Enhancing Inventory Management through Real-Time Power BI Dashboards and KPI Tracking
Effective inventory management is essential for op- timizing supply chain operations, reducing costs, and ensuring seamless product availability. Traditional inventory tracking methods often lead to inefficiencies due to delayed data updates and a lack of real-time insights. This study explores how Power BI dashboards and Key Performance Indicator (KPI) tracking can revolutionize inventory management by providing real-time visibility, data-driven decision-making, and predictive analytics. Power BI integrates with databases like SQL Server and cloud- based platforms such as Microsoft Azure, enabling businesses to monitor stock levels, forecast demand, and optimize ware- house operations through interactive dashboards. By leveraging essential KPIs—including stock turnover ratio, demand forecast accuracy, and order fulfillment rate—organizations can proac- tively manage inventory levels, reduce holding costs, and improve supply chain responsiveness. Additionally, this study examines the challenges associated with real-time inventory tracking, such as data integration complexities, cybersecurity risks, and system scalability. The findings highlight that companies using Power BI for inventory management enhanced efficiency, improved decision-making, and reduced operational risks. This research underscores the significance of real-time business intelligence tools in modern inventory management and proposes future enhancements, including AI-driven forecasting and IoT-based monitoring, to further optimize supply chain operations.
Authors
- Srikanth Yerra (ORCID: https://orcid.org/0000-0002-5636-6568)
Institutions
- University of Tennessee Health Science Center (US)
Publication Details
- Journal
- International Journal of Scientific Research in Computer Science Engineering and Information Technology
- Published
- 2025-03-14
- DOI
- https://doi.org/10.32628/cseit25112458
- Citations
- 7
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 16.23