Moneyball Sourcing: Don’t Overlook The Role That Tools Play In The Science Of Winning

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Jun 12, 2012

In the decade since Michael Lewis published Moneyball, The Art of Winning an Unfair Game, “Moneyball” lessons and applications have become far reaching—even into sourcing and recruiting.  In previous articles, I have looked at Sourcing Through the Lens of Moneyball; illustrated how the principles of Moneyball are applicable to talent sourcing,  social recruiting as well as talent acquisition analytics.  Today I would like to explore real hero in Moneyball–analytical tools and a sourcing platform that enhance Moneyball Sourcing.

In the context of Moneyball, the Moneyball Sourcing model follows a similar three step path:

  1. Challenge conventional wisdom
  2. Understand the science of winning
  3. Adapt or die

Gaining an understanding of the “science of winning” was the big “a-ha” for Moneyball and the Moneyball strategy.  While the geeks and the data miners were gaining a loader voice in baseball, there was a definite line of resistance to move from the art of evaluating baseball talent to looking at wining through a more scientific lens.

Moneyball is a book about how to create a winning team by putting the players on the field that are capable of accomplishing the activities that predict success or winning baseball games.  The Moneyball strategy emphasizes a sophisticated understanding of data and statistics to help small budget baseball teams compete with their higher-spending rivals.  The tool the Oakland A’s employed was subscribing to the services of Ken Mauriello and Jack Armbruster and their advanced value matrix, (or A.V.M.), which eventually transformed conventional baseball accounting.  This tool was essential to parsing through the big data and producing a useful product; because without the proper tool, the result was lot of useless data.  The A.V.M. tool was the real hero of the story.  I believe that same situation exists in sourcing talent—using the right tool to analyze and parse the data can become the game changer.

The Moneyball Sourcing strategy that features the game changing tools

  • Imagine a database that allows you to search all the software developers in the world.
  • Imagine that you view a complete profile on a prospective candidate that was compiled or aggregated from a number of sources.
  • Imagine using mobile as a recruiting platform
  • Imagine being able to determine the level of technical expertise of each software developer—that’s right, you are able to determine the difference between “A” & “B” players.
  • Imagine using the “social signals” to be alerted when talent is showing signs of looking for a different job.

Sheeroy Desai and his team at Gild are offering a platform for technical sourcing that is very intriguing. Gild Source, when completed, is expected to have over 5 million profiles of software developers and engineers that will reflect hobbies, interests, work history, social graphs and a scoring of their technical abilities—everything a technical sourcer or recruiter needs.

Like, the baseball Moneyball counterparts, Sheeroy offers a different perspective or thinking when it comes to evaluating target talent.  In baseball, Moneyball thinking moved from a “gut feeling” to measuring actual performance and putting that information (data) into a useable format.  In sourcing, instead of looking primarily at the schools, companies and titles of the individuals, this Moneyball approach analyzes the target audience’s software code and scores their technical competence.  Sheeroy explains, “Great developers are really deep in programming languages and have a breath of languages. They spend their free time coding, writing, dabbling and trying to pick up new languages. Gild Source focuses on grabbing all the relevant data and aggregating and scoring the right information. Ultimately, we want our customers to know who (target talent) they are, what interests them, and when is the right time to call them.”

When the word got out that AVM Systems (Ken Mauriello and Jack Armbruster) data was the real reason that the Oakland A’s were able to compete against the baseball powers and win, baseball talent decisions were made on a very sophisticated approach to analyzing performance.  This new approach went beyond just the collection of data but to analyze it in the context of the game and offer a way to score the results—thus making winning more predictable.  When word gets out about Gild, I imagine this platform will have the same ground leveling impact on technical sourcing and recruiting—if you spend your efforts on recruiting the best talent, the results can be game changing for your business—no matter its size.

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