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What Can Workforce Predictions Learn from Polls, Surveys and the Election?


Nate Silver and other election prognosticators have received some flak about his predictions in the presidential election.  Since we are also in the predictive modeling business, we collectively discussed his results and how or if it could have been more accurate.

voteModels learn after they are deployed and updated but they also have to contain the correct ‘inputs’, so our discussion focused on what variables Nate might have been using for his models.  We were hypothesizing of course, since Nate’s models are proprietary.  Hypothetically we know certain variables were there.

What we all wondered was, “what was left out” that made these models deliver such skewed results!

Can HR and Workforce Professionals Learn from this Election?

We can bring the conversation about Nate’s model and the election into the field of workforce analytics by asking, how does HR, at times, get it so wrong in their hiring decisions? Talent Acquisition teams are making predictions whether they are using predictive models – or whether they are using a less formal gathering of data.

  • Are they are they interested in HR metrics that come from a resume and other standard hiring data or using predictive workforce methods?
  • Are they reporting the outcomes of their predictions? Typically this data isn’t gathered.

Most companies don’t fully understand the power of hiring, polling or predictive methods.  This is changing as workforce analytics begins to come alive. Business outcomes are where “the rubber meets the road”.  If you want success in HR and or Workforce Analytics you need to tie your predictions to actual success or lack of success – whether or not you’re using sophisticated analytics or more traditional methods of evaluating job candidates.

Hats off to Nate Silver and others who put their predictive models and themselves “out there”.  Predictions aren’t perfect.  They need to deliver better success than randomness.  Nate and his models have historically delivered incredible value.  Workforce analytics’ models need to do the same.

Nate Silver is a Statistician and writer who analyze baseball and elections. He is the editor-in-chief of ESPN’s FiveThirtyEight and a Special Correspondent for ABC
https://en.wikipedia.org/wiki/Nate_Silver




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