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Chapter 9 Knowledge Management


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Title: Chapter 9 Knowledge Management

Chapter 9Knowledge Management
Learning Objectives
  • Describe the role of knowledge management in the
  • Be able to evaluate intellectual capital.
  • Understand knowledge management systems
  • Illustrate the role of technology, people, and
    management with regards to knowledge management.
  • Understand the benefits and problems of knowledge
    management initiatives.
  • Learn how knowledge management can change
  • Define knowledge.
  • Learn the characteristics of knowledge
  • Describe organizational learning.
  • Understand the knowledge management cycle.
  • Understand knowledge management system technology
    and how it is implemented.
  • Learn knowledge management approaches.
  • Understand the activities of the CKO and
    knowledge workers.

Data , information and Knowledge
  • Data  Is a numbers and symbols, images, sounds,
    which are elementary truths, which need to
    organize and handle to provide a specific
  • Examples
  • names of students.
  • scores of students.
  • staff salaries.
  • date of birth.
  • The price of crude oil is 80 per barrel.

Data , information and Knowledge (cont.)
  • Information Is the set of organized data, and
    arranged to meet a specific need .
  • Example
  • The price of crude oil has risen from 70 to 80
    per barrel.

Data , information and Knowledge (cont.)
  • Knowledge  is a combination of information,
    experience and insight .
  • Examples
  • "When crude oil prices go up by 10 per barrel,
    it's likely that petrol prices will rise by 2p
    per litre" is knowledge.
  • Temperatures, when you know that the atmosphere
    will be very cold and rainy, without any warning
    you will get out your coat and your Umbrella.
  • elementary school children . They can tell you
    that "2 x 2 4" because they have amassed that
    knowledge (it being included in the times table).
    But when asked what is "1267 x 300", they can not
    respond correctly because that entry is not in
    their times table

Data , information and Knowledge (cont.)
  • Data
  • Facts,numbers,symbols

Information Selected,orgnized,analyzed data
Knowldgement Integrated of information and
Knowledge Management (km)
Km Definition Is the process of gaining
insights, experiences and assembled and exchange
to enable companies and project success.
Knowledge Management (cont.)
  • Examples to understand the importance of
    knowledge management 
  • You works in a large organization , at one day
    you encounter a big problem at work. 
  • When you have a large capital and want to invest
    it in a domain. 
  • Came to you an important client to meet the
    boss, then you talk to the Assistant Director,
    but he tell you that he is on vacation. 

Knowledge Management (cont.)
  • The benefits from knowledge management
  • To respond to developments and changes
  • reduce the costs and efforts.
  • Planning
  • Decision-making.
  • Solve problems.
  • The development of production.

characteristics of knowledge management
  1. Knowledge management is about people and is
    directly linked to what people know, which is
    dependent on human skills, intuition, ideas, and
  2. Knowledge management and constantly changing
    There's nothing like the law is subject to change
    in knowledge management. Is a test of knowledge
    and constantly updated and revised, and sometimes
    even "disabled" when it is no longer in practice.
  3. Knowledge management and value-added It depends
    on the pooling of experiences and
    relationships. Organizations can exchange ideas
    by bringing in experts from the field to advise
    or educate managers on recent developments.

  • Explicit knowledge
  • Objective, rational, technical
  • Policies, goals, strategies, papers, reports
  • Codified
  • Leaky knowledge
  • Tacit knowledge
  • Subjective, cognitive, experiential learning
  • Highly personalized
  • Difficult to formalize
  • Sticky knowledge

Knowledge Management
  • Systematic and active management of ideas,
    information, and knowledge residing within
    organizations employees
  • Knowledge management systems
  • Use of technologies to manage knowledge
  • Used with turnover, change, downsizing
  • Provide consistent levels of service

Organizational Learning
  • Learning organization
  • Ability to learn from past
  • To improve, organization must learn
  • Issues
  • Meaning, management, measurement
  • Activities
  • Problem-solving, experimentation, learning from
    past, learning from acknowledged best practices,
    transfer of knowledge within organization
  • Must have organizational memory, way to save and
    share it

Organizational Learning
  • Organizational learning
  • Develop new knowledge
  • Corporate memory critical
  • Organizational culture
  • Pattern of shared basic assumptions

