The study presents an interpretable process mining approach to identify improvements, reduce waste, and suggest redesigns in knock-out check processes.
Lashkevich, K., Mediavilla Ponce, L. M., Camargo, M., Milani, F., & Dumas, M. (2023). Discovery of Improvement Opportunities in Knock-Out Checks of Business Processes. RCIS 2023 read
The text discusses overprocessing waste in business processes and highlights the use of knock-out checks to identify and eliminate this waste. A novel, interpretable process mining approach is proposed to detect improvement opportunities and recommend process redesigns. The paper presents an implemented software tool and showcases its applicability on real-life processes.
Knock-out checks are tasks in a business process that classify cases as either "accepted" or "rejected". If a case is rejected, it triggers the execution of an anchor, a pre-determined point in the process, effectively ending the process. When a knock-out check leads to a case's rejection, all the work up to that point is deemed overprocessing waste, leading to inefficiency in terms of time and cost.
The proposed method uses an event log to discover and analyze knock-out checks. The process involves discovering knock-out checks, their decision rules, and dependencies from the event log, then assessing overprocessing waste and effort-per-rejection rates. It supports three modes of operation: semi-automatic discovery, automatic discovery, and known knock-out checks.
The final step is to identify improvement opportunities and suggest possible redesigns based on the knock-out checks. These redesigns include knock-out reordering (least effort to reject), knock-out relocation (earliest possible point), and knock-out rule adjustment (changing attribute values).
Overall, the process mining approach provides insight into process redesign opportunities to reduce overprocessing waste. The interpretability of the results supports decision-making and increases confidence in redesign recommendations.