Towards Flexibility in Business Processes by Mining Process Patterns and Process Instances

The possibility to react to unexpected situations in business process execution is restricted since all possible process flows must be specified at design-time. Thus, there is need for a flexible approach that reflects the way in which human actors would handle discrepancies between real-life activities and their representation in business process definitions. In this paper, we propose a novel approach that supports dynamic business processes and is based on a framework comprising a process pattern library with domain-specific patterns and execution logs for mining related process instances. Given a running business process and an unexpected situation, the proposed approach provides a largely automatic adaptation of the business process by replacing failed activities with fitting process alternatives identified by exploring existing process knowledge. The feasibility of the approach is demonstrated by applying the main steps to a business scenario taken from the industry domain.