Knowledge Management: Tools and techniques

By : |May 30, 2002 0

Knowledge Management (KM) tools run the gamut from standard, off-the-shelf
e-mail packages to sophisticated collaboration tools designed specifically to
support community building and identity. Generally, tools fall into one or more
of the following categories: Knowledge repositories, expertise access tolls,
e-learning applications, discussion and chat technologies, synchronous
interaction tools, and search an data mining tools.

Says Purple Yogi’s vice president-engineering, Ramesh Subramonian,
"There are many different methods and tools available in the knowledge
management industry. However, all the tools do not allow for a combination of
automatic classification and human intervention, and do not support processes
for managing knowledge at all levels within an organization."

Agnitio Management Systems CEO Zulfikar Deen outlines some of the tools
adopted for various functions:

    • Collaborative tools: Tools that enable sharing of knowledge across
      time and distance. These tools may enable both structured and free-flow
      sharing of knowledge and best practices. Transcripts of the use of these
      tools may be incorporated into a knowledge base for future use.

    • Content management tools: Technologies that allow the capture and
      management of explicit experience — they allow people to capture, codify
      and organize experiences and ideas in central repositories. A more general
      term than data management, content management includes structured and
      unstructured data.

    • Document management tools: Tools that would enable document
      creation, review and retrieval.

    • Data mining tools: Applications of nontrivial algorithms to large
      amounts of data for the purpose for extracting useful data patterns. Data
      mining tools use a variety of techniques including case-based reasoning,
      data visualization, fuzzy query and analysis, and neural networks.
      Case-based reasoning tools provide a means to find records similar to a
      specified record or records. These tools let the user specify the
      "similarity" of retrieved records. Data visualization tools let
      the user easily and quickly view graphical displays of information from
      different perspectives. Although the term data mining is sometimes used
      interchangeably with the term knowledge discovery, it is generally accepted
      that data mining is one step in the knowledge discovery process.

    • Decision Support Systems (DSS): Interactive computer-based systems
      intended to help decision-makers utilize data and models to identify and
      solve problems and make decisions. The system must aid a decision-maker in
      solving unprogrammed, unstructured (or "semi-structured")
      problems. The system must possess an interactive query facility, with a
      query language that is easy to learn and use.

    • Knowledge modeling tools: Tools that would facilitate modeling
      disparate pieces of relevant information into taxonomies (like hierarchical
      structures) and ontologies (rule based associations).

    • Indexing and search engine tools: Tools that would crawl through
      various kinds of documents and repositories, and retrieve metadata about
      them — and those that would map user queries into relevant result sets

    • Intelligent agents: Software that works without the assistance of
      users by making choices. The choices are based on rules of behavior that
      software developers have identified and built into the software.

    • Connectors: The set of tools that would make the communication
      possible between a corporate entity’s mail, database and (any such) legacy

There are very few tools providing a truly integrated set of functions to
support the tasks associated with knowledge management. The following lists
some tools that have been used to support various aspect of managing knowledge:

  • Knowledge Capture:

    • PC PACK is a portable package of integrated tools for requirements
      and knowledge engineering.

    • Clementine Data Mining (or Knowledge Discovery) software package
      from ISL

    • Intelligent Miner, another data mining tool this time from IBM
    • The Information Discovery System (IDIS), a data mining tool from
      Information Discovery.

  • Knowledge Sharing:

    • ART*Enterprise – object-oriented client/server tool with case-based
      retrieval of both structured and unstructured information from Brightware

    • GrapeVINE – two versions, one for Lotus notes and one for Netscape
      in which users can set up an interest profile that identifies what is useful
      to them and so filter information.

    • Knowledge Software – two products PKM (the Personal Knowledge
      Manager) and PDP (the Personal Development Plan) both based on Lotus Notes.

    • Knowledge Xchange – TM Knowledge Management System – a Lotus Notes
      based system, the current users are Andersen Consulting professionals.

Knowledge modeling techniques co-exist along with traditional business
management techniques and hence employ basic techniques like:

  • SWOT (Strengths Weaknesses Opportunities Threats) analysis, balanced

  • Modeling languages such as: IDEF (Process Flow and Object State
    Description Capture Method, and RADs (Role Activity Diagrams).

Several models set to be developed, each of which represent a different
perspective on the organization which can be characterized as "How, What,
Who, Where, When and Why" such as:

  • How the organization carries out its business – modeling the business

  • What the processes manipulate – modeling the resources
  • Who carries out the processes – modeling capabilities, roles and

  • Where a process is carried out – modeling of the communication between

  • When a process is carried out – this specifies the control over

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