Supply Chains need your Analytics Skills — Here is how you can help
Learn how to use analytics to optimize supply chains for cost reduction and sustainability with 70+ real-world case studies and source code.
Supply chains are under pressure like never before.
From climate-driven disruptions to geopolitical shifts, businesses must adapt to rising costs, trade barriers, and sustainability demands.
At the beginning of February 2025, the U.S. Postal Service suspended parcel services from China and Hong Kong following new trade tariffs.
In this new world where supply chains face uncertainty, data analytics is essential to keep resilient operations.
In this article, I will introduce a Supply Chain Analytics Cheat Sheet that compiles more than 70 case studies published on my blog.
The idea is to help analytics professionals gain a competitive edge by learning to use data to optimize operations.
You will find practical examples based on my 8 years of international experience designing, monitoring and optimizing supply chain solutions.
🙌TL;DR
- Companies facing inflation and geopolitical instability need your analytics for their transformation. Use the cheat sheet as a competitive edge for your career.
- The sheet includes 70+ case studies covering logistic operations, supply chain flow optimization, business strategy and sustainability.
- Articles include real examples with a problem statement, a solution provided and the source code ready to be used (and adapted to your problem).
- Bookmark the sheet, as I will update it with all the content I publish on Medium, GitHub, YouTube, or Twitter.
What is Supply Chain Analytics?
This is a collection of tools and methodologies for extracting insights from data associated with all processes in the value chain.
You can use transactional data from Enterprise Ressource Planning (ERP), Warehouse Management Systems (WMS) or Transportation Management Systems (TMS) to build analytics tools that will support operations.
As a Supply Chain Solution Manager and Data Scientist in the logistics industry, I have used analytics in international projects to design and optimize supply chain solutions.
Since the summer of 2020, I have shared more than 70 case studies on this blog, compiled into a simple cheat sheet 👇
How (and why) can I use this cheat sheet to start my supply chain analytics journey?
Whether you are a supply chain professional or an analytics expert, I will guide you using this cheat sheet to support companies in their operational transformation.
If you prefer to watch it, here is the video version
Why is it the right time to learn these skills?
Since the pandemic, companies have faced challenges, including inflation, geopolitical instability and exploding raw materials costs.
Therefore, your company is probably working on transformation projects to minimize risks, reduce costs, and boost competitiveness.
How can we use analytics to improve profitability?
Data Analytics to Boost Business Profitability
The first section of the cheat sheet is about data analytics for Business Strategy.
It includes practical case studies on how to use data to support business executives in their strategic decision-making.
For instance, the series of articles, “Business Planning with Python”, is based on a real example of a business managed by my friend.
“We have to refuse orders as we don’t have enough cash to pay suppliers for stock replenishment.”
Starting from this assertion, I built a simulation model to help him better understand the weaknesses in his value chain and provide insights to support his business growth.
They illustrate how you can add value to small, medium, and large business owners.
What about optimization of supply chain operations?
Supply Chain Analytics for Logistics Operations
As I spent years designing, monitoring and optimizing supply chain solutions, you will find many case studies focusing on warehousing and transportation operations.
In this section, most case studies are based on an actual reengineering project I have conducted in Asia or Europe.
Boss: “Samir, we need to reduce warehousing costs by 15% if we want to renew the contract with the retail company XXX.”
They focus on optimizing a specific process in a warehouse (order preparation, value-added services) or transportation operations (routing, scheduling).
Go to the nearest warehouse and ask: ‘What are your problems?’ You can be sure they will find some for you.
You can start with these examples to find the first project to support your logistic operations.
- Review the case studies to understand the problem statement and the solution.
- Pull the source code from my GitHub repository.
- Search for a similar problem in your company
- Adapt the code to build a solution to your specific problem
The code is usually a simple Python script or a jupyter notebook that can be easily adapted.
What if you want to have a greater impact? Focus on a flow optimization.
Data Analytics for Supply Chain Optimization
The main driver of the reengineering projects I have conducted was cost.
Usually, customers tracked logistics costs, i.e. the percentage of turnover spent on logistic operations.
Therefore, we needed to find solutions (as a third-party logistic service provider) to reduce this percentage without impacting our profitability.
What if we deliver US east cost from a warehouse in Charlotte?
The solutions presented in the previous section are too localized. We need to take a step back and consider flow optimization.
These case studies focus on the optimization of goods flow using
- Replenishment rules and forecasting algorithms to optimize inventory
- Linear/Non-Linear programming to match the supply with demand at the lowest cost
- Statistical tools for diagnostic and improvement of specific processes
For instance, the supply chain network optimization algorithm helps you find the optimal set of factories and warehouses to minimize costs.
These tools can be used for strategic transformation projects that require advanced insights for critical decisions.
For some examples, I have deployed the models in a web application developed for my startup LogiGreen.
The demo version is publicly available for you to test the models; more information here.
What about sustainability?
We just need to change the objective function.
If you want to support the green transformation of your company, I have some examples for you.
Data Analytics for Supply Chain Sustainability
Since my first project focused on sustainability, I was convinced that green transformation was similar to supply chain optimization.
Therefore, you can find 17 examples of optimization solutions using this approach to minimize CO2 emissions or resource usage.
I also decided to cover the reporting side of sustainability with analytics for Life Cycle Assessment, CO2 emissions calculations or ESG reporting.
Beyond measuring, you can simulate initiative for decarbonization.
After reporting, companies usually develop a sustainability roadmap that includes initiatives to reduce their environmental footprint by 2030.
To validate a specific initiative, you need
- Estimate the impact on costs and performance
- Calculate a return on investment (impact reduction)
Data analytics can be used to support this process.
In this section, I have included examples focusing on green inventory management and circular economies.
Now it’s your turn!
Conclusion
I hope this brief introduction to the cheat sheet helped you better understand the content published on the different platforms I operate.
Do not hesitate to bookmark this cheat sheet as I will update it each time a new content is published.
I would like to use this article or the YouTube video as a forum to collect your feedback or questions.
Do not hesitate to use the comment section for that!
If you have used any case studies for some of your projects, I would be happy to learn more about the results.
About Me
Let’s connect on Linkedin and Twitter. I am a Supply Chain Engineer using data analytics to improve logistics operations and reduce costs.
For consulting or advice on business analytics and sustainable supply chain transformation, feel free to contact me through Logigreen Consulting.
If you are interested in data analytics and supply chain, please visit my website.
