Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach

Article Subjects > Engineering Europe University of Atlantic > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Project-based organizations need to procure different commodities, and the failure/success of a project depends heavily on procurement management. Companies must refine and develop methods to simplify and optimize the procurement process in a highly competitive environment. This paper presents a methodology to help managers of project-based organizations analyze procurement processes to determine the optimal framework for simultaneously addressing multiple objectives. These goals include minimizing the time between the generation and required approval for a purchase, identifying unnamed activities, and allocating the budget efficiently. In this paper, we apply process mining algorithms to a dataset consisting of event logs on Oracle Financials-based enterprise resource planning (ERP) procurement processes in ERP systems and demonstrate interesting results leading to project procurement intelligence (PPI). The provided log data is the real-life data consisting of 180,462 events referring to seven activities within 43,101 cases. The logged procurement processes are filtered and analyzed using the open-source process mining frameworks PrOM and Disco. As a result of the process mining activities, a simulation of the discovered process model derived from the event log of the entire procurement process is presented, and the most frequent potential behaviors are identified. This analysis and extraction of frequent processes from corporate event logs help organizations understand, adapt, and redesign procurement operations and, most importantly, make them more efficient and of higher quality. This study shows that after the successful formulation of guiding principles, data refinement, and process structure optimization, the case study results are considered significant by the organization’s management. metadata Butt, Naveed Anwer and Mahmood, Zafar and Sana, Muhammad Usman and Díez, Isabel de la Torre and Castanedo Galán, Juan and Brie, Santiago and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, santiago.brie@uneatlantico.es, UNSPECIFIED (2023) Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach. Applied Sciences, 13 (7). p. 4145. ISSN 2076-3417

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Official URL: http://doi.org/10.3390/app13074145

Abstract

Project-based organizations need to procure different commodities, and the failure/success of a project depends heavily on procurement management. Companies must refine and develop methods to simplify and optimize the procurement process in a highly competitive environment. This paper presents a methodology to help managers of project-based organizations analyze procurement processes to determine the optimal framework for simultaneously addressing multiple objectives. These goals include minimizing the time between the generation and required approval for a purchase, identifying unnamed activities, and allocating the budget efficiently. In this paper, we apply process mining algorithms to a dataset consisting of event logs on Oracle Financials-based enterprise resource planning (ERP) procurement processes in ERP systems and demonstrate interesting results leading to project procurement intelligence (PPI). The provided log data is the real-life data consisting of 180,462 events referring to seven activities within 43,101 cases. The logged procurement processes are filtered and analyzed using the open-source process mining frameworks PrOM and Disco. As a result of the process mining activities, a simulation of the discovered process model derived from the event log of the entire procurement process is presented, and the most frequent potential behaviors are identified. This analysis and extraction of frequent processes from corporate event logs help organizations understand, adapt, and redesign procurement operations and, most importantly, make them more efficient and of higher quality. This study shows that after the successful formulation of guiding principles, data refinement, and process structure optimization, the case study results are considered significant by the organization’s management.

Item Type:	Article
Uncontrolled Keywords:	process mining; event log analysis; real-life application; procurement process; Petri net; heuristic miner
Subjects:	Subjects > Engineering
Divisions:	Europe University of Atlantic > Research > Scientific Production Fundación Universitaria Internacional de Colombia > Research > Scientific Production Ibero-american International University > Research > Scientific Production Ibero-american International University > Research > Scientific Production Universidad Internacional do Cuanza > Research > Scientific Production
Date Deposited:	17 Apr 2023 23:30
Last Modified:	17 Apr 2023 23:30
URI:	https://repositorio.unic.co.ao/id/eprint/6774

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Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach

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