April 17, 2025 • 37 mins
Danielle Bushen, Global Head of People & Culture Technology Strategy at Sanofi, joins us this episode to discuss HR data governance. She explains what “data governance” actually means, outlines common data governance challenges HR teams face, and offers practical first steps toward better governance practices.
[0:00] Introduction
- Welcome, Danielle!
- Today’s Topic: Demystifying HR Data Governance
[5:54] What does “data governance” actually mean?
- Understanding transactional vs. analytical HR data
- Why cross-team interoperability and collaboration are key
[16:58] What are common HR data governance challenges?
- Navigating the complexity of balancing multiple jurisdictions
- How the lack of standardized practices creates governance headaches
[27:15] Where do you start your data governance journey?
- Establishing clear data ownership
- When to address urgent issues before tackling comprehensive data cleanup
[36:28] Closing
- Thanks for listening!
Quick Quote
“[Data governance] is owned by people, enabled by processes, and supported by technology.”
Contacts:
Danielle's LinkedIn
David's LinkedIn
Dwight's LinkedIn
Email us!
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Announcer (00:01):
The world of business is more complex than ever. The
world of human resources andcompensation is also getting
more complex. Welcome to the HRdata labs podcast, your direct
source for the latest trendsfrom experts inside and outside
the world of human resources.
Listen as we explore the impactthat compensation strategy, data
and people analytics can have onyour organization. This podcast
(00:24):
is sponsored by salary.com Yoursource for data technology and
consulting for compensation andbeyond. Now here are your hosts,
David Turetsky and Dwight Brown.
David Turetsky (00:38):
Hello and welcome to the HR Data Labs
podcast. I'm your host. DavidTuretsky, alongside my best
friend, partner in crime andco-host from Salary.com, Dwight
Brown. Dwight, how are you?
Dwight Brown (00:50):
David Turetsky, I am wonderful today. How are you
David Turetsky (00:53):
You're wonderful. And I'm I'm freezing
doing?
my butt off here inMassachusetts. It is a cold
spell from hell, or, you know,if hell, if hell or cold? I
won't rub it in what thetemperature is here, don't. But
today we have with us a evencolder, but brilliant person,
(01:14):
Danielle Buschen and Danielle,how are you?
Danielle Bushen (01:17):
I'm good. I am chilly. I hope I'm not cold. No,
no. Your personality
David Turetsky (01:21):
is certainly not cold, but you are potentially
colder because you are comingfrom the great white north of
Toronto,
Danielle Bushen (01:29):
north of the border, and it is very chilly
here today. It is well into thedouble digits below zero
Celsius.
David Turetsky (01:37):
For those who can't convert that to
Fahrenheit, we'll actually putthe equation in the show notes.
Dwight Brown (01:44):
Equals cold as hell.
David Turetsky (01:45):
I think it's minus 32 times five divided by
nine, something like that.
Danielle Bushen (01:52):
Oh, you're right. I just know that some
things, I'm a Canadian, right,so I'm almost up. Some things
get measured in Celsius, but mypool temperature gets measured
in Fahrenheit.
Dwight Brown (02:02):
Go figure. Wow.
Oh, interesting. Well,
David Turetsky (02:05):
if it's like exchange rates, it's like point
six to the Fahrenheit orsomething, exactly. So,
Danielle, tell us a little bitabout you. I know you're a
repeat offender on the HR datalabs podcast. You were with us
for the HR data labs podcastfrom the HR technology show.
Danielle Bushen (02:22):
I was running Vegas together. At the time, I
was working as a data governanceleader for Sanofi, and I still
at Sanofi, I'm now focusing onour HR technology strategies.
I'm the Global Head of peopleand Culture Technology Strategy
at Sanofi pharmaceuticalcompany. Globally scaled
(02:44):
footprint in about 70 pluscountries. Wow. And close to
well more than 120,000 people inour total workforce, including
both our employees andcontingent workers. So, big
footprint,
David Turetsky (02:56):
yes,
Dwight Brown (02:57):
wow.
David Turetsky (02:57):
Big job too. So Danielle, we actually ask every
one of our guests what's one funthing that no one knows about
you. So you have to come up withsomething different from the
last time.
Danielle Bushen (03:08):
Oh, that's not fair. I'd forgotten this
question. That's okay.
David Turetsky (03:11):
I'll tell you that's something that I
remembered from the last time.
