When the Next Pandemic Hits, Will Firms Be Ready?

When COVID-19 swept across the globe, Vedat Verter suddenly became quite popular. The department chair for supply chain management at Michigan State University at the time, Verter found himself fielding media interviews and calls from policymakers, explaining concepts he and his colleagues had been trying to get people to pay attention to for years. The pandemic had exposed what supply chain scholars had been warning about: Our systems are not resilient. They are fragile, optimized for efficiency over everything else, and woefully unprepared for disruption.

“The phenomena that we observed during the pandemic, the non-resilience of supply chains, has been a topic that has been covered by supply chain scholars and, in some cases, practitioners, for a while,” says Verter, now Stephen J.R. Smith Chair of Management Analytics at Smith School of Business. “All of a sudden, people started showing interest in our research findings.”

The pandemic killed almost seven million people worldwide, challenged even the most advanced healthcare systems, and exposed the vulnerability of global supply chains. But it also revealed something else: Management science — the discipline focused on data-driven decision-making, optimization and systems thinking — has tools desperately needed for the next health crisis or natural disaster.

Management science draws from economics, engineering, business strategy, behavioural science and other disciplines to provide a systematic way to make decisions. For those who need to prepare for, or respond to, a pandemic, it offers a way to analyze risk, model scenarios for both health impact and economic consequences, and optimize how resources — personnel, equipment, supplies — are allocated. 

A short horizon

But these are all blunt tools without one asset that is too often in short supply: long-term thinking. An uncomfortable truth Verter learned through direct experience is that the people making decisions about pandemic preparedness often have little incentive to prepare for pandemics.

“The main takeaway is that the short-term perspective we see in many cases, in policymaking and, more importantly, managing companies, may not be the best way to go,” Verter says. That’s partly tied to high executive turnover: The average tenure for outgoing CEOs of S&P 500 and S&P 1500 firms fell to just 6.8 years in the first half of 2025, the lowest since 2018. When you make plans for a pandemic that might hit in 10 years or later, you may not be around to see the results. The costs are immediate while the benefits are distant and uncertain.

Verter recounted a conversation that crystallized the problem. He was discussing technology decisions with a hospital system CEO when the impatient CEO responded, “Why would I care? I’m not going be here in 15 years.”

It’s a brutal calculus, but an honest one. If your performance is measured quarterly and your tenure might end in seven years, why would you invest in expensive preparedness measures for events that are uncertain and might occur on someone else’s watch?

Pandemic preparedness, resilience and response are inherently long-term concepts. The short-term work around pandemics, such as stopping contagion, is the ambit of health sciences, medicine and epidemiology. But the work of building systems that can withstand disruption requires thinking in decades, not quarters. This is where academic researchers that prioritize depth rather than speed becomes essential.

“If policymakers and companies were interested in longer-term solutions, that should provide a natural incentive to establish better partnerships with academia,” says Verter, who is co-editing a special issue of Health Care Management Science (with Hrayer Aprahamian of Texas A&M University and Manaf Zargoush of McMaster University) that focuses on lessons from COVID.

Trade-offs in the supply chain

Pandemic preparedness is also about assessing trade-offs inherent in any strategic decision or policy. One of management science’s core strengths is making those trade-offs visible, says Verter. Nowhere is this more apparent than in supply chain design.

For decades, companies moved production to far-off countries to cut costs. If a firm’s primary objective is decreasing expenses — and Verter is clear that despite what companies say about other priorities, their actions reveal cost reduction as paramount — operations inevitably will be moved to locations offering cost savings. Offshoring, however, makes supply chains harder to manage and more vulnerable to disruption. As a result, Verter says, “we’re seeing a trade-off between the resilience of the supply chain and the cost.”

It’s one thing if offshoring decisions are based on rigorous analysis. But, in Verter’s experience, too often such decisions are based on intuition or mimicking what competitors do.

This is where management science becomes invaluable. “The main way management science can help is to actually get an evidence-based handle on the nature of these trade-offs and provide information to decision-makers to make those choices,” Verter says.

The best evidence requires robust data that is accessible when needed. Here again, a long-term perspective is needed. If an organization goes into data collection mode once a health crisis or disaster hits, Verter says, “you have no chance because many of your data sources are now broken.”

This is why pandemic preparedness emphasizes having analytical infrastructure in place before an uncertain event occurs. Databases need to be populated, and models built. When the crisis hits, an organization can only tweak existing systems to reflect new realities in their supply chain.

Most of the data companies need — cost structures, supplier locations, transportation modes, supplier reliability — should already exist. Companies should know their supply chains, but COVID revealed troubling blind spots, most evident in the automotive sector. Car manufacturers had built resilient relationships with their first two layers of suppliers. But those suppliers had outsourced to deeper layers — six or seven levels down — that were not visible to the original manufacturers. When those deep-layer suppliers failed, the second-tier suppliers were helpless.

“If you don’t really know your supply chain, you have a problem," Verter says, “and not just during a pandemic. Period.”

Management scientists have been studying these issues for years, developing models and frameworks and evidence-based approaches to building resilient systems. The pandemic proved they were right to worry. The question now is whether organizations will learn the lesson.

Will CEOs and policymakers invest in preparedness when the benefits might not materialize on their watch? Will companies build supply chain visibility into the deepest layers, even when it is costly? Will they establish the data infrastructure and analytical systems before the next crisis, or once again wait until it is too late? 

“Most of the concepts we deal with in terms of mitigating the undesirable consequences are more longer-term concepts that come with some costs,” says Verter. “The main challenge from our perspective is: How do you justify those costs? And who pays for them?”

That’s the sticking point. But, as Verter says, management science can at least make the trade-offs clear, the evidence accessible and the choices informed.