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Implementing Key Performance Indicators and Designing Dashboard Solutions in an Automotive Components Company: A Case Study

Author

Listed:
  • Francisco Nunes

    (Department of Electromechanical Engineering, Faculty of Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal)

  • Edgar Alexandre

    (ACI—Automotive Compounding Industry Ldª/Perplastic Group, 6300-625 Guarda, Portugal)

  • Pedro Dinis Gaspar

    (Department of Electromechanical Engineering, Faculty of Engineering, University of Beira Interior, 6201-001 Covilhã, Portugal
    C-MAST—Centre for Mechanical and Aerospace Science and Technologies, 6201-001 Covilhã, Portugal)

Abstract

In the context of highly competitive markets, organizations face dynamic challenges, requiring effective solutions to maintain and enhance their competitive standing. Performance measurement, supported by advanced information systems, is critical for organizational improvement. This study involves the implementation of key performance indicators (KPIs) within an automotive components company. Insights from employees across various departments were gathered for the development and deployment of 22 new KPIs across the Purchasing, Sales, Logistics, Quality, Human Resources, Occupational Health and Safety, Research and Development, and Finance departments of the company. The new indicators implemented were applied to all the group’s companies and standardized throughout the companies’ group. As a result, the implementation of new indicators and the consultation of graphs and visual elements present in the dashboards developed using Power BI enabled senior managers to make detailed and precise analyses, which led to faster and more considered decisions. It also enabled senior managers to make comparisons between the results of the group’s different companies by looking at dynamic, interactive graphs. The methodologies and tools discussed (KPIs and dashboards) have broader applications across different industries, highlighting the relevance and versatility of KPIs and dashboards in organizational performance management.

Suggested Citation

  • Francisco Nunes & Edgar Alexandre & Pedro Dinis Gaspar, 2024. "Implementing Key Performance Indicators and Designing Dashboard Solutions in an Automotive Components Company: A Case Study," Administrative Sciences, MDPI, vol. 14(8), pages 1-16, August.
  • Handle: RePEc:gam:jadmsc:v:14:y:2024:i:8:p:175-:d:1454538
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    References listed on IDEAS

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    1. Merendino, Alessandro & Dibb, Sally & Meadows, Maureen & Quinn, Lee & Wilson, David & Simkin, Lyndon & Canhoto, Ana, 2018. "Big data, big decisions: The impact of big data on board level decision-making," Journal of Business Research, Elsevier, vol. 93(C), pages 67-78.
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