Danielle Bushen (03:15):
So last time, I think I told you that I make jam
of practice archery in my sparetime. Today, I will share that I
spent the New Year's in LA andwas so fortunate to get a chance
to see that part of the worldand spend time in Pasadena and
Altadena and Malibu. Rightbefore everything went I was
(03:35):
literally I got on a plane tocome home. I took off, and
everything was fine, and Ilanded and the news was just
exploding, so enormouslygrateful that I got to spend
time in a greater LA area andfeeling really badly for
everything that's going on inthat part of the world right
now.
David Turetsky (03:52):
Yeah, and our hearts go out to all the people
who are our regular listenersand even the people who aren't
our listeners, for how this isaffecting you. It's really
horrible. And I can't make anyjokes about it, because it's
just so terrible. No, but
Danielle Bushen (04:05):
I will tell you the bucket list item. I got to
go to the Rose Bowl parade whileI was out there. Really nice,
fantastic. Highly recommend thisas something to go and spend
your time on if you have theopportunity.
David Turetsky (04:17):
That's really cool. Nice Rose Bowl. Who played
in that this year.
Danielle Bushen (04:21):
Oh, now you're asking me a football question.
The Rose Bowl was there? No, I'mpretty sure it was Ohio and
Oregon. Okay, well, but you areat the far limit of my American
football knowledge. Now,
David Turetsky (04:39):
it's okay.
That's okay. When you tested usever about the Canadian Football
League, we'd probably have lessknowledge. So,
Danielle Bushen (04:46):
yeah, I would also have less knowledge. No,
there's not a league thatanybody follows,
David Turetsky (04:50):
but maybe we can talk hockey a little bit.
Dwight Brown (04:52):
I have to admit that I couldn't even have
answered that question. I don'tI like watching football. I
don't pay attention to who'sdoing. And what? So I had no
idea who was in the Rose Bowl,
David Turetsky (05:03):
but if I asked you if the Toronto Maple Leafs
are doing okay this season,would you know?
Danielle Bushen (05:07):
Oh,
Dwight Brown (05:08):
I'd say, is that a basketball team?
Danielle Bushen (05:12):
If you really want to upset me, you can tell
me their an ice hockey team, asopposed to a hockey team. And
there's only one kind of hockey.
Dwight Brown (05:24):
Big differentiator in there,
David Turetsky (05:26):
one kind of hockey, although my friends who
actually play field hockey wouldbe upset with me if I said that.
So today, we have a phenomenaltopic to talk to our friend,
Danielle about, because it isone of those things that are
near and dear to the hearts ofDwight and myself, HR Data
Governance.
(05:54):
So Danielle, from your currentrole as well as your past role,
what is HR data governance? Whatdoes it actually mean?
Danielle Bushen (06:02):
It's a great question. And I think people
often think about datagovernance as a bunch of data
lineage, tracing and technologystuff, and deploy a bunch of
tools and talk to the ITdepartment and get the data
office involved and worry aboutprivacy. Yes, that is a piece of
the story. It is not the pieceof the story that I find most
(06:24):
compelling or that adds the mostvalue for me. HR data governance
is about making sure that yourdata reflects the business value
propositions of the company, thepeople that work there, the
processes that you want totransact. And it is all about
getting that story right. It'sabout digitizing the HR function
in a way that you can automateit. It's about making the
(06:46):
experience of work as seamlessas possible. And we talk about
HR data probably two ways mostof the time. One is
transactional HR data and theother is analytical HR data, and
when you're talking analytics,directionally correct is great,
probably good enough. You canhelp people understand lots of
(07:08):
good things about what's goingon in the function, and it
doesn't have to be exactlyright. But when you talk about
transactional HR data, guesswhat? It makes a huge difference
if one of your person's genderis wrong or their salary was off
by a zero, or the yourtermination date was in 2525
instead of 2025 which actuallyhappened in a colleague system
(07:29):
just recently, they found thedata error. But this is the
stuff of exactly right. This iswhat data governance is all
about. And when I talk aboutdata governance, I always say to
people that it is owned bypeople. It is owned by the HR
function itself. It's not an ITthing. It is supported by
process, and it is enabled bytechnology. And it's all those
(07:52):
three pieces coming togetherthat makes data governance so
interesting and so impactful.
David Turetsky (07:58):
I think one of the complications is it's
actually also owned by theemployee and by the manager and
by everybody else in the valuechain, that, or I mean, even
candidates have a have a hand inyour HR data governance, right?
