C o n f i g u r i n g P r o d u c t V a r i a n t s I n C u s t o m i s a t i o n S t r a t e g i e s
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Hence, increasing the options available for a product does not automatically yields
superior levels of satisfaction;
(ii) Matching need with product specification: clients might also have difficulties in
configuring a product variant due to the lack of knowledge and skills to transfer their
requirements into an explicit product specification. Even a common product like a pair of
sport shoes can have a complex configuration process if the client has do explicit decide
between different widths, sizes, cushioning, colour, and patterns for the outsole; and
In summary, there are pros and cons in collaborative and transparent approaches.
Configuration problems are avoided when a transparent approach is adopted. However,
the benefits that emanate from client active engagement are also lost. Therefore, the
definition of the approach to be adopted (transparent, collaborative, or a mix of both) is a
strategic decision that should be made by the organisation developing the customisation
strategy. In any case, the chain of decisions of a configuration process should enable a
product variant to be effortless created, regardless of who (clients or organisation) will be
involved in this process. Clearly, should the configuration process involve a collaborative
approach, minimization of configuration problems and exploitation of benefits that arise
from clients’ engagement should also be included as goals.
Method
As previously described, this paper presents part of a conceptual framework developed
in the Ph.D investigation of the first author. The research method adopted in that
investigation is a design science or constructive research approach. Design science is a
mode of producing scientific knowledge. In this mode, knowledge is produced by
creating and testing a solution that manipulates a particular phenomenon (Vaishnavi and
Kuechler 2007). For example, in pharmaceutics, a new drug can be view as a solution
since it cures a disease (disease is the phenomenon manipulated). It differs from formal
sciences (e.g. mathematics), which produce knowledge by creating abstract propositions
and testing their internal consistency (Van Aken, 2004). It also differs from explanatory
science, which produce knowledge by proposing scientific claims (i.e. descriptions,
explanations, causality) concerning a phenomenon and empirically testing them (March
and Smith 1995). Two fundamental activities of design science research are: (i) develop
and apply solution and (ii) test its usefulness in solving real world problems. Hence, the
three elements proposed in this paper are applied to analyse the configuration
sequences in four case studies
. Opportunities for improvements that could
also be drawn based on these analyses are also presented here.
Case
study
Product
Overview of the organisation and location
1
Pre-fabricated floor tiles
Manufacturer of floor tiles (Brazil)
2
Apartments for high-end clients
Contractor (Brazil)
3
Residential schemes for social housing
Contractor (UK)
4
Residential schemes for social housing
A consortium of registered providers (UK)
Figure 1: Overview of the case studies
Defining the chain of decision of a configuration process
Three elements define the chain of decisions of a configuration process
: tree,
branches, and levels (horizontal and vertical). The starting point to define this chain of
decisions is to elicit the customisation units used in the customisation strategy. Each
customisable attribute and the range of items offered for it forms a customisation unit. In
the hypothetical example shown in Figure 2, there are three customisation units: C1, C2,
and C3. After that, the tree, which is the chain of decisions concerning each
