The Moneyball Recruiting Opportunity: Analytics & Big Data

 

Earlier this year, I traveled to Australia to present a keynote at the Australasian Talent Conference on the topic of the Moneyball opportunity that exists for companies when they are sourcing, identifying, assessing, recruiting, and developing talent, and how big data and predictive analytics will be the next major area of competitive advantage in the war for talent.

Below you will find my keynote presentation, including a couple of YouTube videos.

Big Data and predictive analytics are just beginning to be leveraged in talent acquisition by a few forward thinking companies, and I am convinced they will both play major roles in the near future.

Unfortunately, at this time there is still some confusion around exactly what “Big Data” is and is not. For example, this Wall Street Journal article¬†incorrectly references the use of personality assessments and other online tests to facilitate hiring as an application of Big Data, when in fact it is really just an example of analytics.

Data from personality assessments and online tests coupled with other human capital data doesn’t represent a combination of high-volume, high-velocity, and/or high-variety information assets, which most experts agree is required for something to be classified as “Big Data.”

In this presentation, I think you will find the examples of how companies are currently leveraging analytics in their recruitment as well as in the analysis of their current workforce to be quite interesting, as well as some of the tools that already exist that do in fact harness high volume, high velocity, and high variety information assets.

You may be shocked to find that data supports the finding that taller and more attractive men and women make more money than their shorter and less attractive peers (especially shocked to find out exactly how much more!) – which gives us a glimpse into how people make hiring and promotion decisions on a daily basis based on unconscious prejudice, similar to how unconscious prejudice, wisdom, and “gut” instincts are and have been used in athletic recruiting – which Billy Beane and Paul Depodesta of the Oakland A’s specifically set out to counter.

As demonstrated in Moneyball, very strong teams can be built with data-based decision making, throwing conventional wisdom to the wind.

Enjoy the presentation, and please do let me know your thoughts. Thanks!

 

 

If you like what you’ve seen in the Slideshare, you may want to read this post I wrote on Big Data, Data Science, and Moneyball recruiting last year.