Talent Analytics, Corp. has a unique approach to workforce predictive analytics. At our firm, we measure success by how our projects quantifiably benefit the Line of Business. We watch it, track it and report success. Our algorithms get better and smarter using the best Data Science methods available.
I’ve been involved in the predictive workforce arena for almost two decades. I must admit, I’m surprised at how many vendors claiming to reduce employee turnover or increase employee performance do little more than offer a solution that sounds effective. They say the right predictive analytics buzzwords, without showing or proving that their solutions actually work for their customers.
An example is the global multi-billion-dollar market of pre-hire talent assessment vendors.
Most pre-hire talent assessment vendors put their energy into creating validated questions that measure interesting human factors. This is called Content and Construct Validation and is just the first step in delivering business usefulness from a pre-hire talent assessment. This level of validation says nothing about whether their surveys are proven to deliver business value.
Few vendors go the extra (and difficult) step of criterion validating their talent assessments.
My observation is that in the last 30 years, businesses and their vendors have moved away from using economic measurements of business outcomes to solve problems with staffing.
We’ve become more obsessed with employee engagement, job satisfaction, fancy software and recording every single activity our employees do instead of focusing on empirical evidence to prove our initiatives actually deliver value for the business, or not!
Predictive analytics delivers outcomes not possible without algorithms. Everyone wants their solution to be predictive. This creates an industry of non-predictive vendors using predictive-sounding phrases like “the highest probability of success” and “pre-hire predictions” and “when the solution was implemented, the company stock price increased.”
It’s hard for prospective buyers to be able to tell the difference, but we owe it to our companies to do so. Ask for proof. Ask for case studies. Ask for documented results. Ask for details about their predictive process. Read about their data scientists on staff. Push to learn more beyond the words they’re using. Just because they say “predictive” or have the word predictive in their company name doesn’t mean they really are.
And for sure, if you’re using talent assessments, ask if they’ve been able to repeatedly criterion validate their talent assessments. In the end, business results are the only measure that matters!
Greta Roberts, CEO & Co-founder
Greta Roberts is an acknowledged influencer in the field of predictive workforce analytics. Since co-founding Talent Analytics in 2001, she has established Talent Analytics, Corp. as the globally recognized leader in predicting an individual’s business performance, pre-hire and post-hire.
Read more from Talent Analytic, Corp. “Are Employees Costs or Assets?”
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