KM Concepts
COR 501
Modules:
Hm
1
2
3
4
5
6
7
8
Contents:
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KM Concepts Module
4: The Knowledge Management View |
Objectives:
You will learn to:
-
identify the difference
between knowledge and information
-
interpret how an organization is like a frog, adapting to its environment
-
differentiate between
artificial knowledge and natural knowledge
KM
Adaptive System
Like
all intellectual disciplines, KM involves the adoption of a definite
perspective. KM researchers view an organization as a complex adaptive
system that receives, stores, retrieves, transforms, and transmits knowledge
to improve its ability to adapt to its environment. These operations of
knowledge are called computations or knowledge
processes., and the view or perspective is called a computational
view or knowledge
processing view of
KM. It is similar to the view held by the related "cognitive
science" that views the mind as a computational or informational
processing organism. Cognitive science is interested in how a single mind processes
knowledge, while KM is interested in how a collective of minds processes
knowledge.
Cognitive science is an interdisciplinary field involving
psychology, linguistics, computer science, philosophy and neuroscience,
providing insights into how to work with multiple fields. It also has many
techniques, tools, models, and theories that are useful in understanding how
a collective processes knowledge. This make the cognitive science/KM
connection very important.
The
computational view provides a mathematical foundation for KM. It allows KM
practitioners to rely on a mathematical foundation to test ideas and
assumptions.
 In the last section, we
introduced you to a way to look at knowledge claims in terms of certain
criteria and considered how the weight of those criteria determines the value and validity
of the knowledge. We can then begin
to differentiate knowledge from information by saying that knowledge is
a
network of rules or set of procedures used to explain or predict phenomena.
These
rules have a useful, predictive, and explanatory power for people.
Knowledge can be broken into two categories: procedural and
declarative.
Procedural
Knowledge
Knowledge
in procedural rules is in its most fundamental form -- it is the
know-how. Work functions such as creating
a proposal or managing a plant are examples of applying this "know-how" type
of procedural knowledge. In procedural knowledge, there is an end goal that requires a series of
steps to accomplish, with the execution of those steps driven by
internal rules. Procedural knowledge can vary in complexity from simple,
such as touching a key on a keyboard, to very complex, such as riding a
bike. Most procedural knowledge is tacit – it has not been,
nor can it be, articulated.
Declarative
Knowledge
Declarative
Knowledge is in the form of statements about a truth -- these are the
know-what rules. An example of declarative knowledge is
knowing who the president of the United
States is or that the world is round.
Effectors,
Detectors, and Tags
A
good illustration of the way organizations use and produce knowledge to
adapt to their environment is the
Holland Model developed by John Holland in 1976; the foundation of
complex adaptive systems (CAS) theory. Imagine a frog in a swamp
waiting for food. He is made up of his detectors, effectors, and tags.
His detectors
are his senses; his effectors are his bodily
organs, such as glands,
muscles, legs, and tongue; and his tags are markings that distinguish
him from all the other frogs in the pond.
An
object that is small, black, and fast crosses the frog's vision (detector).
This information - "small, black" - is processed by the frog and
triggers the action: "Now I'm going to flick my tongue." The frog flicks
because it has stored a set of rules that identifies this object as food.
If
a large, slow, and non-black object is detected, the frog will flee based on
the "knowledge" that this is a dangerous object -- a bird.
The
frog accumulates new knowledge by surviving new experiences.
If
the frog encounters a new object such as something fast, black, and
medium-sized, the frog has no rule to help it make a decision. It has to
make a choice based on its current rule set. Because the object is closer to
a food object (fly) than a predator object (bird), the frog decides to
flick. The object turns out to be a large wasp; the frog is bitten but survives and now
has a new rule to help it avoid those types of wasps.
 The
frog's environment is a key factor, for if the environment changes, all of
these rules could be invalid. For example, if you move the frog from an
American swamp to a South American swamp, a small, black, fast- moving object
could end up being deadly.
Like
our frog, an organization also is a complex adaptive system.
It also can change its rules as experience accumulates. The key is to identify action rules based on "IF--THEN":
if certain
conditions occur, then certain adjustments can be
made. In seeking to adapt to
changing circumstance, the parts of an organization develop ‘rules’ (models)
that anticipate the consequences of responses.
At its simplest, this is a process not much different from Pavlovian
conditioning.
One of the most
valuable types of knowledge is predictive knowledge -- the ability to
look ahead to a certain condition and adjust before that condition occurs.
Also valuable is adaptive knowledge -- the knowledge
that guides an organization to change itself when the economic
environment calls for it.
Soft vs. Hard KM Technology
KM
makes a distinction between soft and hard KM
technology. In a
Soft KM Technology (SKMT),
an alien might land on earth to study humans in a Fortune 500 company.
It is interested in understanding how the firm manages its knowledge. It
observes employees in their natural setting and notices how humans use techniques
and artifacts to produce, transmit, use, store, refine, and acquire
knowledge. In fact, it studies this firm in the same way an anthropologist
studies a tribe in the Amazon. An anthropologist
 might use KM to
study tribal techniques for transmitting knowledge from one generation to
another or for producing a tool or weapon. The alien in the same
manner might observe a manager making a KM decision to hire a man for her
team because of his experience. The alien and the anthropologist will each
see an active KM system as integral parts of the firm or the tribe.
From both viewpoints, KM is soft technology for it is based on cultural
innovations.
A Hard KM Technology (HKMT) is
the related to information and communications technology and is product of a
SKMS. HKMT is
concerned with developing and integrating the hardware and software that can
help humans better manage knowledge and improve human knowledge process
performance.
Cognitive science, organizational psychology,
organizational learning, business management, finance, sociology, economics,
science of science, sociology of science, sociology of knowledge, and
other related social science disciplines are all
 involved
in
the Soft
KM Technologies. HKMT involves computer science with its specialties such as
artificial intelligence, information technology, databases, GroupWare, data
warehouses, document management, etc.
Within
the field of KM, HKMT is actually a subset of SKMT. HKMT is an artifact
created and used by a SKMT. Advances in an Hard KM Technology are extremely important for
advances in KM, for HKMT can be KM’s primary tool in developing
computational models as well as helping manage knowledge and knowledge
processes.
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