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60 Chapter 3

Although few would argue that knowledge is unimportant, the overriding problem is
that few managers and information professionals understand how to manage knowl-
edge in knowledge-creating organizations. There is a tendency to focus on “ hard ” or
quantifi able knowledge; and KM is often seen as some sort of information processing
machine. The advent of knowledge management was initially met with a fair degree
of criticism — many people felt this was yet another buzzword and bandwagon that
they were expected to jump on. One of the reasons that KM has now established itself
more credibly as both an academic discipline of study and a professional fi eld of
practice is the work that has been done on theoretical or conceptual models of knowl-
edge management. Early on, more pragmatic considerations about the processes of
KM were complemented by the need to understand what was happening in organiza-
tional knowing, reasoning, and learning.
A more holistic approach to KM has become necessary as the complex, subjective,
and dynamic nature of knowledge has developed. Cultural and contextual infl uences
further increased the complexity involved in KM, and these factors also had to be
taken into account in a model or framework that could situate and explain the key
KM concepts and processes. Last but not least, measurements were needed in order to
be able to monitor progress toward and attainment of expected KM benefi ts.
This holistic approach is one that encompasses all the different types of content to
be managed, from data, to information, to knowledge, but also conversions from tacit
to explicit and back to tacit knowledge types. The KM models presented in this chapter
all attempt to address knowledge management in a holistic and comprehensive
manner.
Davenport and Prusak (1998 , 2) provide the following distinctions among data,
information, and knowledge, which recap the examples in chapter 1:
Data A set of discrete, objective facts about events.
Information A message, usually in the form of a document or an audible or visible
communication.
Knowledge A fl uid mixing of framed experiences, values, contextual information, and
expert insight that provide a framework for evaluating and incorporating new experi-
ences and information. It originates and is applied in the minds of those who know.
In organizations, it often becomes embedded not only in documents or repositories,
but also in organizational routines, processes, practices, and norms.
Davenport and Prusak (1998) refer to the distinctions among data, information,
and knowledge as operational, and argue that we can transform information into
knowledge by means of comparison, consequences, connections, and conversation.