Why you should care
Because some startups are making that glass ceiling a little more rubbery.
As the newly appointed engineering director for Yahoo’s India office, Abhijit Khasnis ran into a problem several years ago when he was expected to recruit and manage over 200 people — ASAP. The best talent was already employed and working jobs that required one to three months notice once someone decided to quit and switch over to a new company. Frustrated, Khasnis didn’t want his projects on hold until he could get the staff he needed, which is when he wondered: Couldn’t he try to grab an overlooked pool of candidates — namely those on their way out from a previous employer?
Bingo. Khasnis’ idea led to Hiree (the startup previously known as myNoticePeriod), which he launched last year with co-founder and former Yahoo colleague Manjunath Talwar. Their solution isn’t as applicable in the U.S., with its fire-at-will policies, but they’ve filled a gap in India and are looking elsewhere in Asia and Europe, where employees must often give lengthy notice periods once they want to quit a gig. In March, they received $3 million in funding from IDG Ventures, and they say they’ve already registered more than 400 companies — including Sony and Hitachi — and over 50,000 active job seekers.
Hiring is broken.
Kedar Iyer, founder of GapJumpers
Getting hiring right is a challenge for companies around the world, and Harvard Business Review estimates that up to 80 percent of employee turnover is due to bad hiring decisions. More startups are now attempting to solve the turnover issue by tackling various problem spots in the human resources pipeline — including gaining access to otherwise hard-to-reach candidates, à la Hiree. Others are coming up with creative solutions, such as job simulation software, to weed out bad fits from the get-go (Prehire), or turning to “gamification” to make the applicant process more fun but effective. Candidates using CodeEval and HackerRank, for instance, play browser-based coding games in which high scores unlock access to recruiters, while those completing Pymetrics’ data-driven neuroscience games get to evaluate and create an “emotional trait profile” that matches them to certain roles.
This movement is being driven, in part, by companies that say traditional hiring techniques such as resume screens and interviews don’t come up with the best candidates. “Hiring is broken,” says Kedar Iyer, founder of GapJumpers. His San Francisco-based company promotes workplace diversity by stripping race and gender data from applications so employers hire blindly and avoid unconscious stereotypes. After 1,200 blind auditions for tech roles, in which anonymous candidates who best perform challenges tailored to employer requirements move on to interviews, 58 percent of those hired turned out to be women — compared with a national average of 13 percent of engineering staff, according to data from the National Science Foundation.
Other hiring-centric startups are also trying to gain an edge among companies that are trying to focus on achieving a better balance across both gender and racial lines in their offices. Prehire CEO Darren Nix calls his work simulation software an “equalizer” because it’s performance-based, while Pymetrics’s head of user acquisition, Alena Chiang, believes that measuring personality with psychometric games ensures a good fit, regardless of gender.
But psychologist Donna Dunning warns that “it’s a misuse” to employ personality tests and psychometric games in recruitment because they can lead to “role casting and not giving people a chance.” Meanwhile, engineer James Maisu has tried gamified coding tests and says he doesn’t think they’re all that practical — they’re good if you want a “passable code monkey” but they don’t offer insight into someone’s thought process. And while these startups are trying to challenge entrenched hiring systems, they’re still in their infancy, so long-term feasibility against giants like LinkedIn is still a question.
Even so, the startups are pushing on by targeting companies with specific issues — such as those struggling to ensure newbies fit their corporate culture and actually stay on board. That’s where Jeff Barson hopes Utah-based HireVue Labs, founded a few years ago as an experimental arm of HireVue, will take off. The startup develops machine learning programs for recruitment that use algorithms to predict the future behaviors of potential employees, divining if candidates are motivated, trustworthy, ethical and full of management potential.
Barson says this is possible due to high-level access that his business has been granted by companies that share data about employee performance and salary changes. By tracking rising stars — and failures — on video interviews, HireVue tries to predict which traits denote success at different companies, and pair them with people who have matching characteristics. “It’s just data, but it has never been available before,” Barson says. “Organizations know who they hire, but not why.”
Sure, this sounds Orwellian, though Barson argues his datacentric method is fairer, as every resume receives equal attention, which results in less staff turnover. And some proponents of this movement argue humans are still needed — especially during the final stages of consideration, when they can choose any candidate they want, for any reason. “We don’t eliminate the bias,” GapJumpers’ Iyer says, “so far as we postpone the reason.”