Knowledge Management Initiatives
  • Aims
  • Make knowledge visible
  • Develop knowledge intensive culture
  • Build knowledge infrastructure
  • Surrounding processes
  • Creation of knowledge
  • Sharing of knowledge
  • Seeking out knowledge
  • Using knowledge

Knowledge Management Initiatives (cont.)
  • Knowledge creation
  • Generating new ideas, routines, insights .
  • Modes
  • Socialization refers to the conversion of tacit
    knowledge to new tacit knowledge.
  • Combination refers to the creation if new
    explicit knowledge.
  • Externalization refers to the conversion of
    tacit knowledge to new explicit knowledge.
  • Internalization refers to the conversion of
    explicit knowledge to new tacit knowledge.

Knowledge Management Initiatives ( cont. )
  • Knowledge sharing
  • Willful explication of ones ideas , insights ,
    experiences to another directly or through an
    intermediary ( internet ).
  • Knowledge seeking
  • Knowledge sourcing

Approaches to Knowledge Management
  • Process Approach
  • Codifies knowledge
  • Formalized controls , Process, technologies
  • Fails to capture most tacit knowledge .
  • Practice Approach
  • Assumes that most knowledge is tacit.
  • Informal systems
  • Social events , communities of practice ,
    person-to-person contacts.
  • The valuable knowledge for these is tacit , which
    is difficult to extract , store , manage.

Approaches to Knowledge Management ( cont. )
  • Challenge to make tacit knowledge explicit.
  • Disadvantage can result in inefficiency.
  • Hybrid Approach
  • Many organization use a hybrid of the process and
  • practice.
  • Tacit knowledge primarily stored as contact
    information becuse repository stores only
    explicit Knowledge.
  • Best practices captured and managed.

Approaches to Knowledge Management(cont. )
  • Best practices
  • Activities and Methods that effective
    organizations use to operate and manage functions
  • Knowledge repository
  • Place for capture and storage of knowledge
  • Neither a database nor Knowledge base
  • Knowledge base and Knowledge repository is very
    different mechanisms
  • Developing Knowledge repository is not an easy

Knowledge Management System Cycle
  • Knowledge Management System Cycle
  • follows six steps .
  • The reason for the cycle
  • Is that knowledge is dynamically
  • refined over time,
  • So knowledge must be updated
  • to reflect the changes.

Knowledge Management System Cycle ( cont. )
  • Creates knowledge through new ways of doing
    things or develop know-how.
  • Capture knowledge Identifies and captures new
    knowledge as valuable and be represented in a
    reasonable way.
  • Refine knowledge new knowledge must be placed
    in context so it is usable.
  • Stores knowledge in repository, so that others
    in the organization can access it.
  • Manage knowledge knowledge must be current,
    Reviews for accuracy and relevance
  • Disseminate knowledge Makes knowledge available
    at all times to anyone.

Components of Knowledge Management Systems
  • Knowledge Management Systems are developed using
    three sets of Technologies
  • Communication Technology
  • Collaboration Technology
  • Storage and retrieval Technology

Components of Knowledge Management Systems
  • Communication
  • Allow users to Access knowledge
  • Communicates with others
  • E-mail, internet, fax machines, telephone
  • Collaboration
  • Perform groupwork Synchronous (groups can work
    together on common documents as the same time) or
    asynchronous(at different time)
  • Same place/different place .
  • Storage and retrieval
  • Using database management system to store
    and manage knowledge. Capture, storing,
    retrieval, and management of both explicit and
    tacit knowledge through collaborative systems .

Technologies supporting Knowledge Management
  • Artificial Intelligence (AI)
  • Intelligent agents
  • Knowledge discovery in databases (KDD)
  • Extensible Markup Language (XML)

Technologies supporting Knowledge Management
  • Artificial Intelligence (AI)
  • - AI methods and tools are embedded in a number
    of knowledge management systems, either by
    vendors or by system developers.
  • - AI methods can assist in identifying expertise,
    eliciting knowledge automatically and

Artificial Intelligence (AI)
  • Expert systems, neural networks, fuzzy logic,
    intelligent agents are used in Knowledge
    Management Systems to do the following
  • Assist in and enhance searching knowledge
  • provide advice directly from knowledge by using
    neural networks or expert system
  • scan e-mail, documents, and database to perform
    knowledge discovery.
  • Identify patterns in data (usually through neural
  • Forecast future result using existing knowledge.

