Challenges and benefits of hiring algorithms
As noted in part one of our look at hiring algorithms, many studies show that when employers lean heavily on them, they end up with workers who are more productive, earn higher performance ratings (from humans, not just computers), and have higher employee retention rates.
But replacing human judgment with fancy analytics, trendy big data, or a spreadsheet tally of qualifications comes with its own challenges. Here’s a brief tour of these complex issues and some approaches to incorporating algorithms into your organizational hiring.
The starting point: manager buy-in
Many business veterans want to believe they’ve developed an eye for spotting candidates who will succeed. Yet countless organizations have found out the hard way that a hiring manager’s instinct and a recruiter’s experience often fall short.
“For many years we struggled with recruitment and retention,” says Carlyle Walton, CEO of Metroplex Health System. “We were always looking for tools to improve this.” Metroplex decided to harness algorithmic hiring to do much of the heavy lifting. After choosing a product, the next hurdle was to persuade managers to use it by involving them in the implementation process. “This journey started with us having managers identify the top performers,” says Walton. “This helped to get buy-in.”
Managers pitching the implementation of recruitment algorithms will indeed “encounter a lot of resistance,” says Nathan Kuncel, a professor of psychology at the University of Minnesota. “We can get a lot of good from the algorithm, but still keep it acceptable to people by emphasizing the roles that they continue to play in the process.” For the time being, Metroplex is allowing use of the software to spread organically through the organization, with each department deciding whether to use the hiring algorithm and to what degree.
Algorithms have limits, but they do boost hiring quality
Another key issue is the functionality that algorithms can fulfill. “We use the software for all positions in a hospital below the executive level: nurse, admitting clerk, pharmacy, and so on,” says Mike Rosenbaum, CEO of Pegged.
Some, like Rosenbaum, believe that algorithms don’t work for executive recruitment — at least not yet. He cites the insufficient amount of data available due to the small number of positions at this level. Others, like Michael Distefano, Senior VP and Chief Marketing Officer for executive recruiter Korn Ferry, think that algorithms can provide greater insight into hiring for the C-suite as well.
Walton believes the use of algorithmic hiring has improved Metroplex’s workforce in general. “We have seen reductions in turnover and increases in quality scores since we started using software to evaluate candidates; this is one piece of what has contributed to these improvements.”
Hiring algorithms don’t eliminate bias liability
For many employers, one of the top reasons for adopting recruitment algorithms is to avoid the very human inclination, whether conscious or not, to hire people who are like oneself. And that can be illegal if the similarity is about race, gender, religion, disability, or other characteristics that define a protected class. However, algorithmic hiring doesn’t automatically eliminate bias.
“If a company is screening out applicants on the basis of a computer algorithm, the managers need to make sure the algorithm has been validated,” says Heather Morgan, global chair of the workforce data and technology practice at law firm Paul Hastings.
“You’ve got to do your due diligence of asking the vendor the right questions,” says Morgan. “It’s hard to validate something that’s continuously learning and changing,” and some algorithms do that.
Morgan further advises that human resources professionals need training from legal on how algorithms should be incorporated into hiring procedures, what the risks are, and how the process should be monitored in order to maintain a legal hiring process.
What about that temptation to overrule the algorithm?
Who wants to hire a candidate — top-rated by a bloodless software application — who struck the hiring manager as somehow just not right for the job? This situation presents a conundrum for HR and company executives.
“There’s a temptation to think ‘My gut can make a better evaluation than Pegged,'” says Walton. “But in our experience, in the three cases where our managers overruled the software, the new employee separated within 90 days. The software is a powerful tool if the leader embraces it.”
Recruiting firms that use algorithms may be especially reticent to suggest that number crunching should trump human judgment. “The algorithm just provides another data point,” says Distefano. “At the end of the day, you go with your gut.”
Others argue that, as with any questionable departure from established HR processes, exceptions should be documented. “Decision makers should be required to write a justification for overriding a hiring algorithm,” says Kuncel.
Improving recruitment — a never-ending task
Even as technology advances to aid recruitment, the human element remains a vital part of the process. Whether you’ve embraced tools like hiring algorithms and AI, or prefer more old-school approaches, there will always be ways to improve your recruitment strategies. Get help from expert recruiting advice and the latest hiring trends when you sign up for Monster Hiring Solutions.