Techniques for reusing experiences (T-REx) in managerial decision-making processes

Abstract

This paper proposes a framework for experience-based decision support by analyzing the use and meaning of experiences in the business context. Two weak points in traditional approaches for reusing experiences e.g. CBR are addressed: First, the lack of adaptability to dynamic business situations and second the lack of analysis capabilities. Therefore, the use of decision support systems that help solving problems by reusing and analyzing experiences with business intelligence methods is proposed. In order to transfer the experiences into computable data a solution adequacy index is calculated that aggregates the single experiences to represent the compiled experience for a specific solution. The whole framework is illustrated by using the example of optimal supplier choice, finally applying two online analytical processing methods out of the BI domain to illustrate the solution adequacy index (SAI).