Strategic Importance of Knowledge Management Essay

This essay has a total of 6553 words and 37 pages.

Strategic Importance of Knowledge Management


Today the world has more and more of free flow of information leading to transfer of
knowledge from a person or an organization to others. Whereas this invariably leads to
faster development, it also impacts the competitive advantage held by the innovators of
processes or technology. It has therefore become strategically important for one and all
in business to understand the knowledge, processes and controls to effectively manage the

system of sharing and transferring the information in the most beneficial fashion.

This paper dwells upon definition, types, scope, technology and modeling of knowledge and
Knowledge Management while examining its strategic importance for retaining the
competitive advantage by the organizations.

What is knowledge?
Plato first defined the concept of knowledge as ‘‘justified true belief'' in his Meno,
Phaedo and Theaetetus. Although not very accurate in terms of logic, this definition has
been predominant in Western philosophy (Nonaka and Takeuchi, 1995). Davenport et al.
(1998) define knowledge as ''information combined with experience, context, interpretation
and reflection''.

The terms ‘‘knowledge'' and ‘‘information'' are often used inter-changeably in the
literature and praxis but a distinction is helpful. The chain of knowledge flow is
data-information-knowledge. Information is data to which meaning has been added by being
categorized, classified, corrected, and condensed. Information and experience, key
components of definitions of knowledge, are put into categories through the process of
labeling with abstract symbols. This allows the process of synthesis to occur more
efficiently than when dealing with masses of individual bits of information. Information
coded into symbols to make it "knowledge" may be stored both inside and outside the
individuals. Thus, knowledge may be stored within a person in his mind or outside the
person in books, manuscripts, pictures, and audio and videotapes or discs. However, while
only the individual himself may retrieve knowledge stored within his mind, knowledge
stored outside can be retrieved by anybody familiar with the storage systems.

In organizations, knowledge is often embedded not only in documents and presentations but
also in "organizational routines, processes, practices, and norms," and through
person-to-person contacts. Even the simplest information about the environment requires
the use of rules for interpreting it. This means that for information to become knowledge,
people make interpretations, apply rules, and create knowledge. "People with different
values ‘see' different things in the same situation" and organize information so as to
create different kinds of knowledge (Davenport and Prusak, 1998).

Types of Knowledge
Systemic knowledge
Systemic knowledge is a sort of knowing how we know. Systemic knowledge is both a process
and a product. As a process it is expressed by Maturana and Varela (1987) as - "reflection
is a process of knowing how we know". As a product it is knowledge on how we think.
Systemic knowledge has bearing on the perspectives of individuals, i.e. what is seen and
how this is perceived. In this way, systemic knowledge directly influences the people's
perception as to what type of explicit knowledge is relevant and meaningful for the
organization. The more uniform this perspective is among the most important actors of the
organization, the more influential this perspective will be as to what knowledge type
(e.g. explicit versus tacit) is critical to the competitive position of the organization.

Explicit knowledge
Explicit knowledge is the part of the knowledge base that can be easily communicated to
others as information. Explicit knowledge involves knowing facts (Sveiby, 1997). Explicit
knowledge can be objective and inter-subjective. Bunge (1983) defines objective knowledge
in the following way: "Let p be a piece of explicit knowledge. Then p is objective if and
only if (a) p is public (intersubjective) in some society, and (b) p is testable
(checkable) either conceptually or empirically".

Tacit knowledge
Tacit knowledge (Polanyi, 1962) is a form of skill, ability or ‘‘techne'', i.e. know
how, which is difficult to communicate to others as information, but "much of what Michael
Polanyi has called tacit knowledge is expressible - in so far as it is expressible at all
- in metaphor" (Nisbet, 1969). In the context of tacit knowledge, Drucker (1993) opines,
"the only way to learn techne was through apprenticeship and experience". David and Foray
(1995) also stress that no knowledge is tacit by nature, what has to be done is to create
incentives to make tacit knowledge communicable. Polanyi (1962) says that this sort of
knowledge also can be regarded as connoisseurship. Such knowledge is deeply rooted in
employee experience or in company culture making it more valuable in sustaining the
competitive advantage because it is much harder for competitors to imitate.

