There are all sorts of analytics out there – some to tell you what has happened and others to give you an idea of what will happen. Predictive analytics for hiring, if used correctly, will bolster your strategy for attracting talent, streamline your recruitment process, identify your workforce needs and improve quality of hire.
Kevin Wheeler, founder and chairman of the Future of Talent Institute, recently shared his expertise in a webinar titled "Predictive Analytics & Quality of Hire." He listed factors that do (and do not) make solid foundations for predictive analytics. Having clean data is vital, meaning it is accurate, complete and relevant. Also important is avoiding assumptions and being aware of biases toward certain aspects of a candidate’s background that might not necessarily indicate what kind of employee they will be.
Delving deep into many different types of roles and workers, Kevin offers factors that predict success for each. He also goes through the pros and cons of current methods of assessing talent, including Boolean resume searches, behavioral interview training, and culture fit tests. New and emerging methods have arisen, and Kevin covers those as well, along with ethical and legal issues that surround the use of some analytics.
In order to apply predictive analytics for hiring, an organization must clearly define what quality of hire means. Some questions to consider include:
- What is expected?
- What is an average performance?
- What would above average look like?
- How can performance be consistently and objectively measured?
- How is information on performance collected?
However your organization defines Quality of Hire, having the correct analytics at your disposal will lead to the type of candidates who will help you make better hiring decisions and reach your goals.
To hear the webinar, “Predictive Analytics & Quality of Hire,” click here.