Customer Information Driven After Sales Service ... - RePub

1.3. Scope, Research Contributions, and Research Methods
As discussed earlier, after sales service management involves the interaction of various
after sales service operations. To narrow the scope further, in this thesis, we focus on the
spare parts logistics aspect of after sales service. Within spare parts logistics, we study
the planning and execution stages of spare parts logistics; i.e. spare parts inventory
planning, spare parts logistics execution and returns execution management. We study
these logistics operations, since any attempt or intervention here directly effects the
customer by impacting the after sales service execution (see Figure 2.2). Furthermore, we
will mainly focus on a reactive type of maintenance policy, since it is the predominantly
adopted maintenance policy for a short product life cycle and slow moving demand
situation. Such characteristics can be commonly observed in the high-tech and capital
goods sector. We should clarify that the results presented in this thesis are also applicable
for the settings of condition based proactive maintenance.
1.3.2 Research Contributions
What are the benefits of using customer related information to drive after sales service
management? From a theoretical perspective, this question relates to aspects of information
acquisition, management, and usage to support value addition in after sales service.
First of all, the question is how customer information should be utilized to induce value
addition in after sales service management. One may argue that customer information
may induce value addition via three mechanisms, i.e. by modifying the existing decision
space, enabling a new decision space, or enabling more accurate decision making in the
existing decision space. After identifying the potential mechanism for value addition,
two factors are key for the realization of value addition. First, a supply chain analytic
or optimization engine that can turn the raw data into useful information for decision
making. Second, a quality data source that provides the appropriate level of detail.
In this thesis, we study both of these factors in a comprehensive manner. First,
we study the existing analytics or optimization solutions from the after sales service
management literature to observe their ability to account for the underlying business
conditions in profit driven after sales service. In the absences of an appropriate solution
available in literature, we attempt to devise such a solution for profit driven after sales
service management. Secondly, we attempt to quantify the value addition enabled by
using IB information to support after sales service management decisions. As mentioned
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