Performance Evaluation Metrics for Information Systems Development: A Principal-Agent Model

Rajiv D. Banker and Chris F. Kemerer
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Rajiv D. Banker: Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455
Chris F. Kemerer: Sloan School of Management, Massachusetts Institute of Technology, 50 Memorial Drive, E53-315, Cambridge, Massachusetts 02142-1347

Information Systems Research, 1992, vol. 3, issue 4, 379-400

Abstract: The information systems (IS) development activity in large organizations is a source of increasing cost and concern to management. IS development projects are often over-budget, late, costly to maintain, and not done to the satisfaction of the requesting user. These problems exist, in part, due to the organization of the IS development process, where information systems development is typically assigned by the user (principal) to a systems developer (agent). These two parties do not have perfectly congruent goals, and therefore a contract is developed to specify their relationship. An inability to directly monitor the agent requires the use of performance measures, or metrics, to represent the agent's actions to the principal. The use of multiple measures is necessary given the multi-dimensional nature of successful systems development. In practice such contracts are difficult to develop satisfactorily, due in part to an inability to specify appropriate metrics. This paper develops a principal-agent model that provides a set of decision criteria for the principal to use to develop an incentive compatible contract for the agent. These criteria include the precision and the sensitivity of the performance metric. After presenting the formal model, some current software development metrics are discussed to illustrate how the model can be used to provide a theoretical foundation and a formal vocabulary for performance metric analysis. The model is also used in a positive (descriptive) manner to explain why current practice emphasizes metrics that possess relatively high levels of sensitivity and precision. Finally, some suggestions are made for the improvement of current metrics based upon these criteria.

Keywords: software engineering; management of computing and information systems (search for similar items in EconPapers)
Date: 1992
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