This is a supply chain analytics project. In which conducted an analysis of supply chain inefficiencies, and developed informative dashboards to inform business stakeholders of potential issues, along with proposing strategic business enhancements.
Blog Post : Here
Tableau Dashboard Link : Here
The project provides a real-world dataset focusing on supply chain analytics. As the main data analyst for Just In Time, you will help solve key shipment and inventory management challenges, analyze supply chain inefficiencies, and create insightful dashboards to inform business stakeholders about potential problems and propose structural business improvements.
In this project, my primary focus is on addressing key challenges related to shipment and inventory management within the supply chain. To achieve this goal efficiently, the project has been divided into few objectives:
Business demand analysis
Requirements: Create dashboard to analyze the business problem and improve the supply chain’s efficiency
Method: descriptive and exploratory analysis
Tool used: Python (Data preprocessing, data cleaning, EDA, inventory segmentation); Tableau (Dashboard)
Business Performance :
=> Dashboard of overall business performance including Profit & Cost of Products, total profit, best products etc
Inventory Management :
=> Dashboard of inventory management including warehouse inventory, Supply/Demand by Product Department, Inventory Storage Cost, Most Overstock products, Most understock products etc
Shipment Invenstigation :
=> Dashboard of shipping management including delay shipping like % of delapy orders, overall delay evolution, shupping delay by location, Most deplayed products etc
Order Fullfillment :
=> Dashboard of average warehouse inventory fullfilment by Product Category
Overall story of Create an interactive dashboard to summarize the research of the problem of the supply chain and suggest the solution
The data pre-procesing and Data cleaning is done using Python. Detailed Notebook : Here
The dataset provides three data tables including order_and_shipment, inventory and fulfillment. After examining the data fields, I noticed that the dataset generally represents the following key information
Customer: General information about customers including identifiers and addresses
Order: Information about the order including date of order, product and quantity ordered, order value
Shipment: Shipping information including shipping date, shipping mode
Product: Specific information about the ordered item including product name, product category, product department
Warehouse Inventory: Information on inventory management for each product name including monthly inventory, warehouse location, storage costs, order fulfillment
1 Profit & Cost :
- Most Profitable Product Department
- Most Profitable Products
- Goods with Highest Profit Margin
- Highest Inventory Storage Cost
2 Inventory Analysis :
- Supply Vs Demand
- Overstock Product Category :
- Under stock Product Category :
3 Shipment Delay Analysis:
4 Order Fulfillment Days:
Detailed analysis including feature metric, Key insights and suggestion can be found of medium Blog Post : Here
Optimize Product Inventory : To improve profits and save on storage costs, we need to optimize our inventory, especially for most profitable and popular products worldwide. It is important to study demand patterns and adjust stock levels to avoid running out during peak periods and reduce excess inventory during slower times. Maintaining a reasonable buffer above expected demand during busy seasons can prevent shortages and optimize inventory expenses.
Reorganize Inventory Distribution : The Fan Shop department’s inventory is insufficient compared to its demand, which may result in missed the sales opportunities. The company should take steps to increase inventory Consider reorganizing inventory distribution between warehouses to reduce shipment delays. Minimizing delays in highly demand products can improve customer satisfaction.
Marketing Strategies : Focus on promoting products with the highest profit margins to increase overall revenue. Consider advertising the top products with the highest profit margins and offer targeted discounts during peak seasons to boost sales and customer engagement.
Monitor Shipment Delays : A further analysis is needed to identify the reasons for shipment delays and implement corrective measures to reduce them. Analyzing shipment processes and addressing potential bottlenecks can lead to improved fulfillment efficiency and customer satisfaction.