What Is People Analytics? (with Workday)

Michael Krigsman: Data and talent are foundational to business today. We're speaking with Caroline O'Reilly, General Manager of People Analytics at Workday. 

Caroline O'Reilly: People analytics is all around discovering meaningful patterns in your people data. And you do that to be able to improve the employee experience and to really accelerate the decision-making in the business.

The challenge of managing people analytics data

When I talk to business leaders, the first thing they tell me is, "There's just a sea of data out there. The data is fragmented, and it's siloed throughout the organization. It's just getting bigger all the time." I heard somebody recently say they were drowning in data in the organization. 

It's very, very hard to know where to get the right insights from. And there's really a bit of FOMO as well, right? The fear of missing out on insights that you may not have discovered. It's why a lot of business leaders are looking to use AI and ML to automatically surface those insights that you may have missed in your own people data.

Another challenge that, when we talk to business leaders, they really want to solve is to get more and more people comfortable with data, that data democratization, and making data more accessible for people.

Understanding the value of people analytics

Michael Krigsman: Caroline, you've described some of the customer challenges when it comes to people analytics. What are the components of the people analytics, of these kinds of products?

Caroline O'Reilly: Enabling our business leaders to accelerate their decision-making, really advising leaders on how to make better decisions. Usually, the way that works, we come up with some hypothesis that we want to prove or investigate, pulling that data together. As we try and solve more complex questions in each business, it's about bringing in third-party data, splicing that, and mixing that with your people data to be able to answer questions that the business has about their people and about the business. 

The real trends that we see are getting that data in the hands of the decision-makers much, much faster than it has been before, getting it in real-time, and getting that data to the people who can take action on it as well. 

Key strategic questions answered by people analytics

Michael Krigsman: It sounds like people in business today have a greater recognition of the importance of data than they did in the past.

Caroline O'Reilly: We've moved much more from reporting to thinking about having agile tools that can move with the business. I think we really saw this in COVID where we had to move really quickly to answer business questions much, much faster than we ever did before. 

Michael Krigsman: What are the strategic questions that people analytics ultimately helps address?

Caroline O'Reilly: I suppose there are common questions that businesses are asking like: "How are people using our offices?" and "How are people feeling if they're working completely remotely?" or they're working in a hybrid mode. "What skills do we have in the organization?" "What skills gaps do we have?"

There are a core set of questions that all our customers are asking. But then there are also those unique questions that, for instance, if a customer is doing an M&A or something, that's a unique thing that's happening in their business, and they should have agile tools that can enable them to answer those data questions.

The types of data used in people analytics

Michael Krigsman: Let's drill into the data. Much of this is completely interwoven and dependent on the data. What kinds of data feed into people analytics?

Caroline O'Reilly: It can be any data that's related to your people, so it could be listening data. It could be skills data. It's data about performance. It's data about org levels and org design. 

We've heard that it can take up to 30 days to create, for instance, a deck for the CHRO. Analysts get into a cadence of creating that same deck every month, perhaps. And when we talk to business leaders, they want to get that done in an automated way. 

That's where they use tools like people analytics to be able to surface that. And so, this is where they can see data around org composition, around diversity and inclusion. 

You might want to ask a question, "What does your female leadership look like in the organization?" Or you may want to look at female representation as you're doing promotions. Or you may want to look at retention and attrition. These are core pieces of people analytics that are almost standard in many different organizations. 

One aspect is very core sets of data that are shared through the different companies that we talk to. But then on the other aspect, there are people questions that businesses want to ask that are very unique to their business where they want to take in listening data, where they want to take in external data sets like benchmarks. That's where they need to blend that data together and get those really rich data sets that could answer their unique challenges and their unique business questions that they have.

How people analytics improves employee experience

Michael Krigsman: Caroline, you mentioned employee experience several times. Where does people analytics fit into creating a better employee experience?

Caroline O'Reilly: During COVID when we all moved to remote work, there was someone who had just started that week sitting beside me in the office. I remember turning to him and saying, "Are you going to be okay?" He had just started this week in the office.

You really have to have an employee listening tool, so we sent out a survey every week to our employees. It's very powerful to hear from employees in their own language what they're feeling and what they're concerned about. 

You can pull all that data together, so I can see a heatmap of where I need to focus. That's really powerful, and that really improves the employee experience.

Michael Krigsman: How does people analytics help you connect with these folks that are working remotely?

Caroline O'Reilly: It helps us connect by answering business questions that we have. For instance, when we came back to the workplace, we wanted to know, did the people who were working remotely feel more connected than the people who were in the office? By using people analytics, we were able to determine that. 

