As Opening Day of a new baseball season dawns, here’s a little baseball riddle for you: What does the worst team in baseball have in common with one of the best?
Well, beginning in 2019, it might just be its use of analytics.
The Baltimore Orioles had – by far – the worst record in the major leagues in 2018, finishing a paltry 47-115. The Houston Astros, on the other hand, were 103-59, falling short of winning their second-straight World Series title, but good enough for the second-best regular season win total. Let’s examine what the two teams have in common and how you can learn from their data-driven approaches to the game.
Baseball analytics: Driving improvements through data
The Astros, subjects of Ben Reiter’s best-selling book Astroball: The New Way to Win It All, employed a heavy dose of analytics in building a World Series champion. The Orioles must have liked what they read in the book, hiring Sig Mejdal away from the Astros this off-season to work with the title Assistant General Manager, Analytics.
The Astros’ approach to analytics offers lessons that can be applied in any industry that uses data…and you don’t even need to hire Sig to improve your performance.
Here’s what you need to know.
Communication is important
One thing the Astros’ front office valued when they made decisions – whether it was at the trade deadline or leading up to the draft – was hearing from everyone involved. Some teams leaned towards the old thinking in baseball, with a room full of scouts talking about a prospect’s personality and performance on the field, while other teams went fully in the other direction with baseball analytics, using only the numbers and diving into statistics to make decisions. The Astros worked to balance both, trying to make sure that when they made a decision, even if it wasn’t a player everyone agreed on, everyone understood why the team made the choice they did.
The takeaway: This is how analytics works best. A silo mentality prevents all information from being used to its full potential. Whether it’s in healthcare or in higher ed, the more communication about the “why” behind the numbers, the better an organization can feel about the decisions the numbers are helping its employees make.
You need buy-in
That communication can certainly help get the necessary buy-in from people in the organization. Buy-in works best when it’s coming from the top-down. When leadership institutes a change across an organization – as the Astros did when it adopted its model – it needs to show that it is committed. The Astros didn’t just employ its practice at the major league level – it continued right down through the minor leagues. And the team needed the right people in place to help make sure there was consistency. The Astros brought in A.J. Hinch as manager because he was the person management deemed was the right fit to act as a conduit between the front office and the players.
At first the pitcher Dallas Keuchel didn’t believe in the new system. But when he was shown how the data could improve his performance through defensive positioning and where to pitch certain batters, he started to buy in. Success on the mound turned him into a believer. That success, of course, is the biggest selling point: once players see the benefits of a method, they are much more likely to get behind it. For Keuchel the result was a Cy Young Award as the league’s best pitcher in 2015. And for the team, the 2017 World Series championship showed everyone that the Astros knew what they were doing.
The takeaway: While it certainly helps to have an organization-wide philosophy that is instituted from the top-down, the important thing is consistency. If you waver from an analytics approach when you’re trying to make a philosophical change, that will affect the way people in the organization approach it. And hold onto the successes. If there is an opportunity to show people how the analytics make things better, make sure they know, especially if they’re in management. That will get them to believe in the philosophy you’re trying to get them to adopt.
Sometimes you swing and miss
You can’t account for everything. The data can bring you insights you might have never otherwise uncovered…but it isn’t perfect. The data is only as good as the people who input it, and sometimes you won’t uncover a flaw in a metric or somewhere else in the system until a mistake is made. The important thing is to use the mistake as a learning experience.
The Astros experienced that with J.D. Martinez, a player who had little success with Houston, spent an off-season improving his swing, and, despite asking for a chance to prove to the team that he had improved, was released and went on to become a star with the Detroit Tigers, the Arizona Diamonbacks, and then the Boston Red Sox. The Astros’ immediate response was to be more open to the human elements that affect change that the data can’t pick up on.
That’s the same approach they’re taking to harder-to-track measures like clubhouse chemistry. When the Astros added the veteran Carlos Beltran before the 2017 season, it was counting on his leadership skills to bring what his bat was no longer capable of. it was a gut move that paid off, and it’s something the Astros – and other teams in other sports – are continuing to research.
The takeaway: Don’t be afraid to make mistakes – and when you do hit a snag, whether it’s in the data itself or using it in the wrong way, make sure the organization learns from that mistake. The idea of growth mindset comes up a lot in Astroball. Don’t look at mistakes as missed opportunities – look at them as opportunities to improve.
At one point in Astroball Jeff Luhnow, the Astros General Manager, says, “Just because you can’t quantify it doesn’t mean it doesn’t exist.” Figuring out how to quantify the currently-unquantifiable could be the next step in the baseball analytics revolution…and it probably won’t be too different from what is happening in any other business using data analytics to succeed.
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