Using Process Mining to Analyze and Improve Process Flexibility

Contemporary information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Workflow management systems are typically considered as too restrictive while groupware applications (e.g., e-mail) tend to offer hardly any process support or control at all. Therefore, we consider adaptive process management systems that allow for runtime changes at both process type and process instance level (e.g., a system like ADEPT). Assuming that these process changes are recorded explicitly, we discuss how this information can be used as input for process mining. So far, process mining has only be applied to operational processes, i.e., knowledge is extracted from event logs (process discovery), or event logs are compared with some a-priori model (conformance checking). In this paper, we propose to apply process mining to change logs, i.e., we not only analyze the operational processes but also the adaptations made at the process type or process instance level. Using such analysis, we envisage to be able to better support flexibility by understanding when and why process changes become necessary.