The field of people analytics is growing exponentially. It has become a bit of a buzzword as organizations are looking for ways to use data to improve decision-making around performance, talent management, and the employee experience. As such, companies are clamoring to hire people analytics pros, or are asking HR teams to upskill their capabilities for data capture and analysis. In fact, myhrfuture.com found that 61% of companies have increased their people analytics team in the last year. But is people analytics all it’s cracked up to be? Yes, according to research we did in conjunction with Josh Bersin: companies that leverage people analytics are 5.6 times more likely to achieve their employee experience and business outcome goals.
If your organization isn’t leveraging the full potential of your employee data, you could be missing out. To help, we got advice from the experts. In a recent webinar, our own in-house people analytics leader, Dr. Brett Wells, sat down with Rob King, Head of People Analytics with Takeda, and Sean Robinson, Director of Global Integrated Talent Management with Goodyear to get their take on the best way to build a successful people analytics practice and what organizations need to know as they continue their employee data journey.
People Analytics: Where to Start?
In recent research, we found that 73% of business leaders say people analytics will be a major priority for their organization, yet only 8% consider themselves strong in it today. And many organizations simply don’t know where to begin when it comes to people analytics or how to fully realize the data they are collecting. We asked Sean and Rob about the key questions companies need to answer before diving into people analytics, and they had similar responses. It starts with buy-in at the top of the organization. The executive and senior leadership have to understand what the organization wants to measure, what questions they want answered, and the role that people analytics plays in providing those answers.
“There needs to be a commitment at the top, and not just at the top, but with your peers within HR as well and that readiness to act,” said King. “Once you're in that role and the function exists, you hope there is that level of buy-in. Going beyond that, once you have the role and the commitment to understand how to make it successful, it's important that you understand the decision-making processes of your organization. Because, at the end of the day, people analytics is a decision support function.”
When it comes to ensuring executives understand the importance of people analytics, Sean goes to his favorite analogy.
“One analogy that I use for the organizations I've worked for is the CFO analogy,” Sean explains. “The CFO, they have a nice clean P&L sheet about financial assets that helps them drive decisions and evaluate progress and success. People analytics, in my world, the talent management function, we're really the chief HR Officer's P&L for our most important asset – the people. When you think of it in terms like that, it takes us from being a soft HR initiative to really understanding your (people) assets in your company, and how you use them to drive your growth.”
Selecting Your People Analytics Team
Once you have leadership buy-in, the next logical step is to build your team. From data scientists, to business analysts, HR practitioners, I/O psychologists, engineers, and program managers, the people analytics function has a varied cast of characters. It can be hard to know where to start in making your first hire, and what skills and competencies are required to create a successful team.
“I'm a huge proponent of bringing in people from outside HR with different skills, different viewpoints and so forth, (but) your first hire, I feel pretty strongly they have to have an HR background,” Rob says. “They have to understand HR. Because, again, we're trying to support HR leaders in making decisions and HR is kind of a complex beast. I think it's really important that I index more on the HR side of things than I do on the technical side of things, because willing people can learn the technical side, but the HR side just takes experience.”
Sean agreed with Rob, but also pointed out that it really depends on where an organization is in terms of data maturity. While agreeing that business acumen and HR experience is key, he also noted that a large people analytics team is not possible for a lot of organizations. For smaller teams, like his own at Goodyear, they “embed people analytics into our ways of working and operating,” and its a collection of teams that are doing the HR work, so while HR knowledge is valuable, he also looks for people who are comfortable with data.
Sean explained, “it’s going back to the ‘crawl before you walk.’ Early on it's really important to make strong business connections about why people analytics matters. … If you're further on your journey, I think some of those roles that Brett was talking about (analysts, consultants, machine learning scientists, data engineers, etc.) …. could be your workhorses. …but if you're just getting started, start small and get momentum. … I’ve found people with IO backgrounds are natural fits because they understand data. They have that stats background, that foundational background of measurement. But really, ultimately, I think even more important than that is just building relationships and being able to use information to influence your leaders. That will get your journey started.”
The Intersection of Continuous Listening and Analytics
The crux of people analytics is really the data. To ensure your organization has enough people data to inform decisions, it is as important to implement a continuous listening strategy as it is to have the right people on the team. Both Rob and Sean have seen successes by utilizing data from their companies’ employee listening programs to influence programs and improve the employee experience. The pandemic really brought the importance of quickly listening to people and acting on their responses to light.
“So for us, it was using data to identify just how much people were struggling from a well-being, mental health perspective. Just using basic surveys and understanding that it was a real problem and that people were impacted heavily,” Rob stated. … “We were able to use a lot of our listening data to understand that and create programs with HR to actually help employees. And so we were able to see this trend over the last year that people are still struggling, but we've been able to really improve dramatically on all of our well-being questions.”
For Sean and Goodyear, their listening program and access to people data is helping them develop a return-to-office/hybrid work approach.
“As many organizations are now kind of figuring out the hybrid work environment and what that looks like moving forward, those survey insights have been really impactful for helping us navigate through all that. Now, I'll, I'll be the first to say we don't have it all figured out right? But I can't imagine where we'd be if we didn't have that continuous listening.”
In addition to continuous listening of your employees, Rob also points out the importance of incorporating outside data into your people analytics.
“I think there's becoming an increasing focus on using external data and combining it with internal data. So knowing what's going on in the talent marketplace, with tools like LinkedIn talent insights, like TalentNeuron, MZ, Burning Glass, figuring out how to take the external competitive pressures and understanding it in the context of your own organization,” Rob describes. “I see that as becoming more and more of a focus within people analytics teams. I know for instance Paul Batten from Liberty Mutual came and spoke at one of one of our people analytics events about what they were doing and it can be really, really powerful.”
Don’t Give In to the Hype
With the help of technology and an increasing mandate for HR to catch-up with other data-centric disciplines within the business, People analytics, and the insights it can deliver, is becoming increasingly sophisticated – some might even say “sexy.” While things like artificial intelligence and machine learning bring tremendous promise, Sean and Rob warn against trying to do too much too fast.
“Artificial intelligence is changing the universe all around us,” Sean points out. “It helps us solve problems … and from a people analytic standpoint, too, we can now make connections between an unlimited amount of data points to help us understand relationships. But, on the other side of the coin, if that's not properly managed, artificial intelligence can really be counterproductive … Being able to understand the why is essential. And I have seen some vendors, some solutions…who have these products and they totally disregard the why. And then the business starts using these solutions to make decisions (about) selection, promotion, terminations, without knowing the why or not being able to explain that ‘black box,’ and it sets them up for some serious risks.”
Simply put, according to Rob, “managing people is a job for people. Machines and algorithms should not be making employment decisions for people; there should always be a human on the other end of that decision.”