Identifying drivers of inefficiency in business processes: A DEA and Data Mining perspective

Abstract

Measuring the performance of business processes in the financial services sector can be tackled from different perspectives. The viewpoint of efficiency is one of them. This paper focuses on the analysis of process efficiency and proposes a new methodology for measuring process efficiency and for further identifying drivers of process inefficiency. It is suitable for a specific perspective on process efficiency. The methodology is based on Data Envelopment Analysis (DEA) and methods from Data Mining. It aims to find strong association rules between process transactions' characteristics and inefficiency values. This approach enables the identification of drivers of inefficiency from a (large) dataset of transactions without any prior assumptions about potential determinants of inefficiency. The methodology is applicable to business processes supported by workflow management systems and it can serve as the basis for an add-on system allowing structural analysis of process inefficiency and its drivers. © 2010 Springer-Verlag Berlin Heidelberg.