1. Working Knowledge: How Organizations Manage What They Know
By: Thomas H. Davenport and Laurence Prusak
Presented By: Jonathan Sage
Undergraduate Senior in Management Information Systems

2. Outline Chapter 5: Knowledge Transfer
Chapter 6: Knowledge Roles and Skills
Chapter 7: Technologies for Knowledge
Management
Chapter 8: Knowledge Management Projects
in Practice
Chapter 9: The Pragmatics of Knowledge

3. Chapter 5: Knowledge Transfer

4. Strategies for Knowledge Transfer
Structured verses spontaneous
MMC and Sematech

5. Water Coolers and Talk Rooms
‘Conversations are the most important form of work’
Human nature
New ideas/old problems in unexpected ways

6. Water Cooler Limitations
Stuck on a particular problem
Major breakthrough

7. Talk Rooms Popular in Japan Expectations for workers 20 minutes a day
Chat about current work

8. Virtual Offices Discourage informal conversation by nature
Extra effort to make up difference

9. Socializing Popular across cultures Establish trust
Focus on rich communication medium, rather than lean

10. Considerations What works in one country isn't universal
Output culture
Knowledge is less valuable when widely shared
Implementation barriers

11. Considerations Suit organizational and corporate culture
What works in one country isn’t universal
Recognize the value of low tech, face to face.
Broaden definition of ‘productivity’
“Real work”/reading example
Ample slack time for workers

12. Knowledge Fairs and Open Forums
Create locations and occasions for workers to interact informally.
Knowledge fair – bring people together without expectations of who should talk to who
Functionality of structure v. unstructured

13. What kinds of knowledge?
Explicit
Captured in procedures, documents and DB
Easy to obtain
Tacit
Extensive personal contact
Partnership, mentoring, apprenticeship.
Include explicit and tacit

14. How to Capture Knowledge
Programs
Japanese use “old-young” model
Mentoring
Responsible for colleague one level down
Technology
Network of colleagues willing to meet/share
Videoconferencing
Record stories/experience to CD/video

15. Culture of Knowledge Transfer
Frictions
Trust
Differences
Time
Selfish reasons
Knowledge gap
Intolerance for mistakes

16. Trust and Common Ground
Proof that change will bring better results
Language
Everyday language
Industry jargon
Proximity
New Zealand/Boston Harbor tunnel engineers
Tech factor

17. Status and Reputation Status of source Reputation of source Why?
Saves time
Human nature

18. Knowledge Transfer Transfer = Transmission + Absorption (and Use)
Resistance
Self esteem
Resistance to change
US info on fat v. obesity level
Knowing is not the same as doing

19. Velocity and Viscosity
Enhanced by technology
Viscosity
Enhanced by richness of medium
Inverse relationship
Mobil Oil example

20. Case Study: 3M Encourage new ideas All levels of employees Scotch Tape
Post It Notes

21. Chapter 6: Knowledge Roles and Skills

22. Knowledge-Oriented Personnel
Everyone
Engineers, managers, secretaries
Needs the right corporate culture to flourish
McKinsey consulting verses Chaparral steel

23. Knowledge Management Workers
“Traditional”
Programmers, system administrators
“New”
Extract knowledge from those who have it
Format it
Maintain it
Need both ‘hard and ‘soft’ skills

24. Knowledge Management Workers
Assign existing workers to new tasks
Assign existing teams to become ‘knowledge managers’
‘Knowledge engineers’
‘Technical communicators’

25. Managers of Knowledge Projects
Skilled in
Project management
Change management
Technology management
Lots of experience
Open to new ideas

26. Chief Knowledge Officer
Build a knowledge culture
Create a knowledge management infrastructure
Technical
Human
Make it economically feasible

27. Chief Knowledge Officer
Location of the CKO role
Stand alone
Work with IS
Work with HR

28. Chief Learning Officer
Focus on
Training
Education
Involved in
Human Resources

29. Chapter 7: Technologies for Knowledge Management

30. Expert Systems and Artificial Intelligence
Early predictions
Expert systems
McDonnell Douglas landing project

31. Case Based Reasoning (CBR)
Extract knowledge from a series of cases from the problem domain
Success in Customer Service problems

32. Implementing Knowledge Technologies
Considerations
Data verses knowledge
On WKID scale
Hardware requirements (a la large volume computers)
People and interpretations
Types of people

