DISTINGUISHING KNOWLEDGE FROM INFORMATION
A Prerequisite for Elaborating KM Initiative Strategy
Michel Grundstein
MG Conseil, 4 rue Anquetil, 94130 Nogent sur Marne, France
Paris Dauphine University, Place du Maréchal De Lattre de Tassigny 75775 Paris, France
Keywords: Information, Knowledge, Knowledge Management (KM), Individual’s tacit knowledge, Commensurability
of Individual’s Interpretative Frameworks, KM initiative strategy, Enterprise’s Information and Knowledge
System (EIKS).
Abstract: Although the technological approach of Knowledge Management (KM) is greatly shared, without
awareness, when elaborating KM initiative’s strategy, we can confuse the notions of information and
knowledge, and disregard the importance of individual’s tacit knowledge used in action. Therefore, to avoid
misunderstanding during the strategic orientation phase of a general KM initiative development, it is
fundamental to clearly distinguish the notion of information from the notion of knowledge. Further, we
insist on the importance to integrate the individual as a component of the Enterprise’s Information and
Knowledge System (EIKS). In this paper, we argue that Knowledge cannot be considered as an object such
as data are in digital information systems. Consequently, we propose an empirical model enabling to
distinguish the notions of information and knowledge. This model shows the role of individual’s
interpretative frameworks and tacit knowledge, establishing a discontinuity between information and
knowledge. This pragmatic vision needs thinking about the architecture of an Enterprise’s Information and
Knowledge System (EIKS), which must be a basis of discussion during the strategic orientation phase of a
KM initiative.
1 INTRODUCTION
Very often, Knowledge Management (KM) is
considered from a technological viewpoint. That
practice induces to consider knowledge as an object
independent of individuals. In that way, as
information, knowledge can be acquired, processed,
stocked, transmitted and restored. However, we
argue that as soon as knowledge is explicit,
formalized and codified in a Digital Information
System (DIS), it becomes information. We call that
information “information source of knowledge for
somebody.” Effectively, individual’s tacit
knowledge is involved to enable the user to give a
sense to that information in order to act. As noticed
by Wiig (2008) “Without knowledge, intelligent and
effective behaviour – the ability to interpret, assess,
understand, innovate, decide, act, and monitor – will
not be possible even if the best information is made
available (p.2).” However, if information can be
acquired, processed, stocked, transmitted and
restored, such is not the case for individual’s tacit
knowledge used in action.
Although the technological approach is greatly
shared, without awareness, when elaborating KM
initiative’s strategy, we can confuse the notions of
information and knowledge, and disregard the
importance of individual’s tacit knowledge used in
action. Therefore, to avoid misunderstanding during
the strategic orientation phase of a Knowledge
Management initiative, it is fundamental to clearly
distinguish the notion of information from the notion
of knowledge. Further, we insist on the importance
to integrate the individual as a component of the
Enterprise’s Information and Knowledge System
(EIKS).
In this paper, after having put down background
theory and assumptions, we propose an empirical
model enabling to distinguish the notions of
information and knowledge. This model shows the
role of individual’s interpretative frameworks and
tacit knowledge, establishing a discontinuity
between information and knowledge. This pragmatic
135
Grundstein M. (2009).
DISTINGUISHING KNOWLEDGE FROM INFORMATION - A Prerequisite for Elaborating KM Initiative Strategy.
In Proceedings of the International Conference on Knowledge Management and Information Sharing, pages 135-140
DOI: 10.5220/0002289001350140
Copyright
c
SciTePress
vision needs thinking about the architecture of an
Enterprise’s Information and Knowledge System
(EIKS), which must be a basis of discussion during
the KM initiative’s strategic orientations phase.
2 BACKGROUND THEORY AND
ASSUMPTIONS
2.1 Creation of Individual’s Tacit
Knowledge
Our approach is built upon the assumption
emphasized by Tsuchiya (1993)
concerning
knowledge creation ability. He states, “Although
terms ‘datum’, ‘information’, and ‘knowledge’ are
often used interchangeably, there exists a clear
distinction among them. When datum is sense-given
through interpretative framework, it becomes
information, and when information is sense-read
through interpretative framework, it becomes
knowledge (p.88)”. Figure 1 represents our own
interpretation of Tsuchiya’s assumption.
Figure 1: Creation of individual's tacit knowledge.
In other words, we can say that tacit knowledge
that resides in our brain results from the sense given,
through our interpretative frameworks, to data that
we perceive among the information transmitted to
us. Or rather, Knowledge exists in the interaction
between an Interpretative Framework (incorporated
within the head of an individual, or embedded into
an artefact), and data.
