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Given all the talk we hear about big data and HR, it’s no surprise that algorithms are playing more of a role in recruiting. That role is growing slowly: Observers agree we’re in the midst of an evolution, not a revolution. But there’s also little doubt that as the use of algorithmic tools spreads, the recruiter’s role will change.
The impact may be especially dramatic on the roles of sourcers, the professionals who hunt around LinkedIn, job boards and other databases to identify potential candidates. Sheeroy Desai, chief executive of San Francisco-based recruiting software developer Gild, thinks the need for their Boolean search skills will disappear as sourcers focus on making initial contact with the candidates uncovered by technology. In essence, he says, their job will be about “getting people into the funnel.”
The idea of using algorithms in recruiting isn’t new. As early as 2010, developer Matt Biddulph was blogging about his machine-based approach to identifying technology talent. In the years since, as discussions grew about the role big data could play in HR, it was natural for a number of people and companies to explore ways data could be harnessed to identify and land better candidates.
However, it’s only been in the last 18 months or so, Desai said, that he’s been able to spend less time evangelizing the idea of algorithmic recruiting and more time talking to customers about specific solutions. “We’re still in the early innings,” he noted.
Meaning Out of Chaos
Most recruiters and developers see much promise in the idea of running algorithms against the increasingly large data sets becoming available on candidates through social media, professional assessments and other channels.
Algorithms are needed “to take massive amounts of data being generated before, during and after the recruiting process and turn it into actionable information—with one goal being to predict whether a person will be right for the job, the team and the company,” said Steve Levy, director of global sourcing at Austin, Texas-based job site Indeed.
But, as Desai observed, algorithmic recruiting can intimidate recruiters. What they don’t realize, he said, is they may already be using algorithms in their work. “My guess is if I asked, recruiters would say they don’t know about algorithmic recruiting but will talk about their neat tools.”
In Desai’s mind, algorithmic technology will sidle into recruiting much as it did into marketing and sales a decade ago. Sales and marketing automation hasn’t led to the demise of the salesperson’s role, he pointed out. But rather than cold calling or digging up their own leads, sales people today use technology to handle the mundane aspects of their work while they focus on building relationships and closing deals. Meanwhile, their executives use algorithms to study data that was previously too unwieldy to do much with—for example, to analyze closed deals for promising trends.
Less Bias, Better Relationships
Thus, one change may be that recruiters spend less time on sourcing and more time on selling the company and the role. “It will make the recruiter’s job easier, but it won’t replace them,” said Lars Schmidt, founder and principal of recruiting and employee-branding consultant Amplify Talent in Reston, Va. “Recruiting is more than candidate identification,” he said.
And once candidates have been identified, they still have to be led through the hiring process. For recruiters, that means developing relationships that can ultimately lead to the right hire. “Top talent is being inundated,” said Schmidt. “So how do you break through the noise? It’s the human capability to reach out and have a conversation, to really learn about the candidate, what they like, what might get them to leave their current job. I haven’t seen software that can do that.”
That doesn’t mean the recruiter’s core skills won’t need to change, suggested Corry Prohens, co-founder and CEO of IQ Workforce, a talent on-demand provider in Princeton, N.J. “Ten years from now, recruiters are going to be part-time analysts working with analytics teams to determine what they want and identify the right parameters,” he predicted.
“On one hand, these complex algos can actually simplify the way sourcers and recruiters identify and engage with candidates by minimizing the impact of implicit biases,” added Levy. “At the same time, the more you automate something, the less human it becomes, and people do notice.”
New Approaches, New Roles
In fact, the algorithm’s greatest impact may be felt by sourcers, the professionals who hunt around LinkedIn, job boards and other databases to identify potential candidates. Desai thinks the need for Boolean search skills will disappear as sourcers begin spending their time making initial contact with the candidates uncovered by technology. In essence, he said, their job will be about “getting people into the funnel.”
The increasing use of algorithms doesn’t appear to worry many sourcers. “Is there a program out there that will capture what the corporate culture is? How will these tools measure that?” asked Lily Li, an independent sourcer in New York. At the same time, Li agreed that the “real value of sourcers will be in candidate engagement and doing better at that.”
Greg Ambrose, a Chicago-based managing consultant at Korn Ferry Futurestep, pointed out that algorithms will only be as effective as the data they work with. “What about people with bad keywords on LinkedIn?” he asked. “We’ll always need people who can identify talent.”
That said, Ambrose thinks that ultimately algorithmic tools will help recruiters become more strategic. In 2014, Korn Ferry launched KF4D, which helps assess the traits of executive candidates in the context of their proposed role’s demands. “We’re seeing that it helps us become more strategic and provide greater insight,” Ambrose said. “We can look at the drivers that make someone successful and how they align with the company’s culture. It provides another data point for the employer to consider.”
And an entirely new position may be created, Desai said: that of the re-marketer. “Companies spend a lot of money getting people to apply for jobs,” he said. “For every 100 of those, they hire three. Well, what about the other 97? No one’s doing anything about nurturing them. You have to keep re-marketing, and I think we’ll see the emergence of that role.”
“The evolutionary beauty behind these algorithms and ‘talent analysis’ is that they’ll actually enable sourcers and recruiters to be more human,” Levy said, “and this will have a positive impact on hiring and retention.”
Mark Feffer is a freelance business writer based in Philadelphia.
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