We were trying to navigate how often should we come into the office. We looked at how people focus. We took in Zoom data to see how much meetings people were doing when they were in the office versus how many meetings they were doing when they were at home.

What we discovered was that people needed focus time. They didn't get focus time when there were multiple Zooms, so people needed a hybrid approach of time to focus to actually finish things, and so it was using our own data that we decided we would do a 50/50 in the office, 50/50 working in a flex way. By using our own data, we came up with that recommendation. 

The growing importance of skills data

Michael Krigsman: Caroline, we hear a lot about skills. What do we mean by that?

Caroline O'Reilly: People and skills are like this now, right? Companies are really using skills to totally supercharge their organization. 

We're moving to skills-based hiring, and you've probably heard the phrase "quiet quitting" last year. We've moved to this "quiet hiring," which is talking about hiring in a different way than we did before. 

Previously, our hiring was very rigid and that we put out our job req. We put out our advertisements. But moving to skill-based hiring is really looking for people with the skills, and maybe they don't have the university degree, or maybe they don't have certain X years' experience, but do they have the skills?

When we talk to companies, I feel the ones who are moving to skills-based hiring and skills-based talent are really supercharging their organization. It's really helping them to internally recruit. It's really helping them to look at their mentoring.

It's helping them to reskill their workforce because, with the ton of shortage that there is, we can't go out and hire all of these people. By being more granular about what skills you need, you can really get the best talent from maybe somewhere that you didn't expect. 

Another thing I love about skills-based hiring is that it really is starting to take the bias out of hiring. You're looking for the skills, and then that's open to everybody. It's really the future of hiring as we see it. 

Michael Krigsman: Caroline, some people say that skills are the next evolution of people analytics. Can you tell us about that?

Caroline O'Reilly: The way we hire people, the way we think about retraining people, the way we think about mentoring people, we're looking at that from a skills perspective. 

A company who has done this really well, actually, is Accenture. They've really supercharged how they use skills in the organization and they know what skills they have and they don't do that from an employee saying, "I have X, Y, Z skills." They apply that based on what the employee has done and what projects they have done.

They use this then to do much faster replanning of the skills that they need and who they need to reskill as well. So, I think Accenture are a great example of how to supercharge your organization with skills.

Examples of people analytics in practice

Michael Krigsman: Caroline, let's talk about customer use cases. Can you give us some practical examples of how organizations (maybe in different industries) are using people analytics?

Caroline O'Reilly: People analytics is key for me because I'm a product leader and engineer leader. But I'm also a people leader, and so I always want the data about how I am as a people leader and also how our product is, right? 

I need data from both perspectives, so we're very passionate about people analytics in Workday. Our people analytics team comes up with hypotheses that we want to answer by looking at our people data in Workday.

One of the questions that people leaders often ask is, "Why do people stay in a team?" or "Why do they stay in a company?" 

We've all heard the hypotheses around that: "Oh, people stay because of their manager," or "People stay because of their compensation," or "People stay because they feel challenged at work." 

We wanted to actually go into the data and really figure it out. And they discovered that the core reason for people to stay at Workday was the ones who had a really challenging and really valuable career conversation with their manager. 

That was something that surprised us because we've always thought that it was maybe the manager or maybe the work that they were doing. But it was around having great career conversations. That discovery was so important from our people analytics team that we have injected in career conversations during the year that all of us have with our managers because we saw, in the data, that it was so important to have that. 

Another company is LeasePlan. LeasePlan are a Dutch financial services provider for fleet management. They are a global organization. They're in 32 different countries. 

They have completely transformed their HR operations. They really wanted all their HR operations across those different entities to come together to be on the same baseline and to give them the real insights that they needed to make their decisions.

They wanted to ask questions like, "How do our employees feel when they onboard?" and "Do they feel different in one country over the other?" "Why do people leave?" "How are we recruiting in different countries, and how is that different?" 

They really wanted to get those insights into the hands of the people leaders and HR business partners so they could be armed with the data that they needed. 

Michael Krigsman: If you look across these particular use cases or other ones – I know you speak with so many Workday customers – are there a common set of success factors or attributes that drive a successful people analytics implementation or deployment?

Caroline O'Reilly: It's the companies who want to get the data into the hands of decision-makers now. 

We've had companies who have moved from a model where they had been extracting data from different entities and pulling it together, and they immediately felt, "This data is old already. We want to transform our business to be able to get that data into the hands of decision-makers now." 

We're moving away from just a core set of people understanding the data. We want to have that data democratization where more and more people in the organization can interpret these results, and that's why we spend a lot of effort into writing the story around the data and writing a narrative around the data, so the HR VP or the business leader can understand what that data is telling them and what that insight is telling them. 

