Uday S. Murthy and Julia A. Swanson

ABSTRACT:

One decision-making task common to most organizations is the process of investigating cost variances resulting from differences between actual and expected or budgeted costs. The cost variance investigation decision involves determining which variances are significant enough to warrant detailed examination and identifying the factors that possibly contributed to the significant variance. This article presents an intelligent decision support system (DSS) for assisting with the variance investigation process. The system architecture is based on an analysis of knowledge required for variance investigation using input received from expert managerial accountants from a Fortune 100 company.

Variance investigation knowledge was categorized into (1) situational knowledge of the data specific to each variance investigation situation and (2) domain independent knowledge of the process of investigating variances. The intelligent DSS encodes the variance investigation process knowledge in a knowledge base and has tables in a relational database system to represent situational knowledge of the data unique to each variance investigation situation. The specifications of the system in terms of the variance investigation process encoded in the knowledge base and the design of the database component are described. The database component was customized to a hypothetical cost environment to demonstrate how the system operates. Sample user interface screens and a hypothetical consultation report are also presented.