Moneyball, as its name suggests, is serious business


I know virtually nothing about — and have even less interest in — baseball.  But I LOVE the movie Moneyball (based on the Michael Lewis book), which is about the application of “HR analytics” to the game.

If you haven’t seen it yet, I highly recommend it.  It is the story of how a soft-spoken, recent Yale economics grad applies his analytic know-how, with the help and support of the Oakland A’s general manager (played by Brad Pitt) to help achieve remarkable success (as measured by games won), with the smallest budget in the league for buying “talent.”

Some of the lines in the movie (I’m paraphrasing here) could be lifted from my day-to-day work life as an economist applying the principles and insights of behavioral economics to the business world:

  • “People are running the business on fundamentally wrong assumptions.”
  • “This is going to fundamentally change the game.”
  • “The reason people are resisting it is because it is going to change how they make a living.”

In addition to being entertaining, Moneyball is worth watching because it has important lessons for business.

There is competitive advantage to be gained through analytics – no matter what business you are in.  And the laggards will be the losers.

Lessons from the world of sports


We’ve observed previously that the world of sports has been in the vanguard in making use of workforce analytics (with the playing field representing the workplace).  Baseball, with its discrete inputs and outputs (balls, strikes, singles, doubles, runs, outs), has always been the ideal sport for stat-heads.  Newer, often exotic-sounding baseball measures like WAR and UZR have even begun to creep into mainstream media coverage when evaluating what teams are most likely to end up on top at the end of the season, who’s productive and who’s not, or who’s earning their salary and who’s not.

On the other hand, until recently, more free-flowing team-oriented games like soccer, hockey, and basketball have proven fairly resistant to the successful application of analytics.  How to measure how much a soccer team’s passing contributed to the end result in a 1-0 game?  Or how to make sense of the often barely-controlled chaos of a hockey game?  Or to measure the extent to which a basketball team’s defensive positioning and teamwork affects the likelihood that a given shot goes in?

Seeking to improve their understanding of what’s really driving the bottom line – wins and losses – team executives and fans alike have combined creative thinking, improved computing methods, and sheer doggedness to create new insights into what matters most in each of those sports as well.

And so it is in the work world outside of sports.  Companies have long deployed statistical measures in key areas that were easier to measure (e.g., ROI, EVA).  The more free-flowing areas of work – like how employees get the job done, how they learn from one another and, most importantly, what matters to the bottom line – have been much more resistant to measurement and analytics.  But no longer.  Tools and techniques (like the McBassi People Index®) now make it possible to measure precisely what specific elements of an organization’s work environment are most important in driving outcomes such as sales or safety or employee retention.

Organizations not pursuing such analytics are increasingly at risk of being left behind, with a lousy won-lost record, mired at the bottom of the latest standings.

(This post was sent via email to our monthly newsletter subscribers earlier in June.  Click here if you’d like to subscribe.)


More on sports analytics


The Boston Globe Magazine’s cover story this past weekend profiled a variety of analysts who are using their talents in the world of sports to drive greater success through thoughtful, creative use of numbers. 

Because of the multitude of statistics available in sports, it’s a perfect field for analytic trailblazers.  We expect this analytic trend to spread far beyond sports in the years ahead, as other industries recognize the power of numbers, work to create meaningful people metrics, and then crunch the numbers to generate new insights about what’s driving key outcomes.

Talent analytics in the NBA


Interesting article about the use of analytic basketball data by Chris Bosh of the Miami Heat (National Basketball Association) and his coach Erik Spoelstra – as well as the challenges in pushing that information too far.

Of course, most employers don’t have anywhere near that level of detail on the specific performance and effectiveness of each of their employees.  But for organizations that are leading the way in applying human capital analytics, there are certainly some comparable insights that are helping to improve overall performance – and leading to the equivalent of more “wins” and fewer “losses.”