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(Don’t) Go with Your Gut

JR Lowry | State Street Global Exchange

December 19,2017

“Trust me. I just know.”

How many times have you heard that phrase? How many times have you uttered it yourself? Perhaps more importantly, how often has that "knowing" actually panned out? At State Street LIVE, Andrew McAfee, Co-Director of the Initiative on the Digital Economy and a Principal Research Scientist at the MIT Sloan School of Management, called out the business advice we've all received but that he no longer believes. He argued that one of the golden rules of the industrial age, "The machine does the routine work. The human makes the judgement calls," just doesn't hold true anymore.

In his talk, Andrew explored how business decisions are often made by the HiPPO (highest paid person's opinion) in the room. We have all been in a meeting with someone like this — the one who goes with their gut, who trusts their instincts, who just has a hunch — and they often get their way.

As it turns out, their way is quantifiably not the right way.

Think of someone you know who is afraid of roller coasters. Statistically, there is a one in 750,000,000 chance that you'll die riding a roller coaster. Compare that to the one in 10,440,000 chance of dying in an elevator. That means you are 7,084 percent more likely to die in an elevator than you are riding a roller coaster. But most of us who have an aversion to roller coasters probably don't hesitate to get on an elevator. Why? Because our fear gets in the way and that influences our decisions. Our emotions win even when the data says otherwise.

What's more, attribution bias, a type of cognitive bias, means we credit success to our own abilities and efforts, but ascribe failure to external factors. Basically, when our gut-check move works, we applaud our gut. When it fails, we find someone else to blame.

The machines are demonstrating excellent judgement. Trust them.

That's a pretty good way to ensure your gut is never wrong. What's more, we seem to remember the examples of judgment calls that paid off but conveniently forget all the ones that turned out badly.  

In his talk, Andrew referenced a research study1 that showed how the decisions of HiPPOs routinely add no value, or worse, cost value, to their companies. Overwhelmingly, the HiPPO doesn’t actually help: Only eight times out of 136 studies was the expert clearly better. Who trusts a hitter with a 0.058 batting average to hit the game winning run? Meanwhile, the data-backed decision was clearly the better choice 46 percent of the time.

So what should the new rule of business be? According to Andrew, "The machines are demonstrating excellent judgement. Trust them."

To leverage the judgement of machines, businesses need to invest more in "Geeks." The Geek is the mortal enemy of the HiPPO; they are like scientists, making a hypothesis and seeing if the data backs them up. If the data supports their hypothesis, they move forward with their plan. If the data says they were wrong, then they change their hypothesis! HiPPOs are far more likely to twist the data to make it support their conclusion (their gut) instead of changing their conclusion to accurately reflect the data.

As the aforementioned study pointed out, clinical judgement (HiPPO) decision making can lead to very different conclusions depending on your background and how you interpret the information you’re working with. Meanwhile, the application of machine-influenced decision-making by the Geeks requires less expert judgment.

In bygone eras of business, when data was limited and we didn’t have the tools to fully leverage what data we did have, the HiPPOs' gut was really the only option. But the technological age has propelled us into a new world of decision-making, one we need to more fully embrace. Even in the professional sporting world, this shift is playing out, with leading athletes and sports organizations becoming much more data-driven. This year's baseball World Series winners, the Houston Astros, took just this approach in managing their player pipeline and adapting their style of play over the past five years, using the data to steer them from being the worst team in baseball to a championship-caliber club.

"We are not in the world of 'small data.' We have weirdly powerful tools," stated Andrew. "Machines aren't necessarily doing things better than we are, but they are doing them differently. They can look so much further ahead than we can in any situation, no matter how complex." The already distinctive performance gap between the HiPPO and the Geek is only going to grow as machine learning and AI enter additional domains of previously human-only activity.

So don't rely on your gut. Trust the Geeks and their machines.

1. Grove, William M, et al. “Clinical Versus Mechanical Prediction: A Meta-Analysis.” Psychological Assessment, vol. 12, no. 1, 2000, pp. 19–30., doi:10.1037//1040-3590.12.1.19.

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Topics: Data Analysis


JR Lowry | State Street Global Exchange

JR Lowry is the head of Innovation & Advisory for State Street Global Exchange, which provides data and analytics solutions for institutional investors. In this capacity, he is responsible for GX’s offerings that support State Street’s clients in their investment management activities, including investment research, advisory, indicators, indices, investable strategies, and interactive tools.