Consequently, we postulate that knowledge is
not an object processed independently of the person
who has to act. So, we can say that formalized and
codified knowledge, that are independent from
individual, are not more than information.
Furthermore, as emphasized by Haeckel (2000) we
must discern “the knowledge of knower and the
codification of that knowledge (p. 295).”
2.2 Definition of Knowledge
Management (KM)
In 1990, the Initiative for Managing Knowledge
Assets (IMKA, 1990) was initiated by a few
companies (Carnegie Group, Inc., Digital Equipment
Corporation, Ford Motor Company, Texas
Instruments, Inc., and US WEST Advanced
Technologies, Inc.). They defined for the first time
the notion of knowledge assets: “Knowledge assets
are those assets that are primary in the minds of
company's employees. They include design
experience, engineering skills, financial analysis
skills, and competitive knowledge.”
Gradually, numerous research works were
carried out, enterprise’s KM initiatives were
deployed, and an abundant literature enriched the
domain of Knowledge Management. So that the
concept of KM highlighted a broad range of topics
and became a fuzzy concept taking as many senses
as people speaking about it. For instance, in his
editorial preface, untitled “What is Knowledge
Management?” Jennex (2005) has gathered some
authors’ definitions that show that there is no
common evidence about what KM is. Regan (2007)
consolidates this observation. She states, “This lack
of agreement on a definition of knowledge
management seems atypical for an emerging
discipline that traces its roots back at least two
decades. Even the most recent textbooks in the field
spend an entire chapter just explaining what
knowledge management is and what it is not, and
provide an entire page of definitions.”
The introduction to KMIS 2009 conference
shows the same understanding: “There are several
perspectives on KM, but all share the same core
components, namely: People, Processes and
Technology. Some take a techno-centric focus, in
order to enhance knowledge integration and
creation; some take an organizational focus, in order
to optimize organization design and workflows;
some take an ecological focus, where the important
aspects are related to people interaction, knowledge
and environmental factors as a complex adaptive
system similar to a natural ecosystem.”
We can add that most of time, KM is considered
from a technological viewpoint. For example, let’s
consider the European Project Team in charge to
elaborate The European Guide to Good Practice in
Knowledge Management on behalf of the European
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136
Committee for Standardization Workshop on
Knowledge Management. This Workshop was
running from September 2002 till September 2003.
The Project Team has collected, categorized and
analyzed more than 140 KM Frameworks. It may be
noted that this work has produced a high-quality
practical outcome that can be used as a reference
point to achieve a good understanding of KM (CEN-
1, 2004). Nevertheless, as contributors to this
project, we observed that few of them were “people-
focused” as highlighted by Wiig (2004). We can
underline the predominant positivist paradigm and
the technological approach of KM that have inspired
the project team. As a result, the authors consider a
system of interrelated objects that can be described
independently of individual. That has induced them
to consider the knowledge as an object, and so to
disregard the importance of people.
Furthermore we distinguished two main
approaches underlying KM: (i) a technological
approach that answers a demand of solutions based
on the technologies of information and
communication (ICT); and (ii) a managerial and
sociological approach that integrates knowledge as
resources contributing to the implementation of the
strategic vision of the company. On the one hand,
the technological approach leads to reduce
knowledge to codified knowledge that is no more
than information. In that case KM initiatives can be
managed in the same way than Information System
projects. On the other hand, the managerial and
sociological approach that integrates knowledge as a
resource is centered on the core business processes,
and people.
In our research group, relying on Tsuchiya’s
works (Tsuchiya, 1993) we argue that knowledge is
dependent of the individual’s interpretative
framework, and the context of his action.
Consequently, knowledge resides primarily in the
heads of individuals, and in the social interactions of
these individuals. It cannot be consider as an object
such as data are in digital information systems.
Thus, it appears that KM addresses activities, which
utilize and create knowledge more than knowledge
by itself. With regard to this question, since 2001,
our group of research has adopted the following
definition of KM (Grundstein and Rosenthal-
Sabroux, 2003): “KM is the management of the
activities and the processes that enhance the
utilization and the creation of knowledge within an
organization, according to two strongly interlinked
goals, and their underlying economic and strategic
dimensions, organizational dimensions, socio-
cultural dimensions, and technological dimensions:
(i) a patrimony goal, and (ii) a sustainable
innovation goal (p.980).” The patrimony goal has to
do with the preservation of knowledge, their reuse
and their actualization; it is a static goal. The
sustainable innovation goal is more dynamic. It is
concerned with organizational learning that is
creation and integration of knowledge at the
organizational level.