Because they're enteringinformation into a system. Might
be your candidate, application,system, contracting, closing,
(08:19):
Yep, yeah. But, but theneverything they enter could be
right or wrong or could becomplete Baloney, and that's
getting into your analytics andyour transactions which make
them wrong.
Danielle Bushen (08:31):
So users have an obligation, duty of care, to
try and give you as complete adata set as you can they also
have rights to choose to giveyou the data or not. Yes, right?
And that's really important tounderstand as you're thinking
about what data am I collectingfor what purpose? How do I want
to use it? Have I informed theowner of that data about how I'm
(08:52):
going to use their information?
But it's also sort of a duty ofcare when we think about process
design, to encourage people togive you the data in the easiest
and most complete way possible.
Yeah, if you're collectingpostal code as a consumer, I can
put my postal code in all inlower case with no spaces, and
it's a Canadian postal code, soit's got letters and numbers in
(09:14):
it. And guess what? Amazonfigures out right away.
Absolutely did. I mean capitall6, capital L, etc, right? It
tells you that. And I think whenHR thinks about data and data
capture and data governance, weneed to bring that sort of
consumer grade experience tobear and help the user to your
point, the user who's providingthat data at the top of the
(09:36):
funnel to give you the bestquality data they can. That's
about a guided experience. Andit's about thinking through
what, what things are likely tobe problems down the road.
Dwight Brown (09:45):
You know, I think back historically, and it's
amazing how quickly thelandscape has moved with this.
The to your point about theabout Amazon being able to sense
those things, it wasn't long agothat there's. Just wasn't the
technology available to be ableto do that, yes, and so, you
know, being able to have thosestops in place that confirm the
(10:09):
information or whatnot, there'sa lot of that stuff in the data
governance arena that wasn'tthere even two years ago. I
mean, you look at where we arerelative to that, done. But it
also underscores the need forboth solid data governance as
well as changing in the waysthat that we administer it. You
(10:30):
make
Danielle Bushen (10:31):
a really good point, right? And when we, when
we think about technologydeployment in HR, very often our
budgets are sort of with a onceand done flavor, yeah, implement
it, carry on. But the reality isthat all of the major HR systems
are making releases every sixmonths, maybe more often.
(10:51):
They're continually upgrading.
They're bringing in newcomponents, adding AI that may
be helpful. May just be a datavalidation rule that's being
checked in the background, ifyou don't stay on top of those
things, then you fall behindthat consumer experience very
quickly, and that makes the HRprocess owners need to be much
more attuned to technology thanperhaps they were in the past.
(11:12):
It's not something you can justthrow a defense to it and
ignore. You really have to begreat partners as a function of,
in terms of continuallydeveloping, how is a, how is the
technology supporting theexecution of the organization?
Dwight Brown (11:29):
Yeah, so many people still like to try to toss
it over the fence to it, becauseit's just easier. Like, yeah,
you guys can program it. Youcan, you can make something to
happen, right? Yeah, exactly,exactly, your jobs are easy.
David Turetsky (11:47):
Well, there's another issue with HR data
governance. And I mean, there'sanother explanation about HR
data governance that touches onso many things across an
organization. HR data governanceisn't just HR data governance,
it's also it's ties to all theother pieces of the value
proposition of a company. Sowhether that's security, whether
(12:07):
it's finance, whether it'severything workforce planning,
all those things aren't just HR.
They're everything else. And sowhenever I deal with my
colleagues from the finance andfinance group, and they say to
me, Hey, I have an accrual thatI have to create for the bonus
program. Well, you need, can yougive us some numbers? Well, that
(12:27):
kind of takes it out of therealm of HR, and now puts it
into the realm of finance. Sonow I have to interface with
them and the things that I doand the decisions I make, I now
have to lay out all myassumptions for them, because
now my data is being used insidethe context of finance, and they
have rules for this stuff. It'sbeyond just us right now. They
have rules. So you know, HR datagovernance is also how do we
(12:51):
interface with other teams,isn't it? Or am I? Am I just
trying to make my arms a littlebit bigger and try and grab
more.
Danielle Bushen (13:03):
I don't think it's about grabbing anything.
It's I think it's aboutunderstanding that the
accountability of HR is tostructure the people data of the
company that may sit in HRtools. It may sit elsewhere.
Head count generally, doesn'tsit entirely in an HR tool.
