Thirty years ago, someone told my father-in-law that his job wouldn’t exist much longer.

He was, after all, a mere conduit between the companies that manufacture steel pipe and the companies that purchase it. Which is to say that he was a middleman.

But thirty years later, he’s still working much the same job: making sure deals get done and everyone ends up satisfied. Could the inevitability of cutting out the middleman be a bit … overblown?

This week, I’ll share a recent study from Kellogg’s Rob Bray that questions the inevitability of ditching the middleman—or what economists call “disintermediation.” Plus: What can the rest of us learn from the NFL’s experience using AI to help with decision-making?

Long live … the middleman?

Internet platforms like Uber, Angi, and Postmates have made it easier than ever for sellers to connect with customers—for a small convenience fee, of course. But once those connections are made, it should also be easy to avoid ever paying a convenience fee again. After all, a homeowner could use Angi to find the perfect handyman—and then deal directly with him from then on, instead of using Angi. Economic theory predicts that both buyers and sellers have a strong incentive to do just this.

But when Robert Bray and his colleagues looked for evidence of disintermediation on an app that connects local house cleaners with clients in Moscow, they didn’t find it. “We set out looking for disintermediation. We wanted to find it. But we just couldn’t,” says Bray.

The housecleaning app recorded the time when a house cleaner was scheduled to perform a particular job, plus the particular location of the residence where the cleaning was performed. But because the app was always passively tracking the house cleaners’ locations, the researchers could also see if they returned to clients’ residences without a job being formally scheduled through the app. Such visits would be compelling evidence that disintermediation had occurred. And … it didn’t.

Bray cautions that no single paper can definitively debunk economists’ current understanding of disintermediation. But he does say that his team’s results suggest that the phenomenon “is a problem in theory, but not in practice” for many platforms.

“We’ve learned that, actually, the convenience of working with the platform is often worth the twenty or thirty percent cut that they take. It’s just easier. So platforms might not need to take the countermeasures [against disintermediation] that theory would suggest.”

Leadership lessons from the NFL

As organizations go, the NFL is … complicated. The stakeholders are many, from franchise owners and coaches to referees and players. Then there are the league’s media partners, the American public (whose tax dollars help pay for stadiums), and, of course, the fans, who range from diehard season-ticketholders to casual followers who like to catch the occasional highlights reel.

Oh, and there’s more than $18 billion in annual revenue at stake if one or more of these stakeholders are unsatisfied.

So perhaps it is no surprise that an organization this big and complex has been using artificial intelligence to aid its decision-making for a long time. Kellogg’s Joel Shapiro recently sat down with NFL Chief Data Officer Paul Ballew to learn more.

One takeaway from their conversation is that, on its own, AI doesn’t make decisions. It’s a tool, meaning AI can be used cynically, or it can be used to promote the organization’s larger goals.

This means that, yes, as some critics have complained, data and AI could be used to create a dull, perfectly optimized game—the Moneyball-ization of a beloved sport. But Ballew points out that they can just as easily be used to set the stage for more-exciting games.

“We continue to enhance [the game] and modify it, and it continues to result in games that are close and competitive,” says Ballew, pointing to “teams like the Texans going from worst to first” and his “hometown Lions making it to an NFC Championship game for the first time in thirty years.”

“You don’t take the human out of the decision-making, but you bring the science to make the decision-making more accurate, more precise, and help the human beings make better decisions,” says Ballew.

Read more from the conversation in Kellogg Insight.

Jessica Love, editor in chief
Kellogg Insight