You don’t have to be a baseball fan to enjoy Moneyball. The film of Michael Lewis’ excellent book casts Brad Pitt as Billy Beane, the manager of the Oakland Athletics, a team who lack the cash of their league rivals to hold onto quality players or attract the box-office names they need to replace their stars when they’re poached by other clubs.
Beane needs an edge and he finds it in the unlikely shape of Peter Brand, an economist working in the Cleveland Indians’ backroom. Brand (played by Jonah Hill) has never played baseball, but he has a firm belief that metrics and statistics are just as important when it comes to building a winning team as recruiting someone who has the talent to keep slugging home runs. You get your edge from data-mining as opposed to sticking with tradition. You get your edge from recruiting players who can give you specific incremental advantages. And because other clubs undervalue these players, you can get them on the cheap.
It’s totally contrary to how Beane’s talent scouts work – these gnarly ex-pros keep talking about the importance of how a player looks and the wisdom of crowds, like all insiders – but he decides to go with it. Beane starts using Brand’s metrics and complex formulae to build a team which makes the talent scouts despair, but which eventually put together a long winning streak.
In an afterword in a later edition of the book, Lewis recounts what happened after Moneyball was published. “The Oakland front office had calls from a cross-section of American business and sporting life: teams from the NHL, NBA and NFL; Wall Street firms; Fortune 500 companies; Hollywood studios; college and high school baseball programs. There was even a fellow who ran a chain of hot dog stands who found a lesson for his business in the experiment occuring inside the Oakland front office. Every nook and cranny of American society, it seemed, held people similarly obsessed with finding and exploiting market inefficiences – and the Oakland front office inspired them”. The only people who weren’t enthused were the club’s major league baseball-playing peers – they still thought they were doing things right and Beane’s success was a fluke.
The problem with insiders is that they wear blinkers. When you’re inside a bubble, you’re unable to see beyond that bubble because you’re surrounded by people who are all thinking the same so you stick with the wisdom of that crowd. Look at the recent presidential election here and how long it took the pol corrs to wake up to the fact that Sean Gallagher’s campaign was gaining huge traction countrywide. The pol corrs didn’t see Gallagher as a potential danger until the latter half of the campaign, whereas those outside the bubble were seeing a huge upswing in support for the soft Fianna Fail candidate.
It’s not as if we don’t have the data to work with. We produce so many data in every business sector that it’s inevitable that you can gain an edge and advantage from mining these numbers and details to see what they throw up. You can see how number-crunching works for tech companies and other early adopters and Moneyball shows how it can work for a cash-poor baseball team like the A’s, but what about the business we write about here day in and day out?
Data-mining already happens at various music companies, though it’s probably not be as sophisticated as how Beane and Brand worked at the A’s. Live music promoters don’t just suck their thumb and rely on their gut reaction to pick a venue for an act they’re booking – they talk to the labels, check the sales figures, look at airplay and then make the call.
Some record labels like Cooking Vinyl, who have signed acts like The Cranberries, Underworld, The Prodigy and Marilyn Manson, show that you can build a business by investing in acts who are no longer on major labels, but who have an established fanbase who will purchase their new releases. There’s always profit to be made from distressed inventory like this who have a following – it’s like those euro shops who sell stuff you don’t realise until you walk in. You can also parse a new music festival like CMJ or SXSW using non-numerical metrics to pick out which acts are going to make a splash.
But beyond these examples, we don’t seem to see much evidence of music executives hiring a geek like Brand to help them get ahead. Sure, there may be individual acts and managers who can point to how they have used metrics to build a successful tour or campaign. But as an industry, we still rely on instinct and experience, like those talent scouts working for A’s using those age-old gut feelings which worked in previous generations.
Like the baseball business, there’s almost a fear of moving beyond the tried and tested. There’s a fear of the geek. During the recent Hard Working Class Heroes convention, one of the panels I chaired was Meet the Geeks to show acts the importance of having a pet geek as part of their team. Yet most acts and music business insiders still see the geek as someone who will build them a website which won’t collapse in the middle of the night. The possibility of going beyond this is never considered or explored. It’s as if fresh thinking or new approaches are frowned on and what worked for the old music business will still do the job. Memo: this is not the old music business.
And the data is largely there. Labels have their Chart Track, Official Charts Company and Soundscan figures to pour over and exploit because people are still buying music (for now, anyway). Promoters can see from Ticketmaster dailies which gigs are hot and cold at different stages of a campaign, which might be a guide to how dynamic ticketing could work. Acts should be able to guage what effect ticket price could have on their long-term career. Indeed, all could take a leaf from the commercial radio stations’ playbook where research dictates what works on air (yes, just as you thought, you can blame the people who listen to radio stations for what you hear on those radio stations).
But the problem, as Beane and Brand encountered when they set out to revolutionise the A’s, is a fear of trying out something new holds people back. Just because something worked for years doesn’t mean it will continue to work in the future because other factors chip away at whatever competitive advantage you once had and disrupt your business model. In the case of the A’s, they didn’t have the cash to keep the bright stars they were developing and lost out to better funded clubs. In the case of the music industry, every sector is under attack from socio-economic changes, yet there is still a residual fondness and affection and enthusiasm and ardour for music, both recorded and live. It’s up to the players to exploit using all means necessary – and that includes some premier league number-crunching and data mining.
