Talent analytics has really taken recruiting and HR practices storm. What many company leaders thought they knew about best hiring practices is being totally obliterated the proven effectiveness of talent analytics.
Just last year you couldn’t click on a blog post or article without reading the words “Big Data”. Speaking of which, I still haven’t understood why it is so commonly capitalized. Anyhow, the talk is over and now through talent analytics, companies can actually use this information to discover what drives performance.
We like to believe that we’ve done a great job speculating what makes for a good hire and transversely a good worker, but case studies like this one from Josh Bersin in a recent Forbes article, shows hiring managers just how wrong they might be. I loved this example, because it takes this complex and sometimes confusing topic and makes it pretty easy to understand the value in talent analytics.
Bersin describes the hiring practices of one of their clients like those of many companies across the globe. They were hiring the good students, from the good schools in the hopes that these ideal candidates would be the performers that they needed. This seemingly common sense tactic has been used in recruiting for a very long time now.
They performed a statistical analysis with information from the first two years of new hires. This analysis explored performance and turnover rates and their correlation to different demographic factors.
What they found was pretty amazing. None of the hiring factors that they previously thought would deliver top performers were correct. Once a new screening process was implemented with the scientifically backed performance factors, the company saw a $4 million increase in revenue within 6 months. Bersin said,
“Companies are loaded with employee, HR, and performance data. For the last 30 years we have captured demographic information, performance information, educational history, job location, and many other factors about our employees. Are we using this data scientifically to make people decisions?”
Boom, this is where the “…and Your ATS” part comes in. The profiles and data that organizations have been collecting for years have some serious value. Even seemingly useless information about employees can end up being a real factor in predicting top performers. For instance, one of the top three factors that were highly correlated with success in Bersin’s example was “employees who had experience selling real estate or autos”.
The more efficient and detailed companies can get with their talent management, the more successful they can become at predicting hiring success. Performance documentation and information gathered through an LMS can also be used in talent analytics. This is shaping up to be a real part of HR and recruiting. Whether or not your organization will dabble in talent analytics, it is important to utilize the applicant tracking system to gather this valuable information in a manner that renders it useful for the future.
