Remember Moneyball? In 2002, the small-budget Oakland A’s used oft-overlooked statistics — on base percentage and slugging percentage — to drive their draft decisions and turn their season around. This data was available to every team in Major League Baseball, but the A’s were the only team who knew how to use it.
That’s exactly the kind of innovation we need to encourage in our understanding of talent in the workplace.
While building 2gn?ME, I have been in contact with a lot of recruiters, social scientists and talent management professionals. When asked what’s the hardest thing about their job, they all say the same thing: it’s incredibly difficult to quantify and compare candidates and employees. And so for the most part, they rely on intuition when they want to rely on data-supported information. When it comes to the qualities that really matter to each job, there are no standardized metrics to go on.
Our customers and experts agree that HR and Talent professionals need a trustworthy process for collecting accurate, actionable data on the traits and skills relevant to being good at a particular job in a particular team. Armed with this information, recruiters have a contextual framework to assess people’s credentials for specific soft traits and qualities in order to understand a candidate before they walk through the door, recognize top talent once they’re on the job, and provide appropriate training where it matters the most.
That’s what we’re trying to build. Because a better approach to utilizing applicant and employee data could make a world of difference in quelling employee disengagement and turnover. We believe that by validating our instincts, relevant data leads to better hiring and retention decisions and, in turn, more employees in rewarding careers.
Ilya Zeldin is the founder of 2gn?ME, a 360-degree awareness platform that helps people see themselves as others see them.
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