Automate does not always mean optimize - case study at logistics company

Dynamic growth of digitized information creates space for systematic collection of data related to business processes. Extraction of this data is an enormous challenge because many systems exist, which store data in many different formats. With the use of advanced analytics techniques, it is possible to present collected data in an “as-is” view of processes and find bottlenecks, loops, delays or deadlocks. In this paper, we present the methodology to extract business-related events from given processes of a logistic company. The logistic company has over the years fully automated their Purchase Order and Invoice Approval processes driven by BPM system. Logistics is always about optimization and cost reduction. The company asked us, whether it was possible to optimize processes furthermore. We analyzed the BPM system and deployed processes to develop connector for event data extraction. Process mining techniques were used to reconstruct processes from event logs. As a result, we identified bottlenecks, over allocated employees, and suppliers’ characteristics.