Dr. Andy Hill and Dr. Rosie Cole are both Senior Lecturers at the University of Surrey in the UK.
Supply chain risk management (Chapter 11) is critical, but often difficult for students to grasp. Risks can range from supply delays and demand shocks to extreme events like pandemics. A risk matrix is a visual tool to help firms prioritize and understand potential risks, and then make informed decisions about how to manage them. Plotting likelihood against impact offers a simple way to see these uncertainties. Its color-coded heatmap (see Module G) makes it an engaging teaching tool.
But risk matrices are riddled with three problems:(1) mathematical compression. Because the scales for likelihood and impact are simplified, rare but catastrophic events often get downplayed. The extremes are squeezed into narrow categories, which means the true scale of a severe event is not represented accurately; (2) presence of ambiguous categories. The labels “low,” “medium,” and “high” are not always clear-cut, and the boundaries between them often overlap. Different managers could look at the same scenario and classify the risk differently, leading to inconsistent decision- making; and (3) false objectivity. Many risk matrices attempt to turn qualitative judgements into numbers, for example by multiplying likelihood and impact scores. While this looks precise, the numbers are often arbitrary and can give a misleading sense of accuracy.
Here are two straightforward fixes for supply chain risk managers: (1) drop the semi-quantitative version and stick with qualitative categories: (2) align categories with probability–impact logic. Using orders of magnitude for likelihood and clearer thresholds for impact makes the tool more reliable. As a classroom exercise, you could ask students to critique a flawed risk matrix, or redesign one so categories are consistent and meaningful.
Perhaps the bigger lesson is that people, not algorithms, make decisions. Managers often rely on heuristics and intuition when assessing risk. This makes risk perception an important teaching point. Why do some managers ignore low-probability but catastrophic risks? How does education or experience shape perceptions? These questions move students beyond the tool itself into understanding decision-making behavior.
For teaching OM, the risk matrix remains a useful entry point into supply chain risk management. It should be framed not as a perfect solution, but as a way to sort risks into acceptable, unacceptable, and “needs more analysis.” Educators can use the risk matrix to teach critical thinking about tools, not just how to apply them.
Temple U. Prof. Misty Blessley shares her insights with our readers monthly.
Global coffeehouse chain, Starbucks, employs a similar collaborative model in the coffee industry. It’s Coffee and Farmer Equity practices enable direct engagement with producers across Latin America, Africa, and Asia to improve sustainability, productivity, and income generation. Starbucks operates regional farmer support centers, provides pre-harvest financing, and integrates ethical sourcing into its procurement decisions. These long-term collaborations help Starbucks secure a dependable supply while positively impacting over 400,000 farming families.
For retailers, traditional online returns impose heavy costs: shipping back, inspecting, restocking or disposing of items, and managing the reverse logistics infrastructure. By eliminating the return flow, retailers cut reverse logistics expenses, simplify operations, and reduce strain on reverse-channel storage and processing staff. Many retailers now use decision-making algorithms to determine return eligibility, factoring in item value, customer return history, resale potential, and handling cost.
Now AI and machine learning are playing a greater role in predictive analytics, helping companies anticipate delivery issues before they occur and proactively adjust. AI can design more efficient delivery routes, improve accuracy and the customer experience, and predict errors before they might happen, writes
In today’s volatile global environment, geopolitical upheaval has emerged as a defining threat to supply chain resilience — on par with natural disasters and the lasting effects of the COVID-19 pandemic. From shifting trade policies and tariffs to rising political tensions and regulatory unpredictability, these forces are disrupting global operations, raising costs, and reshaping supplier networks.
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During the last decade an average of 1,300 containers were lost at sea. In 2022, 661 containers were lost. In 2024, 576 containers that were lost. A notable cause of container loss is severe weather. In the 2024, three incidents off the Cape of Good Hope resulted in losses of 99, 44, and 46 containers, respectively. The region is known for its rough seas. However, due to Houti terrorists in Yemen, more ships are rerouting around Africa instead of passing through the Red Sea, increasing exposure to such risks. (About 1/3 of lost containers are eventually recovered).
The country’s biggest automaker, BYD, recently lowered the price of a starter EV to less than $8,000. To hit such low prices, suppliers say the company is squeezing them by demanding lower prices and dragging out payment periods.
Following the accident, two dozen master beekeepers were employed in a coordinated effort to help with the recovery by reconstructing roughly 300 beehives one by one and capturing many of the honeybees. There was not a total loss of the $160,000 but there were significant losses due to the costs of labor for cleanup, restoration of the beehives and capture of the bees.
India, Malaysia, Thailand, Vietnam, and Taiwan have emerged as the most prominent alternative suppliers to China for the technology industry, despite Taiwan’s own geopolitical challenges.
