Supply Chain Analytics Use Case

But before we begin, if you're someone who wants to build projects for Data Science Portfolio then keep your tabs on what's happening in the world of Data Science & Businesses, and Hit EARLY ACCESS if you haven't already. 

If you already have Early Access, you can just go ahead and read our Data Story! 😀

‍

‍

No surprise, right? Managing supply chains is getting trickier. It's a challenge for businesses but also has great potential.

A recent study found that only about 22% of companies are really getting strategic about their supply chain networks. That's a bit of a wake-up call, isn't it?

Talking about data, the Logistic Sector is a data goldmine. Tons of it flows in daily, and guess whose job it is to track and report it to stakeholders like the supply chain manager? 

Yup, us data analysts!

Reporting isn't just about numbers and Charts; it's understanding what the supply chain manager wants.

Thankfully! In this use case, we'll help you figure out What are needs, wants, goals and objectives so we can give them the insights they crave.

Let's start by understanding the data.

‍

About Dataset

Let’s Inspect our Superstore dataset. This dataset got all the deeds on sales – order IDs, order and shipping dates, shipping mode, customer names and where they're at, plus product info like category and name. And of course, we've got the numbers – sales amount, quantity, discounts, and profit. 

This data enables analysis of sales performance, profitability, and customer behavior to improve supply chain management decisions. Here are some sample Rows & Columns of the Superstore Dataset.

‍

‍

‍

Each row in the dataset corresponds to an order made by a customer. We have the following features:

Order Shipment : 

‍

Product : 

‍

Other Feature : 

‍

The SuperStore Dataset contains over 10194 orders and 13 of our Columns have String Data type, 4 of our Columns have Integers Data Type and 2 of the columns have Date Data Type.

‍

How to Analyze Supply Chain Optimization and Performance Analysis?

To start with the analysis of chain optimization and its performance, it is necessary to follow the 4 factors of Data Analysis and that are : 

• 1. Identify the users or stakeholders for the dashboard.
• 2. Design Empathy Map to define Users' Goals and Challenges or pain points.
• 3. Identify Metrics or KPIs Matter the Most.
• 4. Understand the Objectives and Goals.
• 5. Ask Business Questions

I know it looks a bit overwhelming that’s why in this article, we'll lay the foundation for a top-notch supply chain optimization analysis. 

‍

Step 1: Identify the users or stakeholders for the analysis.

Define the User or stakeholder  who will use the supply chain data story. In our case, We’ll use a Supply Chain Manager. Recognizing their diverse needs, challenges, and priorities becomes the cornerstone for tailoring an effective data story. 

‍

User Persona : Supply Chain Manager

Responsibilities:

• Optimizing supply chain processes to improve efficiency and reduce costs.
• Managing inventory levels to meet customer demand while minimizing holding costs.
• Ensuring timely delivery of products to customers.
• Collaborating with suppliers and logistics partners to streamline operations.

Needs:

• Access to comprehensive supply chain data for analysis and decision-making.
• Tools for inventory management and demand forecasting.
• Regular updates on inventory levels, order fulfillment, and delivery performance.

Challenges:

• Balancing inventory levels to avoid stockouts while minimizing holding costs.
• Addressing disruptions in the supply chain, such as delays or shortages.
• Ensuring compliance with regulatory requirements and quality standards.

Since, we have defined the User Persona & have mapped the needs, challenges and responsibilities. Our Next step will be to design an Empathy Map which will map the pain points of the user.

‍

Step 2: Design Empathy Map

To truly connect with the experiences and expectations of Supply Chain Manager, the creation of an empathy map is invaluable. This visual tool allows for a deeper understanding of the emotions, aspirations, and pain points of users. 

By empathizing with their perspectives, we can design a data story that not only meets functional requirements but also resonates with the human elements of their roles.

‍

Step 3: Identify the Key Performance Indicators (KPI’s)

The heartbeat of any analysis lies in KPI’s and their Metrics. It's crucial to identify the KPIs that matter most to achieving the defined objectives and by focusing on the most relevant metrics, organizations can gain actionable insights into their supply chain operations. 

‍

Step 4: Understand the Goals & Objectives of User

Now, on the basis of Empathy Map and KPI’s, we need to define our goals and objectives of the Users. So, that it will align with the data story functionalities to ensure decision making. Here are the Key Objectives & Goals : 

Objective : To enhance supply chain efficiency and profitability by analyzing sales, profit, and shipment data to optimize shipping methods, improve same-day delivery performance, maximize regional impact, and optimize technology subcategory performance.

Goals : To Improve supply chain efficiency and reduce costs, enhance customer satisfaction through timely delivery and product availability, strengthen relationships with suppliers and logistics partners and mitigate risks and uncertainties in the supply chain.

Based on the defined goals & objectives, your next step will be to provide actionable insights to make a mark on Business Decisions.

Actionable Insight: Refrain from shipping machines via same-day delivery mode due to their profitability constraints. Allocate machines to more cost-effective shipping methods to mitigate losses and improve overall profitability within the same-day.

‍

Step 5 : Ask Business Questions

Beyond KPI’s, organizations must engage in business-driven inquiry. This involves asking strategic questions that directly align with overarching business objectives. 

‍

Q1) What Are the Sales And Profit By Ship Mode?

Metrics: Total sales amount, total profit generated

Key Analysis: Calculate total sales and profit for each mode of shipment (e.g., standard, express, same-day) to determine the most profitable and efficient shipping methods.

‍

Q2) How Are Sales And Profit Performing Yearly On Same-Day Ship Mode?

Metrics: Yearly sales, yearly profit

Key Analysis: Evaluate the yearly performance of sales and profit specifically for same-day shipments to identify trends and potential areas for improvement in same-day delivery services.

‍

Q3) Which Region Is Not Performing On Same-Day Mode In 2023?

Metrics: Same-day shipment performance by region

Key Analysis: Identify the region that is underperforming in terms of same-day shipments in 2023 based on metrics such as sales, profit, and delivery efficiency.

‍

Q4) What Is Category Wise Impact In South Region In Year 2023?

Metrics: Sales and profit by product category

Key Analysis: Analyze the impact of different product categories on sales and profit in the South region during 2023 to understand which categories contribute the most to performance in the region.

‍

Q5) Technology Subcategory Profit And Sales In South Region Same Day 2023?

Metrics: Sales, profit (by category and subcategory by Region)

Key Analysis: Dive deeper into the performance of the Technology subcategory specifically for same-day shipments in the South region in 2023 to understand the factors influencing its profitability and sales within the same-day delivery segment.

‍

Explore Supply Chain Analytics Data Story Here👇

By framing this data story in alignment with business goals, organizations can get deeper insights that drive impactful decisions.

Conclusion

By combining a user-centric approach with data-driven insights and strategic inquiries, organizations can navigate the complexities of their supply chains with confidence and agility. The end goal is not just efficiency but the creation of a supply chain that adapts, evolves, and serves as a strategic asset in a competitive marketplace.