Moving from Complexity to Clarity in Supply Chain
Supply Chain Analytics
Project Description
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.
Define Objective
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 four main objectives:
1.Business Performance (Profit & Cost) :
- The first objective analyzing the Profit and Cost of Products. By determining this insights, we can identify the organization’s overall performance.
2. Inventory Analysis (Supply vs Demand):
- The second objective is centered around analyzing the ratio between supply and demand for each product in the supply chain.
- By determining the Supply vs Demand ratio, we can identify situations of overstock or understock for individual products. This insight will aid in optimizing inventory management, ensuring products are efficiently stocked and reducing any potential inventory-related inefficiencies.
3. Shipment Delay Analysis:
- This objective involves analyzing the trend of shipment delays over time. By compiling information on the average days of shipment delay.
- Through this analysis, I intend to provide valuable insights into the efficiency of the shipment process, enabling us to identify potential areas for improvement to reduce delays and enhance overall performance.
4. Order Fulfillment Days:
- This Objective involves to analyze how many days it takes for individual products to fulfill the stock.
By focusing on these specific objectives, we aim to gain a comprehensive understanding of supply chain dynamics, highlight potential inefficiencies, and create insightful dashboards that will inform business stakeholders about current challenges and propose structural improvements to enhance overall operations. The smaller objectives allow for a targeted and time-efficient approach in achieving our overarching goals.
Data Overview
In the second step, the data analysis is performed using Python in Jupyter Notebook to gain insights about the data. This involves various data preprocessing, cleaning, and transformation tasks to prepare the data for further analysis.
Notebook Link : here
To view the detailed step-by-step process, you can refer to the provided link. The link will lead you to a comprehensive notebook or script that outlines the data analysis procedures. This step is crucial in understanding the data and extracting valuable information for the subsequent objectives of the project.
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
Data cleaning
- Drop unnecessary columns (Order Item ID, Order Time)
- Fix the datatype of the columns
- Remove special characters in Customer Country column
- Check for missing value
- Check for duplicate value
After cleaning the data files, lets visualize the data using Tableau.
Feature Metric
- Created Date time feature
- Profit Margin : Total Profit / Total Gross Sales *100
- Storage Cost : Inventory cost per unit * Warehouse inventory
- Shipment Delay : Shipment Days Actual — Shipment Days Scheduled
- Inventory to Sales Delta : SUM(Warehouse Inventory)- SUM(Order Quantity)
- Under or Overstock : IF Inventory to Sales Delta >0 THEN ‘Overstock’ ELSE ‘Understock’ END
Parameters :
- Popular Products
- Top N
Key Insights :
1 Profit & Costs :
The monthly profit typically ranges from 104,000 to 135,000 dollars. However, there was a noticeable decline in profit from October to December 2017, which requires further investigation due to potential data limitations.
Most Profitable Product Department :
- Fan Shop : generating approximately $50,000 in monthly profit.
- Other top-profit product departments include Apparel, Golf, and Footwear, which also incur the highest inventory expenses.
Most Profitable Products :
- Perfect Fitness Perfect Rip Deck
- Field & Stream Sportsman 16 Gun Fire Safe
- Nike Men’s Free 5.0+
Goods with Highest Profit Margin :
- Hirzl Women’s Soffft Flex Golf Glove
- Under Armour Women’s Ignite PIP VI Slide
- O’Brien Men’s Neoprene Life Vest
Highest Inventory Storage Cost :
- Highest Storage Cost Spends in Apparel department
- Other top-cost product departments include Golf and Fan Shop
2. Inventory Analysis :
There are some overstock products which basically increasing the storage cost and its demand is less.
Supply vs Demand :
Highest demanding product department is Fan Shop, but its supply(inventory) is compared to less.
Below are overstock and overstock products.
Overstock Product Category :
- Cleats
- Shop By Sport
- Toys
Under stock Product Category :
- Indoor/ Outdoor Games
- Water Sports
- Fishing
3. Shipment Delay Analysis:
The average 61% of shipment delay across all orders. Notably, highest delay experiences are USA, France and Mexico.
The period between January 2015 and May 2016 witnessed the greatest number of orders with delays.
Interestingly, one of most profit margin products, Under Armour Women’s Ignite PIP VI Slide, is also products with the highest average Shipment delay.
4. Order Fulfillment Days:
Product categories Video Games, Crafts, and Women’s Clothing take 8.8, 7.1, and 6.9 (average) days, respectively, to fulfill their stock into the warehouse.
Suggestions :
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.
Thank you for reading. Feel free to give suggestions and tips.
Tableau Dashboard : here
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