New research shows that computer algorithms are better at picking the best job candidates than humans.
Employees, picked by ‘job tests’ stay longer and perform better, according to the National Bureau of Economic Research, which studied 15 companies and in excess of 300,000 employees in low-skill service-sector jobs.
Who should make hiring decisions? Resumes, interviews, and other screening tools are often limited in their ability to reveal whether a worker has the the right skills or will be a good fit.
The report argued that managers who are employed to interpret the information have poor judgement or preferences that are imperfectly aligned with the company’s objectives.
It said that the increasing adoption of workforce analytics and job testing has provided companies with new hiring tools.
The research found that job testing substantially improves the match quality of hired workers: those hired with job testing have about 15% longer tenure.
It also found that managers who overrule test recommendations more often hire workers with much lower match quality, as measured by job tenure.
“The second result suggests that managers exercise discretion because they are biased or have poor judgment, not because they are better informed,” the research paper said.
“We propose an empirical test for assessing whether firms should rely on hard metrics such as job test scores or grant managers discretion in making hiring decisions,” the research paper said.
“Our results suggest that firms can improve worker quality by limiting managerial discretion. This is because, when faced with similar applicant pools, managers who exercise more discretion – as measured by their likelihood of overruling job test recommendations – systematically end up with worse hires,” the report said.