Data and talent are foundational to business. Today we're speaking with Caroline O'Reilly, the General Manager of People Analytics at Work Day. 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. When I talk to business leaders, the first thing they tell me is. There's just a sea of data out there and the data is fragmented and it's siloed throughout the organization and 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 that 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. 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? Enabling our business leaders to accelerate their decision making, really advising leaders on how to make better decisions. And usually the way that works, we come up with some hypothesis that we want to prove or investigate, pulling that data together.
And as we try and solve more complex questions in each business, it's about bringing in 3rd party data and 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. It sounds like people in Business Today have a greater recognition of the importance of data than they did in the past. 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, right, where we had to move really quickly to answer business questions much, much faster than we ever did before. So what are the strategic questions that people analytics
ultimately helps address? 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's also those unique questions that for instance, you know for customers doing an MA 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. Let's drill into the data. So much of this is completely interwoven and dependent on the data. What kinds of data feed into people analytics? Can be any data that's related to your people.
So it could be listening data, it could be skills data. It's stated by performance. It's stated by 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. And let's 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. And 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 or composition around diversity, inclusion. You might want to ask a question, what's 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. And these are core pieces of people analytics that are almost standard in many different
organizations. 1 aspect is it's very core sets of data that are shared through the different companies that we talk to. But then on the other aspect, there's 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.
And that's where they need to blend that data together and get those really rich data sets like we answer their unique challenges and their unique business questions that they have. Caroline, you mentioned employee experience several times. Where does people analytics fit into creating a better employee experience? During COVID, when we all moved to remote work, there was
someone who had just started. That week sitting beside me in the office and I remember turning to him and saying like, are you going to be OK? And just started this week in the office. It really helped to have in the employee listening to. 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. And so you can pull all that data together. So I can see a heat map of where
I need to focus. That's really powerful and that really improves the employee experience. How does people analytics help you connect with these folks that are working remotely? It helps us connect by answering business questions that we have. For instance, when we came back to the workplace, we wanted to know that the people who were working remotely feel more connected than the people who
were in the office. And 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. And what we discovered was that people needed focused time. They didn't get focused 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 5050 in the office, 5050 working, you know, in a flex way. So by using our own data, we came up with that recommendation. Caroline, we hear a lot about skills. What do we mean by that? People and skills are like this now, right? And companies are really using skills to totally supercharge their organization.
We're moving to skills based hiring and you've probably heard the the phrase, you know, quite quitting like last year. But 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, right. We put out our advertisements.
But moving to skills 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 a 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 re skill their workforce because with the talent shortage that there is, we can't go out and hire all these people. So 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 know you're looking for the skills and then that's open to everybody. It's really the future of hiring as we see it, Caroline. Some people say that skills are the next evolution of people analytics. Can you tell us about that? 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's done this really well actually is a censure.
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 XYZ skills. They apply that based on what the employee has done and what projects they have done, and 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 like Accenture are a great example of how to supercharge your organization with skills.
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? People analytics is key for me because I'm a product leader and engineer and 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. So I I need data from both perspectives. So we're very passionate about
people analytics in work day. Our people analytics team comes up with hypothesis that we want to answer by looking at our people data and work day. And 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? And we've all heard the hypothesis around that, oh, people stay because of their manager, or people stay because of their compensation, or people stay because, you know, they feel challenged at work.
And we wanted to actually go into the data and really figure it out. And they discovered that the core reason for people to stay out work day was the ones who had a really challenging, a really valuable career conversation with their manager. And that was something that surprised us because we've always thought that it was maybe the manager or maybe it's the work that they were doing. But it was around having great career conversations.
And 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 lease Plan and lease plan are a Dutch financial services provider for fleet management. They are a global organization. They're in 32 different countries and they have completely transformed their
hatred operations. They really wanted all their hatred 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 are on board 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? And 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. If you look across these particular use cases or other ones I know you speak with so many work day customers, are there a common set of SuccessFactors or attributes that drive a successful people analytics implementation or deployment? 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 have been extracting data from different entities and pulling it together and they immediately felt. The state 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 a story around the data and writing a narrative around the data. So the HRBP or the business leader? Can understand what that data is telling them and what that insight is telling them and then they can drill down and do another level of analysis for
themselves. So 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 and empowers them.
