Extending predictive process monitoring for collaborative processes

TL;DR

This paper extends predictive process monitoring techniques to collaborative, inter-organizational processes, addressing their unique complexities and adding new predictive features like participant activity and message exchanges.

Contribution

It introduces an extension of traditional process prediction methods tailored for collaborative processes, incorporating new predictive features specific to inter-organizational interactions.

Findings

Enhanced prediction accuracy for collaborative process activities.

Ability to forecast next participant actions and message exchanges.

Improved understanding of inter-organizational process dynamics.

Abstract

Process mining on business process execution data has focused primarily on orchestration-type processes performed in a single organization (intra-organizational). Collaborative (inter-organizational) processes, unlike those of orchestration type, expand several organizations (for example, in e-Government), adding complexity and various challenges both for their implementation and for their discovery, prediction, and analysis of their execution. Predictive process monitoring is based on exploiting execution data from past instances to predict the execution of current cases. It is possible to make predictions on the next activity and remaining time, among others, to anticipate possible deviations, violations, and delays in the processes to take preventive measures (e.g., re-allocation of resources). In this work, we propose an extension for collaborative processes of traditional process prediction, considering particularities of this type of process, which add information of interest in this context, for example, the next activity of which participant or the following message to be exchanged between two participants.