Knowledge Management: Tools and techniques

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
etc.
• 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
application(s).

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

• SWOT (Strengths Weaknesses Opportunities Threats) analysis, balanced
  scorecards.
• 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
processes
• What
the processes manipulate - modeling the resources
• Who
carries out the processes - modeling capabilities, roles and
authority
• Where
a process is carried out - modeling of the communication between
agents
• When
a process is carried out - this specifies the control over
processes