Hidden knowledge
Hidden knowledge influences the way we think and act, as a sort of personal paradigm, or
the technical-economic paradigm in the business world, a trajectory which leads our way of
thinking and acting when expressing and interpreting, among other things, new ideas.
Hidden knowledge organizes the development of mental models, the nature of the abstraction
we make, the choice of variables, problems or phenomena, the facts we choose to focus on,
our underlying metaphysical positions, our theoretical ‘‘tastes'' etc. Support for the
concept ‘‘hidden knowledge'' is found in Schutz' (1990, Vols. 1 and 2) ‘‘epoche''

Relationship knowledge
Relationship knowledge "involves the social capability to establish relationships to
specialized groups in order to draw upon their expertise" (Lundvall, 1995). In a time
where turbulence, change and hypercompetition, are accelerating it is crucial for
organizational survival to invest in relationship knowledge. The type of relationship
knowledge which is relatively easy to communicate, may be classified as explicit

Knowledge management [KM]
A business discipline called Knowledge Management emerged that identifies captures,
organizes, and processes information to create knowledge. Knowledge Management is a
conscious effort to get the right knowledge to the right people at the right time so that
people can share and put information into action in ways that improve an organization's
performance. Knowledge is crucial to the operation of businesses, to predicting outcomes
of events, to understanding how and why things function, and to appreciating things that
are happening around us.

With the rising importance of knowledge in our global economy, knowledge management has
gained worldwide attention. Individuals including Sveiby (1997), Stewart (1997), Davenport
and Prusak (1998), Allee (1997) and Nonaka (1991) have worked in the area to discover the
opportunities, practices and benefits of knowledge management. Companies such as Buckman
Laboratories, Dow Chemicals, Skandia, Hewlett-Packard, Celemi, and IBM to name a few, have
made use of knowledge management in order to more effectively manage and utilize the
knowledge and expertise in their organizations.

A number of disciplines have influenced the field of KM thinking - the important ones
being philosophy (in defining knowledge); cognitive science (in understanding knowledge
workers); social science (understanding motivation, people, interactions, culture,
environment); management science (optimizing operations and integrating them within the
enterprise); information science (building knowledge-related capabilities); knowledge
engineering (eliciting and codifying knowledge); artificial intelligence (automating
routine and knowledge-intensive work) and economics (determining priorities). This
naturally leads to a host of working definitions of KM.

Some of the definitions of KM are:
• "Conscious strategy of getting the right knowledge to the right people at the
right time and helping people share and put information into action in ways that strive to
improve organizational performance'' (O'Dell and Jackson, 1998).

• ‘‘Formalization of, and access to, experience, knowledge and expertise that
create new capabilities, enable superior performance, encourage innovation and enhance
customer value'' (Beckman, 1997).

• ‘‘Collection of processes that govern the creation, dissemination and
utilization of knowledge to fulfill organizational objectives'' (Murray and Myers, 1997).

• Knowledge management is the process of creating, capturing, and using knowledge to
enhance organizational performance (Bassie, 1997).

• Knowledge management is the management of the information, knowledge and
experience available to an organization, "its creation, capture, storage, availability and
utilization" in order that organizational activities build on what is already known and
extend it further (Mayo, 1998).

• Knowledge management is the process of capturing a company's collective expertise
wherever it resides, and distributing it to wherever it can help produce the biggest
payoffs (Blake, 1998).

• Knowledge management is about encouraging individuals to communicate their
knowledge by creating environments and systems for capturing, organizing, and sharing
knowledge throughout the company (Martinez, 1998).

