People-focused knowledge management

Knowledge
Optimization and
Special Situation
Operating Strategies
Abnormal and Undesired
Operating Situations
Routine and Normal
Operation
Information
Control Algorithms
to
Regulate Process
Operating
History
KDD
Knowledge
Discovery
in Databases
Process Dynamics
and
Characteristics
Information
Knowledge
Figure 3-4
Differences between knowledge and information in process control computers.
Copyright © 1994 by Karl M. Wiig. Reproduced with permission.
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People-Focused Knowledge Management
embedded general knowledge on optimization and control principles
in teaching materials, scientific papers, textbooks, and generic com-
puter software used to generate the control algorithms. That knowl-
edge is assembled by programmers and built into control programs.
The static and dynamic operating history of the process is ana-
lyzed by conventional, but sophisticated, statistical methods or
advanced knowledge discovery in databases (KDD) to obtain data on
selected process characteristics, including process dynamics. This his-
torical knowledge becomes part of the control algorithms embedded
in the control computer. Hence, the process control computer uses
historical knowledge to regulate and control the process as a “busi-
ness-as-usual” process. The computer cannot create new knowledge
or innovate or improvise even when required.
On Information, Knowledge, and Discontinuity
To obtain perspectives on how we can manage knowledge or other
kinds of intellectual capital assets — and appreciate that systematic
KM must be different from how we manage information — we must
define what we mean by the terms information and knowledge.
Our understanding of “knowledge” and “information” is princi-
pally different. At first, it may appear that they are part of a contin-
uum from signals to data to information to knowledge and onwards
and that they are all part of the same domain. However, when exam-
ining the nature of these conceptual constructs and the processes that
create them, we find that undeniable discontinuities make informa-
tion fundamentally different from knowledge. There are other 
differences as well, as will be discussed and indicated in Figure 3-5.
The discontinuity between information and knowledge is caused
by using prior knowledge to create new knowledge from received
information. The process by which we develop new knowledge is
complex. The new inputs are compared to prior knowledge to deter-
mine and hypothesize if they are reasonable and acceptable. The
process uses prior knowledge to make sense of the new information
and, once accepted for inclusion, internalizes the new insights by
linking with prior knowledge. To become knowledge, the new and
accepted insights are internalized by establishing links with already
existing knowledge, links that can range from firmly characterized
relationships to vague associations. Hence, the new knowledge is as
much a function of prior knowledge as it is of received inputs. A dis-
continuity is thus created between the received information inputs
and the resulting new knowledge.
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A
ctions
A
re
Initia
ted by
K
no
wledgeable
P
eople
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