Analysis of Cargo Release Services with Process Mining

Abstract

Process Mining (PM) uses event logs extracted from process-oriented IS in order to uncover, analyse, diagnose and improve processes. However, the number of studies demonstrating PM applicability is limited, particularly in the field of logistics. This paper presents a methodological framework for a multi-faceted analysis of real-life event logs based on PM and the usefulness of its techniques, combined with traditional IE&M methods, thus offering an innovative approach on multiple levels by combining the use of PM and more traditional methods; using PM to demonstrate the actual movement of goods and generate a physical map of movements inside the warehouse; and enabling continuous tracking. A case-study, implemented on the cargo release process of a large Israeli logistics company, demonstrates this approach. Results reflect a major gap between the actual and the described processes, as an automatic creation of the process from logs shows that 64% of the customers received their goods after 4.5 hours (instead of 90 minutes, as service standard requires). Practical implications include detailed steps and a recommendation for additional analyses. Research value analysis shows that PM techniques constitute an ideal means to tackle organizational challenges by reflecting real-time situations, suggesting process improvements and creating companywide process awareness.