• Beckman (1999) asserts that KM concerns the formalization of and access to
experience, knowledge, and expertise that create new capabilities, enable superior
performance, encourage innovation, and enhance customer value.

• Coleman (1999) defines KM as an umbrella term for a wide variety of interdependent
and interlocking functions, including knowledge creation; knowledge valuation and metrics;
knowledge mapping and indexing; knowledge transport, storage, and distribution; and
knowledge sharing.

Most of the definitions imply that KM can incorporate any or all of the following four
components: business processes, information technologies, knowledge repositories and
individual behaviors (Eschenfelder et al., 1998). A consistent theme in all espoused
definitions of KM is that it provides a framework that builds on past experiences and
creates new mechanisms for exchanging and creating knowledge.

Influence of Organizational Relationships and Processes on KM
Knowledge management may be severely affected by the relationships and processes of the
organization. Relationships are the arrangements of a system's parts at a moment in
three-dimensional space. Processes are the dynamic changes of a system over time. For
knowledge to be useful in the future, it must be stored in some memory system. Ways of
doing things or procedures are maintained and stored within routines that different people
perform in the organization. Thus, organizational processes not only record knowledge, but
also shape the way in which knowledge is retrieved for use in the future.

Different Models of KM
Different practitioners have given different models for KM. Some of the models are - the
cognitive model of KM (Swan and Newell, 2000), the network, community (Swan and Newell,
2000), philosophical, and quantum. Each model treats knowledge in its own particular way;
thus, has different KM approaches (Swan and Newell, 2000).

Philosophy-based model of KM
The philosophical model is concerned with what constitutes knowledge. Its main concern is
how one gathers information about social and organizational reality and is focused on
objectives, concepts, with the relationship of knowledge to other notions such as
certainty, belief justification, causation, doubt and revocability.

The philosophical model of KM is an attempt to think deeper on how one thinks and acts by
posing deep-knowledge questions about knowledge within organizations (Murray, 2000). The
model provides a high-level strategic overview and creates a valuable framework of
understanding, which informs later knowledge initiatives. This model is built along the
lines of Polanyi's (1966) argument that ‘‘We can know more than we can tell and we can
tell nothing without relying upon our awareness of things we may not be able to tell''.

The philosophy-based KM model is based on interactive dialogues within a strategic
context. Numbers of international research studies conducted by the Cranfield School of
Management (Murray and Myers, 1997; Kakabadse and Kakabadse, 1999) show that the
philosophy-based model of KM is practiced by top teams in learning organizations; where
the environment is conducive to an open, quality dialogue.

The model holds that KM need not be technology intensive and should not be technology
driven - rather, it is actor intensive and actor centered. It is based on the Socratic
definition of knowledge and a search for the highest knowledge - wisdom (Plato, 1953).

Cognitive model of KM
Leading management and organizational theorists have suggested that for an organization to
remain competitive it must effectively and efficiently create, locate, capture and share
knowledge and expertise to solve problems and exploit opportunities (Winter, 1987;
Drucker, 1991; Kougot and Zander, 1992). The model is deeply embedded in positivistic
science as the tool for understanding a mechanical universe driven by single cause effect
relationships (Skolimowski, 1994). For knowledge-based industries, knowledge itself is the
commodity traded (Gibbons et al., 2000).

For the cognitive model of KM, knowledge is an asset; it is something that needs to be
accounted for and a number of efforts are being made to develop procedures for measuring
it (Sveiby, 1997; Swan and Newell, 2000). Knowledge is seen as something that needs to be
managed (Dodgson, 2000). This model builds particularly on definition of knowledge by
Schank and Abelson (1977), Holliday and Chandler (1986), and Edvinsson and Malone (1997).

