Working Knowledge: How
Organizations Manage What They
Know
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By: Thomas H. Davenport and Laurence Prusak
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Presented By: Jonathan Sage

Undergraduate Senior in Management Information Systems
Outline
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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
Management
Chapter 5: Knowledge
Transfer
Strategies for Knowledge
Transfer
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Structured verses spontaneous
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MMC and Sematech
Water Coolers and Talk Rooms
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‘Conversations are the most important form
of work’
Human nature
New ideas/old problems in unexpected ways
Water Cooler Limitations
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Stuck on a particular problem
Major breakthrough
Talk Rooms
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Popular in Japan
Expectations for workers
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20 minutes a day
Chat about current work
Virtual Offices
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Discourage informal conversation by nature
Extra effort to make up difference
Socializing
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Popular across cultures
Establish trust
Focus on rich communication medium, rather
than lean
Considerations
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What works in one country isn't universal
Output culture
Knowledge is less valuable when widely
shared
Implementation barriers
Considerations
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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’
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“Real work”/reading example
Ample slack time for workers
Knowledge Fairs and Open
Forums
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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
What kinds of knowledge?
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Explicit
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Captured in procedures, documents and DB
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Easy to obtain
Tacit
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Extensive personal contact
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Partnership, mentoring, apprenticeship.
Include explicit and tacit
How to Capture Knowledge
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Programs
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Japanese use “old-young” model
Mentoring
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Responsible for colleague one level down
Technology
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Network of colleagues willing to meet/share
Videoconferencing
Record stories/experience to CD/video
Culture of Knowledge Transfer
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Frictions
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Trust
Differences
Time
Selfish reasons
Knowledge gap
Intolerance for mistakes
Trust and Common Ground
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Proof that change will bring better results
Language
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Everyday language
Industry jargon
Proximity
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New Zealand/Boston Harbor tunnel engineers
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Tech factor
Status and Reputation
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Status of source
Reputation of source
Why?
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Saves time
Human nature
Knowledge Transfer
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Transfer = Transmission + Absorption (and
Use)
Resistance
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Self esteem
Resistance to change
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US info on fat v. obesity level
Knowing is not the same as doing
Velocity and Viscosity
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Velocity
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Viscosity
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Enhanced by technology
Enhanced by richness of medium
Inverse relationship
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Mobil Oil example
Case Study: 3M
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Encourage new ideas
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All levels of employees
Scotch Tape
Post It Notes
Chapter 6: Knowledge Roles and
Skills
Knowledge-Oriented
Personnel
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Everyone
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Engineers, managers, secretaries
Needs the right corporate culture to flourish
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McKinsey consulting verses Chaparral steel
Knowledge Management
Workers
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“Traditional”
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“New”
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Programmers, system administrators
Extract knowledge from those who have it
Format it
Maintain it
Need both ‘hard and ‘soft’ skills
Knowledge Management
Workers
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Assign existing workers to new tasks
Assign existing teams to become ‘knowledge
managers’
‘Knowledge engineers’
‘Technical communicators’
Managers of Knowledge
Projects
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Skilled in
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Project management
Change management
Technology management
Lots of experience
Open to new ideas
Chief Knowledge Officer
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Build a knowledge culture
Create a knowledge management
infrastructure
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Technical
Human
Make it economically feasible
Chief Knowledge Officer
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Location of the CKO role
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Stand alone
Work with IS
Work with HR
Chief Learning Officer
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Focus on
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Training
Education
Involved in
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Human Resources
Chapter 7: Technologies for
Knowledge Management
Expert Systems and Artificial
Intelligence
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Early predictions
Expert systems
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McDonnell Douglas landing project
Case Based Reasoning (CBR)
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Extract knowledge from a series of cases
from the problem domain
Success in Customer Service problems
Implementing Knowledge
Technologies
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Considerations
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Data verses knowledge
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On WKID scale
Hardware requirements (a la large volume computers)
People and interpretations
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Types of people
Broad Knowledge Repositories
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Usually in document form
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Internet is best example
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Human internet brokers
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Consider false/odd information
Better than technology
Emergence of private intranets
Broad Knowledge Repositories
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Lotus Notes
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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
Broad Knowledge Repositories
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Web based
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Thesaurus
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Intuitive
Multiple formats and media supported
HTML for ease of linking
Expands results/accuracy in online searches
On keyword searching
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Positive: original articles have good knowledge
Negative: potentially inaccurate results
Broad Knowledge Repositories
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Expert locators
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Problems: get ‘experts’ to give themselves expert
title
Get experts to post/update bios.
Focused Knowledge
Environments
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Good for expert systems
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Few experts/many users
Hard to update
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System must remain stable
Focused Knowledge
Environments
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Constraint Based Systems
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High levels of data, less quantitative than neural
network
Narrow problem domains
Capture and model constraints that govern
complex decision making
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Usually object oriented
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Easy to update
Real Time Knowledge Systems
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Case Based Reasoning
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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
Longer Term Analysis Systems
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Neural Networks
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Requires time and knowledge in statistics
Lots of quantitative data and powerful computers
Keeps user in the dark in terms of explaining the
results
Longer Term Analysis Systems
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Data Mining
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Large amounts of data to knowledge
Humans needed to:
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Initially structure the data
Interpret the data to understand the identified pattern
Make a decision based on knowledge
Generate hypothesis for analysis
What Technology Won’t Do
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Make things happen by themselves
Enhance process of knowledge use
Chapter 8: Knowledge
Management Projects in Practice
Knowledge Repositories
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Knowledge in documents in one place
Types
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External knowledge
Structured internal knowledge
Informal internal knowledge
Tacit knowledge
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Community based electronic discussion
Knowledge Access and
Transfer
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Focus on linking possessors and prospective
users of knowledge
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“Yellow Pages”
Knowledge Environment
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Measure or improve value of knowledge
capital
Build awareness and cultural receptivity
Change behavior as it relates to knowledge
Improve the knowledge management process
Projects with Multiple
Characteristics
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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
Success in Knowledge
Management Projects
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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
Factors Leading to Knowledge
Project Success
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Knowledge oriented culture
Technical and organizational infrastructure
Senior management support
Link to economics or industry value
Modicum of process orientation
Factors Leading to Knowledge
Project Success
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Clarity of vision and language
Nontrivial motivational aids
Some level of knowledge structure
Multiple channels for knowledge transfer
Chapter 9: The Pragmatics of
Knowledge Management
Common Sense About
Knowledge Management
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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
Getting Started in Knowledge
Management
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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
Leveraging Existing
Approaches
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Select the right anchor
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Leading with technology
Leading with quality/reengineering/best practices
Leading with organizational learning
Leading with decision making
Leading with accounting
Knowledge Management
Pitfalls
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“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
Cross Cutting Themes
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The value of the human being
Recognizing knowledge management
Easy to fail
Comments on “Working
Knowledge”
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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
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."
Questions?