Last Reviewed: June 2026
During the pandemic, supply chain bottlenecks left shelves empty. Demand forecasting and predictive analytics didn’t foresee a rise in demand, labor shortages, and transportation issues. By studying business analytics for supply chains, students can learn how to use data science, statistics, and machine learning to forecast demand more accurately, lower costs, and avoid shipping delays.
This guide is for students deciding whether to study business analytics within a supply chain degree. It covers what the course teaches, the tools and programming languages employers expect, real-world company examples, and where to study it.
At a Glance
- Business analytics teaches students predictive analytics, demand forecasting, inventory management, machine learning, and statistical analysis.
- Students are taught how to use programming languages and business analytics software, such as Tableau, SQL, Power BI, and Microsoft Excel.
- Many supply chain careers rely heavily on business analytics, so this course or a similar one is a common inclusion in many supply chain degrees.
What Is Business Analytics for Supply Chains?
Business analytics for supply chains focuses on gathering, analyzing, and using large data sets to improve supply chain operations. Mathematics, statistics, and computer software are used to identify patterns in the data, forecast demand, and optimize the supply chain. It combines technological tools with human expertise to evaluate risks and make better business decisions.
What’s Covered in Business Analytics for Supply Chains?
During this course, students will spend time studying data analytics, data visualization, key performance indicators (KPIs), inventory management, demand forecasting, and statistical analysis. They must learn how to use statistical analysis software to make better business decisions. For example, Azure Machine Learning, Microsoft Power BI, Oracle Analytics Cloud, SAP Integrated Business Planning, and Tableau are just a few of the software tools commonly used as part of this course (Association for Supply Chain Management (ASCM), 2026).
Skills Needed to Succeed
During a business analytics course, students will study data collection, inventory management, forecasting, performance metrics, and statistics. Often, many of the topics overlap with what students would learn in a supply chain analytics course as well.
- Data collection
- Data analysis and interpretation
- Inventory management
- Demand forecasting
- Performance metrics
- Statistics
- Data visualization
- Problem solving
- Logistics
Why Business Analytics Matters for Your Career
Business analytics is necessary for supply chain optimization and making informed business decisions. For students, the same skills learned in business analytics are essential for day-to-day work in the industry. Even with the best artificial intelligence and machine learning programs, businesses still need skilled workers who can use critical thinking to make data-informed decisions.
When I was studying analytics during my master’s degree in business administration (MBA), I remember one particular case study that stood out. In 2018, Zillow created a machine learning system known as Zillow Offers that automated the buying of homes. Rather than rely on traditional inspections and walk-throughs, it made fast offers on properties. Perhaps unsurprisingly, the iBuying business ended up losing $421 million in just the third quarter of 2021 (Journal of Information Systems, 2024).
In this case, Zillow failed to accurately forecast demand and struggled to create accurate valuations. The predictive analytics needed the human element to check homes for foundation issues or leaky pipes. The failure of Zillow Offers demonstrates the importance of having human expertise to interpret data instead of allowing data systems to make decisions on autopilot.
Real-Life Applications in the Workplace
Once you finish this course, you can use the knowledge gained to prevent bottlenecks, improve inventory management, forecast demand, and optimize delivery timelines. The following are a few real-world examples of business analytics being used in the supply chain.
Walmart
Problem: Walmart has a global supply chain, over 100,000 SKUs, and fluctuating demand.
Solution: The retail behemoth uses predictive analytics and an AI-powered inventory system to forecast demand based on seasonal patterns, weather, local events, and other contributing factors. As a result, Walmart is able to optimize its delivery timelines, inventory management, and pricing (Walmart, 2023).
Amazon
Problem: With a global supply chain, Amazon needed better data oversight to avoid supply chain bottlenecks.
Solution: Amazon created a supply chain data lake (SCDL) for better data management. The SCDL provides integrated data across internal and external organizations. This reduces excess inventory and provides better forecast accuracy (Amazon Web Services, 2024).
UPS
Problem: UPS requires efficient routing and deployment for more than 100,000 drivers.