Technologies supporting Knowledge Management
  • Intelligent agents
  • Systems that learn how users work and provide
    assistance in thair daily tasks.
  • There are number of ways that Intelligent agents
    can help in Knowledge management system .
  • Examples
  • IBM offers an intelligent data mining family,
    including intelligent decision server ,for
    finding and analyzing massive amount of
    enterprise data.
  • Gentia (planning sciences international) uses
    Intelligent agents to facilitate data mining with
    web access and data warehouse facilities.

Technologies supporting Knowledge Management
  • Knowledge discovery in databases (KDD)
  • Process used to search for and extract
    information from volumes of documents and data.
  • Internal data and document mining .
  • External model marts and model warehouses.
  • Data mining is ideal for eliciting knowledge
    from database.
  • Intelligent Data mining discovers information
    within database, data warehouse, and knowledge

Technologies supporting Knowledge Management
  • Extensible Markup Language (XML)
  • Enables standardized representations of data
    structures, so that data can be processed
    appropriately by heterogeneous systems with out
    case-by-case programming.
  • Better collaboration and communication through
  • XML can solve the problem of integrating data
    from disparate sources.

Knowledge Management System Implementation
  • Challenge to identify and integrate
  • Early systems developed with networks,
    groupware, databases
  • Knowware
  • Technology tools that
    support knowledge management Collaborative
    computing tools .
  • Groupware
  • Knowledge servers
  • Enterprise knowledge portals
  • Document management systems
  • Content management systems
  • Knowledge harvesting tools
  • Search engines
  • Knowledge management suites
  • Complete out-of-the-box solutions

Knowledge Management System Implementation
  • Implementation
  • Software packages available
  • Include one or more tools
  • Consulting firms
  • Outsourcing
  • Application Service Providers

Knowledge Management System Integration
  • Integration with enterprise and information
  • DSS/BI
  • Integrates models and activates them for specific
  • Artificial Intelligence
  • Expert system if-then-else rules .
  • Natural language processing understanding
    searches .
  • Artificial neural networks understanding text .
  • Artificial intelligence based tools identify
    and classify expertise .

Knowledge Management System Integration
  • Database
  • Knowledge discovery in databases
  • CRM
  • Provide tacit knowledge to users
  • Supply chain management systems
  • Can access combined tacit and explicit knowledge
  • Corporate intranets and extranets
  • Knowledge flows more freely in both directions
  • Capture knowledge directly with little user
  • Deliver knowledge when system thinks it is needed

Human Resources
  • Chief knowledge officer
  • Senior level .
  • Sets strategic priorities .
  • Defines area of knowledge based on organization
    mission and goals.
  • Creates infrastructure .
  • Identifies knowledge champions .
  • Manages content produced by groups .
  • Adds to knowledge base .

Human Resources (cont. )
  • CEO
  • Champion knowledge management .
  • Upper management
  • Ensures availability of resources to CKO .
  • Communities of practice
  • Knowledge management system developers
  • Team members that develop system .
  • Knowledge management system staff
  • Catalog and manage knowledge .

Knowledge Management Valuation
  • Asset-based approaches
  • Identifies intellectual assets
  • Focuses on increasing value
  • Knowledge linked to applications and business
    benefits approaches
  • Balanced scorecard
  • Economic value added
  • Inclusive valuation methodology
  • Return on management ratio
  • Knowledge capital measure
  • Estimated sale price approach

  • Financial
  • ROI
  • Perceptual, rather than absolute
  • Intellectual capital not considered an asset
  • Non-financial
  • Value of intangibles
  • External relationship linkages capital
  • Structural capital
  • Human capital
  • Social capital
  • Environmental capital

Factors Leading to Success and Failure of Systems
  • Success
  • Companies must assess need
  • System needs technical and organizational
    infrastructure to build on
  • System must have economic value to organization
  • Senior management support
  • Organization needs multiple channels for
    knowledge transfer
  • Appropriate organizational culture
  • Failure
  • System does not meet organizations needs
  • Lack of commitment
  • No incentive to use system
  • Lack of integration
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