Then they can drill down and do another level of analysis for themselves. That frees up then the analyst team to work on other strategic questions that the business needs to ask, and it gets the data into the hands of more people, and it empowers them. 

That's where I see the companies making the biggest impact; more and more people having access to the data and having access to it now. 

Michael Krigsman: It sounds like you're talking about creating a data-centric mindset or culture where data is infused or used throughout the organization to help support the business strategy and help folks make key, important decisions.

Caroline O'Reilly: You don't get there overnight. Companies who are starting out on that journey, what they'll usually do is start off with a small team or a tiger team who are interested in analytics, and they will start implementing areas that they're interested in.

Imagine they have a hypothesis around diversity and inclusion, and they may implement a product like people analytics which shows them some key insights and trends around diversity and inclusion. They will come together. Maybe that month they will focus on that data set.

They will enable those leaders to do the next drill-down. Then, over time, those leaders become really proficient in interpreting that data themselves. Then they widen it out to more of the business. 

By pulling together these different data sets and by blending different people data together, you can really uncover and discover fascinating insights into your organization and your business.

About analytics at Workday and the democratization of data

Michael Krigsman: I can tell you the most innovative companies that I speak with talk about it just this way, creating that data mindset, the democratization of data. You are general manager of analytics at Workday. Tell us about these tools.

Caroline O'Reilly: We have a number of tools around analytics.

The first one is people analytics, and I always describe people analytics as an analyst in the box. It's a prebuilt application that is surfacing trends around your people data, so it is running in the background surfacing people trends for you. 

It's also surfacing anomalies that you may not have seen, and it uses ML and AI to do that in the background. It's telling you where you may need to focus on diversity and inclusion, on org composition, on hiring, or on talent, or on skills. 

The wonderful thing about people analytics is that it gives you a story around the trend. First of all, you see the trend. You see the story. Then it's tightly woven into Workday so you can see the data behind that story, so you can drill in, right into the Workday data, and slice that how you want to be able to see where that story came from.

That's the important thing about data. We always want to be able to explain where that data came from and where that insight came from.

The other product that we have is called Prism Analytics. You asked me about people analytics and the different data that that involves. That could be any data that you want to blend which are people data now.

The way that customers want to ask questions about their people data is just vast and growing and unique. And so, Prism Analytics allows you to pull in third-party data that you can blend with your people data to ask those unique business questions that you may have. 

The reason it's so important is that the people data is so sensitive. We are hyper-focused on security of that data at Workday. That's our number one priority. 

Our customers really make that strategic decision to keep that people data in Workday, but they want to blend it with third-party data. Using Prism Analytics, you can blend that third-party data and bring that third-party data in with your people data. 

Another product that we have is Peakon Employee Voice. That's a way of surveying your employees. Peakon tells you where to focus either on a geo level or on a managerial level or where you need to focus on aspects of your people data.

We also have our core reporting functionality that's in the box in Workday which enables you to create your own reports and ad hoc reports. You can build your dashboards as well. 

AI and machine learning for Workday People Analytics

Michael Krigsman: Caroline, you mentioned AI and machine learning. Can you tell us where these approaches fit into analytics at Workday?

Caroline O'Reilly: Data is just getting to be so vast, and there are so many different data points. It is going to become increasingly hard to go through that data in a manual way and surface insights. More and more, our business leaders are going to want to use ML and AI to be able to surface those insights because there are just so many different data points now. 

We've been using ML and AI for almost a decade now. One of the places we use it is in Skills Cloud, which is a taxonomy of your skills data. 

Now, it's not a static taxonomy of your skills. It's using ML and AI to grow over time and to learn and to evolve. 

We also are using ML and AI in our people analytics in what we call our Storyteller Engine. When we talked about the people data and the points that you need to be able to discovery those insights, it's vast. And so, we run ML and AI over your Workday people data to surface those trends to you – trends about diversity, trends around your skills data, trends around recruiting or your org composition – and we're showing you how you compare to your wider organization as well.

I see ML and AI as really going to help us with that automation of tasks. We often hear people tell us, "It takes me 30 days to go through my people data and to create a package for the OCHRO about the people trends." 

They want to move to tools like people analytics which will do this for them in an automated way that they can export to presentation for the CHRO. But also, more importantly, it surfaces those anomalies you may have missed if you were doing it in the same way every month.

Ensuring data security and privacy for Workday customers

Michael Krigsman: Caroline, you mentioned security and privacy earlier. How can organizations protect this very important employee confidential data but, at the same time, take advantage of the capabilities that are available with people analytics tools?

Caroline O'Reilly: That's such an important part of people analytics, Michael, and it's one that we take really seriously is around security of this data that we are hosting on behalf of our customers.

