5 Google People Analytics Lessons You Can Steal
The Google People Analytics team is famous for their data-based HR and talent practices.
Google recognized early on the value of creating a people analytics department to optimize the recruitment, development, and advancement of their people based on data insights.
They are clearly doing it right because today, Google employs more than 10,000 people, receives more than 50,000 resumes weekly, and ranks number one on Fortune’s 100 best companies to work.
To help you optimize your HR and talent practices like Google, here are 5 lessons from Google’s People Analytics that you can steal.
Google People Analytics lesson #1: Clean your data before conducting analyses
The Google People Analytics team was created in 2006. But before the team could perform any useful data analyses on their workforce, they had to improve the collection, storage, and cleanliness of the data on their job applicants, interview scores, headcount, attrition, and other HR data.
This cleaning of the data is estimated to take up to 80% of the time spent conducting data analyses.
The takeaway here is that your data doesn’t have to be perfect, but it does need to be organized and accessible enough to be useable for your people analytics purposes.
Google People Analytics lesson #2: Test your assumptions in your hiring process
The Google People Analytics team first gained fame when they admitted their entire interview process was full with mistakes.
They used to conduct several interviews with each job candidate but decided to test whether all those interviews were even useful. Their data showed that after four interviews, each subsequent interview added no additional benefit.
The Google People Analytics team crunched their interview data and found that their infamous brainteasers didn’t predict performance once the candidate was hired, which made it an easy decision to get rid of them.
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The point here is not to blindly follow Google’s people analytics for recruitment practices but to test whether you’re truly picking the best candidates by testing the assumptions in your hiring process. Test your assumptions by collecting and analyzing the data.
Google People Analytics lesson #3: Understand how unconscious bias can prevent workplace diversity
Google was among several big tech companies that released their diversity stats recently. The evidence-based practitioners and researchers of the Google People Analytics team quickly recognized unconscious bias was a barrier for increasing workplace diversity.
They created a workshop Unconscious Bias @ Work to educate themselves and others on the negative effects of unconscious biases in the recruitment process such as the halo effect and in-group bias.
The takeaway here is recognizing that bias is often unconscious and accidental and the first step is becoming aware of them and then holding yourself and your colleagues accountable. Google also recommends creating structure in your HR-related decisions because applying the same criteria and evaluation methods for everyone reduces bias.
Google People Analytics lesson #4: Recognize the importance of the human in HR
One of the first projects the Google People Analytics team worked on was an algorithm that identified which software engineers should get promoted.
The promotion algorithm was reliable, stable, and tested to be 90% accurate for about a third of Google’s promotion decisions.
So what happened? The algorithm was never used to make promotion decisions at Google because the engineers hated it.
The point here is Google recognized people want to make decisions about people. That means your people analytics function should provide human decision makers with better information, not replace them.
Google People Analytics lesson #5: Invest the time and resources required to achieve long-term results
Google recognized that people analytics results take time. Laszlo Bock, the former SVP of People Operations, commissioned the People Analytics team to conduct research that could serve as the foundation for future HR decisions and practices.
While some people analytics experiments can lead to quick wins, the takeaway is to be realistic about the timeline needed to achieve desired outcomes such as lower attrition or increased revenue.
The results of optimizing your HR function through people analytics can take several months to a few years to achieve. That means you need to trust your data and believe that the methods you’re using are right.
In today’s knowledge economy, the Google People Analytics team are ahead of the game by recognizing the value of their employees. They achieve this by collecting the right data and using evidence-based methods to optimize their HR practices.
Their people analytics lessons include:
- Cleaning your data before conducting analyses
- Testing the assumptions in your hiring process
- Understanding how unconscious bias can prevent workplace diversity
- Recognizing the importance of the human in HR
- Investing the time and resources required to achieve long-term results
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