Hacking Tech's Diversity Problem

When Google, Yahoo, LinkedIn, and Facebook disclosed their woefully low levels of female employment in the summer of 2014, admitting that they had a lot of work to do to improve them, they signaled a shift for the technology industry. It’s remarkable that the sector is finally stepping up to the plate on diversity—and refreshing that its focus is on metrics rather than rhetoric.

Make no mistake: Improving those metrics will be challenging. A key feature of the tech culture—the shared belief that it’s a meritocracy—may work against change. An important study by Emilio J. Castilla and Stephen Benard has shown that when an organization’s core values state that raises and promotions are “based entirely on the performance of the employee”—in other words, when a company sees itself as a meritocracy—women are actually more likely to get smaller bonuses than men with equivalent performance reviews. Subtle biases against women are clearly at work here. Moreover, 40 years of social science have taught us that such biases will be perpetuated unless they’re intentionallyinterrupted, and people who think they work for meritocracies are less likely to do what it takes to interrupt them.

On the other hand, if tech’s senior leaders are serious about gender diversity, they could be perfectly positioned to lead change. As they so often remind us, they’re not about business as usual. They’re out to change the world, with corporate mottoes like “Don’t be evil” and “Move fast and break things.” One thing I hope they’ll break with is the “diversity industrial complex”: the standard approach of making token hires, offering sensitivity training, setting up mentoring networks, and introducing other incremental changes that focus on altering women’s behavior to, say, make them better negotiators. When an organization lacks diversity, it’s not the employees who need fixing. It’s the business systems.

This article is intended to help tech companies—and others—fix those systems. It describes a new metrics-based approach that pulls from the lean start-up playbook: Collect detailed data about whether gender bias plays a role in daily workplace interactions; identify company-specific ways to measure its effect; create hypotheses about what “interrupters” might move those metrics; and then throw some spaghetti at the wall and see what sticks. Measure what happened, adjust your hypotheses, and do it all over again until you get it right.

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