We are very careful about that. That's PII data, obviously, and that is why we have infused our people analytics product into the core of Workday because we don't want to have our customers have to extract that data, bring it into a pipeline, and manipulate it. 

With people analytics, it's actually infused into the core of Workday, so you can protect that with your Workday security model, the one that you're used to using already, so that you're protecting your PII data, as you always have done with the Workday security model. That means you're only surfacing that data in reports to people who should see that. That's a really core, fundamental part of what we do in Workday and what we do in our people analytics product as well.

Michael Krigsman: You're simplifying that data pipeline and, obviously, simplicity when it comes to anything to do with security and privacy is really important.

Caroline O'Reilly: That's exactly it, Michael. For our people analytics product, that's out of the box so you don't even have to see the pipeline. We do that for you. It's all contained in Workday, and you can apply your Workday security model on top of that.

Otherwise, you might have to extract that. You would have to audit that. And what we hear from customers (if they do have people data elsewhere), they have to manage that security. They have to replicate it.

We simplify all that for our customers. We keep it in the core. You secure it in the same way that you normally do for your Workday data. And it's all protected in Workday.

How to build a data-centric culture and drive organizational adoption of people analytics

Michael Krigsman: Caroline, we spoke earlier about building a data-centric culture. How important is that to organizations that want to take full advantage of the data that's available?

Caroline O'Reilly: It's super important. The people analytics team inside of Workday, they're run by Phil Willburn, who is a great friend of mine and really great leader. They take a very product-oriented view when they are creating dashboards for me, for instance.

They spend a lot of time investing in what is the product, what is the dashboard we're delivering for all the people leaders in Workday. They go out, and they do interviews with us. They are really trying to get to the core of what is the data that Caroline needs to run her organization? How does she need it? How does she need to splice and dice it?

They assign actually a product owner to each of these dashboards because what they do not want to do is spend so much time and then for it not to be adopted. That team really invests in the upfront requirements gathering of what that dashboard is that they're going to create so that when we all get it into our hands, we are going to adopt it and use it. I think that's a really good model to use as you start your people analytics journey. There's a lot of upfront designing that goes into it to make sure it's going to be adopted.

Michael Krigsman: It sounds like adoption ultimately relies on having empathy for the end user, what they need to accomplish, how will that data be useful.

Caroline O'Reilly: That's completely right. The easiest thing would be to quickly build a dashboard and just assume it's what the user needs. But the more you can invest, the more you can spend time with the users who are going to consume that, the better the product. That's why our internal analytics team really invests heavily in doing the upfront work in the design and listening to how people are going to use it.

What they usually do is that they'll build a first version after spending a lot of time talking to us. Then they'll change it. They modify it, and they make it better because it's always hard to get it right exactly the first time until somebody has a chance to play around with it. It's an evolution as well.

Michael Krigsman: On that point, how can HR leaders encourage their organizations to adopt these kinds of data-focused tools?

Caroline O'Reilly: You need to start with the group of people who really want to use these tools first. Get them into their hands and just get started. Set up a tiger team. 

It always starts with a business question, right? It never starts with the tools. It starts with what are you trying to do in the business and how do you want your people to experience that. How do you want them to help in the business?

It starts with those questions. Then you look at, well, how do we answer these questions? As a tiger team gets more and more up to speed, they get comfortable, and they realize that by using narrative and storytelling, they can actually understand the data and get to maybe do the next level of analysis themselves. 

Best practices and advice for implementing people analytics

Michael Krigsman: Caroline, what advice do you have for HR professionals who are just beginning this data-driven people analytics journey?

Caroline O'Reilly: First of all, don't think about the tools. Start with what your business strategy is and how your people support that strategy.

Then think about, okay, what are your business questions that you want to answer. What are your data questions that you have? 

Then look at what tools fit into those questions. Whatever tools you're going to use, just make sure that they're agile tools because what you need to ask today is going to be different next week. 

Utilize ML and AI. The data is growing. I hear it all the time from business leaders I talk to. It's hard to get a handle on all the data that's in your organization. It's fragmented. It's siloed. You're going to have to use tools that are using and utilizing ML and AI to be able to surface those insights because it's just getting to vast to do it in a manual way. 

I would say, have fun. We really enjoy working with our people analytics team in Workday because we discover really interesting ways that we can provide better employee experiences for our whole organization. So, have fun. It's a really interesting place to be.

Michael Krigsman: Caroline O'Reilly, General Manager of Analytics at Workday, thank you so much for spending the time with us today.

Caroline O'Reilly: Thank you so much, Michael. I really enjoyed our chat.