#96-31-B
"Measuring the Efficiency of Service Delivery Processes: With Application to Retail Banking"
Summary: This paper presents a methodology that determines the role of design in calculating the efficiency of service delivery processes. Traditional efficiency studies measure the performance of a firm or decision making unit by its ability to transform inputs to outputs. Often, the actual way in which these inputs are transformed to outputs is ignored. This paper argues that the design of the transformation process is a critical component in the decision making unit's relative performance. Further, this paper submits that the design of the transformation mechanism, or the process design, must be fully studied and integrated into performance analysis in order to provide useful managerial recommendations.
The authors present a new method for determining the role of process design in calculating efficiency. Using a variation of frontier estimation (DEA-like) techniques, this methodology helps address the question of how much each unit's inefficiency is due to the wrong process design, and how much inefficiency is due to poor execution.
Consistent with expectations, the results of the analysis show that no single process design dominates. The analysis in this paper introduces the concept of process design groups which allows comparisons relative to both a common design group, as well as to the entire set of organizational units. It is through this analysis that the authors were able to determine which portion of performance results is due to the right design and which portion due to poor execution. A case example of one organization in a defined process group is used to illustrate the analysis.
The paper also argues that in the analysis of customer service delivery processes, in particular, the focus should not be solely on traditional measures of productivity or financial performance. Rather, comparisons based on intermediary measures which evaluate the drivers of performance from the perspective of all participants in the service delivery process must also be considered. The empirical examples in this paper make use of such intermediary measures.
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