People analytics at Google: using data to make Google a great place to work
Google applies its data and analytical rigor to a new domain: workforce management.
Google may be the most data-rich company in the world. It owns and operates at least 15 data centers around the globe to support its products (1), and Google search alone receives 2.3M+ queries/minute (2). Data and algorithms may drive the success of Google鈥檚 products, but they also drive the success of Google鈥檚 HR function. Armed with company-supplied laptop stickers that state 鈥淚 have charts and graphs to back me up. So f*** off,鈥� Google鈥檚 people analytics team uses data to enhance the workforce component of Google鈥檚 operating model (3).
People Analytics at Google
Google鈥檚 focus on 鈥減eople analytics鈥� began when Laszlo Bock was hired as SVP of People Operations in 2006. Bock, who believed that data could unlock ways to improve the workplace (4), created a team of PhDs and ex-consultants to analyze workforce data and support the People Operations mission: 鈥渇ind them, grow them, keep them鈥� (5).
Project Oxygen may be the most well-known people analytics project. After a failed 鈥渆xperiment鈥� with eliminating managers in 2002, Google wanted to better understand the role of managers (6). The people analytics team encoded more than 10K observations from performance reviews/upward feedback and compared it to productivity metrics to prove the value of managers (7). Mixing this with double-blind interviews, they identified the 鈥�8 Behaviors for Great Managers at Google,鈥� which now govern Google鈥檚 feedback and development processes (8).
Another project was the development of an algorithm–possibly built using data on current employees (resumes, productivity, etc.)–that reviewed rejected resumes for high potential candidates. Moreover, the people analytics team uses data–possibly attrition rates, encoded exit interviews, surveys, productivity, etc.–to guide decisions about benefits, such as the decision to increase maternity leave to 18 weeks.
The Value of People Analytics
Data and algorithms are a core part of Google鈥檚 DNA, so it鈥檚 no surprise that this seeps into workforce management. It鈥檚 also not surprising because of the value it brings to a company rooted in innovation.
Talent management is critical to how Google creates value: through technological innovation. Google鈥檚 use of data to recruit and develop employees has proved its effectiveness; training programs based on Project Oxygen, for instance, achieved a statistically significant improvement in manager quality for 75% of underperforming managers (7). Strong talent management also helps Google capture value through cost savings. Attrition is costly to Google, not only because they must recruit, but also because ex-Googlers accumulate valuable organizational knowledge. Analytics help Google reduce attrition in cost-effective ways; the decision to extend maternity leave reduced new mother attrition rates by 50% and 鈥渨as much better鈥� for Google鈥檚 bottom line (9). Google also uses algorithms to predict which employees may quit, which allows for an intervention that may retain the employee (10).
Challenges and Competitors
If it鈥檚 so beneficial, why aren鈥檛 all companies doing it? The answer is that it鈥檚 challenging. It requires a large amount of hiring, performance, productivity, etc. data; an all-star analytics team; and buy-in from employees. Google was better poised to tackle these challenges than many companies. In addition to its digitized application process, Google collected workforce data on a frequent basis (e.g., 2 reviews/year) and has a workforce that is fluent in data. To bring the right talent into People Operations, Google created a People Innovation Laboratory. To give them direction while an innovation process was designed, Google focused initial efforts around themed 鈥減rojects.鈥�
Looking ahead, one major challenge is the fact that its competitors are following suit. Experts believe that Google鈥檚 people analytics team was unique as late as 2009 (7). While competitors may have relied on intuition and descriptive analytics to manage their workforces, Google was using predictive/prescriptive analytics and even running experiments. A quick search, however, revealed that Facebook, Microsoft, and Amazon may now have people analytics teams using these techniques. If the competition is following suit, will Google maintain its edge in being one of the best places to work?
Another challenge for Google鈥檚 people analytics team is ensuring the proper balance of human-machine collaboration in workforce management. Repeated success will certainly build trust in these algorithms, but blindly accepting the output of machine learning algorithms can be dangerous. Contrary to popular belief, algorithms can exhibit biases just like humans (11). Given its expertise in designing algorithms, I imagine Google will develop聽best practices to avoid this risk.
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Great post. Really thoughtful approach by Google. Glad they are doing this, since for the first many years of the company’s existence, they were fixated on top schools, high GPAs, and perfect SAT scores, which offer only limited insight into a candidates’ potential for success on the job.
Really interesting post. I didn’t realize the extent to which they were doing this, though it makes a lot of sense given the amount they have had tho hire and the number of applications they receive for job openings. Hopefully it is something that catches on at other large companies, at least in the tech sector, given that the HR function often isn’t viewed in the best light.
I echo Yun’s sentiments on the role of HR. Everyone recognizes the value of hiring the best talent. But HR’s positioning as a cost center has for long inhibited innovation in hiring practices. Hopefully, data will help establish the NPV in investing in a world-class HR team. I wonder if new companies pursuing people analytics have performed an A/B test to compare the performance and attrition among employees hired through traditional methods and those brought on through a data-driven approach.
This post has been quite a revelation. I agree with Yun and Kunal that HR has always been looked at as a cost centre. I have personally wondered what happens to the 360 degree feedback that I fill each year. Does it yield results? It is good to learn how Google is using that data to actually take decisions for employee management. Hope they are able to build a an enterprise wide platform which can be bought by other organizations.