Enterprise Supply Chain Logistics Analysis is an end-to-end Power BI analytics solution designed to monitor and optimize supply chain operations through interactive dashboards and business intelligence reporting.
The project focuses on delivery performance, inventory risk monitoring, supplier quality assessment, operational efficiency, and order-level analysis. The dashboard provides actionable insights that support data-driven decision-making across logistics and supply chain functions.
Supply chain organizations face challenges related to:
- Delivery delays
- Inventory shortages
- Product damages
- Supplier performance monitoring
- Logistics efficiency
- Operational visibility
The objective of this project is to develop an interactive Power BI dashboard that enables stakeholders to identify operational bottlenecks, monitor key performance indicators, and improve supply chain performance.
The project uses a simulated enterprise supply chain dataset containing operational, inventory, warehouse, supplier, and logistics information.
- One Year of Operational Data
- 100,000 Orders
- Multiple Warehouses
- Multiple Suppliers
- Multiple Delivery Partners
- Multiple Product Categories
- Revenue and Profit Metrics
- Inventory Monitoring Metrics
- Delivery Performance Metrics
- Fact_Orders
- Dim_Product
- Dim_Customer
- Dim_Supplier
- Dim_Warehouse
- Dim_Partner
The data model follows a star schema approach for efficient reporting and analytical performance.
Executive landing page providing an overall snapshot of supply chain performance.
- Total Orders
- Total Revenue
- Delayed Orders
- Inventory Risk Orders
- Damage Orders
- High Delay Rate
- Revenue Contribution
- Top Revenue Category
- Inventory Risk Status
Provides high-level operational and financial performance analysis.
- Revenue by Category
- Delay Reason Analysis
- Revenue and Profit by Region
- Damage Percentage by Supplier
- Total Revenue
- Net Profit
- Total Orders
- Delay Percentage
- Average Delivery Rating
Focused on delivery efficiency and delay investigation.
- Delay Performance Heatmap
- Delay Reason Analysis
- Delay Percentage by Weather Condition
- Delivery Partner Analysis
- On-Time Delivery Percentage
- Delayed Orders
- Average Delivery Time
- Damage Percentage
- Average Delivery Rating
Monitors inventory health and stock exposure.
- Inventory Risk Heatmap
- Inventory versus Safety Stock
- At Risk Inventory by Category
- Total Inventory
- Safety Stock
- At Risk Orders
- Inventory Risk Percentage
- Inventory Buffer
Operational drill-through page for detailed order-level analysis.
- Order Tracking
- Delivery Status Monitoring
- Revenue Tracking
- Profit Tracking
- Inventory Risk Monitoring
- Damage Monitoring
| KPI | Description |
|---|---|
| Total Revenue | Total revenue generated from orders |
| Net Profit | Overall profitability |
| Total Orders | Number of processed orders |
| Delay Percentage | Percentage of delayed orders |
| On-Time Delivery Percentage | Orders delivered on schedule |
| Average Delivery Rating | Customer delivery satisfaction |
| Damage Percentage | Percentage of damaged orders |
| Inventory Risk Percentage | Inventory below safety stock |
| Inventory Buffer | Available inventory above safety threshold |
- More than 80 percent of orders experienced delivery delays.
- Customs Clearance Delay was the largest contributor to delayed deliveries.
- Severe Weather Impact was the second largest contributor to delivery delays.
- Electronics generated the highest revenue contribution among all categories.
- East region contributed the highest overall revenue share.
- Approximately 15 percent of inventory remained below safety stock levels.
- Certain product categories showed higher inventory exposure compared to others.
- Damage rates varied significantly across suppliers.
- Supplier-level monitoring can help reduce damaged shipments and improve service quality.
- Power BI Desktop
- Power Query
- DAX
- Data Modeling
- Microsoft Excel
- Data Visualization
- Business Intelligence Reporting
enterprise-supply-chain-logistics-analysis/
│
├── 01_raw_data/
│ └── Enterprise_Supply_Chain_Dataset.xlsx
│
├── 02_powerbi_report/
│ └── Enterprise_Supply_Chain_Logistics_Analysis.pbix
│
├── 03_documentation/
│ └── Business_Requirements_&_Data_Dictionary.txt
│
├── assets/
│ ├── home_page.png
│ ├── executive_overview.png
│ ├── delivery_performance.png
│ ├── inventory_risk.png
│ └── order_details.png
│
└── README.md
- Download the repository.
- Open the Power BI report located inside the 02_powerbi_report folder.
- Refresh the dataset if required.
- Interact with filters and slicers to explore operational insights.
- Navigate across dashboard pages using the built-in navigation menu.
✔ End-to-End Supply Chain Analytics
✔ Executive-Level KPI Monitoring
✔ Delivery Performance Investigation
✔ Inventory Risk Assessment
✔ Supplier Quality Analysis
✔ Interactive Power BI Dashboard
✔ Star Schema Data Modeling
✔ DAX-Based KPI Development
Email: vipul.paighan.in@gmail.com
GitHub: https://github.com/vipulsystems
This project is intended for educational, portfolio, and demonstration purposes.