An Empirical Analysis of Diagnosis of Industrial Business Processes at Sub-process Levels

TLDR: An empirical diagnostic analysis of control flow errors such as deadlock and lack of synchronization as well as syntactic errors arising out of poor modeling practices for real-life industrial process models is provided.

Abstract: Business process models expressed in languages such as BPMN (Business Process Model and Notation) play a critical role in implementing the workflows in modern organizations. However, control flow errors such as deadlock and lack of synchronization as well as syntactic errors arising out of poor modeling practices often occur in industrial process models. In this paper, we provide an empirical diagnostic analysis of such errors for real-life industrial process models. The investigation involved models from different application domains. It turns out that error frequency has non-linear relation with error depth (the maximum depth at which an error occurred) across models from all domains. Error occurrence has statistically significant correlations (p