3 DISTINGUISHING THE
NOTIONS OF INFORMATION
AND KNOWLEDGE
Numerous authors analyzed the notions of data,
information and knowledge. Let us quote notably
Davenport and Prusak (1998, pp.1-6)), Sena and
Shani (1999), Takeuchi, and Nonaka, (2000), Amin,
and Cohendet, (2004, pp. 17-30), Laudon and
Laudon, (2006, p. 416). Besides, Snowden (2000,)
makes the following synthesis: “The developing
practice of knowledge management has seen two
different approaches to definition; one arises from
information management and sees knowledge as
some higher-level order of information, often
expressed as a triangle progressing from data,
through information and knowledge, to the apex of
wisdom. Knowledge here is seen as a thing or entity
that can be managed and distributed through
advanced use of technology…The second approach
sees the problem from a sociological basis. These
definitions see knowledge as a human capability to
act (pp. 241-242).”
Here, one must think “Wisdom” as the level of
the “collective, application of knowledge in action”
(Sena 1999, p.8-4), or as “the collective and
individual experience of applying knowledge to the
solution of problems (Laudon and Laudon 2006, p.
416).”
In the following paragraphs, we clarify our
approach.
3.1 Commensurability of Interpretative
Frameworks and Individual
Sense-Making
Tsuchiya emphases how organizational knowledge
is created through dialogue, and highlighted how
“commensurability” of the interpretative
frameworks of the organization’s members is
indispensable for an organization to create
organizational knowledge for decision and action.
Here, commensurability is the common space of the
DISTINGUISHING KNOWLEDGE FROM INFORMATION - A Prerequisite for Elaborating KM Initiative Strategy
137
set of interpretative frameworks of each member
(e.g. cognitive models or mental models directly
forged by education, experience, beliefs, and value
systems). Tsuchiya states “It is important to clearly
distinguish between sharing information and sharing
knowledge. Information becomes knowledge only
when it is sense-read through the interpretative
framework of the receiver. Any information
inconsistent with his interpretative framework is not
perceived in most cases. Therefore,
commensurability of interpretative frameworks of
members is indispensable for individual knowledge
to be shared (p. 89).”
Therefore, we consider information as
knowledge when members having a large
commensurability of their set of interpretative
frameworks commonly understand it. In that case,
we call it “information source of knowledge for
someone.” Such is the case for members having the
same technical or scientific education, or members
having the same business culture. In these cases,
formalized and codified knowledge make the same
sense for each member. However, one must take into
account that interpretative frameworks evolve in a
dynamic way: they are not rigid mindsets.
Especially, when considering that, as time is going
on, contexts and situations evolve. Thus, the
contribution of scientific results, techniques and new
methods, the influence of young generations being
born with Web (Y generation or Digital Native), the
impact of identity crisis and multiple cultures,
modify the interpretative frameworks, and create a
gap between individuals’ commensurability of
interpretative frameworks.
3.2 From Data to Individual’s Tacit
Knowledge
Let’s consider two individuals P
1
and P
2
acting in
different contexts and situations, at different points
in time (Fig. 2).
While P
1
’s previous knowledge is necessary for
elaborating information from data gathered and
filtered in the present time, once created this
information becomes a frozen object. This static
object is independent from P
1
, and time. Then, at
another time, when this information is captured by
P
2
, only some data contained in the information are
selected and interpreted, taking sense for P
2
. In that
way, the P
2
’s tacit knowledge is modified.
Figure 2: From Data…to Individual’s Tacit Knowledge.
In a first step, P
1
, in his context and situation,
gathers a set of data outside him. Then, during a
sense-reading process that depends of his pre-
existing interpretative frameworks activated
depending of his context, his situation, and his
intentions, he selects some of these data that take
sense for him. In the same time, a sense-giving
process using P
1
’s previous tacit knowledge enables
P
1
to aggregate, and organize selected data he
perceived, into information. It is this information
that is passed on by the individuals, or by means of
the DIS where it is stored, treated and transmitted as
a stream of digital data. During this process, P
1
’s
pre-existing interpretative frameworks are not
changing; previous tacit knowledge can be
reorganized and modified into new tacit knowledge.
In a second step, this information is captured by
P
2
. According to his own context and situation, P
2
,
during a process of sense-reading, interprets this
information filtering data through his pre-existing
interpretative frameworks activated depending of his
context, his situation, and his intentions. In the same
time a sense-giving process that uses P
2
’s previous
knowledge operates, and engenders new tacit
knowledge. That’s the way that changes P
2
’s pre-
existing framework and enriches P
2
’s previous tacit
knowledge enabling P
2
to understand his situation,
identify a problem, find a solution, decide, and act.
