Super Bowl rings, Olympic gold medals, and big data
Published: March 23, 2018
But there’s a less glamorous reason as well: data analytics.
Let’s look at two recent sports success stories: the Philadelphia Eagles & the Netherlands’ Olympic speed skating medal sweep.
Nick Foles and the Eagles are still enjoying the accolades of winning a Super Bowl, and they’re also giving credit to the role of data analytics.
ESPN Staff Writer Tim McManus explains it like this:
“The situations in which the Eagles decide to strike might seem random, but in fact they are quite calculated. And they’re often decided before the start of the game – or even before the start of the season. The approach is driven by an analytics team so involved in the operation that two members of the department communicate with (head coach) Pederson in-game.
“After [Pederson has] made the third-down call the phones can be silent for a few seconds, and one of the guys might chime in and say, ‘Hey Coach, if this ends up short fourth-and-2’ – I’m using fake terminology – ‘it’s green, go for it. The charts say go for it,’" explained offensive coordinator Frank Reich. “Or, ‘Hey, if it’s anything less than fourth-and-3, we’re good. Other than that, it’s your call, Coach.’ Or, ‘Anything more than fourth-and-10, no.’
“The analogy I think of is kind of like a stoplight. There’s green, there’s yellow and there’s red, and then there’s shades of green, there’s shades of yellow and then there’s shades of red. So some of them are, ‘Hey, it’s green. Yellow, proceed with caution’ – and that’s how it operates.”
The Eagles’ Super Bowl win provides a powerful example of smart, capable experts combining their experience with the power of refined mathematical models.
Think the Eagles are alone in using analytics to drive game time decisions? Nope.
Skaters from the Netherlands have become known to dominate Olympic speed skating. They’ve taken 36 of 69 medals home in the last two Olympics. How do they do it? Through predictive analytics:
“In classic Dutch fashion, they chose to devise the most rational solution they could imagine. Leaning on statisticians, the team developed an algorithm to tell the coaches how best to deploy their squad of 10 skaters across the 14 Olympic medal events to maximize their chances of winning gold. It bakes in two years’ worth of results, calibrates them for location, since ice conditions and altitude affect speed skating times, and compares them to other results around the world. The answers that the computer spits out form the basis of the Dutch strategy. It’s Winter Olympics Moneyball, only for the team with the most money and talent,” writes the Wall Street Journal’s Joshua Robinson.
Sports analytics is now a broadly recognized discipline with degrees, conferences, and huge talent demand because meaningful results are being generated by organizations that incorporate analytical capability into management decisions.
And those that are not embracing analytics are at a disadvantage.
Predictive analytics hold the power to give commodities companies the same competitive edge in decision making as they do sports organizations. Instead of which shooting strategy to take given an opponent’s defensive strategy, it’s what ad to run in a given week. Instead of which defensive player to put in when the team is up or down x points, it’s how to price a portfolio of products given inventory and service level objectives. It’s the same discipline, different application.
As new technology enables faster and more powerful computing, meat companies throughout the value chain stand to benefit in a big way from new analytics-driven insights that can change strategies and drive margin.
This article was originally published on Meatingplace.
