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.