Visier's Predictive Analytics Technology Identifies Resignation Risk Employees
VANCOUVRE, BC: Visier, global provider in applied Big Data cloud technology and workforce intelligence, shared the results of patented predictive technology. The report states that Visier is 8 times more accurate in pointing out at employees who will resign the job rather than guesswork or intuition.
Visier follows continuous Machine Learning approach, where it looks back over 18 months of all the employees variables and attributes, categorizes them within each attribute and determines how much each correlates to the employee resignations that have occurred during that period It also tags each employees with “at risk” score ranging from highest to lowest resignation risk. For instance, if HR analyst, business partner or leader asks which employees are “at risk” in a specific employee sub-group like: specifying role, location, tenure and performance level, Visier, will automatically provide current relevant data based details “There has been significant hype around predictive workforce analytics, specifically around identifying employees most at risk of exiting an organization, Visier results is an unprecedented ability to validate how accurate the predictions are, says Dave Weisbeck, chief strategy officer, Visier. It adopts clustering analytics to generate a Key Drivers analysis, which highlights potential employees, attributes related to an increase or decrease in resignations.