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Case Level Counterfactual Reasoning in Process Mining

2021-02-25 09:52:18
Mahnaz Sadat Qafari, Wil van der Aalst

Abstract

Process mining is widely used to diagnose processes and uncover performance and compliance problems. It is also possible to see relations between different behavioral aspects, e.g., cases that deviate more at the beginning of the process tend to get delayed in the last part of the process. However, correlations do not necessarily reveal causalities. Moreover, standard process mining diagnostics do not indicate how to improve the process. This is the reason we advocate the use of \emph{structural equation models} and \emph{counterfactual reasoning}. We use results from causal inference and adapt these to be able to reason over event logs and process interventions. We have implemented the approach as a ProM plug-in and have evaluated it on several data sets. Our ProM plug-in produces recommendations that indicate how specific cases could have been handled differently to avoid a performance or compliance problem.

Abstract (translated)

URL

https://arxiv.org/abs/2102.13490

PDF

https://arxiv.org/pdf/2102.13490.pdf


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