Managing Knowledge

1. Managing Knowledge Making organizational knowledge more Accessible, Quality, & Currency

2. Canadian Tire • Five interrelated companies • 57,000 employees • 1,200 stores • Independently owned and operated • Spread across Canada • Need efficient and effective ways to communicate with workforce and dealers

3. Dealer portal & employee information intranet • Dealer portal • Central source for • Merchandise setup info • Alerts • Best practices • Products ordering • Problem solution • Save money by reducing daily and weekly mailings • Easy access info for dealers

4. Employee intranet • TIREnet • Catalogued more than 30,000 documents • Search technology • Easier to keep document current • Reduce the time required to find info

5. 11.1 The knowledge management landscape 11.2 Enterprise-wide knowledge management systems 11.3 Knowledge work systems 11.4 Intelligent techniques

6. The knowledge management landscape • Communicating & sharing knowledge • Knowledge management • Collaboration • Production & distribution • Information • Knowledge • Companies’ value depend on • its ability to create and manage knowledge

7. Important dimensions of knowledge • Data • Events or transactions captured • Information • Organized data into categories of understanding • Monthly, regional, store-based reports

8. Knowledge • Discover patterns, rules, and contexts where the knowledge works • Wisdom • Collective and individual experience of applying knowledge • Where, When, How

9. Tacit knowledge • Knowledge resides in the mind of employees • Explicit knowledge • Knowledge has been documented • Emails • Voice mails • Graphics • Knowledge is • Situational & contextual

10. Organizational learning and Knowledge management • The ability to reflect and adjust from learning • Create new business process • Change of patterns of management decision

11. The knowledge management value chain

12. Knowledge acquisition • Corporate repositories • Documents, reports, presentations, best practices • Unstructured documents • Online expert networks • Enable employee to find “experts” • Knowledge work stations • Discovering patterns in corporate data

13. Knowledge storage • System for employees to retrieve and use knowledge • Encourage the development of corporate-wide schemas for indexing documents • Reward employees for taking time to update and store documents properly

14. Knowledge Dissemination • Portal • Email • Instant message • Wikis • Social networks • Search engines • Collaboration technologies

15. Knowledge application • Build knowledge into • Decision makings systems • Decision support systems • Business processes • Enterprise systems • ERP • SCM • CRM

16. Building organizational and management capital: Collaboration, community of practice, & office environments • Communities of Practice • Professionals and employees • Similar work-related activities and interests • Reduce the learning curve for new employees • Spawning ground for new ideas

17. Types of knowledge management systems

18. 11.1 The knowledge management landscape 11.2 Enterprise-wide knowledge management systems 11.3 Knowledge work systems 11.4 Intelligent techniques

19. Three kinds of knowledge • Structured text documents • Reports, presentations • Semi-structured • Emails, digital pictures, graphs • Tacit knowledge • Reside in the heads of employees

20. Enterprise content management systems • Capabilities for knowledge • Capture • Storage • Retrieval • Distribution • Preservation • Enable users to access external sources of info • Create a portal for easy access

21. Fig 11-3, An Enterprise Content Management System

22. Leading vendors • Open Text Corporation • EMC (Documentum) • IBM • Oracle

23. Taxonomy • Classification scheme • Organize information into meaningful categories

24. Knowledge network systems • Expertise location and management systems • Online directory of corporate experts • Best practices knowledge base • FAQ repository

26. Collaboration tools and Learning management systems • Web technology to foster collaboration and information exchanges • Portal • Emails • Chat, instant message • Blog, wikis

27. Social bookmarking • Users save their bookmarks • Tag bookmarks • Tags can be shared or searched • Delicious, Digg • Learning management systems • Track and manage employee’s learning • Whirlpool corporation • Training program for 3,500 salepeople

28. 11.1 The knowledge management landscape 11.2 Enterprise-wide knowledge management systems 11.3 Knowledge work systems 11.4 Intelligent techniques

29. Specialized systems for knowledge worker to create new knowledge • Knowledge workers • Researchers • Designers • Architects • Scientists • Engineers

30. Requirements of knowledge work systems • Substantial computing power for graphics, complex calculations • Powerful graphics and analytical tools • Communications and document management • Access to external databases • User-friendly interfaces • Optimized for tasks to be performed (design engineering, financial analysis)

32. Examples of knowledge work systems • Computer-aided design (CAD) • Traditional • A Mold • A Prototype • CAD • Designs can be easily tested and changed • Virtual reality systems • Boeing CO. • 787 Dreamliner mechanics’ training

33. Augmented reality • Enhance a direct or indirect view of a physical real-world environment • Virtual reality for the web • Virtual reality modeling language • DuPont Chemical • VRML for a virtual walkthrough of a plant

34. 11.1 The knowledge management landscape 11.2 Enterprise-wide knowledge management systems 11.3 Knowledge work systems 11.4 Intelligent techniques

35. Tools to capture individual and collective knowledge • Capture tacit knowledge • Expert systems • Case-based reasoning • Fuzzy logic • Discovering knowledge • Neural networks • Data mining

36. Generating solutions to problems • Genetic algorithm • Automate routine tasks • Intelligent agent

37. Artificial intelligence (AI) • To emulate human behavior Watson Won Jeopardy

38. Capturing knowledge: expert systems • Specific and limited domain of human expertise • Compare to human experts, ES lack • the breadth of knowledge • the understanding of fundamental principles • Diagnosis a m/c • Grant credit of a loan

39. Rules in an Expert system

40. Knowledge base • 200 to many thousands of rules • Inference engine • Forward chaining • Begin with the info entered by the users • Search the rule base • Arrive a solution • Backward chaining • Start with a hypothesis • Asking the user questions • Until hypothesis is confirmed or disproved

41. Examples of successful expert systems • Con-Way transportation • Automate and optimized planning of overnight shipping route • 50,000 shipments of heavy freight each night • across 25 states • Dispatcher tweak the routing plan provide by the expert system

42. Organizational intelligence: case-based reasoning • Cases • Descriptions of past experiences of human specialists • Systems • Search the stored cases • Find the closest fit and applied the solution EX: diagnostic systems in medicine

43. Fuzzy logic systems • Human • tend to categorize things imprecisely • Each categories represent a range of values • Use rules for making decisions that may have many shades of meaning

45. Applications • Sendai subway system • Use fuzzy logic control to accelerate • so smoothly that standing passengers need not hold on. • Auto focus of cameras

46. Neural network • Solving complex, poorly understood problems • Large amount of data have been collected • Parallel the processing patterns of the biological or human brain • Learn the correct solution by examples

48. Applications • Screening patients for disease • Visa international • Detect credit card fraud

49. Genetic algorithm • Finding the optimal solution for a specific problem • Dynamic and complex • Involve hundreds or thousands of variables or formulas • Large number of possible solutions exists • Inspired by evolutionary biology • Inheritance, mutation, selection, crossover (recombination)