There's a whole bunch of financecomponents to that. You're in
the middle of hiring somebodyfor a global role in a
(13:25):
multinational Guess what?
There's going to be transferpricing, pricing behind the
scenes. You want to structurethe real estate footprint for a
hybrid workforce. You need tounderstand how often are those
people on site, and that'spartly badging data and partly
security and partly contracts.
You know, who's who's on a fullyremote contract, who's supported
(13:46):
for their tax treatment of that,you're bringing in so many
departments that all need totalk to each other and learn to
speak a common language. And Ithink the opportunity for HR is
to be that translator,particularly around the people
do it. I mean, we need to lookto others to be the experts in
certain things, but we also needto bring that conversation
(14:07):
together. Last week, Ifacilitated a conversation
between our single sign on,team, our service now team, our
work day team, our Microsoft 365team and our CUPA procurement
team, sure, because we weretrying to solve exactly one of
these kinds of problems, and so,you know, there's five functions
represented around the table,and we're talking about, what
(14:27):
portion of our workforce, ournon employees, do they still
need network IDs? What's theirsingle sign on identifier? Do
they have a work day identifier?
What's our regulatory obligationto those people? HR is at the
heart of that conversation, butwe can't do it without all those
other people at the table.
David Turetsky (14:45):
Oh my God, there's such a compliance issue
there, too, with all the rulesthat California had created, or
that had been started inCalifornia, about what is an
employee and what is the if youstart putting putting them in
the HRIT. What does that mean?
Danielle Bushen (15:02):
Co-employment risk, super interesting, data,
governance topic,
David Turetsky (15:06):
exactly, important, yeah,
Dwight Brown (15:08):
yeah.
Danielle Bushen (15:09):
And these are the things that create a lot of
anxiety within an organization.
You know? This, this tribal myththat, oh my gosh, we can't touch
that. It's a regulatory problem,right? One of the things that I
focus on a lot with in thosekinds of conversations is Tell
me more, what regulation, whatexactly are we trying to comply
with in what part of the world?
(15:30):
Because if you can articulatethat, then you can figure out,
where's the room for creativeflexibility. How do you create a
seamless model? At Sanofi, we'rein the process of looking at
bringing our total workforceinto a single set of systems.
And for years, we had a beliefwithin the company that we could
not put contingent workers intowork day. Anybody who's a
(15:52):
workday user knows that'spossible. It's just about how
you think about theconfiguration of that profile.
Make sure that you've got theright kind of data for the type
of worker that you're lookingat.
David Turetsky (16:02):
I think one of the other complications is that
when you're trying to balanceall those different regulations
you're talking about, forexample, California has
regulations on pay transparency.
Illinois just created paytransparency legislation that
says you need to keep five yearsof history on how you paid, and
the decision points along theway, and the posting
(16:22):
information, so you might havean employee comes along and
says, I want to be forgotten. Sowho are you going to follow? You
going to follow California'srules. You're going to follow
the EU's GDPR. Are you going toallow them to be forgotten? And
then now, kind of break the lawin Illinois if they're an
Illinois employee. So, you know,there's so many things that you
have to comply, have to worryabout from a compliance
(16:44):
perspective,
Announcer (16:47):
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David Turetsky (16:58):
That's kind of lends me into our next question
of, what's the problem with HRData Governance? I mean, I guess
we're talking about it rightnow. It's complex, right?
Danielle Bushen (17:09):
It is, and people want a clear answer, and
there isn't always time. So, soyour example is a perfect one.
If you look at the deployment ofAI in HR, New York City has its
own rules for this stuff. Therange of jurisdictions that you
might be looking at, the waysthat you look at how your
(17:30):
technology and your dataretention plans and all these
other things fit into theconversation, are going to be
varied. So there's not going tobe one clear answer. And I think
it's incumbent upon HR leadersto think about thoughtful risk
management. Yes, you need togive the employee the ability to
ask to have their data removedafter they leave the company so
(17:50):
they want to be forgotten, butyou have to balance that with we
may have obligations to you as afuture retiree. We may have
components of tax treatment thatneed to be managed. And so those
those different regulations area little bit in conflict with
each other, right? Which onetakes precedence? And as long as
you can demonstrate that you'vetaken a thoughtful approach to
(18:11):
removing data that's nonessential, retaining things that
might have a specific obligationfor the company or for the
individual that they're just notthinking about, then you've got
a leg to stand on, then you'vegot a way of justifying your
approach. And most regulatorsare quite receptive to that.
