Are All Predictive Talent Acquisition Platforms Created Equally?

Interview between Greta Roberts, CEO and Carla Gentry, Data Scientist, Talent Analytics, Corp.

Many people ask whether or not you lose a bit of the “human element” when you use talent acquisition platforms.

Q1 Carla:  More and more companies are using predictive processes to lend insight to new hires.

What kinds of platforms do you see most useful and the most popular?

A1 Greta:  Most useful and most popular are sometimes 2 different answers.  I’ll address both.

Most Useful Predictive Platforms identify candidates who are predicted to a) perform and b) last longer in their role.

Detailed predictions require a level of interaction with your company’s data (HR data plus Line of Business Data) to determine what attributes predict a top performer for your company vs. another company.  These attributes can be very different company and by company.

An example of a pre-hire predictive platform is Talent Analytics’ own predictive platform called “Advisor” which identifies top performers (either internal or external candidates) based on what a top performer is in your company and in your specific role.

How you know these predictive platforms work?  They track the predictive results and share them with your company monthly or quarterly. The only reason to use a predictive model is if it is working.

Ask your platform vendor how often you will receive results on how your predictions are performing.

“Silver Bullet Platforms” are sometimes the most popular.  These platforms claim to identify great candidates for your company without the need to process significant data about current employee performance at your company.  We call these Silver Bullet Platforms because they are easy for the company and HR to use.  Just a single silver bullet does the job.

They don’t require data analytics work on the part of the vendor.  They are somehow magically able to “tell” if a candidate would work out for your firm without knowing what is currently working for your firm.

They seem almost “too good to be true” and in fact they are.  They tend to have a beautiful interface, and are easy to use.

Read more about how other fields are using predictive analytics here ->
3 Parallels Between the Future of Retail and the Future of the Workforce

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