Outsourcing Prioritization for Bottleneck Processes Using Process Mining: A Logistics Case Study

If properly monitored, systems in the real world generate data when a process is executed. This data is a valuable resource for creating process models and analyzing performance. Process mining can be used to identify, predict, and avoid bottlenecks and inefficiencies in processes. Thus far, (most) existing research has been done regarding the discernment and subsequent understanding of bottlenecks. Inspired by the limited amount of research regarding the prediction of bottlenecks and the subsequent elimination strategies, this research proposes a method for mitigating bottlenecks using process mining and outsourcing techniques. Outsourcing is a technique in which an organization contracts a third party to complete work, manage operations, or deliver services on its behalf. Many organizations outsource so they can use their limited internal resources better. However, organizations usually face the challenge of determining exactly what to outsource. If there are several bottlenecks, it can be challenging to select one. Thus, this study aims to provide a (full-fledged) method for outsourcing prioritization of bottlenecks in various processes. Furthermore, a logistics case study demonstrates the feasibility of the proposed method. Although preliminary, the presented method is expected to enrich the scientific field of process mining and bottleneck processes.