“The thing that you start to hear as you get bigger, when someone talks about a candidate they want to hire, they often start talking about how they’re excited because this person will hit the ground running,” LinkedIn’s Dan Shapero tells Quartz. “And hitting the ground running is a very short-term benefit.”
Shapero’s organization has certainly gotten bigger. He heads LinkedIn’s Talent Solutions group, which provides tools for recruiters and is by far the most profitable of its three major divisions. It produced $245.6 million in revenue last quarter, 55% of the company’s total. In Q2 of 2011, the first time LinkedIn reported earnings after its IPO, the division made $58.6 million.
The better way to hire, Shapero says, is to think about long-term potential and cultural fit.
“I’m trying to change the language on a team so they’re not talking about hitting the ground running, but about long-term potential,” Shapero says. “Who, over the course of two or three years, is going to have the biggest possible impact on the organization? That pivot has changed the way we think about new hires.”
Some of his most successful people, he says, don’t have a background typical to the job they have. They take a bit longer to get going, but it’s worth it.
“There was something in them, a fit with who we want to aspire to be as a company, a real aptitude, and a real motivation that we saw something in and were willing to take a bet and wait a little longer to see play out,” Shapero says.
The same was true for Shapero himself. He had no sales experience before coming to LinkedIn, but now leads its largest sales team.
Hiring for fit and potential is an advantage that his group hopes to bring to its customers. It’s offering them a more detailed fit between Linkedin members and open positions at companies. For instance, it shows companies “passive” candidates—people who aren’t actively searching but are open to the right approach, and who make up roughly 60% of LinkedIn’s 277 million users. Among the data it uses to pick them out are things like who they’re connected with, which company pages they follow, and which articles they’ve shared. It also hopes that blog posts by LinkedIn users—it recently decided to open up its publishing platform so any user can publish a post there—will provide another source of data.
“There are a lot of factors we can bring to the table to analyze fit,” Shapero says. “One is the connectedness of that person to a company. Another is whether that person has skills and traits that are reflected in that company’s most successful hires historically. It’s a very early part of our roadmap, but it’s something we think has tremendous future potential which no one else has really cracked.”
LinkedIn’s most recent acquisition, Bright.com, used data and machine-learning algorithms to match candidates with jobs. Applying that sort of technology to LinkedIn’s huge user base gives it an edge over other recruiters. Companies often have poor data about the people within their own company—an old resume, but little else. And they have little knowledge about passive candidates elsewhere.
“We sit on a tremendous amount of data. For many clients we know more about the recruiting environment around them or even about their own employees than they do themselves,” Shapero says.