How Scalable Is Your Hiring Process? Lessons From Uber

In a recent Wall Street Journal article, the co-founder and CEO of Uber, Travis Kalanick, reveals the company expects to grow from 550 employees to “the 1,500-to-2,000 range” by the end of 2014.

That level of human capital expansion – hiring 450 to 1,450 employees – is a formidable challenge for any company, let alone a startup that’s been around for less than four years. So what strategies are Uber using to scale their hiring process?

scalability-largeAccording to an interview Kalanick gave to, Uber’s hiring process involves “job-specific tests of an applicant’s ability to think-on-the-fly and perform the specific job they’re seeking.”

Specifically, candidates for operations positions (i.e., logistics and number crunching) take an analytics test while those for community positions (i.e., customer support and social media presence) are given a creativity test. General managers, who oversee both operations and community, take both types of tests.

Uber is in the enviable position of explosive growth, but anyone who’s hired even one employee knows that it requires sizeable investments in time and effort to do it properly. In fact, Deloitte’s 2013 Human Capital Trends research reveals that the third most pressing HR concern is aligning HR to business critical priorities, which requires “investing in a scalable and flexible platform” that “delivers scalable, targeted, solutions.”

Many strategies that increase your chances of hiring the best talent, such as structured interviews, involve additional time and effort. Fortunately, not all of them do: Uber is smart to include a scalable strategy such as pre-hire employment assessments, which can be administered to an unlimited number of job candidates simultaneously and scored automatically to rate or rank them.

With their recent expansion in Asia and their foray into courier services, Uber’s scalable hiring strategy appears to be a huge success.

Be proactive and make sure your hiring strategy involves processes that not only accurately identify the best candidates, but that are easily scalable. When (or whether) you’re enjoying explosive growth of your own, you’ll be thanking yourself you did.

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Ji-A Min

Ji-A Min

Head Data Scientist at Ideal
Ji-A Min is the Head Data Scientist at Ideal. With a Master’s in Industrial-Organizational Psychology, Ji-A promotes best practices in data-based recruitment. She writes about research and trends in talent acquisition, recruitment tech, and people analytics.
Ji-A Min