Chapter 9 Knowledge Management

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Chapter 9Knowledge Management
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Learning Objectives

• Describe the role of knowledge management in the
  organization.
• Be able to evaluate intellectual capital.
• Understand knowledge management systems
  implementation.
• 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
  organizations.

• Define knowledge.
• Learn the characteristics of knowledge
  management.
• 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.

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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
  meaning.
• Examples
• names of students.
• scores of students.
• staff salaries.
• date of birth.
• The price of crude oil is 80 per barrel.

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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.

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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

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Data , information and Knowledge (cont.)

• Data
• Facts,numbers,symbols

Information Selected,orgnized,analyzed data
Knowldgement Integrated of information and
experience
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Knowledge Management (km)
Km Definition Is the process of gaining
insights, experiences and assembled and exchange
to enable companies and project success.
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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. 

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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.

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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
   motivation.
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.

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Knowledge

• 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

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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

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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

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Organizational Learning

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

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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

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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.

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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

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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.

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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.

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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
  

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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.

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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.

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Components of Knowledge Management Systems

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

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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 .

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Technologies supporting Knowledge Management

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

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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
  semiautomatically

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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
  network)
• Forecast future result using existing knowledge.

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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.

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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
  repositories.

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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
  portals
• XML can solve the problem of integrating data
  from disparate sources.

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Knowledge Management System Implementation

• Challenge to identify and integrate
  components
• 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

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Knowledge Management System Implementation

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

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Knowledge Management System Integration

• Integration with enterprise and information
  systems
• DSS/BI
• Integrates models and activates them for specific
  problem
• 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 .

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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
  involvement
• Deliver knowledge when system thinks it is needed

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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 .

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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 .

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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

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Metrics

• 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

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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