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July 28, 2024
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March 8, 2024
Here are the top 2 Supply Chain Analytics Data Story use cases every beginner should know.
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It's becoming increasingly evident that managing supply chains is becoming more complex. While it poses challenges for businesses, it also holds significant potential.
According to a recent study, only approximately 22% of companies are genuinely adopting strategic approaches to their supply chain networks. This statistic serves as a wake-up call for many.
The logistics sector is a treasure trove of data. It sees a constant influx of information daily, and it falls upon data analysts like us to track and present this data to stakeholders, including supply chain managers.
Reporting goes beyond just presenting numbers and charts; it involves understanding the specific needs and preferences of the supply chain manager.
Fortunately, in this scenario, we can assist in identifying their requirements, desires, goals, and objectives, thereby providing them with the insights they seek.
Let's begin by delving into understanding the data better.
In this project, we will start by exploring the dataset and assess how the products are being distributed across different sales channels and what is performance of products by each of those distribution channels. Here are the 4 steps that we are going to follow to analyze the dataset:
Let's say, for this use case our Business Persona will be - Distribution Manager. We will look into the data with a distribution manager perspective so that we have a starting point on how we perceive the data.
Once, let's get into the mind of our Distribution Manager with an Empathy Map:
Now, let’s define the objective of our Distribution Manager based on the empathy map we just created. Here are some objectives:
Next, let's measure success with some KPIs:
Finally, let's ask some burning questions during our Exploratory Data Analysis (EDA):
1. How different channels of distribution are contributing to overall sales?
2. What are the top brands selling across each channel?
3. How is our cost per unit and average margin percentage distributed across channels?
4. What kind of packaging is making the most profit across different channels? Is there any packaging type that we need to consider?
5. How are tetra packs performing across the country in terms of Sales and Profits?
This project focuses on optimizing logistics and customer satisfaction. Through advanced data visualization, it examines shipping times, costs, and order fulfillment efficiency to streamline operations, reduce costs, and enhance overall shipping performance in the retail superstore.
Let's say, for this use case our Business User will be - Logistics Optimization Manager
Once, let's get into the mind of our Logistics Optimization Manager with an Empathy Map:
And now, let’s define the objective based on the Logistics Optimization Manager Empathy Map
Objective : The objective is aimed at delving into shipping data to enhance cost-effectiveness and operational efficiency. Shipping costs are a substantial expenditure for businesses, and optimizing these costs is crucial for overall financial performance.
Next, let's measure success with some KPIs:
Finally, let's ask some burning questions during our Exploratory Data Analysis (EDA):
1. What Are My Sales And Profit By Ship Mode?
2. How Are My Sales And Profit Performing Yearly On Same-Day Ship Mode?
3. Which Region Is Not Performing On Same-Day Mode In 2023?
4. What Is Category Wise Impact In South Region In Year 2023?
5. Technology Subcategory Profit And Sales In South Region Same Day 2023?
We at Super AI are on a mission to tell #1billion #datastories with their unique perspective. We are the community that is creating Citizen Data Scientists and we are committed to help you become one of the Top 1% data storytellers.
With Saurabh Moody and Preksha Kaparwan you can start your journey as a Citizen Data Scientist.
All the Best❤️
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