged as a scientific discipline in the early 1990s. It was initially supported by individual practitioners, when "Skandia 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 organisations. Gradually, CKOs became interested in practical and theoretical aspects of KM, and the 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 organisations. The KM discipline has been gradually moving towards academic maturity. First, 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 to 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 increased regarding "theory and practice, including:
Regardless of the "school of thought, core components of KM roughly include people/culture, processes/structure and technology. The details depend on the "perspective. KM perspectives include:
The practical relevance of academic research in KM has been questioned with "action research suggested as having more relevance and the need to translate the findings presented in academic journals to a practice.
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.
The Knowledge Spiral as described by Nonaka & Takeuchi.
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-internalised' 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 which can make knowledge difficult to share outside of 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 of 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 categorizing knowledge dimensions distinguishes embedded knowledge of a "system outside of a human individual (e.g., an information system may have knowledge embedded into its design) from "embodied knowledge representing 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) vs. the "transfer or exploitation of "established knowledge" within a group, organisation, 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.
Knowledge may be accessed at three stages: before, during, or after KM-related activities. Organisations 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 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 (codification).
Another strategy 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) provide "insights to requestor (personalisation).
Hansen et al. defined the two strategies. 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. Information technology plays a less important role, as it is 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)
- "Storytelling (as a means of transferring tacit knowledge)
- Cross-project learning
- Make knowledge-sharing as a key roles in employees' job description
- "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)
- "Expert systems (knowledge seeker responds to one or more specific questions to reach knowledge in a repository)
- Best practice transfer
- Knowledge fairs
- Competence management (systematic evaluation and planning of competences of individual organisation members)
- Proximity & architecture (the physical situation of employees can be either conducive or obstructive to knowledge sharing)
- Master–apprentice relationship, Mentor-mentee relationship, Job-shadowing
- "Collaborative software technologies (wikis, shared bookmarking, blogs, "social software, etc.)
- Knowledge repositories (databases, "bookmarking engines, etc.)
- Measuring and reporting intellectual capital (a way of making explicit knowledge for companies)
- "Knowledge brokers (some organisational members take on responsibility for a specific "field" and act as first reference on a specific subject)
- Inter-project knowledge transfer
Multiple "motivations lead organisations to undertake KM. Typical considerations include:
- Making available increased knowledge content in the "development and provision of "products and "services
- Achieving shorter development cycles
- Facilitating and managing innovation and organisational learning
- Leveraging "expertises across the organisation
- Increasing "network "connectivity between internal and external individuals
- Managing business environments and allowing employees to obtain relevant insights and "ideas appropriate to their work
- Solving intractable or "wicked problems
- Managing intellectual capital and assets in the workforce (such as the expertise and "know-how possessed by key individuals or stored in repositories)
Knowledge management (KM) technology can be categorised:
- "Groupware—Software that facilitates collaboration and sharing of organisational information. One of the earliest successful products in this category was "Lotus Notes: it provided tools for "threaded discussions, "document sharing, organisation-wide uniform email, etc.
- "Workflow systems—Systems that allow the representation of processes associated with the creation, use and maintenance of organisational knowledge. For example, the process to create and utilise forms and documents.
- "Content management and "document management systems—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 modeled along with the tasks in the process and validation criteria. Commercial vendors started either to support documents (e.g. "Documentum) or to support web content (e.g. "Interwoven) but as the Internet grew these functions merged and vendors now perform both functions.
- "Enterprise portals—Software that aggregates information across the entire organisation or for groups such as project teams (e.g. "Microsoft SharePoint).
- "eLearning—Software that enables organisations to create customised training and education. This can include lesson plans, monitoring progress and online classes.
- Planning and "scheduling software—Software that automates schedule creation and maintenance (e.g. "Microsoft Outlook). The planning aspect can integrate with "project management software such as "Microsoft Project.
- "Telepresence—Software that enables individuals to have virtual "face-to-face" meetings without assembling at one location. Videoconferencing is the most obvious example.
These categories overlap. Workflow, for example, is a significant aspect of a content or document management systems, most of which have tools for developing enterprise portals.
Proprietary KM technology products such as Lotus Notes defined 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: for example, the "Stanford "Protégé Ontology Editor. 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.
Legal Knowledge Management
Knowledge management in law firms has evolved through three phases. Phase one focused primarily on the development of taxonomies to systematize attorney work product and related research. The second phase focused on enterprise search to mine the growing volume of information managed by law firms. Legal industry specific search engines such as Recomimind were deployed by many AmLaw 100 law firms during this phase. Phase 3 was driven by changes in the legal market place and growing competition that led to price pressure and increased demands for efficiency from clients. A major focus of law firm KM today is in using historical billing information to generate alternative fee arrangements and more generally in the area of legal project management to more efficiently deliver legal services to clients.
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Our research question is: how do we explain the surprising success of Web 2.0 and the equally surprising non-fulfillment of the Semantic Web. Building on a case study approach we conducted a in depth comparative analysis of the two emerging technologies. We propose two conclusions. First, traditional top-down management of an emerging global technology has proved not to be effective in the case of the Semantic Web and Web 2.0, and second, the success for such global technologies is mainly associated with bootstrapping an already installed base.
- ^ Grimes, Seth (7 January 2014). "Semantic Web business: going nowhere slowly". "InformationWeek. Retrieved 5 September 2017.
SemWeb is a narrowly purposed replica of a subset of the World Wide Web. It's useful for information enrichment in certain domains, via a circumscribed set of tools. However, the SemWeb offers a vanishingly small benefit to the vast majority of businesses. The vision persists but is unachievable; the business reality of SemWeb is going pretty much nowhere.
- ^ Cagle, Kurt (3 July 2016). "Why the Semantic Web has failed". "LinkedIn. Retrieved 5 September 2017.
This may sound like heresy, but my personal belief is that the semantic web has failed. Not in "just give it a few more years and it'll catch on" or "it's just a matter of tooling and editors". No, I'd argue that, as admirable as the whole goal of the semantic web is, it's just not working in reality.
- ^ Zaino, Jennifer (23 September 2014). "The Semantic Web's rocking, and there ain't no stopping it now". dataversity.net. Retrieved 5 September 2017.
Make no mistake about it: The semantic web has been a success and that's not about to stop now. That was essentially the message delivered by W3C Data Activity Lead Phil Archer, during his keynote address celebrating the semantic web's ten years of achievement at last month's Semantic Technology & Business Conference in San Jose.
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