33. Broad Knowledge Repositories
Usually in document form
Internet is best example
Consider false/odd information
Human internet brokers
Better than technology
Emergence of private intranets

34. Broad Knowledge Repositories
Lotus Notes
Good overall tool, but Web has better outlook for future performance/utility
Steep learning curve
Becomes difficult to use/find relevant knowledge at high volumes

35. Broad Knowledge Repositories
Web based
Intuitive
Multiple formats and media supported
HTML for ease of linking
Thesaurus
Expands results/accuracy in online searches
On keyword searching
Positive: original articles have good knowledge
Negative: potentially inaccurate results

36. Broad Knowledge Repositories
Expert locators
Problems: get ‘experts’ to give themselves expert title
Get experts to post/update bios.

37. Focused Knowledge Environments
Good for expert systems
Few experts/many users
Hard to update
System must remain stable

38. Focused Knowledge Environments
Constraint Based Systems
High levels of data, less quantitative than neural network
Narrow problem domains
Capture and model constraints that govern complex decision making
Usually object oriented
Easy to update

39. Real Time Knowledge Systems
Case Based Reasoning
Looks at past problems to solve current
Used in customer service and support process
Best when one or two experts construct cases and maintain over time
Know when to add, remove, verify cases

40. Longer Term Analysis Systems
Neural Networks
Requires time and knowledge in statistics
Lots of quantitative data and powerful computers
Keeps user in the dark in terms of explaining the results

41. Longer Term Analysis Systems
Data Mining
Large amounts of data to knowledge
Humans needed to:
Initially structure the data
Interpret the data to understand the identified pattern
Make a decision based on knowledge
Generate hypothesis for analysis

42. What Technology Won’t Do
Make things happen by themselves
Enhance process of knowledge use

43. Chapter 8: Knowledge Management Projects in Practice

44. Knowledge Repositories
Knowledge in documents in one place
Types
External knowledge
Structured internal knowledge
Informal internal knowledge
Tacit knowledge
Community based electronic discussion

45. Knowledge Access and Transfer
Focus on linking possessors and prospective users of knowledge
“Yellow Pages”

46. Knowledge Environment
Measure or improve value of knowledge capital
Build awareness and cultural receptivity
Change behavior as it relates to knowledge
Improve the knowledge management process

47. Projects with Multiple Characteristics
Development of an expert network
Development of internal document repositories
Efforts to create new knowledge
Development of “lessons learned” knowledge bases
A high level description of the KM process
Use of evaluation and compensation system to change behavior

48. Success in Knowledge Management Projects
Growth in resources attached to project
Growth in volume of knowledge content and usage
Project is an organizational initiative
Organization wide familiarity of knowledge management
Evidence of fiscal return

49. Factors Leading to Knowledge Project Success
Knowledge oriented culture
Technical and organizational infrastructure
Senior management support
Link to economics or industry value
Modicum of process orientation

50. Factors Leading to Knowledge Project Success
Clarity of vision and language
Nontrivial motivational aids
Some level of knowledge structure
Multiple channels for knowledge transfer

51. Chapter 9: The Pragmatics of Knowledge Management

52. Common Sense About Knowledge Management
Start with high value knowledge
Start with a focused pilot project, let demand drive additions
Work along multiple fronts at once
Don’t put off what gives you the most trouble
Get help throughout the organization ASAP

53. Getting Started in Knowledge Management
Results first, boast later
Start where its needed most
Start where knowledge is a factor
Start outside of your area of expertise
Do just enough to test the concept
Start on multiple fronts

54. Leveraging Existing Approaches
Select the right anchor
Leading with technology
Leading with quality/reengineering/best practices
Leading with organizational learning
Leading with decision making
Leading with accounting

55. Knowledge Management Pitfalls
“If we build it…”
Put the personnel manual online
None dare call it knowledge
Every man a knowledge manager
Justification by faith
Restricted access
Bottoms up

56. Cross Cutting Themes The value of the human being
Recognizing knowledge management
Easy to fail

57. Comments on “Working Knowledge”
Material seems dated
Several examples from small pool of instances
No quantitative figures to back up claims
Overall, authors did a good job of introducing material

58. Additional Insight of “Working Knowledge”
American Way "Thomas H. Davenport and Laurence Prusak provide much more than another treasure map to the knowledge-management fields....[They] offer impressive lodes of actions you can actually start on Monday morning."

59. Questions?