The results of these processes are modified
interpretative frameworks, and new tacit knowledge.
The process of transformation of data into
knowledge is a process of construction of
knowledge. Created knowledge, can be very
different from one individual to another when the
commensurability of their interpretative frameworks
is small, whatever are the causes of it. There are
large risks that the same information takes different
senses for each of them, and consequently generates
KMIS 2009 - International Conference on Knowledge Management and Information Sharing
138
a construction of different tacit knowledge in the
head of the decision process stakeholders. Unlike the
information, knowledge is dynamic. Once
constructed it cannot be considered as an object
independent from the individual who built it, or the
individual who appropriates it to make a decision
and to act.
As a result one can understand the importance to
clearly distinguish static factual information, which
allows describing the context and the situation that
raise a problem, from the knowledge of the
individual who processes this information to learn
and get knowledge he needs to carry out his tasks.
To answer this issue, distinguishing information
from knowledge leads to conceive what we call
Enterprise’s Information and Knowledge Systems
(EIKS).
4 ENTERPRISE’S
INFORMATION AND
KNOWLEDGE SYSTEM (EIKS)
The enterprise’s information and knowledge system
(EIKS) consists mainly in a set of individuals and
digital information systems. EIKS rests on a socio-
technical fabric, which consists of individuals in
interaction among them, with machines, and with the
very EIKS. It includes (Fig. 3):
A Digital Information Systems (DIS),
which are artificial systems, the artifacts
designed from information and
communication technologies (ICT)
An information system constituted by
individuals who, in a given context, are
processors of data to which they give a
sense under the shape of information. This
information, depending of the case, is
passed on, remembered, treated, and
diffused by them or by the DIS.
A knowledge system, consisting of tacit
knowledge embodied by the individuals,
and of explicit knowledge formalized and
codified on any shape of supports
(documents, video, photo, digitized or not).
Under certain conditions, digitized
knowledge is susceptible to be memorized,
processed and spread with the DIS. In that
case, knowledge is no more than
information.
Figure 3: The Enterprise’ s Information and Knowledge
System (EIKS).
If “Technology provides the possibility of
making information available across time and space”
(Kautz and Kjaergaard 2008, p. 49 ) we always have
to keep in mind, paraphrasing these authors, “the
role of individual in the knowledge sharing process,
but we do also pay attention to how individual use
technology to share knowledge (p. 43).” So,
considering EIKS, we insist on the importance to
integrate the individual as a component of the
system (Grundstein, 2007, pp. 243-247). Three
natures of information must be distinguished: the
Mainstream-Data, the Source-of-Knowledge-Data,
and the Shared-Data (Grundstein and Rosenthal-
Sabroux, 2003, pp. 980-981). Among the tools, the
Information and Knowledge Portals supply a global
access to the information, and can meet the needs of
Knowledge Sharing. In that case, the functional
software and the tools answering the aim of KM are
integrated into the DIS.
5 PROSPECTS
When launching a KM initiative, the Strategic
Orientation Phase is crucial and can avoid to get KM
resources go unused as noticed by Stewart (Stewart,
2002) “One flaw in knowledge management is that it
often neglects to ask what knowledge to manage and
to what end (p.117).” We should add that KM is
often oriented towards Information and
Communication Technologies (ICT) that leads
confusing notions of information and knowledge,
and misunderstanding the goals: do we have to
develop an Information System or do we have to
implement a KM System? Therefore, the Strategic
Orientation Phase must help to build a general KM
vision that makes a clear distinction between
DISTINGUISHING KNOWLEDGE FROM INFORMATION - A Prerequisite for Elaborating KM Initiative Strategy
139
technology as a support to share individual’s tacit
knowledge, and technology as a means to collect,
store, and distribute explicit and codified knowledge
that is no more than information (see § 2.1).
Distinguishing Information from Knowledge
open our mind on a different view of information
systems that leads to conceive what we call
Enterprise’s Information and Knowledge Systems
(EIKS). These systems include individuals and are
based on Digital Information System (DIS). This
pragmatic vision needs thinking about the
architecture of an Enterprise’s Information and
Knowledge System (EIKS), which must be a basis
of discussion during the strategic orientation phase
of a General KM Initiative.
ACKNOWLEDGEMENTS
I am grateful to Camille Rosenthal Sabroux and
Virginie Goasdoue whose continuous contribution
and relevant questioning encouraged me to clarify
and improve the model presented in this paper.
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