ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector

Kevin J. Rojas; Emerson M. Dávila; Pedro Castañeda

doi:10.1007/978-3-031-64359-0_29

ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector

Kevin J. Rojas
, Emerson M. Dávila
, Pedro Castañeda

Research output: Chapter in Book/Report › Conference contribution › peer-review

Abstract

The logistics process in small and medium-sized enterprises (SMEs) in the industrial sector is often exposed to various challenges, such as information loss, redundant activities, prolonged waiting times, and delivery failures, due to poor logistics management. In response to this problem, the implementation of an ERP system based on Process Mining is proposed to enhance the management of the logistics process in SMEs within the industrial sector. This system represents a comprehensive technological solution specifically designed to address logistics inefficiencies and optimize processes in the supply chain of these companies. As part of the evaluation methodology, performance indicators have been established to discuss the results obtained. These indicators have been defined using the Celonis tool, which has been employed for process mining. Findings obtained from the analysis of 30,000 records validate the optimization of the logistics process in companies within this sector, demonstrating a significant reduction in the percentage of key indicators for undesired activities in the logistics process.

Original language	American English
Title of host publication	Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers
Editors	Shuliang Li
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	375-387
Number of pages	13
ISBN (Print)	9783031643583
DOIs	https://doi.org/10.1007/978-3-031-64359-0_29
State	Indexed - 2024
Externally published	Yes
Event	10th International Conference on Information Management, ICIM 2024 - Cambridge, United Kingdom Duration: 8 Mar 2024 → 10 Mar 2024

Publication series

Name	Communications in Computer and Information Science
Volume	2102 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	10th International Conference on Information Management, ICIM 2024
Country/Territory	United Kingdom
City	Cambridge
Period	8/03/24 → 10/03/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

ERP
Logistics
Process
Process Mining
SMEs

Access to Document

10.1007/978-3-031-64359-0_29

Cite this

Rojas, K. J., Dávila, E. M., & Castañeda, P. (2024). ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector. In S. Li (Ed.), Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers (pp. 375-387). (Communications in Computer and Information Science; Vol. 2102 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-64359-0_29

Rojas, Kevin J. ; Dávila, Emerson M. ; Castañeda, Pedro. / ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector. Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. editor / Shuliang Li. Springer Science and Business Media Deutschland GmbH, 2024. pp. 375-387 (Communications in Computer and Information Science).

@inproceedings{cbe2a34775a14a8d87a3f6369f77ff26,

title = "ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector",

abstract = "The logistics process in small and medium-sized enterprises (SMEs) in the industrial sector is often exposed to various challenges, such as information loss, redundant activities, prolonged waiting times, and delivery failures, due to poor logistics management. In response to this problem, the implementation of an ERP system based on Process Mining is proposed to enhance the management of the logistics process in SMEs within the industrial sector. This system represents a comprehensive technological solution specifically designed to address logistics inefficiencies and optimize processes in the supply chain of these companies. As part of the evaluation methodology, performance indicators have been established to discuss the results obtained. These indicators have been defined using the Celonis tool, which has been employed for process mining. Findings obtained from the analysis of 30,000 records validate the optimization of the logistics process in companies within this sector, demonstrating a significant reduction in the percentage of key indicators for undesired activities in the logistics process.",

keywords = "ERP, Logistics, Process, Process Mining, SMEs",

author = "Rojas, \{Kevin J.\} and D{\'a}vila, \{Emerson M.\} and Pedro Casta{\~n}eda",

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doi = "10.1007/978-3-031-64359-0\_29",

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Rojas, KJ, Dávila, EM & Castañeda, P 2024, ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector. in S Li (ed.), Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. Communications in Computer and Information Science, vol. 2102 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 375-387, 10th International Conference on Information Management, ICIM 2024, Cambridge, United Kingdom, 8/03/24. https://doi.org/10.1007/978-3-031-64359-0_29

ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector. / Rojas, Kevin J.; Dávila, Emerson M.; Castañeda, Pedro.
Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. ed. / Shuliang Li. Springer Science and Business Media Deutschland GmbH, 2024. p. 375-387 (Communications in Computer and Information Science; Vol. 2102 CCIS).

Research output: Chapter in Book/Report › Conference contribution › peer-review

TY - GEN

T1 - ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector

AU - Rojas, Kevin J.

AU - Dávila, Emerson M.

AU - Castañeda, Pedro

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024

Y1 - 2024

N2 - The logistics process in small and medium-sized enterprises (SMEs) in the industrial sector is often exposed to various challenges, such as information loss, redundant activities, prolonged waiting times, and delivery failures, due to poor logistics management. In response to this problem, the implementation of an ERP system based on Process Mining is proposed to enhance the management of the logistics process in SMEs within the industrial sector. This system represents a comprehensive technological solution specifically designed to address logistics inefficiencies and optimize processes in the supply chain of these companies. As part of the evaluation methodology, performance indicators have been established to discuss the results obtained. These indicators have been defined using the Celonis tool, which has been employed for process mining. Findings obtained from the analysis of 30,000 records validate the optimization of the logistics process in companies within this sector, demonstrating a significant reduction in the percentage of key indicators for undesired activities in the logistics process.

AB - The logistics process in small and medium-sized enterprises (SMEs) in the industrial sector is often exposed to various challenges, such as information loss, redundant activities, prolonged waiting times, and delivery failures, due to poor logistics management. In response to this problem, the implementation of an ERP system based on Process Mining is proposed to enhance the management of the logistics process in SMEs within the industrial sector. This system represents a comprehensive technological solution specifically designed to address logistics inefficiencies and optimize processes in the supply chain of these companies. As part of the evaluation methodology, performance indicators have been established to discuss the results obtained. These indicators have been defined using the Celonis tool, which has been employed for process mining. Findings obtained from the analysis of 30,000 records validate the optimization of the logistics process in companies within this sector, demonstrating a significant reduction in the percentage of key indicators for undesired activities in the logistics process.

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KW - Logistics

KW - Process

KW - Process Mining

KW - SMEs

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M3 - Conference contribution

AN - SCOPUS:85200477811

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T3 - Communications in Computer and Information Science

SP - 375

EP - 387

BT - Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers

A2 - Li, Shuliang

PB - Springer Science and Business Media Deutschland GmbH

T2 - 10th International Conference on Information Management, ICIM 2024

Y2 - 8 March 2024 through 10 March 2024

ER -

Rojas KJ, Dávila EM, Castañeda P. ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector. In Li S, editor, Information Management - 10th International Conference, ICIM 2024, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2024. p. 375-387. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-64359-0_29

ERP System Based on Process Mining for Improving Logistic Management Efficiency in Small and Medium-Sized Enterprises in the Industrial Sector

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Fingerprint

Cite this