Variations of the cognitive model of KM are practiced by most organizations with formal KM
processes in place. Some prominent cognitive models of KM are the SECI model (Nonaka and
Takeuchi, 1995; Nonaka and Konno, 1998); state of knowledge (Earl, 1998), organization
knowledge networks model (Carayannis, 1999), pillars and functions of knowledge management
model of intellectual capital (Wiig, 1993; Edvinsson and Malone, 1997); intellectual
capital management model (Van Buren, 1999); and the knowledge management model based on
cognitive science, semiotics and epistemological pragmatism (Snowden, 1998).

Cognitive models of KM are integrative or controlling in approach, operating predominately
at the operational level (McKinlay, 2000). The focus of many cognitive models is on
repetitive action, replication and standardization or routinization of knowledge and its
replication (Swan and Newell, 2000). An important point to be noted is that this model can
become an obstacle for change and new knowledge as changing static routines is difficult.
In today's environment of rapid change and technological discontinuity, even knowledge and
expertise that can be shared often and quickly becomes obsolete (Zack, 1999). Establishing
a dynamic balance is the fine line between exploration and exploitation proposed by the
SECI model (Nonaka and Konno, 1998) and has been achieved only by a few organizations.

Network model of KM
The networking perspectives of KM emerge parallel with the theories of the network
organization and focus on acquisition, sharing and knowledge transfers. Network
organizations are thought of to be characterized by horizontal patterns of exchange,
interdependent flow of resources and reciprocal lines of communication (Powell, 1990).
From the network perspective, the idea of knowledge acquisition and sharing is seen as a
primary lever for organizational learning in order for an organization to choose and adopt
new practices where relevant (Everett, 1995). This model builds on conception of knowledge
as defined by Samuel Johnson (quoted in Boswell, 1979), and Frantzich (1983) where the
important knowledge concerned resides within networks of actors.

With the proliferation of Web-based technology, IT-based tools gained increased importance
in the network perspective of KM as a facilitating tool for maintaining and building
networks for knowledge sharing and transfer (Hayes, 2001; Swan and Newell, 2000). Network
models of KM are integrative in approach as they try to develop networks structures and a
way to control flow of information. It has the strategic intention of tapping across
levels within organization and industry (Swan and Newell, 2000).

Community of practice model of KM
Perhaps one of the oldest models of KM, community of practice (CP), is receiving revival
and recognition within contemporary organizations. The CP model of KM builds on the
sociological and historical perspective. Kuhn (1970) argued that scientific knowledge is
‘‘intrinsically the common property of a group or else nothing at all''. This
assertion was supported and expanded among others by Rorty, 1979; Barabas, 1990. Barabas
(1990) opines that ‘‘there is no universal foundation for knowledge, only the
agreement and consensus of the community''. Knowledge has been traditionally passed from
generation to generation by means of stories. Storytelling is a well-known technique for
conveying complicated meaning in a simplified format to handle complex situations.

The term ‘‘community of practice'' was coined in the context of studies of traditional
apprenticeship (Lave and Wenger, 1991). A CP model is widely distributed and can be found
at work, at home or amongst recreational activities. The model proposes the coming
together of members, relationships of mutual engagement that bind members together into a
social entity and the shared repertoire of communal resources that members have developed
over time through mutual engagement (Wagner, 2000). In organizations, community of
practice arises as people address recurring sets of problems together. Since membership is
based on participation rather than on official status, community of practice is not bound
by organizational affiliation. Models of community of practice have a variety of relations
to the organization in which they exist, ranging from completely unrecognized to largely
institutionalized (Wagner, 2000). The CP model builds on the concept of knowledge defined
by Heron (1996) and Nonaka and Takeuchi (1995) that holds that one cannot separate
knowledge from practice. CP models can retain knowledge in ‘‘living'' ways rather than
in the form of a database or manual.

