A Comparative Evaluation of Log-Based Process Performance Analysis Techniques

TL;DR

This paper introduces a framework for categorizing and selecting process performance analysis techniques in process mining, based on a systematic review of existing research and considering various aspects of performance measurement.

Contribution

It provides a structured framework to help organizations choose suitable process performance analysis methods based on context and data availability.

Findings

Developed a comprehensive categorization framework

Reviewed existing process performance measurement techniques

Guidelines for selecting appropriate analysis approaches

Abstract

Process mining has gained traction over the past decade and an impressive body of research has resulted in the introduction of a variety of process mining approaches measuring process performance. Having this set of techniques available, organizations might find it difficult to identify which approach is best suited considering context, performance indicator, and data availability. In light of this challenge, this paper aims at introducing a framework for categorizing and selecting performance analysis approaches based on existing research. We start from a systematic literature review for identifying the existing works discussing how to measure process performance based on information retrieved from event logs. Then, the proposed framework is built starting from the information retrieved from these studies taking into consideration different aspects of performance analysis.