Analysis of Transport Company Processes (Process Mining)

Each day transport companies are faced with a lot of challenges. It is becoming increasingly difficult to maintain a low level of transportation costs, and customer requirements are constantly growing. In order to gain competitive advantage, organizations need to carefully monitor the effectiveness of their business processes. For this reason, numerous transport companies use information systems, in particular ERP, SCM, TMS, to monitor and optimize their work. The rich functionality of these systems allows organizations to store huge amounts of data about processes in special event logs. Process Mining is an approach to discover, diagnose, visualize processes by extracting event logs from an information system. The technology of Process Mining differs considerably from other methods of business operations analysis because it is based on real data. Moreover, it bridges the gap between classical model-based process diagnosis and data-centric technics, including machine learning and data mining. As a result, Process Mining methods provide unique opportunities to use data volumes in a business process context. This approach has already been considered effective in such areas as healthcare, software development, online education. However, Process Mining is still unpopular in the field of transport services. The purpose of this study is to uncover the practical potential of the Process Mining approach for analyzing logistics processes. During the research, the cases of the application Process Mining in transport companies were considered. Then, the advantages and disadvantages of the method were identified. Based on the obtained data, there were discovered several issues that were neglected by other researchers. Some of these problems were disclosed in the practical part of the paper. As a result, the opportunities of Process Mining were described, and recommendations for successful work were formulated.