NEW CHANGES TO TALENTRANK

It’s taken us a long time and many iterations to develop the right algorithms for sorting candidates. As a company that is mapping the global human capital pool of billions of individuals, we’re constantly adding more signals to our TalentRank algorithm. Nuance is everything when trying to winnow 100 million candidates down to the right 20.

One of the conclusions based on user testing is that we should offer several solutions and let the recruiter decide which approach delivers the best candidates for them. This is why we will allow recruiters to sort candidates to use our aggregated algorithms that look at dozens dimensions, but also allow them to sort specifically on the dimensions that are of most import to them.

In practice, what does this look like. Let’s look at John Sumser @johnsumser vs. Felix Wetzel @felixwetzel vs. Bill Boorman @billboorman. Our system has given them very similar professional engagement scores (they all interact with senior professionals in their field and blog/tweet about subjects relating to their professional role).

Based upon our proprietary education/company scoring

  1. @johnsumser
  2. @felixwetzel
  3. @billboorman

Based upon our scoring of the lexical density of their online posts:

  1. @felixwetzel
  2. @johnsumser
  3. @billboorman

Based upon scoring system for social authority:

  1. @billboorman
  2. @johnsumser
  3. @felixwetzel

Obviously, they’ve had different career paths, with different roles. And, so, our skills/job titles relevancy scoring would depend upon what the roll the recruiter was looking to fill.

But, if we merely offered recruiters candidates based on a single TalentRank score, we believe that we’d be doing them a disservice, since a recruiter is much better suited to determine the optimal weighting for ranking candidates. Bill, John, and Felix are all senior professionals at the top of their game and great hires for any company, but, if one were limited to just pick one, it all depends.


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