Powered by data, driven by people: The travel sector’s future

Without human beings to develop and apply new technology, to direct the analytics, and to implement the findings, nothing ever happens.

This past April, McKinsey senior partner Harry Bowcott spoke at the MarketHub Americas conference (in Riviera Maya, Mexico) about the ongoing relationship between people and data in the travel sector. Among other topics, he discussed the new industrial revolution of the 21st century, the hype around data analytics, the need to curate and personalize travel offerings, how to make a data-enabled transformation work, and cultural change, as well as the long-term impact of automation, machine learning, and robotics. What follows is an edited version of his remarks.

Back in the stone ages, there weren’t enough data to create anything much beyond the odd cave painting of buffalos. Roll forward a few thousand years, and you get papyrus—the start of an exciting journey. Human beings have been generating more and more data and learning to use them more and more capably ever since, particularly in the past few years.

Yet it’s too easy to be dazzled by this new industrial revolution. Data analysts who obsess about predictive insights or automated processes or seamless customer experiences risk forgetting that without people to develop the technology, direct the analysis, and implement the recommendations, there won’t be any businesses to run. Data may power companies, but people drive them.

Here’s a story illustrating the centrality of the relationship between people and data. Several years ago, an airline wanted to use its assets more efficiently by turning its aircraft around faster and doing less unplanned maintenance. The analysis compared fault codes appearing in cockpits with the parts that eventually resolved the problems. It uncovered an 80 percent chance that one of three parts would be needed. The airline got them onto the engineering manifest and had them ready for airplanes when they landed, so they could be fixed more quickly. Higher asset utilization for the airline and fewer disruptions for customers—a fantastic thing.

But the analysis completely ignored a basic people reality: engineers at airports get their pride in the job, and their sense of standing in the company, from diagnosing the problems of aircraft. At first, they resisted the new system. In the end, they accepted it—but much more slowly than they would have if their point of view had been considered from the start. As this story shows, companies should think carefully about how to apply data-driven insights without antagonizing the very people who must implement them.

A second lesson about people and data comes from hotel pricing and revenue management, which are susceptible to marginal gains from data analytics. There’s something of an arms race going on among providers of the latest black-box software promising higher yields. But in my work, I find that what’s really important is the difference between the best and worst revenue managers (exhibit). In fact, it’s probably greater than the value promised by the next update of yield-management software.

The slightly counterintuitive conclusion is that the best way to implement data-enabled pricing and revenue management is to focus on people. Companies must ensure that the data are transparent to all revenue managers and that transparency helps them improve their performance. The data should be presented and visualized in a way that’s intuitive, user friendly, and manipulable at a granular level. In one typical case, this kind of effort delivered a 7 percent increase in yield, with no IT bill whatsoever.

Three things are often misunderstood in all the hype around data. The first is the implication of the much greater analytic horsepower that’s now available. Some people think that companies should aggregate all their data and look at the result. But that ignores management’s responsibility to identify, understand, and focus on the main drivers of value in a business.