Transcript Knowledge Management

Chapter 10, 11, 12
Knowledge Management
Business Intelligence
Decision Making
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Knowledge
Knowledge is very distinct from data and information and provides
a higher level of meaning about that data and information.
The ability to act is an integral part of being knowledgeable.
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Data are a collection of:
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Information is organized or processed data that are:
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Facts
Measurements
Statistics
Timely
Accurate
Knowledge is information that is:
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Contextual
Relevant
Actionable.
Having knowledge implies that it can be exercised to
solve a problem, whereas having information does not.
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Example
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A map giving detailed driving direction from
one location to another
An up-to-the-minute traffic bulletin along
the freeway that indicates a traffic
slowdown due to construction
Awareness of an alternative, back-roads
route
Having knowledge implies that it can be
used to solve a problem, but not the same
with information
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Knowledge Management
Knowledge management (KM) is a process that helps
organizations identify, select, organize, disseminate, and transfer
important information and expertise that are part of the
organization’s memory.
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Structuring of knowledge enables
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Knowledge management initiatives focus on
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effective and efficient problem solving
dynamic learning
strategic planning
decision making.
identifying knowledge
how it can be shared in a formal manner
leveraging its value through reuse.
Knowledge management can
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promote organizational learning
help solve problems
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Knowledge – Explicit knowledge
Explicit knowledge has been codified (documented) in a form that
can be distributed to others or transformed into a process or
strategy without requiring interpersonal interaction.
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Explicit knowledge (or leaky knowledge) deals with
objective, rational, and technical knowledge
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Data
Policies
Procedures
Software
Documents
Products
Strategies
Goals
Mission
Core competencies
The more knowledge is made explicit, the more
economically it can be transferred.
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Knowledge – Tacit knowledge
Tacit knowledge is usually in the domain of subjective, cognitive,
and experiential learning; it is highly personal and difficult to
formalize. It is also referred to as embedded knowledge since it is
usually either localized within the brain of an individual or
embedded in the group interactions within a department or
business unit.
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Tacit knowledge is the cumulative store
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of the corporate experiences
Mental maps
Insights
Acumen(點子)
Expertise
Know-how
Trade secrets
Skill sets
Learning of an organization
The organizational culture
Tacit knowledge is generally slow and costly to
transfer and can be plagued by ambiguity.
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Knowledge – Knowledge Management Systems
The goal of knowledge management is for an organization to be
aware of individual and collective knowledge so that it may make
the most effective use of the knowledge it has. Firms recognize the
need to integrate both explicit and tacit knowledge into a formal
information systems - Knowledge Management System (KMS)
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A functioning knowledge management system follows six
steps in a cycle dynamically refining information over time
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Create knowledge.
Capture knowledge.
Refine knowledge.
Store knowledge.
Manage knowledge.
Disseminate knowledge.
As knowledge is disseminated, individuals develop,
create, and identify new knowledge or update old
knowledge, which they replenish into the system.
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Knowledge Management Initiatives
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Knowledge management initiatives have one of three
aims:
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to make knowledge visible mainly through
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Maps
yellow pages
hypertext
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to develop a knowledge-intensive culture,
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to build a knowledge infrastructure
There are several activities or processes that surround
the management of knowledge.
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Knowledge Creation
Knowledge Sharing
Knowledge Seeking
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Knowledge Management
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Continued
Knowledge creation or knowledge acquisition is the
generation of new insights, ideas, or routines.
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Socialization mode refers to the conversion of tacit knowledge to new
tacit knowledge through social interactions and shared experience.
Combination mode refers to the creation of new explicit knowledge by
merging, categorizing, reclassifying, and synthesizing existing explicit
knowledge
Externalization refers to converting tacit knowledge to new explicit
knowledge
Internalization refers to the creation of new tacit knowledge from
explicit knowledge.
Knowledge sharing is the exchange of ideas, insights, solutions,
experiences to another individuals via knowledge transfer computer
systems or other non-IS methods.
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Knowledge seeking is the search for and use of internal
organizational knowledge.