That's where I see the company is making the biggest impact, more and more people having access to the data, having access to it. Now, 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. You don't get there overnight.
The 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 inclusion and they may implement a product like people analytics, which shows them some key insights and trends around diversity 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 and then over time those leaders become really, you know, proficient in. Interpreting that data themselves and 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. 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're a general manager of analytics at Workday. Tell us about these tools. 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 and is also.
Surfacing anomalies that you may not have seen and it uses ML and AI to do that in the background. So it's telling you where you may need to focus on diversity, inclusion on or composition, on hiring or on talent or on skills. And so the wonderful thing with people analytics is that it gives you a story around the trend. So first of all, you see the trend, you see the story and 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 because 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 with your people
data now. And the way that customers want to ask questions about their people data is just fast and growing and unique. And so Prism analytics allows you to pull in 3rd party data that you can blend with your people data to ask those unique business questions that you may have. And the reason it's so important is that the people data is so sensitive. We are hyper focused on security of that data in work day.
That's our number one priority. Our customers really make that strategic decision to keep that people data in work day, but they want to blend it with third party data and using Prism analytics you can blend that third party data and bring that third party data in. Which are people data.
Another product that we have is Pecan Employee Voice and that's a way of surveying your employees and Pecan 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 and you can build your dashboards as well. Caroline, you mentioned AI and machine learning.
Can you tell us where these approaches fit into analytics at Workday? Data is just getting to be so vast and there's so many different data points it is going to become increasingly hard to. Go through that data in a manual way and surface insight. So more and more our business leaders are going to want to use ML and AI to be able to surface those insights because there's 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 too and what we call our storyteller engine. So when we talked about the people data and the points that you need to be able to discover
those insights, it's fast. And so we run ML and AI over your work day 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. And I see Mlnai is 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. You know they want to move to tools like people on IT, 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. 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 analytics tools? That's such an important part of people analytics, Michael, and it's one that we take really seriously is around the security of this data that we are hosting on behalf of our customers. We are very careful about.
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 bringing into a pipeline manipulated. 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.
And that means you're only surfacing that data in reports to people who should see that. And that's a really core fundamental part of what we do in Workday and what we do in our People Analytics product as well. So you're simplifying that data pipeline and obviously simplicity when it comes to anything to do with security and privacy is really important. 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 work day and then you can apply your work day 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 and working. 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?
It's super important. The people on the next team inside of Work Day, they're run by Phil Wilburn, who's a great friend of mine, a really great leader and they take a very product oriented view when they are creating dashboards for me, for instance. So 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 Work Day and they go out and they do interviews with us.
They're really trying to get to the core of what is the data that Caroline needs to run our organization. How does she need it? How does she need to splice and dice it? And 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. So 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 that we are going to adopt it and use it. And I think that's a really good model to use as you start your people on that externality a lot of upfront. Designing that goes into it to make sure it's going to be adopted. It sounds like adoption ultimately relies on having empathy for the end user. What they need to accomplish? How will that data be useful?
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. And 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. And what they usually do is that they'll they'll build a first version after spending a lot of time talking to us, and then they'll change it and they modify it and they make it better because, you know, it's always hard to get it right exactly the first time until
somebody has a chance to play around with it. So it's an evolution as well. And on that point, how can HR leaders encourage their organizations to adopt these kinds of data focused tools? Need to start with the group of people who really want to use these tools first, get them into their hands. Like just get started, set up a Tiger team. And it always starts with a
business question, right? It never starts with the tools, 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? So it starts with those questions and then you look at, well, how do we answer these questions?
And as a Tiger team gets more and more up to speed and they get comfortable and they realize that using narrative and storytelling, they can actually understand the data and get to maybe do the next level of analysis themselves. Caroline, what advice do you have for HR professionals who are just beginning this data-driven people analytics journey? First of all, don't think about the tools. Start with what your business strategy is and how your people support that strategy.
And then think about, OK, what are your business questions that you want to answer? What are your data questions that you have? And 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. 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 too vast to do it in a manual way. And I would say have fun. We really enjoy working with our people, analytics team and 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. Caroline O'Reilly, general manager of analytics at Workday, thank you so much for spending the time with us today. Thank you so much, Mike. I really enjoyed our chat.