Directly Follows-Based Process Mining: Exploration & a Case Study

Many organisations now seek to analyse and improve their processes using event logs from various IT systems supporting their operations. Process mining aims to obtain insights from such process data, using process discovery, conformance checking and performance measures. While many commercial process mining tools feature user-friendly directly follows-based process maps, they typically do not offer a way to assess the quality of the model, leaving users with potentially unreliable insights, which could lead to the wrong conclusion being drawn from these insights. In contrast, academic tools typically provide verifiable results, but are often difficult to use and understand for stakeholders, sometimes overgeneralising behaviour to fit more extensive process model formalisms. In this paper, we bridge this well-known gap between commercial and academic tools by combining sound process discovery, conformance checking and performance capabilities with user-friendly directly follows-based process models. We implemented these techniques in a new process mining tool and applied them to analyse several business processes in a Queensland Government department. We discovered sound directly follows-based process models from their logs, compared them with prescribed models and analysed the performance of these processes. In particular, our conformance checking techniques allowed to pinpoint deviations between prescribed processes and actual recorded behaviour. The outcomes of this case study are now being used to document, review, improve and automate processes.