Ditch instinct: Why data drives business

Is your business running on top executives' opinions or cold hard data? Be prepared for vast cultural changes if you choose to start making decisions based on analytics, not instinct.

Business and technology leaders aiming to foster more of a data-driven company culture are up against a complicated case of nature vs. nurture.

Digital natives and immigrants alike, it seems, just aren't wired to run on hard data. This is especially true for seasoned business veterans with lots of experience.

"As humans, our brains are wired to rely on [past] experience, but unfortunately, the future doesn't look just like the past," says Bruno Aziza, chief marketing officer at Alpine Data Labs and author of Drive Business Performance: Enabling a Culture of Intelligent Execution. What's more, "overconfidence and over-reliance on experience will typically drive companies to crash," he adds.

Another big obstacle -- and one deeply ingrained in just about every corporate culture -- is a tendency to rely on HiPPOs. A term coined by MIT research scientist Andrew McAfee, HiPPO is shorthand for "the highest-paid person's opinions."

In a traditional business hierarchy, top executives are expected to have the right answers. Presumably, that's why they earn the big bucks. But now, in the era of big data and analytics, experts say those leaders must figure out the next big questions to answer. After that, the answers lie in the data.

"With our ability to collect more information from social sites and unstructured data sources, we can mine a lot more information at a much larger scale and it's putting pressure on intuition and experience -- [they're] becoming less and less valuable," Aziza says.

Andrew McAfee
"Most HiPPOs are not going to go quietly," says MIT research scientist Andrew McAfee.

The problem is that many of the highest-paid people remain stubbornly blind to this shift, and worse, "most HiPPOs are not going to go quietly," says McAfee.

There's resistance from subject-matter experts as well.

A few years back, when CNA Insurance began using data models and analytical tools from SAS to help identify fraud, "we had pushback from our own people, especially those who had been doing this job a long time and were used to using their own intuition. They wondered whether we'd still need them," says Tim Wolfe, head of CNA's Scottsdale, Ariz.-based special investigations unit.

"We had to make clear that we weren't replacing people with technology but that technology was augmenting what we do. It's a two-part arsenal," he explains.

Today, using analytic tools and data models is just another part of employees' regular workflow. "It was a learning curve, and with some people, we had to win them over one claim at a time," Wolfe says. But the business results have been impressive. Thanks to hard data and predictive analytics, the insurer is identifying 10% more claims for denial and mitigation than before, he says.

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