Knowledge Management In Universities University

- 02.13

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Knowledge management (KM) is the process of creating, sharing, using and managing the knowledge and information of an organization. It refers to a multi-disciplinary approach to achieving 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 sciences. Other fields may contribute to KM research, including information and media, computer science, public health, and public policy. Several universities offer dedicated Master of Science 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, information technology, or human resource management departments. Several consulting companies provide advice regarding KM to these organisations.

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 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 a focus on encouraging the sharing of knowledge. KM is an enabler of organisational learning.


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History

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, knowledge repositories, group decision support systems, intranets, and computer-supported cooperative work have been introduced to further enhance such efforts.

In 2005, the term personal knowledge management was introduced; it refers to the management of knowledge at the individual level.

In 2012, Mohamed Chatti introduced the PKN model to KM as an alternative perspective on personal knowledge management, based on the concepts of personal knowledge network (PKN) and knowledge ecology.

In the enterprise, early collections of case studies recognized 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 organizational 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 organizations if they are purposeful, concrete, and action-orientated.


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Research

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 maximize 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.

Multiple KM disciplines exist; approaches vary by author and school. As the discipline matured, academic debates increased regarding theory and practice, including:

  • Techno-centric with a focus on technology, ideally those that enhance knowledge sharing and creation.
  • Organisational with a focus on how an organisation can be designed to facilitate knowledge processes 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 the perspective. KM perspectives include:

  • community of practice
  • social network analysis
  • intellectual capital
  • information theory
  • complexity science
  • constructivism

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.

Dimensions

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 internalized 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.

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 recognizes 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 internalized tacit knowledge into explicit knowledge to share it, and the same effort must permit individuals to internalize 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.

Strategies

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 (personalization).

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
  • 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
  • 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 whom to talk about a specific subject)
  • Inter-project knowledge transfer

Motivations

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 new product development cycles
  • Facilitating and managing innovation and organisational learning
  • Leveraging the expertise of people 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 intellectual assets in the workforce (such as the expertise and know-how possessed by key individuals or stored in repositories)

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KM technologies

Knowledge management (KM) technology can be categorized:

  • Groupware--Technologies that facilitate collaboration and sharing of organizational information. One of the earliest successful products in this category was Lotus Notes. Notes provided tools for threaded discussions, sharing of documents, organization wide uniform email, etc.
  • Workflow--Workflow tools allow the representation of processes associated with the creation, use, and maintenance of organizational knowledge. For example, the process to create and utilize forms and documents.
  • Content/Document Management--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--Web sites that aggregate information across the entire organization or for groups such as project teams.
  • eLearning--Enables organizations to create customized training and education software. This can include lesson plans, monitoring progress and online classes.
  • Scheduling and planning--Automate schedule creation and maintenance, e.g., Microsoft Outlook. The planning aspect can integrate with project management tools such as Microsoft Project.
  • Telepresence--Enables individuals to have virtual "face-to-face" meetings without assembling at one location. Videoconferencing is the most obvious example.

Workflow for example is a significant aspect of a content or document management system and most content and document management systems have tools for developing enterprise portals.

The adoption of Internet standards led 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 organizations to work at the semantic level, as part of the Semantic Web. One, for example, is the Stanford Protege Ontology Editor.

Source of the article : Wikipedia



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