Hiring and retaining top talent keeps getting harder. Bad hires, however, are easy to make and they impact businesses at many levels, from productivity decrease to reputation damage and high turnover rates, companies have a lot more to lose besides money.

Also very often, hiring managers end up looking bad in the picture due to the impact bad hires have on the organisation. As such, it is crucial to stop using traditional, gut feeling-based recruiting and selection methods which leave hiring decisions up to chance.

When it comes to getting the right talent in the right roles, traditional hiring methods are not good enough, anymore. Hiring managers and recruiters need to push further, and using a data-driven hiring strategy can definitely improve decision making and help onboard the best talent in a faster and more efficient way.

As bringing in a new hire is always a risk, any tool that helps identify a better hiring decision is essential, and predictive hiring technology offers the best approach to improve and boost talent acquisition.


What is Predictive Hiring?

Predictive hiring is a recruiting technology that uses data and analytics to improve recruitment outcomes by recommending best-fit candidates to recruiters and hiring managers.

While traditional hiring practices are often based on brief resume screenings and the recruiter's gut-feeling during interviews, predictive analytics for hiring leverages historical data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future. Meaning, allowing to make predictions about candidates and improve the talent acquisition process through data-driven decision making.




Communicated by skeeled

Publié le 09 décembre 2020