KM concepts

From Wikipedia, the free encyclopedia

The Knowledge management discourse has adopted, invented and refined concepts from a wide range of disciplines and practices. There follows a list of concepts and language in use in the field. At the moment there is no clear consensus on what is or is not a core concept. The ordering of the list has no significance. Some knowledge of these terms and their background could be summarised as What one should know to be considered a proficient KM adviser and knowledge worker

  • Corporate memory - a collection of best practices, heuristics, process documents and other texts that help define how a business operates. (related terms: organizational memory or group memory). Capturing, maintaining, and growing a knowledge base, selecting appropriate technologies, and motivating quality contributions are all key KM themes.
  • Intellectual capital - the intangible assets of a firm. These include competencies, culture and connections that enable and foster innovation, agility, awareness, adaptation and corporate survival. KM plays a role in mapping, recording, evaluating, stewarding, marketing and growing intellectual capital and knowledge assets.
  • DIKW (data / information / knowledge / wisdom)
  • codification vs. personalization - the trade-off between capture and storage of explicit information and making connections to people who know as well as to acquire external knowledge yourself.
  • exploration vs. exploitation (1) - should an adviser focus on gathering external information and buying (recruiting) expertise or capture internal best practices and grow local competencies?
  • exploration vs. exploitation (2) - from the use of complexity science in knowledge management. Exploitation focuses on discovery, opening up to new concepts and ideas. Exploitation as it says is making those ideas work in practice. The assumption is that work is a balance of both, but that they cannot co-exist
  • practice vs. process - the balance between informal learning and strictly defined repeatable activities.
  • best practices - pattern language, distinctions, collaborative writing, ontologies, inquiry, reflection, concept mapping. There is a tendency (BSI standards for example) to replace "best" with "good" to distinguish knowledge management from business process engineering.
  • after action reviews (AARs) - learning by gathering participants after completion of a significant project, exploring, reflecting, recording advances and mistakes.
  • peer reviews - inviting colleagues who have experience with similar projects to share their tips, tricks and lessons learned before starting out.
  • knowledge mapping & audits - discovering opportunities, knowledge gaps and charting flows. A survey to understand where current knowledge is created and who needs it.
  • lessons learned (learning histories) - a systematic review of failures and successes conducted by a neutral party.
  • 'Ba' - a physical or virtual collaborative space, where participants feel safe and exchange insights.
  • Cynefin - a Welsh equivalent of Ba used for an approach to KM based on complexity theory and narrative.
  • Narrative - growing in use in KM based on an adaption of Polayani "we always know more than we say" to add "and we always say more than we can write down. The use of narrative is growing in knowledge magement as an alternative to content management and CoP and is linked in part to social computing.
  • induction (aka data mining) - searching for patterns, rules and interesting insights from collected (business) data.
  • source documents - collaborative scripts that set forth the intention and vision of the firm or group.

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