Human resources has officially moved into the C-suite. Where HR was in the past called upon for arithmetical facts about the workforce and its makeup, the department’s new position of influence now puts it on the hook to answer qualitative questions about the state of the workforce and the future of the business. But without quantitative backing, those answers are, at best, guesswork made in good faith.

People analytics is proving a popular instrument. SHRM found in 2021 that HR teams using people analytics report achieving their DEI and retention goals and being more competitive for talent than HR teams that don’t.

But people analytics platform Visier estimates that people operations teams still spend about 70% of their time on foundational analytics, that is, figures like headcount, turnover, and diverse representation. But as HR is increasingly called upon to be a strategic contributor to the business, the team needs to satisfy complicated concerns, like, Are we underpaying in our industry? Who’s most at risk for leaving the company? And how can we keep them?

From Day One spoke with Visier’s VP of product management, Ian Cook, about HR’s move from counting workers to needing a PhD on the team just to answer business questions.

Cook develops ways for HR teams to avoid staffing someone like him to answer their people operations questions. He equips them to do it themselves, no advanced mathematics and no PhD required. At the same time while people analytics capabilities are growing more sophisticated, the tech that powers it is becoming more accessible, and many who are tasked with analysis have little to no quantitative expertise–and that’s not a bad thing.

Q: I now hear the term ‘people analytics’ more often than I do ‘human capital management.’ What’s the difference?

A: Traditionally, HR’s focus has been on process control: Who works for us? When did they start? How much are they paid? When did they move roles? Human capital management systems are the record-keeping systems for that data. That information used to be kept in file cabinets, but within the last 30 years, it’s all been digitized, and that means they’re a valuable source of useful information.

People analytics answers questions about your business: Who’s the right person for this job? If we move this department under another leader, is it still going to function? Are we paying too much for this particular set of capabilities? Your human capital management system has the record-level detail, but it has no way of taking that information, running a calculation or an analysis, and giving you the right answer. People analytics brings evidence to HR decisions.

Q: So, you answer these kinds of questions?

A: We are not a consulting business that does the work for our clients. They do the work, using our technology to find the answer for themselves, because they can.

This is a pivot from how HR typically operates, which is going to an outside expert, having them decide what’s wrong and then how to fix it. We put that capability inside the business so they can apply it themselves. Evidence doesn’t become a project from a consulting firm, it becomes the way the business operates.

Q: What do people get wrong about people analytics and how it fits into HR strategy?

A: People tend to think that you do your work, then you do the analysis later to find out whether it worked. But that’s the wrong way around. I would rather do analysis up front so we can substantiate the decisions we make. Let’s not look at it as a retroactive justification, let’s be proactive. The people analytics team is the strategy arm of the CHRO.

Others tend to think of people analytics as this weird science project. As in, we do HR, and then we do people analytics on the side. I fundamentally disagree with that. People analytics is how we should be doing HR.

Q: I hear from HR leaders that they’re getting a directive from the C-suite: Start using AI. But without further direction, some don’t know where to start and whether they can meet expectations for what artificial intelligence can do.

A: HR individuals are right to be skeptical about AI, because depending on how the models are built and what you’re doing with the models, you can’t just throw your people data into a model and say, Tell me who to hire and tell me who to fire. An HR professional being tasked by business leaders to use AI must educate themselves on what is real and possible versus what is not.

Q: Can you tell me more about Visier’s generative AI tool, Vee? 

A: It makes the analytics process really human. Most people think in questions, like, I wonder if we’re losing people in this area. Is that normal? With the generative AI capability, you can put your question into the bot, and the bot will interpret it and return you an answer.

The traditional way these problems were solved was with handmade answers. You would build somewhere to store the data, and you would build some SQL code to run calculations on top of that, then you would put that into a different piece of technology to create charts. Someone would then assemble and distribute that. 

With Vee, it sits over a customer’s data that their people analytics team would access via our platform, and opens up the opportunity for any employee to simply ask questions, in natural language, without needing a data analyst to decipher the answer, with their precise security applied.
Generative AI reduces the barrier to entry for everybody to become analytically informed. At the same time, no customer data is ever sent to a large language model which removes the fear we talked about earlier.

Q: How is it different from other AI-powered HR tools available at the moment?

A: We’re faster, cleaner, more integrated, and have a higher level of security. The teams running Visier are half the size of the traditional teams.

We don’t recommend you shrink the team because, invariably, the demand on the team is always greater than it can solve, but with the same number of people, you can serve four to eight times the number of inputs and requests. Generative AI is designed to accelerate that even further.

For instance, where a large financial institution may have 100 full-time employees running their people analytics team, one of our clients maintains just three dedicated FTEs to make the Visier component run. We’ve taken what has been a specialist, an expert, and made it into a process. We’ve created a high degree of automation, and we’ve layered in specific HR expertise, so that you don’t need to hire a whole bunch of data scientists to deliver the answers that your business needs.

Q: If you can use it to answer questions about a given business, can you also use it to benchmark a business against its competitors? 

A: Sometimes ‘good’ is not an absolute inside an organization; it can be relative performance.

All of our customers live in exactly the same data shape, which isn’t true for every other competitor, so we can publish benchmarks on resignations, promotions, diversity percentage of managers, and we’ve got some design benchmarks coming out around span of control, etc. All of that can be compared against the Visier customer population and broken down by size of organization, geography, and more. For instance, with that, we were able to demonstrate that Visier customers’ resignation rates were going up slower than the market. It’s available inside the application to any customer.

Q: Could it be used to prevent over-reaction to employee attrition or engagement?

A: Yes. Lots of executives run down the corridors, worried that everyone’s leaving, going to a competitor for tons of money. But an analyst hears that and says, that’s an interesting perception, let’s have a look. Sometimes you might find that you have a problem with attrition, but you might also find that one person left this week for a competitor, and that’s just one out of a hundred. Let’s keep our money and not overplay a reaction based on a specific individual’s perception.

Q: Do you think analytics will be a permanent component of the HR function?

A: Analytics is kind of a scary word, and it’s often presented in a way to make things seem difficult and important. I would rather talk about an evidence-based HR practice.

If you can have the evidence that this program is going to manage to retain people better, why wouldn’t you use the evidence? We’re really passionate about pulling this whole practice away from having to be math experts just to understanding your people and your business.

Editor’s note: From Day One thanks our partner, Visier, for sponsoring this sponsor spotlight. To learn more, tune into their webinar on July 30. 

Emily McCrary-Ruiz-Esparza is a freelance journalist and From Day One contributing editor who writes about work, the job market, and women’s experiences in the workplace. Her work has appeared in the Economist, the BBC, The Washington Post, Quartz, Fast Company, and Digiday’s Worklife.