{"id":18297,"date":"2025-05-19T22:20:46","date_gmt":"2025-05-19T22:20:46","guid":{"rendered":"https:\/\/talentest.com\/blogue\/la-science-derriere-la-predictibilite\/"},"modified":"2025-09-04T09:47:32","modified_gmt":"2025-09-04T09:47:32","slug":"the-science-behind-predictability","status":"publish","type":"post","link":"https:\/\/talentest.com\/en\/blogue\/the-science-behind-predictability\/","title":{"rendered":"The science behind predictability: why certain data can (really) help you choose the right person"},"content":{"rendered":"\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t

\n\t\t\t\t\tCan we really predict a candidate's success at work?\t\t\t<\/h3>\n\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

This is the big question, not only in HR, but in all areas where decisions are made about human beings. When we talk about predictability, especially in the world of psychometric assessment, we’re not talking about crystal balls or managerial intuition. We’re talking about data, science, and validated and tested models.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

At TalenTest, we like to go beyond simple fit or interview impressions. We rely on science to offer tools that truly predict behavior, performance, and adaptability. And that’s possible thanks to what we call psychometric predictability.<\/span><\/p>

This topic resonates particularly with Sylvain Brodeur<\/span><\/a>, a well-known figure in the HR world who stands out for his human, nuanced, and strategic approach. His perspective on predictability is invaluable: he reminds us that behind every piece of data is a person, a team, an impact. For him, the challenge is not to predict for the sake of predicting, but to do so in order to better support, better guide, and better decide.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t\t\t\t\t\t

In this article, Sylvain provides an accessible (yet rigorous) overview of the science behind predictability. Why is it important? How does it work? And above all: how does it actually change your HR decisions?<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t

\n\t\t\t\t\t1. What is predictability?\t\t\t<\/h3>\n\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

In simple terms, predictability refers to the ability of a tool or indicator to predict a future outcome. In HR, this outcome could be job performance, job stability, ability to collaborate, or even job satisfaction.<\/p>

Concrete example:<\/strong>
If a test measures logical ability and people who score high perform better in analytical positions, we can say that this test is predictive of performance in this type of role.<\/p>

But be careful:<\/strong>
For a tool to be truly predictive, it is not enough for it to \u201cseem\u201d relevant. It must have been scientifically validated, i.e., studies must have demonstrated that there is a significant correlation between the test result and the target criterion (e.g., performance, commitment, long-term success).<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t

\n\t\t\t\t\t2. Predictability is a matter of correlation... but not only that\t\t\t<\/h3>\n\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

In scientific jargon, we often talk about predictive validity. It is measured using correlation coefficients, generally between 0 and 1. The higher the correlation, the more predictive the tool.<\/span><\/p>

Here are some benchmarks:<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t\t\t\t\t\t