Authors : Gautham Krishna; Nihal Hussain; Newslin S.; Balaji A.

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/y8b4aefk

Scribd : https://tinyurl.com/2p75t68s

DOI : https://doi.org/10.38124/ijisrt/26apr410

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Contemporary supply chains produce massive amounts of operational data in the areas of procurement, storage, logistics, and order fulfillment. Unfortunately, many organizations face the challenge of transforming operational data into valuable insights that can help detect inefficiencies and bottlenecks within the supply chain. This paper proposes a datadriven analytical approach for supply chain bottleneck analysis through the use of Microsoft Power BI. The proposed methodology combines structured supply chain data and leverages systematic data preprocessing, feature development, and key performance indicator modeling to assess performance from a multi-stage operational perspective. Interactive dashboards are designed to display key performance indicators such as order cycle time, on-time delivery rate, supplier delay percentage, and warehouse processing efficiency. Through the assessment of these KPIs within an integrated platform, the methodology facilitates the detection of suppliers with high delay risks, capacity-limited warehouses, and inefficient transportation. The findings of the paper illustrate the potential of business intelligence tools to improve operational visibility and facilitate data-driven evaluation. The findings illustrate the potential of dashboard analytics to improve supply chain visibility and performance analysis. This paper makes a significant contribution to the increasing use of business intelligence and data visualization tools in supply chain management and operational optimization. The system successfully identifies bottlenecks across suppliers, transportation, and locations using interactive KPI-based visualization.

Keywords : Supply Chain Analytics, Business Intelligence, Power BI, Bottleneck Analysis, KPI Modeling, Data Visualization, Decision Support.

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