A connectance‐based approach for managing manufacturing knowledge

Publication Date01 Feb 2004
AuthorKim Hua Tan,Ken Platts
SubjectEconomics,Information & knowledge management,Management science & operations
A connectance-based
approach for managing
Kim Hua Tan and
Ken Platts
Many researchers (Senge, 1990; Prahalad and
Hamel, 1990; Nonaka and Takeuchi, 1995;
Davenport and Prusak, 1998; Hansen et al.,
1999; Hargadon and Sutton, 2000; Hsieh et al.,
2002; Paiva et al., 2002) have stressed and
recognised the strategic importance of
knowledge. They point out that in today's
``knowledge-driven'' economy, organisations in
both the manufacturing and service sectors
need to leverage employees' knowledge in order
to gain competitive advantage. This theoretical
proposition of the performance-critical role of
knowledge in business context is further
supported by a recent survey of UK industry by
Microsoft Corp. (Microsoft, 2000). Of the
surveyed organisations, 80 per cent identified
that knowledge exploitation could lead to the
potential benefit of ``innovation and growth''. In
a world wide market forecast, IDC (2000)
estimated that company spending on
knowledge management initiatives will increase
by a compound annual growth rate of 40.7 per
cent to $12 billion in 2005.
However, the process of capturing managers'
knowledge is never an easy task. Macintosh et
al. (1998) pointed out that knowledge takes
time to experience and acquire. Moreover,
knowledge has many facets and stages and there
is no single right approach to manage it
effectively (Bohn, 1994; Davenport and Prusak,
1998; Lee and Hong, 2002). Polanyi (1966)
classified knowledge into two types, namely
tacit and explicit. Tacit knowledge is usually
embedded in individuals, and in informal
organisational relationships. Explicit or
``codified'' knowledge usually refers to
knowledge that is transmittable in formal
written documents or electronic files. Bohn
(1994) has distinguished eight levels of
knowledge, from the awareness of a problem,
up to the capability of producing formal and
general models.
Many researchers have further made
distinctions between data, information and
knowledge. Davenport and Prusak (1998)
pointed out that data are objective facts,
presented without any judgement or context.
Data becomes information when it is
categorised, analysed, summarised and placed
in context. Information, however, is data
The authors
Kim Hua Tan is Researcher and Ken Platts is Reader, both
at the Centre for Strategy and Performance, University of
Cambridge, Cambridge, UK.
Knowledge management, Ideas generation,
Management techniques
This paper proposes the use of the connectance concept for
managing manufacturing knowledge. The concept utilises
inductive rules to specify relationships between variables. A
software tool called Tool for Action Plan Selection (TAPS)
has been developed based on the connectance concept.
TAPS enables managers to sketch and visualise their
knowledge of how variables interact in a connectance
network. This network is a useful means for discussion and
understanding a particular problem. The information on the
network can be stored in a database, to be managed and
shared within a firm. TAPS allows managers to analyse
possible actions and suitable tools and techniques aimed at
solving specific manufacturing problems. Results from case
studies have indicated that TAPS is feasible and seems to be
applicable even beyond the manufacturing domain.
Electronic access
The Emerald Research Register for this journal is available at
The current issue and full text archive of this journal is
available at
Industrial Management & Data Systems
Volume 104 .Number 2 .2004 .pp. 158-168
#Emerald Group Publishing Limited .ISSN 0263-5577
DOI 10.1108/02635570410522134

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