Data-Driven Process Performance Measurement and Prediction: A Process-Tree-Based Approach

To achieve operational excellence, a clear understanding of the core processes of a company is vital. Process mining enables companies to achieve this by distilling historical process knowledge based on recorded historical event data. Few techniques focus on the prediction of process performance after process redesign. This paper proposes a foundational framework for a data-driven business process redesign approach, allowing the user to investigate the impact of changes in the process, w.r.t. the overall process performance. The framework supports the prediction of future performance based on anticipated activity-level performance changes and control-flow changes. We have applied our approach to several real event logs, confirming our approach's applicability.