COVID-19 has thrust us into an era of huge uncertainty, forcing people to make major changes at work and at home, while companies pivot to new ways of operating. For investors and corporate decision-makers, this new environment poses a multitude of complex questions. To what extent will people go back to working in offices? What will transport services look like in the future? How will global trade and supply chains be transformed by the pandemic?

Some changes forced on us will turn out to be permanent; others could snap back once the coronavirus recedes. But how can we tell which ones? Answering such questions is a key challenge for investors and corporations – but  with our usual frames of reference removed, it’s easy to jump to the wrong conclusions.

For example, plenty of news coverage about the effects of COVID-19 has included stories involving people in big cities moving to towns and rural locations in search of a new work-life balance. It’s perhaps not surprising that this has created a widespread view that urban flight – or “deurbanization” – is one of the big trends to have emerged from the pandemic. But a closer look at data tells a more revealing story.

In the U.S., a moving company surveyed 1,350 people who had moved home between January and June this year to discover the extent to which their move had been triggered by COVID-19. It turned out that only 15 percent fell into this category. The rest had relocated for reasons familiar in the pre-pandemic era: the desire for a better home or the lure of a new job.

At times like these, it’s essential to question the basis on which we make judgments. And having the right data with which to make them is more important than ever. 

Navigating uncertainties

Crises often highlight how long-held assumptions can be challenged, exposing shades of cognitive bias and leading to faulty interpretations of unfolding trends.

Some of this carries an echo of the behavioral economics thinking pioneered by Israeli economist Daniel Kahneman, whose work on the psychology of judgment and how biases affect financial decision-making earned him a Nobel Memorial Prize in 2002. In a conversation with UBS in 2017, Prof. Kahneman talked about how human judgment is “much less stable and much noisier than most people think.”

Those words could just as well have been spoken today as investors and corporate executives grapple with how to navigate huge uncertainties triggered by the pandemic. Now, more than ever, there is a real need to ask smarter, better questions to guide what data you need to look for to get more useful answers, while recognizing and mitigating the cognitive biases that can lead to poor judgment.

Data and judgment are at the heart of UBS Evidence Lab, an alternative data provider that partners with the bank’s analysts across the world to equip investors with ways to read the right signals and spot trends ahead of the curve. In existence for six years, the unit powered more than 3,000 research reports in 2019, covering every sector and all geographies.

It exists alongside the UBS Question Bank, the largest global database of market-related questions asked by professional investors.

Barry Hurewitz, Group Managing Director, Global Head of Evidence Lab Innovations UBS, explains that his team’s mission is to surface relevant insights that “advance understanding on the uncertainties” by distilling the most important debates and turning them into central research questions that can be tested. These debates include questions about deurbanization and the reordering of global supply chains, about shifts in consumers’ habits or what social distancing might look like coming out of the current crisis.

“The starting point is determining what the most important questions are now, in the near-term and over the long-term,” says Mr. Hurewitz. “Then, you have to think about which of those questions will be hardest for the market to calibrate.”

The value of alternative data

That’s where having the right data comes in. For investors, that data will not always be the structured kind that has been used in the past – such as quarterly earnings or monthly sales figures – but will need to be drawn from sources hitherto overlooked or that are hard to access. This might involve tracking the status of ships to follow the movement of goods, or electronically trawling through transcripts of quarterly earnings calls to spot where supply-chain issues are being flagged.

UBS Evidence Lab has worked on several important studies on the economics of social distancing using an alternative-data approach. For air travel, the unit created real-world simulations involving computer-aided design (CAD) drawings of different aircraft, overlaid with historical passenger booking data, to test various assumptions about social distancing. In another example, the unit used geospatial techniques to digitize a Disney theme park and build simulations for how many visitors could be accommodated under various social-distancing scenarios.

Hundreds of other projects related to COVID-19 are currently under way. The methods they employ to assess the “new normal” are essential in order to avoid using past data patterns that may not be a reliable guide to what comes next. “There are a lot of questions that have been asked up to now that are highly stable – such as how a business is likely to do next quarter,” explains Mr. Hurewitz. “But now, in the pandemic era, the questions are highly unstable and the ability to use patterns to make predictions about the future is more constrained.”

Moreover, when alternative data first started to be used, investors would often try to build models to predict company revenue for the quarter with sources such as credit-card transaction data or email receipts. Now, with COVID-19, those models – along with many of the beliefs investors have about economic behavior and markets – need to be reconsidered and recalibrated. “If your beliefs and assumptions about the pace of recovery do not accurately represent reality, you’re going to have a hard time in this market,” says Mr. Hurewitz.

Uncovering investment opportunities

The rigor of the UBS Evidence Lab approach extends to gathering as much evidence on so-called counterfactuals as possible. That includes plugging in the expert view that’s least likely to be priced into the market. Ultimately, this forces a search for evidence in a more intellectually honest way than merely trying to prove the market hypothesis.

Armed with the right data and approach, investors should be in a better position to take on key challenges ahead.

Dealmakers face a landscape that is shifting rapidly, but watching data closely to understand anything from infrastructure to commercial real estate and retail shifts can help spot clusters of opportunity amid the COVID-19 distress. Similarly, pandemic pressures are accelerating the pace of digitization and disruptive technologies, so having an accurate read on those will increase the odds that investors will be able to profit from them.

Being able to rely on the right resource to help deliver that is now possible. “We not only have a lot of data and insight frameworks organized, but we have a lot of resources that we can redeploy quickly,” says Mr. Hurewitz, of UBS Evidence Lab’s capabilities. “That speed to market and the quality of insights we can bring to bear has really resonated. Size, scale, and experience really matter at a time like this.”