An operational support approach for Mining Unstructured Business Processes

Authors

DOI:

https://doi.org/10.22456/2175-2745.106277

Keywords:

Process Mining, Operational support, Unstructured Business Processes, Structured Business Process, Spaghetti process model, Lasagna process model, Structuring techniques, Heuristics Miner, BPMN

Abstract

The refined process mining framework contains a set of activities that use extracted information from event logs, discovered models and normative ones. Among these activities, we find those dealing with running events in a Structured Business Process (SBP) context, which are the Detect, the Predict and the Recommend activities. These three activities are nominated as an operational support system that aims at detecting deviations, predicting events and recommending actions. In this regard, operational support systems perform well on SBP while, it stills a challenging task for an Unstructured Business Process (UBP). This puts forward the difficulty of predicting events and recommending actions for UBP, because of its complex structure. In this context, simplification and structuring operations must be applied. Therefore, the intervention of other process mining activities is required for business process simplification and structuring. To this end, we present an operational support approach dealing with UBP, using the refined process mining framework activities.

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Author Biographies

Zineb Lamghari, LRIT associated unit to CNRST (URAC 29), Rabat IT Center, Faculty of Sciences, Mohammed V University in Rabat, Morocco

Zineb Lamghari received her Technical University degree in Software Engineering at the Higher School of Technical Education, Mohammed V – Souissi University, Morocco, and her Licence degree in Information Systems Management from Polydisciplinary Faculty then her Master’s degree in Computer System and Network from the Faculty of Technical Sciences, Abdelmalek Essaadi University, Morocco. She prepares her PhD in Business Process Improvement at the Computer Science and Telecommunication Research Laboratory (LRIT), Faculty of Sciences, Mohammed V University. Her interests cover mainly business process management, software engineering and process mining techniques.

Maryam Radgui, SI2M Laboratory and LRIT associated unit to CNRST, Rabat

Maryam Radgui is an Assistant Professor at the National Institute of Statistics and Applied Economics (INSEA) in Rabat. She is a member of the Information Systems, Intelligent Systems and Mathematical Modelling Laboratory (SI2M) of INSEA and she is also a member of the
Computer Science and Telecommunication Research Laboratory (LRIT) in Mohammed V University in Rabat. She received her PhD in Software Engineering from the Mohammed V University in Rabat, Morocco in 2015. Her research interests are mainly focused in information
systems, software development, business process, process mining, reuse and service-based development methods. She has published several papers in international journals, conferences
and workshops.

Rajaa Saidi, SI2M Laboratory and LRIT associated unit to CNRST, Rabat

Rajaa Saidi is an Associate Professor at the National Institute of Statistics and Applied Economics – Rabat (INSEA-Morocco); she is a member of the Information Systems, Intelligent Systems and Mathematical Modelling Laboratory (SI2M) of (INSEA). She holds a PhD degree in
Information Systems and Software Engineering from Mohammed V University of Rabat, Morocco and the Grenoble Institute of Technology (INPG-France). She is also a member of the Computer Science and Telecommunication Research Laboratory (LRIT) in Mohammed V University. Her research areas include information systems, business process management, ubiquitous computing, context-aware information systems, service-oriented architectures and
component-based engineering.

Moulay Driss Rahmani, LRIT associated unit to CNRST (URAC 29), Faculty of Sciences, Mohammed V University in Rabat, Morocco

Moulay Driss Rahmani is a Professor of Higher Education at the Faculty of Sciences Rabat, Morocco. He received his PhD in Computer Science from the Montpellier University,
Department of Semiconductors, Materials and Devices, France. His interests are mainly focused on human-computer interaction, scientific computing and urbanism. He has published several papers in international conferences, workshop and journals on these topics.

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Published

2021-01-19

How to Cite

Lamghari, Z., Radgui, M., Saidi, R., & Rahmani, M. D. (2021). An operational support approach for Mining Unstructured Business Processes. Revista De Informática Teórica E Aplicada, 28(1), 22–38. https://doi.org/10.22456/2175-2745.106277

Issue

Section

Special Issue on Business Process Management