INDUCTIVE MODEL ANALYSIS SYSTEMS - ENHANCING MODEL ANALYSIS IN DECISION-SUPPORT SYSTEMS

After building and validating a decision support model, the decision m aker frequently solves (often many times) different instances of the m odel. That is, by changing various input parameters and rerunning diff erent model instances, the decision maker develops insight(s) into the workings and tradeoffs of the complex system represented by the model . The purpose of this paper is to explore inductive model analysis as a means of enhancing the decision maker's capabilities to develop insi ght(s) into the business environment represented by the model. The jus tification and foundation for inductive model analysis is based on thr ee distinct literatures: 1) the cognitive science (theory of learning) literature, 2) the decision support system literature, and 3) the mod el management system literature. We also propose the integration of se veral technologies that might help the modeler gain insight(s) from th e analysis of multiple model instances. Then we report on preliminary tests of a prototype built using the architecture proposed in this pap er The paper concludes with a discussion of several research questions . Much of the previous MIS/DSS and management science research has foc used on model formulation and solution. This paper posits that it is t ime to give more attention to enhancing model analysis.