Optimization of Sports Equipment Management through Business Intelligence: Cantonal Sports Federations

Authors

Abstract

The research developed a web-based system using Business Intelligence to optimize the management of sports equipment in cantonal sports federations. The main objective was to improve decision-making and operational efficiency through a platform that simplifies the registration and tracking of processes related to the delivery, receipt, and request of sports equipment. A mixed methodological approach was used, including structured interviews and Fuzzy Cognitive Maps for information processing. The analysis revealed the interconnection between multiple factors affecting the management of sports equipment, providing a solid foundation to address existing challenges. The proposal was based on the Kanban methodology, implemented through visual boards for project management. Limits for work in progress were established, and a clear workflow was defined, using Excel to create the Kanban board. The developed system integrates modern technologies such as HTML5, CSS, and JavaScript with BI tools, offering an intuitive interface and advanced functionalities such as dynamic report generation, real-time inventory tracking, and predictive analysis for acquisition planning. Preliminary results indicate a substantial improvement in operational efficiency, inventory control accuracy, and decision-making quality. This technological solution radically transforms the management of sports equipment, representing the main achievement of the research.

Keywords: Decision-making, sports management, sports equipment, cantonal federations.

Published

2024-09-05

How to Cite

Albarracin Zambrano, L. O., Edmundo José, J. A., Molina Chalacan, L. J., & Quintanilla Diaz, N. M. (2024). Optimization of Sports Equipment Management through Business Intelligence: Cantonal Sports Federations. Revista Científica Cultura, Comunicación Y Desarrollo, 9(3), 105–111. Retrieved from https://rccd.ucf.edu.cu/index.php/aes/article/view/636