Detecting change in processes using comparative trace clustering

Real-life business processes are complex and show a high degree of variability. Additionally, due to changing conditions and circumstances, these processes continuously evolve over time. For example, in the healthcare domain, advances in medicine trigger changes in diagnoses and treatment processes. Besides changes over time, case data (e.g. treating physician, patient age) also influence how processes are executed. Existing process mining techniques assume processes to be static and therefore are less suited for the analysis of contemporary flexible business processes. This paper presents a novel comparative trace clustering approach that is able to expose changes in behavior. Valuable insights can be gained and process improvements can be made by finding those points in time where behavior changed and the reasons why. Evaluation on real-life event data shows our technique can provide these insights.</p

Process Mining as a Strategy of Inquiry: Understanding Design Interventions and the Development of Business Processes

Process (re-)design and improvement are important aspectsof the Business Process Management (BPM) life-cycle. Yet, there is lit-tle empirical evidence on how design interventions materialize in actualprocess execution, leading to repeated failure of such initiatives. In thisdissertation I use the emerging affordances of process mining algorithmsto address this important limitation. In particular, I devise a methodthat combines process mining and grounded theory to study processualphenomena. Consequently, this method is applied to investigate changein business processes. This thesis contributes to the body of knowledgein BPM and bordering disciplines by demonstrating how process min-ing can be used as a method to study processual phenomena. Furtherthis research sheds light on the impact of design interventions on actualprocess execution and vica versa