Using Life Cycle Information in Process Discovery

Understanding the performance of business processes is an important part of any business process intelligence project. From historical information recorded in event logs, performance can be measured and visualized on a discovered process model. Thereby the accuracy of the measured performance, e.g., waiting time, greatly depends on (1) the availability of start and completion events for activities in the event log, i.e. transactional information, and (2) the ability to differentiate between subtle control flow aspects, e.g. concurrent and interleaved execution. Current process discovery algorithms either do not use activity life cycle information in a systematic way or cannot distinguish subtle control-flow aspects, leading to less accurate performance measurements. In this paper, we investigate the automatic discovery of process models from event logs, such that performance can be measured more accurately. We discuss ways of systematically treating life cycle information in process discovery and their implications. We introduce a process discovery technique that is able to handle life cycle data and that distinguishes concurrency and interleaving. Finally, we show that it can discover models and reliable performance information from event logs only.