Predictive Process Monitoring Methods: Which One Suits Me Best?

TL;DR

This paper reviews and categorizes existing predictive process monitoring methods, providing a framework to help organizations select suitable techniques and maximize value from process data analysis.

Contribution

It develops a systematic, value-driven framework for classifying and choosing predictive process monitoring methods based on their characteristics and organizational needs.

Findings

Systematic classification of existing approaches

Development of a decision-support framework

Guidance for organizations to select appropriate methods

Abstract

Predictive process monitoring has recently gained traction in academia and is maturing also in companies. However, with the growing body of research, it might be daunting for companies to navigate in this domain in order to find, provided certain data, what can be predicted and what methods to use. The main objective of this paper is developing a value-driven framework for classifying existing work on predictive process monitoring. This objective is achieved by systematically identifying, categorizing, and analyzing existing approaches for predictive process monitoring. The review is then used to develop a value-driven framework that can support organizations to navigate in the predictive process monitoring field and help them to find value and exploit the opportunities enabled by these analysis techniques.