Jakub Andar, Jakub Dyntar
Adopting Business Intelligence to Enhance Cross-Dock Operations
Číslo: 3/2025
Periodikum: Acta Informatica Pragensia
DOI: 10.18267/j.aip.259
Klíčová slova: Logistics; Cross-docking; Layout; Data visualisation; Business intelligence
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Anotace:
Background: Cross-docking optimization plays a crucial role in supply chain management by enhancing efficiency, reducing costs and streamlining operations. However, challenges arise from inaccurate data and a lack of digital tools to support decision making.
Objective: The objective of this study was to integrate business intelligence (BI) tools with cross-dock operation data to optimize warehouse layout and improve decision making processes.
Methods: A combination of Microsoft Visio and Microsoft Power BI was used to visualize and optimize warehouse layout based on historical cross-dock operation data. The methodology focused on integrating real-time data with spatial layout visualization to minimize total travel distance within the warehouse.
Results: The integration of BI tools led to a 10% reduction in total travel distance, enhancing operational efficiency and reducing costs. The study demonstrates that BI-based decision support tools offer significant advantages over traditional optimization methods. However, challenges remain in scalability, real-time adaptability and user adoption.
Conclusion: The proposed BI-driven solution improved warehouse layout optimization and facilitated data-driven decision making. Future research should explore the integration of BI with other optimization techniques and investigate its scalability in different warehouse environments.
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Objective: The objective of this study was to integrate business intelligence (BI) tools with cross-dock operation data to optimize warehouse layout and improve decision making processes.
Methods: A combination of Microsoft Visio and Microsoft Power BI was used to visualize and optimize warehouse layout based on historical cross-dock operation data. The methodology focused on integrating real-time data with spatial layout visualization to minimize total travel distance within the warehouse.
Results: The integration of BI tools led to a 10% reduction in total travel distance, enhancing operational efficiency and reducing costs. The study demonstrates that BI-based decision support tools offer significant advantages over traditional optimization methods. However, challenges remain in scalability, real-time adaptability and user adoption.
Conclusion: The proposed BI-driven solution improved warehouse layout optimization and facilitated data-driven decision making. Future research should explore the integration of BI with other optimization techniques and investigate its scalability in different warehouse environments.