From automatic workaround detection to process improvement: a case study

Abstract

The improvement of business processes through learning and investigating workarounds has attracted research attention in recent years. Workarounds can be considered as a symptom of needed process improvements but adopting them does not necessarily lead to an appropriate one. Hence, identifying and understanding the underlying problems or perceived barriers that motivate workarounds is essential for suggesting an appropriate process improvement solution. In this paper, we propose a streamlined end-to-end approach that attempts to leverage workarounds to improve processes. This approach is based on two pillars: (1) a semi-automated workarounds detection by using the SWORD framework, which consists of twenty-two patterns to detect workarounds from events logs. (2) workarounds investigation and analysis using a motivational model that serves to reveal problems that lie under the identified workarounds. This analysis contributes toward proposing tailored and targeted process improvements. We report on an industrial case study that demonstrates the proposed approach, from workaround detection to proposing tailored process improvements. The improvements have been accepted by the organization and are currently being implemented.