How investing in “people analytics” has dramatically changed Google’s hiring process — and saved the company time and money in the process.
Back in February, OpenView’s Talent Team attended a Talent Strategy Summit session with Tina Burke, People Analytics Manager at Google. Tina took us through several examples of how Google is using “people analytics” to improve the company’s processes and decision-making, specifically when it comes to using data to better hire, manage, and maintain top talent.
One project in particular she discussed was the Rule of Four (Or Five).
If you search “interviewing at Google,” you may actually come across some horror stories in your results. Of course, positions at the company are notoriously competitive, and in some cases it’s been reported that the interviewing process could historically require as many as 10+ interviews spanning over four or more months. Aware of their hiring reputation in the market and that their lengthy interview process was draining everyone involved (interviewees and interviewers alike), Google took action. The company’s people analytics team set out to improve efficiency in the hiring process, while still ensuring that the business hired the best candidates for each position. That is where data came into play. To test efficiency, Google used data to determine who the best interviewers were by grading people against the success of their hiring recommendations. For Google, that meant asking an important question: “Which interviewers are the best predictive indicators of whether we will (or won’t) hire a candidate?” In addition, Google also dug into the effectiveness of the company’s atypically high interview count. Burke and her team found that after four interviews, the company could say with 86 percent certainty that it would (or would not) hire a candidate. With every additional interview thereafter, that percentage increased by only one percentage point. Armed with this new information, Google capped its interview process at four interviews for non-technical roles and five interviews for technical roles. If hiring managers wanted to conduct any additional interviews beyond that, they needed to seek director-level approval. Ultimately, this finding has dramatically changed the company’s interview process. By using predictive data to determine hiring outcomes, the people analytics team has not only shortened the company’s hiring process (making both interviewees and interviewers happier), it’s also saved the business considerable time, money, and resources. Of course, Google is just one example of a tech business using big data to approach recruiting and HR objectively. How is your company using “people analytics” to improve its recruiting function?
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