Rhiannon Garth Jones — February 15, 2019
What can “Moneyball” teach us about data-driven decision-making?
Remember Moneyball? The hit book and movie told the story of how Sports Manager Billy Beane revolutionized baseball by using data-driven analysis to recruit players to his Oakland Athletics side. More recently, a similar approach was used by Danish football team FC Midtjylland. They went from relegation candidates to Danish Superliga winners on a tiny budget; the year before Leicester City managed a similar feat in the English Premier League.
Both the Oakland A’s and FC Midtjylland felt they couldn’t compete with the bigger, wealthier sides in their respective competitions. They aimed to solve that problem by leveraging data analysis into finding better value targets and improving their efficiency (FC Midtjylland were averaging a goal a game from set-pieces at one point, a particularly impressive performance stat). Both of them did so with extraordinary success.
And yet, this data-driven approach to success hasn’t caught on. There are relatively few other sides, either in American baseball, or European football, who have (publicly, at least) adopted this approach. Why?
We see this conundrum in business. The NVP Big Data Executive Survey 2018 found that firms were increasingly committing to creating a data-driven culture:
97% of respondents said they were investing in big data, data analytics, and AI projects.
73% of respondents said they have already received measurable value from these initiatives.
79.4% recognised the threat of disruption and displacement from effectively data-driven companies.
Yet only a third of respondents felt they had succeeded at shifting to a more data-driven culture. The evidence, acknowledgement, and intention are all there but most companies are failing to make the switch. Again, why?
The NVP survey highlighted something else: the impact of people. More than half of the executives who responded identified people challenges and cultural resistance as the greatest barrier to embracing a data-driven culture.
Paul DePodesta, Beane’s assistant at the Oakland A’s, has explained this problem: humans develop ‘affirmation bias’, DePodesta said. "Once we’ve made up our minds, we resist information that doesn’t agree with our conclusion". In baseball, this was the idea that some athletes just looked more like great baseball players than others.
Interestingly, DePodesta also highlighted this as an issue in business, citing Malcolm Gladwell’s research on height and business success. Gladwell found that around 30% of Fortune 500 CEOs are 1.88m or taller, despite only 3.9% of American men being that height. Gladwell called this as ‘unconscious prejudice’ and it’s basically the same thing: humans tend to trust their instincts. Quite a lot of the time, it turns out, we shouldn’t.
Ignore your gut?
It’s probably pretty obvious now why there is a disconnect between understanding the value of making data-driven decisions and actual implementation. The advice to ‘trust your gut’ clashes with the idea of data-driven decision-making.
"We turned to data as our flashlight in the cave – our guiding light," DePodesta said. "We said 'unless we can prove it, we’re not going to believe it.' We had to be absolutely relentless in asking the naïve question. The only thing we were wed to was the idea of being open-minded." It was a controversial approach at the time and it still is.
Telling staff to ignore their gut probably won’t make the difference companies need to shift to a more data-driven culture. Taking the time to explain and demonstrate to staff why embracing a data-driven approach can help them might.
Get your team on board
If you can show your Sales team how a new data-based tool can generate 100 new qualified leads in 5 seconds, they’re much more likely to continue using that tool than if you just tell them that they should. The same goes for a tool like Google Analytics for Web Analytics – using it saves time and energy that can be directed elsewhere. Your team will appreciate that if you take the time to show them rather than just tell them.
Don’t devalue their existing skill-set. Demonstrate how much easier their jobs can be if they add data-driven decision-making to their existing skill-set and you are much more likely to get staff on board than if you instruct them to completely change their approach.
Remember, the data isn’t actually doing the job; just the legwork. Until the robots take over, you still need your staff. Making them feel valued as you add data-driven tools to your process will make the transition much easier and the results much better.
Of course, there are other aspects to consider: exactly how you use data, which tools you use, how and where you invest. We’ll look at those another time. But getting your team on board is the first big step to switching to successful data-driven decision-making.
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