Analytics, Sales and Marketing, and “Moneyball” The Promise (and Peril) of Relying on Data

Way back in 1983, as a baseball-crazed teen who wasn’t that good at playing baseball, two books were top of my reading list: The Art of Hitting .300 by Charlie Lau, which I hoped would make me hit the ball like George Brett, and Bill James’ Baseball Abstract.Analytics-Sales-and-Marketing-and-Moneyball

Charlie Lau let me down, but Bill James did not. For those not steeped in the history of baseball statistics, James was obsessed with statistics, and not just the standard statistics that appeared on the back of baseball cards: average, runs, home runs and runs batted in (RBIs) for hitters, and wins, saves, strikeouts and earned run average (ERA) for pitchers.

James’ advanced analysis (along with that a few like-minded numbers nerds) resulted in the creation of SABRmetrics (SABR standing for the Society for American Baseball Research). This study resulted in scores of new ways of examining baseball data, the most readily used being stats like OPS (on-base plus slugging percentage) for hitters and WHIP (walks plus hits per innings pitched) for pitchers. It also gave new weight to existing but undervalued statistics, like on-base percentage (which factors in the times a batter reaches base by a walk or by being hit with a pitch).

These statistics were what Billy Bean used to make the low-payroll Oakland A’s competitive for many years. This was dramatized in the movie “Moneyball,” based on Michael Lewis’ book. Using metrics that were different from his competitors gave Bean a genuine competitive advantage; he could sign players other teams overlooked for less money and get very good results from them.

The sad part about the film “Moneyball” is that it denigrated the work of the talent scouts who signed many of the star players of the 2002 A’s. Only a handful of players on the roster were “Moneyball”-style offbeat signings. The “big three” of the pitching staff – Mark Mulder, Barry Zito and Tim Hudson – were the results of scouting; star infielders Miguel Tejada, Eric Chavez and Mark Ellis all came up through the A’s farm system.

This metaphor is nearly perfect for what’s going on in sales and marketing right now. We’re moving hard toward a greater and greater acceptance of data – in determining leads’ readiness to buy, in discovering what actions move leads toward a purchase decision, and in dozens of other areas. This requires us to look at sales data, and sales performance data in new ways. It also requires us to have systems in place to collect and manage this data. It’s an extremely exciting time to be a sales manager, because there are multiple opportunities available to gain a competitive advantage by using data in a creative way that your competitors have missed.

With the advent of things like CallidusCloud’s Predictive Sales Performance Platform (introduced at C3 2105 – if you haven’t seen the keynote that explains it, do yourself a favor and check it out), managers will be able to use this data to develop a projection about the future performance of their sales team, right down to the individual sales rep. The opportunity this offer for building the right kinds of sales teams and for motivating sales people is tremendous.

But, at the same time, this analysis is meaningless if it’s not combined with the right sales talent. Understanding the people on your team as people is another task that sales managers need to master, and it’s one the technology can only provide limited help in accomplishing. There is still space for the traditional ways of building and motivating a sales team – allow those skills to atrophy at your peril.

The other lesson to learn from “Moneyball” is that the A’s didn’t win the World Series in 2002, or in any year since Bean has been manager using his “Moneyball” methodologies. However, the Boston Red Sox adopted many of Bean’s tactics and combined that with a significantly higher budget, and won the World Series in 2004.

In other words, analysis cannot completely overcome a deficiency in resources – and that goes for sales and marketing. Expecting your sales performance to be strong with an undermanned, underequipped sales and marketing team simply because they’re smart at analysis is completely unrealistic; it’s making the mistake of using technology as a panacea. Making the proper investments in people is critical if you hope to harness the insights analytics reveals.

Data and analytics is critical for the success of any sales and marketing organization – but only when it’s used right and paired with the right talent. Make the 2004 Boston Red Sox your role model, not the 2002 A’s.

By Chris Bucholtz | September 11th, 2015 | Marketing

About the Author: Chris Bucholtz

Chris Bucholtz

Chris Bucholtz is the content marketing director at CallidusCloud and writes on a host of topics, including sales, marketing and customer experience. The former editor of InsideCRM, his weekly column has run in CRM Buyer since 2009. When he's not pondering ways to acquire and keep customers, Chris is also an avid builder of scale model airplanes.