eprintid: 6774 rev_number: 9 eprint_status: archive userid: 2 dir: disk0/00/00/67/74 datestamp: 2023-04-17 23:30:08 lastmod: 2023-04-17 23:30:09 status_changed: 2023-04-17 23:30:08 type: article metadata_visibility: show creators_name: Butt, Naveed Anwer creators_name: Mahmood, Zafar creators_name: Sana, Muhammad Usman creators_name: Díez, Isabel de la Torre creators_name: Castanedo Galán, Juan creators_name: Brie, Santiago creators_name: Ashraf, Imran creators_id: creators_id: creators_id: creators_id: creators_id: juan.castanedo@uneatlantico.es creators_id: santiago.brie@uneatlantico.es creators_id: title: Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach ispublished: pub subjects: uneat_eng divisions: uneatlantico_produccion_cientifica divisions: unincol_produccion_cientifica divisions: uninimx_produccion_cientifica divisions: uninipr_produccion_cientifica divisions: unic_produccion_cientifica full_text_status: public keywords: process mining; event log analysis; real-life application; procurement process; Petri net; heuristic miner 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. date: 2023 publication: Applied Sciences volume: 13 number: 7 pagerange: 4145 id_number: doi:10.3390/app13074145 refereed: TRUE issn: 2076-3417 official_url: http://doi.org/10.3390/app13074145 access: open language: en citation: Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica Universidad Internacional Iberoamericana México > Investigación > Producción Científica Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica Universidad Internacional do Cuanza > Investigación > Producción Científica 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; Mahmood, Zafar; Sana, Muhammad Usman; Díez, Isabel de la Torre; Castanedo Galán, Juan; Brie, Santiago y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, juan.castanedo@uneatlantico.es, santiago.brie@uneatlantico.es, SIN ESPECIFICAR (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 document_url: http://repositorio.unini.edu.mx/id/eprint/6774/1/applsci-13-04145-v2.pdf