Business and Science Are Pointing in the Same Direction

In deciding when to reopen states, politicians don’t have to choose between public health and the economy.

Shutterstock / Paul Spella / The Atlantic

About the authors: Kevin G. Volpp, MD, PhD, is a professor at the Perelman School of Medicine and the Wharton School at the University of Pennsylvania. David A. Asch, MD, MBA is a professor at the Perelman School of Medicine and the Wharton School at the University of Pennsylvania. Ralph W. Muller is the former CEO of the University of Pennsylvania Health System.

The question on everyone’s mind now is when it will be safe to come back out. Business interests argue that the economy should be reopened; public-health scientists argue that it is still too early; and politicians are struggling to find a path forward. What they need, though, is not a path, but a process. And when it comes to designing a process for making crucial decisions, business leaders and scientists are surprisingly well aligned.

Over the past several decades, businesses around the world have turned to the discipline of the scientific process to make decisions when the stakes are high and the outcomes are uncertain. Instead of relying on a handful of people sitting in a corporate boardroom to make sweeping and often-irreversible choices, companies have embraced experimentation. Today, innovative companies are more likely to take a series of small steps based on carefully controlled A/B tests of market demand or detailed analyses of market segmentation.

The United States needs a process that reflects the strengths of this approach and that will help us answer a series of crucial questions: What assumptions might take us down the wrong path? What is the quickest way to resolve these uncertainties? How can we learn, and adapt? And perhaps most important, how can we welcome competing evidence and use it to change course?

There are many ways to apply the problem-solving process used by businesses and scientists to the current situation, but at least three stand out.

We should be performing, or at least observing, multiple social experiments. Different states and jurisdictions, and different countries around the world, can provide observational evidence of what works and what doesn’t. We have a long history of using states as laboratories for the nation. Instead of taking a rigid, national approach, or allowing each state to go its own separate way, we can seize the opportunity to critically assess what’s happening in each state—and to evaluate the connections among their environmental conditions, the social policies they invoke, and the trajectory of illness they reveal. Then, we can share these lessons across the nation, so that other states can apply them.

Communities, like people, behave heterogeneously. In examining that variation, we often uncover the more elemental principles that today define precision medicine. What we once thought of as breast cancer is in fact a collection of diseases distinguishable in part by their different natural histories and their responsiveness to different treatments. That sort of thinking already informs our interpretation of what has happened in other nations: Why has Italy suffered so, and why has Germany been relatively spared? Why has Singapore’s early success been followed by a rapid escalation in cases? Here in the United States, we can apply it to states, cities, and neighborhoods.

But as state and local governments carry out their real-time experiments, we’re going to need a way to oversee the process. Conventional scientific trials in high-risk situations are overseen by a board with the authority to stop a trial should interval information show that either the costs or the benefits are more dramatic than anticipated. Both good scientific practice and good innovation practice establish early-warning and surveillance mechanisms up front to stop an experiment or pivot if needed. What we would look for here would be early spikes in infection rates; policies that aim to reopen the economy would almost certainly have to include robust and representative efforts at testing. Good practice would similarly create a nonpartisan and independent board to oversee the collection of those data and make timely recommendations based on them.

Perhaps most important, what good scientific and business practices offer is a willingness to test hypotheses and admit when they are wrong. Politicians tend to defend their decisions even in the face of contrary evidence. The best scientists and business innovators recognize that the false paths they discover provide insight into where the right paths lie.

Politicians, it turns out, don’t have to choose between science and business. Instead, they can use innovation principles embraced by both to chart the way forward, one experimental step at a time.