Adopting Business Intelligence to Enhance Cross-Dock Operations
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 wa...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Prague University of Economics and Business
2025-08-01
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| Series: | Acta Informatica Pragensia |
| Subjects: | |
| Online Access: | https://aip.vse.cz/artkey/aip-202503-0002_adopting-business-intelligence-to-enhance-cross-dock-operations.php |
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| Summary: | 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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| ISSN: | 1805-4951 |