For more and more companies, the hiring boss is an algorithm. The factors they consider are different than what applicants have come to expect. Jobs that were once filled on the basis of work history and interviews are left to personality tests and data analysis, as employers aim for more than just a hunch that a person will do the job well. Under pressure to cut costs and boost productivity, employers are trying to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims or steal.
Some companies are screening for such variables as attitudes toward alcohol use or the distance an applicant lives from the job. The process could get companies into legal trouble if it ends up excluding minorities or the disabled. Even if it doesn't, it might come off as unfair, or even creepy.
"The public gets less comfortable when you're using extrinsic or personal factors," said Dennis Doverspike, a professor of industrial and organizational psychology at the University of Akron in Ohio.
Though hiring is a crucial business function, conventional methods are remarkably short on rigor, experts say. Depending on who decides, what gets candidates hired can vary wildly—from academic achievement to work experience to appearance.
Managers who go with their gut might get it right sometimes, but their hunches generally have little value in predicting how someone will perform on the job. Companies peddling a statistical approach to hiring say they can improve results by reducing the influence of a manager's biases.
Source: The Wall Street Journal, September 20, 2012