Abstract
Process mining techniques provide insights into operational processes by systematically analyzing event data generated during process execution. These insights are used to improve processes, for instance, in terms of runtime, conformity, or resource allocation. Time-based performance analysis of processes is a key use case of process mining. This paper presents the performance analysis functionality in the process mining software tool Cortado. We present novel performance analyses for block-structured process models, i.e., hierarchical structured Petri nets. By assuming block-structured models, detailed performance indicators can be calculated for each block that makes up the model. This detailed temporal information provides valuable insight into the process under study and facilitates analysts to identify optimization potential.
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Schuster, D., Schade, L., van Zelst, S.J., van der Aalst, W.M.P. (2022). Temporal Performance Analysis for Block-Structured Process Models in Cortado. In: De Weerdt, J., Polyvyanyy, A. (eds) Intelligent Information Systems. CAiSE 2022. Lecture Notes in Business Information Processing, vol 452. Springer, Cham. https://doi.org/10.1007/978-3-031-07481-3_13
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