Knowledge
Management
By: Jenny Enderby
and Chris Papin
What is Knowledge Management?
• According to www.brint.com
– KM is “caters to the critical issues of organization
adaptation, survival and competence in face of
increasing discontinuous environmental change…
Essentially, it embodies organizational processes that
seen synergistic combination of data and
information processing capacity of information
technologies, and the creative innovative capacity of
human beings.”
Simplified
• Knowledge
– Refers to a set of
information with which
we have experience
– Usually gained through
work, school or other life
experiences
• Management
– Refers to the ability of an
individual or group to
lead and organize others
in business to produce a
desired outcome
The Knowledge Process
The Knowledge Production
Information Acquisition
Individual and Group Learning
Knowledge Claim Formulation and
Evaluation
The Knowledge Process
Knowledge Integration
Knowledge and Information Broadcasting
Searching and Reviewing
Knowledge Sharing
Teaching
Put it all together…
• Knowledge production and integration compile
together with non-electronic information as well
as electronic information to for a database of
knowledge that is the basis for KM.
Electronic Information
• Data Mining and Data Warehousing
– Two tools that help turn information and data into
useful knowledge
Defined
• Data Warehouse
– A database that stores
larges amounts of
historical business data
– Another way:
Warehousing brings your
data together for analysis
• Data Mining
– The practice of extracting
data from a warehouse in
order to analyze patterns
trends and relationships
– Another way: Mining
sorts through the data you
collected and turns up
interesting and useful
connections
Why Use DM?
• Firms identify patterns
which generate valuable
knowledge for the
company
How Companies Use DM
•
•
•
•
•
•
•
Market Segmentation
Customer Churn
Fraud Detection
Direct Marketing
Interactive Marketing
Market Basket Analysis
Trend Analysis
Fraud Detection Example
Wal-Mart Example
How These Apply to KM
• DM and DW can turn data into useful
knowledge that can give companies a
competitive advantage over their rivals
• DM takes a proactive approach to selling
products to customers rather than a reactive
approach by predicting patterns, trends, and
behaviors.
Why So Difficult
• Implementation of KM programs
• How to estimate the return on KM
• How to store KM data
• Techniques on utilization of the knowledge
Implementation Problems
• Knowledge is Power
– Incentive structures to
share information
• Resistance to Change
– People are reluctant to
change
– 56% of executives say
“changing people’s
behavior” is the most
difficult obstacle
• “Sharing knowledge is an unnatural act. You
can't just stand up and say, 'Thou shalt
share knowledge'—it won't work.”
HUBERT SAINT-ONGE, PRINCIPAL, SAINTONGE ALLIANCE
Returns on KM
• KPMG invests $40 million
• Quality knowledge is the goal
• “Data separates you from the competition”
How to Store New Data
• New techniques to “gather, store, process and
distribute this kind of knowledge”
• It isn’t contained in typical rows or columns
• How do we store the human element?
Utilization of the Knowledge
• Problems with change
• Dept. of Defense and post combat data
• Management must encourage change
Implementation Barrier
• “94% of business executives believe that it
would be possible, through more deliberate
management, to leverage the knowledge existing
in [their organization] to a higher degree”
• BUT….
Implementation Barrier
• “71% believe embedding knowledge in process,
products, and/or services”
• Why not in the people making these processes,
products and/or services?
Implementation Case Study
• E&Y implements a knowledge management
system in an effort to reach $1 billion in
revenues by 1997.
• Process called Future State 97 or FS97.
E&Y
• A major focus was to capture knowledge
• Elected a Chief Knowledge Officer
• Formed a Center for Business Knowledge
E&Y
• People were the key
• Technology was the enabler
• How do you adapt to the change needed?
Similarities
• E&Y had the same difficulties as others
– Implementation was a new venture and risky
– Returns are still not 100% clear, though they are
assumed to be part of the KM program
– How did they obtain and keep the data?
– Problems getting the knowledge distributed
Questions?