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Knowledge Management Systems Life Cycle

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Presentation on theme: "Knowledge Management Systems Life Cycle"— Presentation transcript:

1 Knowledge Management Systems Life Cycle
B. Information Technology (IS) CISB454: Introduction to Knowledge Management Knowledge Management Systems Life Cycle

2 Learning Objectives At the end of this lesson, you should be able to:
discuss the challenges in building KM Systems compare CSLC and KMSLC elaborate on the stages of KMSLC

3 Knowledge Management Systems Life Cycle
Challenges in Building KM Systems

4 Challenges in Building KM Systems
Culture getting people to share knowledge Knowledge evalua-tion assessing the worth of knowledge across the firm

5 Challenges in Building KM Systems
Knowledge process-ing documenting how de-cisions are reached Knowledge imple-mentation organizing knowledge and integrating it with the processing stra-tegy for final deploy-ment

6 Knowledge Management Systems Life Cycle
CSLC vs. KMSLC

7 versus Conventional System Life Cycle KM System Life Cycle
Recognition of Need and Feasibility Study Logical Design (Master Design Plan) Physical Design (coding) Testing Implementation (File Conversion, User Training) Operations and Maintenance Software Requirements Specifications Iterative KM System Life Cycle Evaluate Existing Infrastructure Knowledge Capture Design KMS Blueprint Verify and Validate the KM System Implement the KM System Manage Change and Rewards Structure Form KM Team Post-system evaluation versus

8 Key Differences Conventional Systems KM Systems
Systems analysts deal with information from the user Knowledge developers deal with knowledge from domain experts Users know the problem but not the solution Domain experts know both the problem and the solution System development is pri-marily sequential System development is inc-remental and interactive System testing normally at end of system life cycle KM system testing evolves from beginning of the cycle

9 Key Differences Conventional system life cycle is process-driven
specify then build KM system life cycle is result-oriented start slow and grow

10 Key Similarities Both begin with a problem and end with a solution
Both begin with infor-mation gathering or knowledge capture

11 Key Similarities Testing is essentially the same to make sure the system is right and it is the right system Both developers must choose the appro-priate tool(s) for de-signing their respec-tive systems

12 Knowledge Management Systems Life Cycle
Stages of KMSLC

13 Stages of KMSLC Iterative Rapid Prototyping
Evaluate Existing Infrastructure Form the KM Team Knowledge Capture Iterative Rapid Prototyping Design KM Blueprint Verify and validate the KM System Implement the KM System Manage Change and Rewards Structure Post-system evaluation

14 (1) Evaluate Existing Infrastructure Systems Justifications
What knowledge will be lost through retirement transfer departure to other firms? Is the proposed KM system needed in several locations?

15 (1) Evaluate Existing Infrastructure Systems Justifications
Are experts available willing to help in building a KM sys-tem? Does the problem in question require long years of expe-rience tacit reasoning to solve?

16 (1) Evaluate Existing Infrastructure The Scope Factor
Consider breadth and depth of the project within financial, hu-man resource, & ope-rational constraints Project must be com-pleted quickly enough for users to foresee its benefits

17 (1) Evaluate Existing Infrastructure The Scope Factor
Check to see how the current technology will match technical requirements of the proposed KM system

18 (1) Evaluate Existing Infrastructure Role of Strategic Planning
Risky to plunge into a KMS without strategy Knowledge developer should consider Vision — Foresee what the business is trying to achieve, how it will be done, and how the new system will achieve goals Resources — Check on the affordability of the business to invest in a new KM system Culture — Is the company’s political and social environment amenable to adopting a new KM system?

19 (2) Form the KM Team Identify the key stake-holders of the prospec-tive KM system Team success depends on: Ability of team members Team size Complexity of the project Leadership and team mo-tivation Not promising more than can be realistically deli-vered

20 (3) Knowledge Capture Explicit knowledge captured in reposito-ries from various media Tacit knowledge cap-tured from company experts using various tools and methodo-logies

21 (3) Knowledge Capture Knowledge develo-pers capture know-ledge from experts in order to build the knowledge base

22 (3) Knowledge Capture Selecting an Expert
How does one know the expert is in fact an expert? How would one know that the expert will stay with the project?

23 (3) Knowledge Capture Selecting an Expert
What backup should be available in case the project loses the expert? How could we know what is and what is not within the expert’s area of expertise?

24 (3) Knowledge Capture Role of the Knowledge Developer
The architect of the system Job requires excellent communica-tion skills knowledge of capture tools conceptual thinking a personality that mo-tivates people

25 (3) Knowledge Capture Role of the Knowledge Developer
Close contacts with the champion Rapport with top management for on-going support

26 (3) Knowledge Capture Role of the Knowledge Developer
Worker Champion Progress Reports Prototypes Demos Feedback Support Knowledge Developer Interactive Interface User Acceptance Solutions Rules Testing Knowledge Knowledge Base Knower

27 (4) Design the KM Blueprint
The KM blueprint addresses several issues Finalize scope of proposed KM system with realized net benefits Decide on required system components

28 (4) Design the KM Blueprint
The KM blueprint add-resses several issues Develop the key layers of the KM software architecture to meet company requirements System interoperability and scalability with existing company IT infrastructure

29 (5) Testing the KM System
Verification procedure Ensures the system has the right func-tions Validation procedure Ensures the system has the right output Validation of KM sys-tems is not foolproof

30 (6) Implement the KM System
Converting a new KM system into actual operation This phase includes conversion of data or files This phase also includes user training

31 (6) Implement the KM System
Quality assurance is important, which includes checking for Reasoning errors Ambiguity Incompleteness False representation (false positive and false negative)

32 (7) Manage Change and Rewards Structure
Goal is to minimize resistance to change Experts Regular employees (users) Troublemakers Resistances via pro-jection, avoidance, or aggression

33 (8) Post-system Evaluation
Assess the system’s impact in terms of effects on People Procedures Performance of the business

34 (8) Post-system Evaluation
Areas of concern Quality of decision making Attitude of end users Costs of Knowledge processing and up-date

35 Key Questions Has accuracy and timeliness of decision making improved?
Has the KMS caused organizational changes? What are users’ reactions towards KMS? Has the KMS changed the cost of operating the business? Have relationships among users affected? Does KMS justify the cost of investment?

36 THE END College of Information Technology
Copyright © 2012 Mohd. Sharifuddin Ahmad, PhD College of Information Technology


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