Solution: The delivery giant implemented the ORION routing system and UPSNav tool to analyze traffic patterns and create shorter routes (IBM, 2026).
Interested in learning more about your career path? Check out our 12-question supply chain quiz to see which path matches your personality.
Tools and Software Commonly Used
In this course, students are likely to use the following tools. Afterward, many of the same tools will likely be needed when they work in the supply chain.
| Tool type | Examples | What it does |
|---|---|---|
| Spreadsheets and data analysis | Microsoft Excel | Organize data, build PivotTables, and create charts |
| Database management | SQL | Query, filter, and analyze databases |
| Statistical analysis | R, IBM SPSS | Run statistical analyses and identify patterns |
| Programming and data analytics | Python | Predictive analysis, data cleaning, and automation |
| Business intelligence and visualization | Tableau, Microsoft Power BI | Monitor KPIs and trends |
Where to Study Business Analytics for Supply Chains
Students can study business analytics as a major for their bachelor’s degree, a specialization in their master’s degree in business administration (MBA), an individual course, or a Master of Science in Supply Chain Analytics (MSSCA). Check out a few examples of how students can study business analytics as a part of a bachelor’s or master’s degree in supply chain management.
- At Southern Methodist University, students can earn a Bachelor of Business Administration in Business Analytics and Supply Chain Management (n.d.).
- Midwestern State University offers an MBA with a business analytics and supply chain concentration (2026).
- During a Bachelor of Science in Project and Supply Chain Management at Penn State World Campus, students are required to take Introduction to Supply Chain Analytics and business courses as a part of their degree (n.d.).
- At the University of Colorado Boulder, students can obtain an MSSCA (n.d.).
- Students can pursue a Master of Science in Supply Chain Management and Business Analytics at the University of Pittsburgh (n.d.).
Should You Prioritize Business Analytics for Supply Chains When Selecting a Program?
If you plan on becoming a supply chain analyst, demand planner, inventory analyst, or business intelligence analyst, a strong background in business analytics for supply chains is essential. Many careers in this field require data management and analysis because of the significant data generated from shipping, warehousing, manufacturing, customer demand, and procurement. Even if you are in a less data-heavy role, you will likely need business analytics, statistics, forecasting, and data visualization in your career.
| Role | What they do |
|---|---|
| Supply chain analyst | Analyze operational data to find and fix inefficiencies |
| Operations research analyst | Model complex problems to guide decisions |
| Business intelligence analyst | Turn supply chain data into dashboards and reports |
| Supply chain risk analyst | Build scenario plans and hedge against disruptions |
Frequently asked questions
What is business analytics for supply chains?
It is the practice of collecting and analyzing large supply chain data sets, using math, statistics, and software, to spot patterns, forecast demand, and optimize operations.
Do you need to know how to code?
It helps. Many analytics roles use SQL to query data and Python or R for modeling and automation, though tools like Excel, Tableau, and Power BI cover a lot of everyday analysis without heavy coding.
What tools and languages are used in supply chain analytics?
Common ones include Excel, SQL, Python, R, IBM SPSS, Tableau, and Power BI, often alongside platforms like SAP Integrated Business Planning and Oracle Analytics Cloud.
What careers use business analytics in supply chains?
Typical roles include supply chain analyst, demand planner, inventory analyst, business intelligence analyst, and operations research analyst.
Why does business analytics matter if AI can forecast demand?
AI and machine learning still need people who can interpret results and apply judgment. Zillow’s iBuying failure, which lost $421 million in a single quarter, shows what happens when data models run without human oversight.
How Does Business Analytics Fit Into Supply Chain Career Paths?
In our supply chain career quiz, we match people to the supply chain career path that suits them the most. For people who love business analytics, the excavator and the architect tend to match best. The excavator is someone who analyzes exactly why operational inefficiencies happen. Often, this personality type excels as an operations research analyst or supply chain analyst. Meanwhile, the architect likes to build scenario plans and risk frameworks, hedging potential risks. People who have this personality type often do well as supply chain risk analysts and chief risk officers.
Ready to take the next step in your career? Take our 12-question quiz to see which supply chain career archetype suits you best.