🚀 Data Analyst Project Series – Part 9

Supply Chain Analytics Project

🎯 Project Goal

The goal of this project is to analyze supply chain operations and discover insights related to:

• Inventory management

• Shipment tracking

• Supplier performance

• Delivery delays

• Warehouse efficiency

• Demand forecasting

Supply Chain Analytics is extremely important because businesses depend on smooth product movement and inventory management.

This project is widely used in:

• Manufacturing companies

• E-commerce businesses

• Logistics companies

• Retail chains

• Warehousing firms

🛠 STEP 1: Choose the Dataset

Recommended Dataset Types

Search on Kaggle:

• Supply Chain Dataset

• Logistics Dataset

• Inventory Management Dataset

• Shipment Tracking Dataset

📂 STEP 2: Understand the Dataset

Common Columns

Column Name : Meaning

Order ID : Unique order number

Product ID : Product identifier

Supplier : Supplier name

Warehouse : Storage location

Inventory Level : Available stock

Shipment Date : Shipping date

Delivery Date : Delivery completion date

Delivery Status : Delivered/Delayed

Transportation Cost : Shipping expense

Region : Delivery location

Demand Forecast : Predicted demand

🧹 STEP 3: Data Cleaning

Supply chain data often contains:

• Duplicate shipment records

• Missing delivery dates

• Incorrect inventory values

• Inconsistent supplier names

✔ Cleaning Tasks

Remove Duplicate Orders

Check:

• Duplicate Order IDs

Handle Missing Values

Common missing fields:

• Delivery Date

• Supplier

• Transportation Cost

Methods:

• Replace missing values

• Remove incomplete rows carefully

Standardize Categories

Example:

• “Delayed”

• “delay”

• “DELAYED”

Convert into one standard format.

Correct Date Formats

Examples:

• Shipment Date

• Delivery Date

Convert into proper date format.

📊 STEP 4: Define Supply Chain KPIs

Essential KPIs

✔ Total Orders

COUNT(Order_ID)

✔ Average Delivery Time

Purpose:

Measures delivery efficiency.

✔ Inventory Turnover Ratio

Purpose:

Measures inventory management efficiency.

✔ Delivery Success Rate

Purpose:

Tracks successful deliveries.

✔ Total Transportation Cost

SUM(Transportation_Cost)

🗄 STEP 5: Analyze Supply Chain Data Using SQL

📌 SQL Query Examples

1. Supplier Performance Analysis

SELECT Supplier,

COUNT(*) AS Total_Orders

FROM Supply_Chain_Data

GROUP BY Supplier

ORDER BY Total_Orders DESC;

2. Delayed Deliveries

SELECT COUNT(*) AS Delayed_Orders

FROM Supply_Chain_Data

WHERE Delivery_Status = 'Delayed';

3. Warehouse-wise Inventory Levels

SELECT Warehouse,

SUM(Inventory_Level) AS Total_Inventory

FROM Supply_Chain_Data

GROUP BY Warehouse

ORDER BY Total_Inventory DESC;

4. Transportation Cost by Region

SELECT Region,

SUM(Transportation_Cost) AS Total_Cost

FROM Supply_Chain_Data

GROUP BY Region

ORDER BY Total_Cost DESC;

**5.