A Data Model to Apply Process Mining in End-to-End Order Processing Processes of Manufacturing Companies

To master ongoing market competitiveness, manufacturing companies try to increase process efficiency through process improvements. Mapping the end-to-end order processing is particularly important, as one needs to consider all order-fulfilling core processes to evaluate process performance. However, process mapping in manufacturing companies is mostly applied in partial processes and not on the end-to-end order processing. Process mining provides a data-based description of processes and their performance and thus objectively and effortlessly maps real as-is processes. The data basis for process mining is an event log. Nevertheless, the generation of an event log in end-to-end order processing is not as trivial as in partial processes, as different data from different information systems must be merged. This paper discusses the development of a data model through an Action Design Research (ADR) method, derived and validated across ADR-cycles. The data model presents, which data can be extracted from integrated database sources to create the required event log for process mining in end-to-end order processing.