78
People-Focused Knowledge Management
Good Reasoning Matches Knowledge and Information
The goal of KM is to provide the best possible tacit and explicit
knowledge to support and improve knowledgeable, competent deci-
sion making that will result in effective actions to fulfill enterprise
and personal objectives. Without the
systematic and deliberate
development, renewal, and maintenance of knowledge and other IC
assets, personal and enterprise effectiveness will suffer. Decision
making/problem solving is normally followed by implemented
actions and builds on application of knowledge assets matched with
corresponding information assets. Matched knowledge and informa-
tion make
it possible for individuals, and the enterprise as a whole,
to collaborate, understand interactions, make detailed and broad,
effective decisions, and to implement them — all while pursu-
ing goals.
As indicated in the simplified decision-making
example of Figure
3-6, appropriately matched knowledge and information are required
to decide and act effectively. The figure indicates the interdependence
of knowledge and information for effective actions. Pertinent infor-
mation about situations is required to describe conditions correctly,
and competent knowledge is applied to interpret what situations
mean and to decide how to handle them to the best advantage.
Effec-
tive information management is required to provide the descriptions
of the world needed to make sense and understand the situation.
Hence, effective management relies extensively and separately on
both KM and information management.
Figure 3-6 indicates knowledge assets and IC (intellectual capital)
on the left side and information capital on the right side. It illustrates
the separation of knowledge management of intellectual capital and
information management of information capital to emphasize the
need to manage both areas separately
and competently in order to
provide the assets needed for effective actions. The figure indicates
paths of knowledge creation —
new knowledge — that is, dis-
coveries, innovations, and insights that pertain to new and original
situations and conditions. It also identifies how
historic knowledge
can be obtained from knowledge discovery in databases (KDD); that
is, knowledge and relationships that pertain to past, often sufficiently
repetitive experiences that make machine learning possible.
In the enterprise, it is not practical to establish the details of knowl-
edge and information for every important job function. That is
feasible only for important and critical
knowledge functions that
are conducted by many people. Examples of such functions include
ch03.qxd 5/3/04 2:35 PM Page 78