Unpacking People Analytics With Dr. Serena Huang
On this episode of Redefining Work, I’m joined by Dr. Serena Huang, founder of Data With Serena, chief data officer at ABE.work and LinkedIn Learning instructor. We discuss all things people data — from aligning people analytics with a larger vision to using data to drive change for the better.
Serena never intended to devote her career to people analytics — it found her. She studied economics and began her career as a labor and employment litigation consultant before taking on a more data-oriented role at Deloitte. From there, Serena was surprised to get a call from the HR leadership team at General Electric, which was establishing the company’s first HR analytics program and wanted her on the project.
Although Serena had no HR training or experience, the GE team insisted that her passion for people and data expertise made her the perfect person for the role.
“They said, ‘We want someone who is passionate, interested in people and knows the numbers stuff. We will teach you the HR,” she says. And that’s where she discovered her passion for people data.
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Find Common Ground With the CHRO
For a people analytics program to succeed and deliver business value, the program leader and the CHRO need to be aligned on the purpose.
HR leaders need to see the value in data analytics for shining a light on organizational blindspots — and be willing to change based on what the stats show. “It's one thing to love data and believe in it,” Serena says, “but it's another to be open-minded enough to take action when the data challenges your beliefs.”
During the Great Resignation, for example, HR leaders needed to make changes to retain their people — and quickly. The traditional approach would be to increase compensation or give retention bonuses, but employees who left during the Great Resignation weren’t always looking for a raise. You can get a more complete picture of the factors affecting turnover from employee engagement surveys and other data sources — and people analytics is instrumental in decoding that information.
Shifting gears from traditional HR leadership to a data-enabled people function isn’t easy, but a strong alignment between the CHRO and people analytics leader eases the process.
And for CHROs who are still on the fence or can’t see the vision, Serena suggests that CHROs “treat your people analytics leader as your reverse mentor.”
Keep a Tight Focus on What the Business Needs
The power of people analytics is in surfacing concerns related to engagement, retention and performance before they become critical. But if people analytics leaders don’t know what the business’ greatest concerns are, they may find it challenging to communicate the urgency or importance of their findings.
People analytics leaders have a “responsibility to not only be able to use data well, but to be able to tell compelling stories with the data that will drive action,” Serena says.
To solve problems that matter most to the C-suite, study the business and observe its needs. Pay close attention to the leadership team’s biggest stressors.
“If you don't know what's keeping your clients up at night — and that could be an HR business partner, that could be a business, a P&L leader, that could be the CEO — if you don't know what's keeping them up at night, you will end up solving the wrong problems,” Serena says.
When she began her people analytics career, Serena took the time to learn the primary pain points of the business so she could tailor her proposed analytics solutions.
Survey Employees to Track Talent Trends
Of course, you can’t have a functional people analytics program without people data. Serena underscores the importance of uncovering trends by collecting employee feedback at every stage of the talent life cycle. Surveying new hires, for example, can reveal potential improvements in the hiring and onboarding process. By comparing trends in a new cohort’s feedback with trends in their length of tenure, you can correlate how hiring and onboarding might be influencing retention.
“That's how I know what is working and what is not working,” Serena says. “And that's a really powerful and simple analysis that you can do without any kind of Python knowledge, without any statistics.”
Once you have data, the next skill to master is asking the right questions. One of Serena’s favorite questions to ask new hires is whether their on-the-job experiences aligned with what they expected. She’s found, time and again, that people who feel lied to are generally the first to quit.
Finally, commit to responding to what the data tells you. “I would ask the tough question: ‘Why do you want to know about quality of hire in the first place?’” Serena says. “And I don't ask that to be difficult. I asked that to make you think about what you will do once you get that data.”
People in This Episode
Serena Huang: LinkedIn, X (Twitter), Data With Serena
