Does Your Accurate Process Predictive Monitoring Model Give Reliable Predictions?

Abstract

The evaluation of business process predictive monitoring models usually focuses on accuracy of predictions. While accuracy aggre gates performance across a set of process cases, in many practical sce narios decision makers are interested in the reliability of an individual prediction, that is, an indication of how likely is a given prediction to be eventually correct. This paper proposes a first definition of business process prediction reliability and shows, through the experimental evalu ation, that metrics that include features defining the variability of a pro cess case often give a better prediction reliability indication than metrics that include the probability estimation computed by the machine learn ing model used to make predictions alone