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Authors: Oscar Avila 1 ; 2 ; Mathias Weske 3 and Alexander Estacio 4

Affiliations: 1 Université de technologie de Compiègne, COSTECH, Compiègne, France ; 2 Department of Systems and Computing Engineering, School of Engineering, Universidad de los Andes, Bogota, Colombia ; 3 Business Process Technology Research Group, Hasso Plattner Institute, Potsdam, Germany ; 4 DSIT, Universidad de los Andes, Bogota, Colombia

Keyword(s): IT Incident Management, Process Mining, Attribute-Based Segmentation, Process Diagnostics, Information Technology Service Management.

Abstract: This article presents a case study on the application of process mining techniques in IT incident management within the Department of Information and Technology Services (DSIT) at a university in Colombia. The study aims to bridge the gap on the use of process mining for diagnostics in IT service management (ITSM) projects. The methodology involves generating an event log from 3440 incident registers exported from the CRM platform this institution uses to manage IT incidents, followed by process discovery and attribute-based segmentation to identify patterns in process execution. The case study demonstrates the feasibility of applying process mining techniques to the diagnostics of IT management processes, highlighting challenges encountered and solutions applied. The results indicate that process mining can help align IT management processes with performance goals, providing valuable insights for the DSIT’s ongoing transformation project.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Avila, O., Weske, M. and Estacio, A. (2026). A Process Mining Case Study in IT Incident Management. In Proceedings of the 28th International Conference on Enterprise Information Systems - Volume 3: ICEIS; ISBN 978-989-758-834-1; ISSN 2184-4992, SciTePress, pages 2174-2181. DOI: 10.5220/0014947000004018

@conference{iceis26,
author={Oscar Avila and Mathias Weske and Alexander Estacio},
title={A Process Mining Case Study in IT Incident Management},
booktitle={Proceedings of the 28th International Conference on Enterprise Information Systems - Volume 3: ICEIS},
year={2026},
pages={2174-2181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014947000004018},
isbn={978-989-758-834-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 28th International Conference on Enterprise Information Systems - Volume 3: ICEIS
TI - A Process Mining Case Study in IT Incident Management
SN - 978-989-758-834-1
IS - 2184-4992
AU - Avila, O.
AU - Weske, M.
AU - Estacio, A.
PY - 2026
SP - 2174
EP - 2181
DO - 10.5220/0014947000004018
PB - SciTePress