Quantum model of KM
The quantum perspective of KM assumes that current information and communication
technology will fundamentally change when built using quantum principles. Quantum
computing will be able to make rational assessment of an almost infinite complexity and
will provide knowledge that will largely make sense to people (Tissen et al., 2000). In
order to cope with new levels of complexity and decision-making, actors will not just need
knowledge but meaningful knowledge that is not fact driven, but scenario driven (Tissen et
al., 2000). Quantum models of KM are highly dependent on quantum computing and assume that
most intellectual work will be performed by IT-based tools which will provide simultaneous
and virtual scenarios of decision outcomes, while actors will prioritize value systems and
select desired futures (Tissen et al., 2000).

The quantum model of KM is simultaneously integrative and interactive of operations at all
levels of organization thereby solving complex, conflicting and paradoxical problems in a
way that is beneficial to shareholders, stakeholders and society.

SECI Model

Figure 1: The SECI process

The SECI process given by Nonaka and Takouchi (1995) depicts four modes of knowledge
conversion with the underlying understanding that an organization creates knowledge
through the interactions between explicit knowledge and tacit knowledge [Fig.1]. The
process is viewed as a spiral, operating at the individual, group, organization, and
inter-organizational levels. The model assumes that tacit knowledge can be transferred
through a process of socialization into tacit knowledge and then become explicit knowledge
through a process of externalization. Also, the model assumes that explicit knowledge can
be transferred into tacit knowledge through a process of internalization, and that
explicit knowledge can be transferred to others, through a process of combination. It is
to be noted that knowledge created through each of the four modes of knowledge conversion
interacts in the spiral of knowledge creation. The spiral becomes larger in scale as it
moves up through the ontological levels. Knowledge created through the SECI process can
trigger a new spiral of knowledge creation, expanding horizontally and vertically across

Socialization is the process of converting new tacit knowledge through shared experiences.
Socialization typically occurs in a traditional apprenticeship or in informal social
meetings outside of the workplace where tacit knowledge can be learned through hands-on
experience or sharing of worldviews, mental models and mutual trust. Socialization also
occurs beyond organizational boundaries.

Externalization is the process of articulating tacit knowledge into explicit knowledge.
When tacit knowledge is made explicit, knowledge is crystallized, thus allowing it to be
shared by others relatively easily, and it becomes the basis of new knowledge. The
successful conversion of tacit knowledge into explicit knowledge depends on the sequential
use of metaphor, analogy and model.

Combination is the process of converting explicit knowledge into more complex and
systematic sets of explicit knowledge through a process of combining, editing or
processing thereby forming new knowledge. It is new knowledge in the sense that it
synthesizes knowledge from many different sources in one context. This new explicit
knowledge is then disseminated among the members of the organization.

Internalization is the process of embodying explicit knowledge into tacit knowledge.
Through internalization, explicit knowledge created is shared throughout an organization
and converted into tacit knowledge by individuals. Internalization is closely related to
‘learning by doing'. Explicit knowledge has to be actualized through action and
practice. When knowledge is internalized to become part of individuals' tacit knowledge
bases in the form of shared mental models or technical know-how, it becomes a valuable
asset. This tacit knowledge accumulated at the individual level can then set off a new
spiral of knowledge creation when it is shared with others through socialization.

Figure 2: Three elements of the knowledge-creating process

Nonaka et al. (2000) extended the SECI model to include three elements of knowledge
creation: the SECI process, Ba, and the moderator of the knowledge creating process. The
first element of the model is the SECI process which, as explained above, places an
emphasis on ‘‘knowledge conversion'', that is the creation of knowledge through
explicit and tacit knowledge interactions [Fig.2]. The second element of the model, Ba,
refers to the context for knowledge creation ‘‘a shared context in which knowledge is
shared, created and utilized''. The last element of the model is knowledge assets that are
‘‘firm-specific resources that are indispensable to create values for the firm''.
These knowledge assets are the inputs, outputs, and moderator of the knowledge-creating
process. The three elements of knowledge creation have to interact with each other to form
the knowledge spiral that creates knowledge The central focus of Nonaka et al.'s (2000)
work is the processes of conversion between tacit and explicit knowledge and the cultural
Continues for 19 more pages >>

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