It has been gnawing at me for a while. Why are are most professional sports leagues hurting for offense? After all, we live in the age of spreadsheets and video cameras. Every athlete has access to hundreds of angles on every action they take on the field, or in the rink. Every swing, every shift, is chronicled by a bevy of assistant general managers and an army of bloggers. Shouldn’t all this information be helping hitters and scorers?
Then it hit me: Big data might as well be hold up a sign that says D-FENSE! Everywhere that advanced analytics arrives, a scoring drought seems to follow. All that information seems to be one-sided. I started talking to sports folks and found my new theory rang true to them. In basketball, analytics helps force top shooters just slightly out of their comfort zones. In hockey, it helps unlock the secrets to “shot suppression.”
As the person that CNBC once dubbed the “Big Data Hater,” I realized the theory fit neatly with my skepticism of the quantitative managing that has swept through American corporate culture — the notion that if you can’t count something, it’s not valuable. Hugh Thompson and I explored the this “data idolatry” in our book The Plateau Effect. But here was an even more concise explanation of the problem. Moneyball, analytics, big data — whatever you call it, I worry it has put much of our culture on the defensive. I explored the theory recently in a column for CNBC.com. The beginning of the piece is below. You can read the rest at CNBC.
If you are wondering why you feel your place at your company is so fragile, why your creativity has trouble fitting into your annual review forms, or why you are feeling so restless, I think this is part of the problem. Here’s the top of the piece to whet your appetite:
Is big data behind scoring drought in professional sports? And your business?
As spring training brings the familiar sounds of baseball, and the annual renewal of foolish optimism that this might be the Cubs’ year, Major League Baseball is hoping for something even more dramatic — more runs. From anyone.
Baseball is in a crisis not seen since the 1960s. Pitchers ran circles around hitters last year, with runs per game and batting averages at decades-long lows. There was an epidemic of defensive 2-1 ball games last year — this at a time when baseball is struggling to remain popular with younger, supposedly attention-span-challenged fans.
But it’s not just baseball. The National Hockey League has an offense problem, too. The game’s biggest star, Sidney Crosby, has only 20 goals three-quarters of the way through the season. Goals per game have shrunk since the 2005-2006 season. And in the NBA, hot-shot scoring has also declined. In the2007-2008 season, there were 27 players who averaged more than 20 points pergame. Today there are 15.
What in the wide-wide-world of sports is going on here? If you own spreadsheet software, you know that advanced analytics are the biggest change to hit professional sports in the past decade. As Michael Lewis explained in his book “Moneyball: The Art of Winning an Unfair Game” that popularized the revolution, sports franchises will do almost anything to get a leg up.
Geeks with video cameras track everything now. Baseball has its spray charts. Defensive shifts based on those charts are so effective that some critics have suggested banning them. Hockey has its Corsi and Fenwick, which measure shot attempts during ice time. The National Basketball Association uses PPP, or points per possession now.
But a funny thing is happening on the way to refining these sports — big data had chosen sides. Moneyball tactics seem to help the defense more than the offense. The tiny tweaks and refinements suggested by nerds are simply better at stopping players than enabling them.
It’s a lot harder to find and exploit defensive weakness than offensive weakness. There’s a lot more available data on what offenses are trying to accomplish than on what defenses are trying to suppress. To play a little loose with an aphorism, it’s a lot easier to criticize than create.
What does this have to do with your business? Businesses are projected to spend nearly $40 billion in big data technology this year,according to collaboration site Wikibon.org,most of it with the idea of Moneyball-ing their companies.
It seems like a no-brainer — run a few spreadsheets, find a few million dollars. But I think there’s a flaw in big data that’s big enough to drive a slap shot through. As in sports, big data helps defense more than offense. That might mean companies are spending a lot of money so they can be penny-wise and pound-foolish.
In the corporate world, playing defense means things like limiting overtime and shrinking health care benefits costs. Offense means finding new markets and inventing new products. Big data is great at optimizing work schedules to minimize labor costs, but not nearly as good at giving employees extra time to tinker with a potentially profitable idea.
Economist Tim Harford, author of the book “The Undercover Economist Strikes Back,” has been a critic of big data because its users often seem to forget that no matter how large a dataset is, it’s still subject to sample bias that leads to errors. It remains true that 5,000 carefully-selected survey takers provide better results than a billion random Google searchers. And he thinks sample bias might be part of why data helps defense more than offense.
“Data analytics are excellent at finding subtle historical patterns that might then be exploitable. They are much less useful at suggesting something radically new, or producing a response to something new,” he said. “Analytics favor the optimiser, the tweaker, but usually not the radical disruptor. Analytics help Google and Facebook optimize their services, but they didn’t really help Jony Ive and Steve Jobs create the iPhone.”
Be the first to comment