1. Making organizational knowledge more Accessible, Quality, & Currency
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. Reduce the time required to find info
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
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 Explicit knowledge Knowledge is
Knowledge resides in the mind of employees
Explicit knowledge
Knowledge has been documented s
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
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
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
s, 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 s
Chat, instant message
Blog, wikis

27. Learning management systems
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
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. Virtual reality for the web
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
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 Automate routine tasks
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 Inference engine 200 to many thousands of rules
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 Auto focus of cameras
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)

51. Examples GE Jet Turbine Aircraft Engine i2 technology
Each design change
requires changes in up to 100 variables
i2 technology
Supply chain management software
Optimize production-scheduling models
Customer orders
Material
Manufacturing capability
Delivery dates …

52. Hybrid AI systems Intelligent agent Neurofuzzy washing machines
Software programs that work in the background
Without human intervention
To carry out specific, repetitive, and predictable tasks

53. INTELLIGENT AGENTS IN P&G’S SUPPLY CHAIN NETWORK

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資訊科技使 Albassami 的工作成為可行
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