Supply chain analysis

This repository presents a comprehensive analysis of the supply chain using Power BI Desktop. The main goal is to monitor Key Performance Indicators (KPIs) and evaluate the performance of products, logistics, and suppliers. The report is designed to make data exploration easy, allowing users to understand key factors affecting operational efficiency and profitability.

Metric Value

 The report highlights variations in **revenue**, **defect rates**, and **profit margins** across different product categories.

Product Type Total Revenue Avg. Defect Rate % Avg. Profit Margin %

Total Revenue by Shipping Carriers:

• Carrier B leads with $250,095
• Followed by Carrier C with $184,880
• And Carrier A with $142,630

Cost and Defect Rate by Transportation Mode:

• Road: Highest cost share (30.52%) and highest defect rate (28.87%)
• Rail: 28.71% of total cost
• Air: 27.25% of total cost, lowest defect rate (20.09%)
• Sea: 13.52% of total cost

 Supplier performance was evaluated based on **profit margin** and **stock level**: - **Supplier 3** achieved the highest profit margin (**91.08%**) - **Supplier 1** holds the highest stock level (**1,142 units**) - **Supplier 3** has the lowest stock level (**654 units**)

Revenue contribution by demographic segments:

• Unknown: 50.11% ($289K)
• Female: 27.96% ($162K)
• Male: 21.92% ($127K)

The report also includes a detailed SKU-level analysis, covering:

• Stock levels
• Order quantities
• Lead time (delivery performance)

Top 5 SKUs by revenue: SKU51, SKU38, SKU31, SKU90, and SKU2.

• Esraa Kamal
• Nabha Ahmed
• Rufyda Rahma
• Marwa Khalil

We complement each other’s skills, cover gaps, and push each other to grow 🚀

• Power BI Desktop – for visualization and dashboard design
• Excel – for data cleaning and preprocessing
• Figma – UX Design

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