A few years ago, Google’s human resources department noticed a problem: A lot of women were leaving the company. Like the majority of Silicon Valley software firms, Google is staffed mostly by men, and executives have long made it a priority to increase the number of female employees. But the fact that women were leaving Google wasn’t just a gender equity problem—it was affecting the bottom line. Unlike in most sectors of the economy, the market for top-notch tech employees is stretched incredibly thin. Google fights for potential workers with Apple, Facebook, Amazon, Microsoft, and hordes of startups, so every employee’s departure triggers a costly, time-consuming recruiting process.
Then there was the happiness problem. Google monitors its employees’ well-being to a degree that can seem absurd to those who work outside Mountain View. The attrition rate among women suggested there might be something amiss in the company’s happiness machine. And if there’s any sign that joy among Googlers is on the wane, it’s the Google HR department’s mission to figure out why and how to fix it.
Google calls its HR department People Operations, though most people in the firm shorten it to POPS. The group is headed by Laszlo Bock, a trim, soft-spoken 40-year-old who came to Google six years ago. Bock says that when POPS looked into Google’s woman problem, it found it was really a new mother problem: Women who had recently given birth were leaving at twice Google’s average departure rate. At the time, Google offered an industry-standard maternity leave plan. After a woman gave birth, she got 12 weeks of paid time off. For all other new parents in its California offices, but not for its workers outside the state, the company offered seven paid weeks of leave.
So in 2007, Bock changed the plan. New mothers would now get five months off at full pay and full benefits, and they were allowed to split up that time however they wished, including taking some of that time off just before their due date. If she likes, a new mother can take a couple months off after birth, return part time for a while, and then take the balance of her time off when her baby is older. Plus, Google began offering the seven weeks of new-parent leave to all its workers around the world.
Google’s lavish maternity and paternity leave plans probably don’t surprise you. The company’s swank perks—free gourmet food, on-site laundry, Wi-Fi commuting shuttles—are legendary in the corporate world, and they’ve driven a culture of ever-increasing luxuries for tech workers. This week, for the fourth consecutive year, Google was named the best company to work for by Fortune magazine; Microsoft was No. 75, while Apple, Amazon, and Facebook didn’t even make the list.
At times Google’s largesse can sound excessive—noble but wasteful from a bottom-line perspective. In August, for example, Forbes disclosed one previously unannounced Google perk—when an employee dies, the company pays his spouse or domestic partner half of his salary for a decade. Yet it would be a mistake to conclude that Google doles out such perks just to be nice. POPS rigorously monitors a slew of data about how employees respond to benefits, and it rarely throws money away. The five-month maternity leave plan, for instance, was a winner for the company. After it went into place, Google’s attrition rate for new mothers dropped down to the average rate for the rest of the firm. “A 50 percent reduction—it was enormous!” Bock says. What’s more, happiness—as measured by Googlegeist, a lengthy annual survey of employees—rose as well. Best of all for the company, the new leave policy was cost-effective. Bock says that if you factor in the savings in recruitment costs, granting mothers five months of leave doesn’t cost Google any more money.
The change in maternity leave exemplifies how POPS has helped Google become the country’s best employer. Under Bock, Google’s HR department functions more like a rigorous science lab than the pesky hall monitor most of us picture when we think of HR. At the heart of POPS is a sophisticated employee-data tracking program, an effort to gain empirical certainty about every aspect of Google’s workers’ lives—not just the right level of pay and benefits but also such trivial-sounding details as the optimal size and shape of the cafeteria tables and the length of the lunch lines.
In the last couple years, Google has even hired social scientists to study the organization. The scientists—part of a group known as the PiLab, short for People & Innovation Lab—run dozens of experiments on employees in an effort to answer questions about the best way to manage a large firm. How often should you remind people to contribute to their 401(k)s, and what tone should you use? Do successful middle managers have certain skills in common—and can you teach those skills to unsuccessful managers? Or, for that matter, do managers even matter—can you organize a company without them? And say you want to give someone a raise—how should you do it in a way that maximizes his happiness? Should you give him a cash bonus? Stock? A raise? More time off?
Some of Google’s HR lessons won’t apply to other companies. The search company has been insanely profitable for much of its history, and many of its problems are atypical. Google has the luxury of worrying about the best way to give people more money instead of, say, the ideal manner in which to lay them off. Still, a few of POPS’ findings—like how to train a better corps of managers and how to improve interviews—will apply to most other firms. And among the tech giants—many of which are also quite profitable and face some of the same problems Google does—the search company is alone in trying to answer its HR questions scientifically. “We make thousands of people decisions every day—who we should hire, how much we should pay them, who we should promote, who we should let go of,” says Prasad Setty, who heads POPS’ “people analytics” group. “What we try to do is bring the same level of rigor to people decisions that we do to engineering decisions. Our mission is to have all people decisions be informed by data.”
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