Use of Process Mining Analytics to Overcome Deficiencies of Process Modeling Practice

• In Event: BUSINESS ANALYTICS: Business Analytics and Retail Applications

Abstract

This paper presents a way of combining process mining analytics with process modeling in order to improve the quality of input data for the process simulation. Process modelers often use insights from traditional sources such as process documentations, observations, and interviews with stakeholders. Obtained information from these sources likely presents a biased and inaccurate view of the real process. Instead, in this paper, it is demonstrated that the process-related components such as activities, relationships, durations, and resources are extracted from process mining and used as input data for the creation of a process model that closely reflects reality.

Authors

• Julian Koech, Illinois State University

• Borinara Park, Illinois State University