Recent advancements in location-aware analytics have created novel opportunities in different domains. In the area of process mining, enriching process models with geolocation helps to gain a better understanding of how the process activities are executed in practice. In this paper, we introduce our idea of geo-enabled process modeling and report on our industrial experience. To this end, we present a real-world case study to describe the importance of considering the location in process mining. Then we discuss the shortcomings of currently available process mining tools and propose our novel approach for modeling geo-enabled processes focusing on 1) increasing process interpretability through geo-visualization, 2) incorporating location-related metadata into process analysis, and 3) using location-based measures for the assessment of process performance. Finally, we conclude the paper by future research directions.
@article{arxiv.2204.08063,
title = {Geo-Enabled Business Process Modeling},
author = {Behshid Behkamal and Asef Pourmasoumi and Mehdi Akbarian Rastaghi and Mohsen Kahani and Hamid Reza Motahari-Nezhad and Mohammad Allahbakhsh and Issa Najafi},
journal= {arXiv preprint arXiv:2204.08063},
year = {2022}
}
Comments
accepted and presented in BPM 2020. https://congreso.us.es/bpm2020/program/accepted/