What the Oakland A’s accomplished in 2002 was just short of miraculous. Winning twenty games in a row broke a record that stood since the 1947 Yankees. They followed that up by winning the American League West. What shocked the baseball world is how they did it – fielding a team of overlooked, ragtag players whose payroll was one third that of the Yankees. Was it miracle or a cunning strategy that you could also benefit from, even if you don't follow baseball or sports in general. As the A's found out, insights from data analytics can shed light on what is costing you performance wins - be it lost sales, failing to secure a key logo, missed earnings, or market valuation that pales in comparison to your nearest competitors.
Out Of Left Field
To all but Billy Bean and Peter Brand (a recent Yale economics graduate and a disciple of 'Sabermetrics" guru Bill James), the A’s success couldn't have been predicted by baseball executives or scouts. Yet, within a very short period, only the most affluently stubborn clubs could afford to ignore what the A's were doing – because repeated the feat of fielding a low budget, competitive team year after year. As Red Sox General Manager John Henry put it to Billy Bean when trying to lure him to the Red Sox - “Anybody not using your model; they're dinosaurs.”
The Anomaly
Reading Michael Lewis’ book or watching the movie ‘MoneyBall’ could easily lead you to conclude the A’s had found a clever data driven approach to identify undervalued players – and in one sense, you’d be right. The players they found were the bottom of the barrel from the perspective of baseball’s scouts – the experts who evaluated talent. But Billy’s predicament, one shared by all small market teams, precluded retaining or attracting high caliber players – the A’s simply couldn’t match payrolls with the big boys.
By accident, Billy came across Peter Brand. Though just out of college, Peter was being consulted on proposed trades Billy was negotiating with the Cleveland Guardians (formerly the Indians) – trades Peter noticeably disapproved of. Questioning Peter afterwards to understand “what went on in there?” changed Billy's life, the fortunes of the A's, and eventually, the game of baseball itself.
So, what was the A’s model and how can you, an executive fielding a team in the competitive world of business learn from it?
The Secret
Here's what Peter said to Billy “There is an epic failure in baseball to understand what is really happening…this leads people who run baseball to misjudge players and mis-manage their teams. Your goal shouldn’t be to buy players, your goal should be to buy wins; in order to buy wins, you need to buy runs.”
Peter then explained how you ‘buy runs.’ Data analytics could identify players that had a knack for getting on base – not measured by their batting average but by on-base percentage i.e., from hits, walks, or being hit by pitch. Analytics could also identify other players with a high slugging percentage i.e., total bases per hits. These two metrics added up to scoring enough runs to winning games - provided similar analysis and metrics were applied to pitching combinations that worked to keep the other team from scoring.
The Spark
Initially, A's manager Art Howe wasn't a fan of the new model. The 25 players Peter identified for winning a championship simply didn’t make sense. So, he continued inserting players he favored into the lineup, doing the best he could with the hand he'd been dealt – and the A’s went into a tailspin, falling to the bottom of their division.
The miracle started to take hold when Billy forced the issue by trading away Art’s favored players, leaving no choice but to field the players who fit Billy and Peter’s strategy. Billy coddled and cajoled Howe and his veteran players until they understood and accepted their role in the new model. Things started to fall into place and the wins started accumulating. Success begat success, and soon the team's mood flipped from complacency to ambition to win it all. And they almost did.
The Lesson
The A’s success proved even the best scout ‘hunches’ or instincts about player abilities were no match for Peter's analysis. In 2002, Sabermetrics reflected a new understanding of winning baseball games - relying on data analytics to provide insights that instinct alone cannot provide. Sabermetrics and the more general field of Complexity Science prove we live in an interconnected world. In this understanding, linear solutions, such as finding a new home run hitter to replace the one you lost, fail in comparison with non-linear solutions that identify combinations that work well together. By embracing this understanding, the A's were able to continually adapt – even in the midst of their predicament. It was 'systems thinking' that ensured resilience, year after year - not a bunch of disconnected 'replacement parts' but a connected system where all the parts fit together for a 'synergetic effect.'
You
Why is this radical thinking critical to your Company's success? As a corporate executive, you're constantly looking for a way to boost performance. Yes, you have good instincts about talent, but are you like John Henry's dinosaur?
To see where your organization’s performance might be suffering from misalignment, click here to take our free, eye-opening survey.
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