They will look at us through alens of, have you done your due
diligence? Have you thoughtabout reasons for retaining that
(18:33):
data, and have you been clearwith the individual? Yes, I've
asked to have my data removed.
No, we haven't removed all ofit. Here's why that's fair and
reasonable.
David Turetsky (18:43):
I think there's also the expectation of privacy
that may not actually existanymore, given things that they
posted on LinkedIn or that theyactually applied using LinkedIn,
but they put their entireemployment profile, even from
your company, on it. And so youknow, how, I mean, how do you
balance that too? Because thedata is in the public domain.
Danielle Bushen (19:05):
And a lot of people aren't very astute or
aware about their digitalfootprint. The amount of
information that could besourced about me from the public
environment is probably akin towhat we store in your hrs, a lot
of the time, until you get tothings like, you know, we just
had a conversation about healthdata being stored in the HRIS,
(19:26):
and why would you need healthdata in your HRIS? And there's
two really interesting usecases. One is understanding
disability or ability, which isactually a health status.
There's a diagnosis attached tothat right and it is really
relevant and helpful for theright people within the HR
(19:46):
organization to be able toprovide accommodations. So
there's a real good reason tostore that data in a
constructive way. But of course,the risk is that data is going
to be misused. It's going to bemisinterpreted, it's going to
create. Bias, and so now you'reinto a conversation about who
has rights to that data for whatpurpose. How are we using it?
How is it being aggregated? Andhaving good rules in place for
(20:10):
those kinds of analytics whichare all about the story of the
whole not about the individual,is really critical to a
successful Data GovernanceProgram
Dwight Brown (20:20):
And good security protocols too on top of it to
make sure that it doesn't getout.
Danielle Bushen (20:26):
Yep. And in the land of Excel, that is a running
rear guard bottle a lot of thetime.
David Turetsky (20:35):
Wait a minute, you're talking about the most
popular database program in thehistory of business.
Danielle Bushen (20:41):
You could all just get rid of Excel. Some days
we'd be a lot happier. Iunderstand why it's used. I get
it. It's easy. Yeah, it doesbring some baggage.
David Turetsky (20:52):
It's not even just that. It's easy. It's
prolifer, proliferate-able. Imean, you don't need, I mean,
you need a license for it, buteverybody's got a license, you
know, thank you, Microsoft,right? Everybody's got a
license. And it's not hard toactually be a database
programmer. If you can put avalue into a cell and then put a
(21:12):
field header at the top of thatof that column, it's ubiquitous.
It's everywhere. It is, it is,and digital skills in it suck,
but that's that's another issuecompletely, but
Danielle Bushen (21:24):
it's not a data governance problem.
Dwight Brown (21:27):
I heard it. I heard an interesting one a
client on I was working up with,up until a short time ago, half
of their HR functions were in anExcel spreadsheet, as opposed
to, they didn't have an HRISyet, or they were just
beginning, and it was littlemicro piece that was built out.
(21:49):
So I think, I think things likethat, and the data governance
side of me just goes, Oh my God.
Danielle Bushen (21:55):
But that may be completely realistic, you know,
for a small startup, but theydon't need to invest in the
fancy HR system, and it probablyisn't a good use of their
limited dollars. It's justbecause you can apply the same
principles of governance to, youknow, a spreadsheet that has
really clear, locked down,restricted rights that you've
understood who's able to editwhich fields, all the same
(22:18):
things that you would do in asophisticated tool with role
based security. You can do it inspreadsheet.
David Turetsky (22:24):
That's a huge assumption. That's a huge
assumption, though, Danielle,that you're going to have all of
those things locked down in a ina canvas. That's kind of what
Excel is.
Danielle Bushen (22:35):
Yep. Yeah. It's true, it takes forethought. It
takes, you know, the ability torecognize, hey, this data is not
generally available. Justputting it in somebody's
personal drive is not safeenough. How do we secure this?
What passwords do we put on it?
And there are good ways to applydata governance principles, even
in a lower tech solution likeExcel. I think the bigger
(22:57):
challenge is when we start toemail files around to each
other, and, oh, here's a copy ofthis. And David, you should see
this information about, youknow, retirement rates, and then
you realize that you've sent afile that has all the source
data of everybody's ages anddates or birth on it, right? Not
ideal.