Activities or Processes
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Knowledge Management – Information Technology
Knowledge management is more than a technology or product, it
is a methodology applied to business practices. However,
information technology is crucial to the success of knowledge
management systems.
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Components of Knowledge Management Systems:
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Communication technologies allow users to access
needed knowledge and to communicate with each other.
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Collaboration technologies provide the means to perform
group work.
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Storage and retrieval technologies (database management
systems) to store and manage knowledge.
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Knowledge Management – Supporting Technologies
Technologies enable advanced functionality in knowledge
management systems and form the base for future
innovations.
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Artificial Intelligence (AI methods: expert
systems, neural networks, fuzzy logic, genetic
algorithms, etc.)
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Assist in identifying expertise
Elicit knowledge automatically and semi-automatically
Provide interfacing through natural language processors
Enable intelligent searches through intelligent agents.
Intelligent agents are software systems that learn
how users work and provide assistance in their daily
tasks.
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Knowledge Management – Supporting Technologies
Continued
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Data mining the process of searching for previously
unknown information or relationships in large databases, is
ideal for extracting knowledge from databases, documents,
e-mail, etc.
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Model warehouses & model marts extend the role of
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data mining and knowledge discovery by acting as
repositories of knowledge created from prior knowledgediscovery operations
Extensible Markup Language (XML) enables
standardized representations of data structures, so that data
can be processed appropriately by heterogeneous systems
without case-by-case programming.
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Expert location system (p. 403)
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Data Life Cycle Process Continued
The result - generating knowledge
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Knowledge Discovery Continued
Discovering useful patterns
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Management
Management is a process by which organizational goals (outputs)
are achieved through the use of corporate resources (inputs).
These organizational decisions (processes) are typically made by
managers.
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A manager's role can be categorized into:
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Interpersonal - figurehead, leader, liaison
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Informational - monitor, disseminator, spokesperson
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Decisional - entrepreneur, problem solver, resource
coordinator, and negotiator
Information systems support all three
roles especially decisional.
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Management Support Systems
Discovery, communication and collaboration tools provide indirect
support to decision making, however there are several other
information technologies used to directly support decision making.
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Decision Support Systems (DSS) provide
support primarily to analytical, quantitative
types of decisions.
Executive (Enterprise) Support Systems (ESS)
support the informational roles of executives.
Group Decision Support Systems supports
managers and staff working in groups.
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Decision Complexity
Decision making ranges from simple to very complex decisions that
fall along a continuum that ranges from structured to unstructured.
Structured processes refer to routine & repetitive problems with
standard solutions. While Unstructured are "fuzzy," complex problems
with no clear-cut solutions.
Obj ect ive
St r at egic
Pr obl em
Compl ex
Impor t ant
Semi
st r uct ur ed
Tact ical
Oper at ional
Unst r uct ur ed
Inf or mat ion
Repet it ive
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St r uct ur ed
Oper at ion
Mul t i
Dimensional
OLAP
It s been
done bef or e
Day t o Day
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Decision Support Systems - Components
Every DSS consists of at least data management, user interface,
model management components, and the end users. A few also
contain a knowledge management component.
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A DSS data management subsystem contains all the data that
flow from several sources, and are extracted prior to their entry
into a DSS database or a data warehouse.
A model management subsystem contains completed models
(financial, statistical, management science, or other quantitative
models), and the routines to develop DSSs applications.
The user interface covers all aspects of the communications
between a user and the DSS.
The Users. The person (manager, or the decision maker) faced with
the problem or decision that the DSS is designed to support
A knowledge-based or intelligent subsystem provides the
expertise for solving some aspects of the problem, or the
knowledge that can enhance the operation of the other DSS
components.
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Executive Information (Support) Systems
An executive information system (EIS), also known as an executive
support system (ESS), is a technology designed in response to the
specific needs of top-level managers and executives.
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EIS are:
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Very user friendly
Is supported by graphics
Provides the capabilities of exception reporting (reporting only
the results that deviate from a set standard)
Provide drill down (investigating information in increasing detail).
ESS goes beyond EIS to include:
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Analyse support
Communications
Office automation
Intelligence support
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