What is Knowledge Management?
Prof. Elaine Ferneley +
Prof. Andrew Basden
[email protected]
Objectives
 What is Knowledge Management (KM)?
 What are the driving forces?
 Role of KM in today’s organization
 Knowledge
 Knowledge Management Systems
 Effective Knowledge Management
Prof Elaine Ferneley
Knowledge as Key Resource
 “ Knowledge has become the key
resource, for a nation’s military strength
as well as for its economic strength… is
fundamentally
different
from
the
traditional key resources of the economist
– land, labor, and even capital…we need
systematic work on the quality of
knowledge and the productivity of
knowledge … the performance capacity,
if not the survival, of any organization in
the knowledge society will come
increasingly to depend on those two
factors” [Drucker,1994]
Prof Elaine Ferneley
A world of rapidly growing knowledge ….
>
One week
in 2007
A person’s lifetime
in 18th century
Prof Elaine Ferneley
What is Knowledge Management?
 Knowledge management (KM)
may be defined simply as doing
what is needed to get the most
out of knowledge resources.
 KM focuses on organizing
and making available
important knowledge,
wherever and whenever it
is needed.
 KM is also related to the
concept of intellectual
capital.
Prof Elaine Ferneley
Skryme (1999) Knowledge Management
Definition
Knowledge Management is the explicit and
systematic management of vital knowledge and
associated processes of creation, organization,
diffusion, use and exploitation
 explicit: knowledge is explicitly recognized;
 systematic: too important to be left to chance;
 vital: focus on what is important;
 processes: encourage knowledge creating
environment.
Prof Elaine Ferneley
Why we need Knowledge Management now
(http://www.aiai.ed.ac.uk/~alm/kam.html)
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Marketplaces are increasingly competitive and the rate
of innovation is rising.
Reductions in staffing create a need to replace informal
knowledge with formal methods.
Competitive pressures reduce the size of the work force
that holds valuable business knowledge.
The amount of time available to experience and acquire
knowledge has diminished.
Early retirements and increasing mobility of the work
force lead to loss of knowledge.
Prof Elaine Ferneley
Why we need Knowledge Management now
(http://www.aiai.ed.ac.uk/~alm/kam.html)
 Most of our work is now information based.
 Organizations compete on the basis of knowledge.
 Products and services are increasingly complex, endowing
them with a significant information component.
 The need for life-long learning is an inescapable reality.
 In brief, knowledge and information have become the
medium in which business problems occur. As a result,
managing knowledge represents the primary opportunity
for achieving substantial savings, significant improvements
in human performance, and competitive advantage.
Prof Elaine Ferneley
Knowledge Management Components
Creating
Capturing
Sharing
Capitalising
This course will focus on these
Knowledge Management Components
K
n
o
w
l
e
d
g
e
Knowledge Management
The composite management of:
People
Processes
Information
Information & Communication
Technology
Prof Elaine Ferneley
What are Knowledge Management “Systems” ?
Social/Structural mechanisms (e.g., mentoring
and retreats, etc.) for promoting knowledge
sharing.
Leading-edge information technologies (e.g.,
Web-based conferencing) to support KM
mechanisms.
Knowledge management systems (KMS):
the synergy between social/structural
mechanisms and latest technologies.
Prof Elaine Ferneley
THE KNOWLEDGE ORGANIZATION
Culture
Competition
Create
Technology
Collect
Knowledge
Maintain Organizatio
n
Organize
Intelligence
Refine
Knowledge
Management
Process
Disseminate
Leadership
KM Drivers
 The middle layer
addresses the KM life
cycle
 A knowledge organization
derives knowledge from
customer, product, and
financial knowledge.
Also from financial
practices
 Indicators of knowledge:
thinking actively and
ahead, not passively and
behind
 Using technology to
facilitate knowledge
sharing and innovation
Prof Elaine Ferneley
Data, Information, and Knowledge
 Data: Unorganized and
unprocessed facts; static; a set
of discrete facts about events
 Information: Aggregation of
data that makes decision
making easier
 Knowledge is derived from
information in the same way
information is derived from
data; it is a person’s range of
information
Prof Elaine Ferneley
The DIKW Pyramid
Prof Elaine Ferneley
Some Examples
 Data represents a fact or statement of event without relation to other things.
 Ex: It is raining.
 Information embodies the understanding of a relationship of some sort,
possibly cause and effect.
 Ex: The temperature dropped 15 degrees and then it started raining.
 Knowledge represents a pattern that connects and generally provides a high
level of predictability as to what is described or what will happen next.
 Ex: If the humidity is very high and the temperature drops substantially the
atmospheres is often unlikely to be able to hold the moisture so it rains.
 Wisdom embodies more of an understanding of fundamental principles
embodied within the knowledge that are essentially the basis for the
knowledge being what it is. Wisdom is essentially systemic.
 Ex: It rains because it rains. And this encompasses an understanding of all the
interactions that happen between raining, evaporation, air currents, temperature
gradients, changes, and raining.
Prof Elaine Ferneley
Learning
Learning by experience: a
function of time and talent
Learning by example: more
efficient than learning by
experience
Learning by sharing,
education.
Learning by discovery: explore
a problem area.
Prof Elaine Ferneley
Mechanistic approaches to KM
 Mechanistic approaches to knowledge management are
characterized by the application of technology and
resources to do more of the same better.
 The main assumptions of the mechanistic approach
include:
 Better accessibility to information is a key, including enhanced
methods of access and reuse of documents (hypertext linking,
databases, full-text search, etc.)
 Networking technology in general (especially intranets), and
groupware in particular, will be key solutions.
 In general, technology and sheer volume of information
will make it work.
Prof Elaine Ferneley
Cultural/behavioristic approaches to KM
 Cultural/behavioristic approaches, with substantial roots in process reengineering and change management, tend to view the "knowledge
problem" as a management issue. Technology — though ultimately
essential for managing explicit knowledge resources — is not the
solution. These approaches tend to focus more on innovation and
creativity (the "learning organization") than on leveraging existing
explicit resources or making working knowledge explicit.
 Assumptions of cultural/behaviouristic approaches often include:
 Organizational behaviours and culture need to be changed … dramatically.
In our information-intensive environments, organizations become
dysfunctional relative to business objectives.
 Organizational behaviours and culture can be changed, but traditional
technology and methods of attempting to solve the "knowledge problem"
have reached their limits of effectiveness. A "holistic" view is required.
Theories of behaviour of large-scale systems are often invoked.
 It’s the processes that matter, not the technology.
 Nothing happens or changes unless a manager makes it happen.
Prof Elaine Ferneley
Classification of Knowledge Management
Systems
Knowledge Discovery
Systems
Knowledge Capture
Systems
Knowledge Sharing
Systems
Knowledge Application
Systems
As this course is an IS course we
will focus on these Knowledge Management Technologies
Prof Elaine Ferneley