Probability Based Heuristic for Predictive Business Process Monitoring

Abstract

Predictive business process monitoring concerns the unfolding of ongoing process instance executions. Recent work in this area frequently applies “blackbox” like methods which, despite delivering high quality prediction results, fail to implement a transparent and understandable prediction generation process, likely, limiting the trust users put into the results. This work tackles this limitation by basing prediction and the related prediction models on well known probability based histogram like approaches. Those enable to quickly grasp, and potentially visualise the prediction results, various alternative futures, and the overall prediction process. Furthermore, the proposed heuristic prediction approach outperforms state-of-the-art approaches with respect to prediction accuracy. This conclusion is drawn based on a publicly available prototypical implementation, real life logs from multiple sources and domains, along with a comparison with multiple alternative approaches.