Application of Business Intelligence in supply chain management

Authors
  • Guilherme Vieira de Oliveira

    Universidade Federal de Catalão - UFCAT

    Author

  • Mariana de Oliveira

    Universidade Federal de Catalão - UFCAT

    Author

  • Aline Gonçalves dos Santos

    Universidade Federal de Catalão - UFCAT

    Author

  • Ricardo Ribeiro Moura

    Universidade Federal de Catalão - UFCAT

    https://orcid.org/0000-0003-4336-0260

    Author

  • Lazaro Antônio da Fonseca Junior

    Universidade Federal de Catalão - UFCAT

    https://orcid.org/0000-0002-5830-757X

    Author

Keywords:
Business Intelligence, Decision-Making Process, Supply chain management
Abstract

Supply chain management is one of the key areas in a company's ability to achieve competitive advantage. In this context, Business Intelligence (BI) emerges as an important tool to enhance the effectiveness and efficiency of sector analysis through quick, accurate, and concise information. The aim of this study was to develop and implement a BI system to reduce the execution time of a task called critical list. To accomplish this, the necessary data was identified, data processing and integration between different databases were performed, and the best graphical indicators for dashboard construction based on key information to be displayed were evaluated. As a result, a 60.31% reduction in the execution time of a non-value-added activity for the company was achieved. The analysis of the supply chain using BI allowed the identification of opportunities to enhance manufacturing capabilities, improve supplier management, reduce costs, and optimize deliveries. Proper information management is crucial for making informed decisions and solving problems in the supply chain.

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Cover Image
Published
2023-10-23
Section
OPERATIONS & PRODUCTION PROCESS
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How to Cite

Oliveira, G. V. de, Oliveira, M. de, Santos, A. G. dos, Moura, R. R., & Fonseca Junior , L. A. da. (2023). Application of Business Intelligence in supply chain management. Brazilian Journal of Production Engineering, 9(5), 60-69. https://doi.org/10.47456/bjpe.v9i5.42709