Chapter 9 Knowledge Management

1. Chapter 9Knowledge Management

2. Learning Objectives • 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. • 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.

3. 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.

4. 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.

5. 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

6. Data , information and Knowledge (cont.) Data Facts,numbers,symbols Information Selected,orgnized,analyzed data Knowldgement Integrated of information and experience

7. Knowledge Management (km) Km Definition : Is the process of gaining insights, experiences and assembled and exchange to enable companies and project success.

8. 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.

9. 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.

10. characteristics of knowledge management • Knowledge management is about people: and is directly linked to what people know, which is dependent on human skills, intuition, ideas, and motivation. • 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. • 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.

11. 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

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

13. 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

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

15. 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

16. 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.

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

18. 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.

19. 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.

20. 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

21. 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.

22. Knowledge Management System Cycle ( cont. ) • Creates knowledge:through new ways of doing things or develop know-how. • Captureknowledge: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. • Manageknowledge:knowledge must be current, Reviews for accuracy and relevance • Disseminateknowledge:Makes knowledge available at all times to anyone.

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

24. 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 .

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

26. 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

27. 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.

28. 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.

29. 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. • IntelligentData mining :discovers information within database, data warehouse, and knowledge repositories.

30. 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.

31. 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

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

33. 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 .

34. 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

35. 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 .

36. 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 .

37. 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

38. 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

39. Factors Leading to Success and Failure of Systems • Failure : • System does not meet organization’s needs • Lack of commitment • No incentive to use system • Lack of integration • 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