David Turetsky (23:14):
Well, I can't tell you how many times I've
seen analyzes that have beenpasted into PowerPoint, but they
paste in the Excel object sourcefile which has exactly it has
the entire source file with allthe employee names in it, with
all their pay in it. And that isan absolute data governance
nightmare. So, yeah, I mean, ithappens. And I guess the other
(23:38):
thing I want to mention,Danielle, is you were talking
about, you know, sending anemail. Remember the days when we
used to send those manilaenvelopes with the extreme
security measure of that? I lovethis, of that little rope, a
little the little string, thered string, and then you'd, you
could even put a piece of tape,very secure. You put a piece of
tape across the front so itwould
Danielle Bushen (24:01):
put a squiggly line on it to see if anybody had
opened the tape.
David Turetsky (24:04):
Opened it. Yeah.
You'd stamp confidential. Soyou'd line up, and you'd make
sure that the c o n wasabsolutely perfectly aligned
when it came back to you,
Dwight Brown (24:15):
the beginnings of cyber security right there.
David Turetsky (24:19):
Yeah, let's see how you can hack that one
Dwight, but that, that's wherewe started with sending inter
office mail that had approvalson forms for people's pay. So,
you know, we're not too muchbetter than that right now.
Danielle Bushen (24:33):
I mean, I think we are. I think they
David Turetsky (24:35):
I'm being overly
Danielle Bushen (24:37):
the the reality is that the problems of data
governance are there's theobvious ones that we've just
been talking about, the issuesof continuity of care through
evaluation. Those things areimportant. I think the harder
ones are when we use thirdparties, which most companies
do, and now you have what'scalled a data controller. Is
(25:00):
changing hands. Somebody else isresponsible for the information,
right? And what happens at theirend? Do they use a
subcontractor? Are theypromoting good governance on it?
Did they, you know, have a hackand somebody got access to all
the credit card data for yourentire company, which happened
to include social securitynumbers, but no longer in your
control. But as an employer,you're still accountable.
Dwight Brown (25:22):
You think of the the Facebook debacle a few years
ago with the analytics company.
I can't remember the name of it,but
Danielle Bushen (25:29):
Cambridge Analytica,
David Turetsky (25:30):
yeah.
Danielle Bushen (25:30):
Cambridge Analytica, exactly yes, yes. And
everything that happened there,and you see that play out
company after company aftercompany. It wasn't isolated to
Facebook, but a lot of that getsback to that, that data
governance piece of things, andwhat is the data? How are we
using the data? What are therules we're putting in place?
(25:51):
And unfortunately, a lot ofcompanies have to learn it the
hard way to really get there.
And I think the opportunity forHR is first to really have clear
ownership of your definition. Sowhat kind of data are we
collecting for what purpose?
What's our pick list? How do wechange it? And that's really
setting the rules of engagementfor the HR function itself,
(26:11):
which, if you're thoughtfulabout it, you can have enormous
impact and really enable a greatprocess for your employees. Then
it that the challenge is toteach those data owners, who own
those different processes andall the different functional
areas, how to think holisticallyabout contracts and engage their
procurement specialists andtheir legal specialists at the
(26:34):
right time for those pieces ofthe process. And they don't
always know to do that. Sothere's, there's an education
campaign around saying you don'tneed to know everything about
all of this, but you do need toknow when to ask for help. Yeah,
David Turetsky (26:49):
Hey, are you listening to this and thinking
to yourself, Man, I wish I couldtalk to David about this. Well,
you're in luck. We have aspecial offer for listeners of
the HR Data Labs podcast, a freehalf hour call with me about any
of the topics we cover on thepodcast or whatever is on your
mind. Go tosalary.com/hrdlconsulting to
(27:11):
schedule your free 30 minutecall today.
One thing that stabs me in theheart right now though, Danielle
is there's a lot here. So wheredo we start? Because this is
what you've mentioned. Cutsacross and you're not 120,000
employee company, whether you'rea 50 employee company, whether
(27:34):
you're a five employee company,whether you're a 10,000 this.
This is a big deal,
Danielle Bushen (27:41):
and the range of obligations doesn't change.
Even if you're only doing it for40 people, those obligations are
still there. So where do youstart at? You start with
ownership, and you start withthe actual concept of
governance. Who gets to make thedecisions on data fields. And if
you can get that part right,then you're having the right
business conversation. Whattechnology you put behind it is
(28:03):
truly secondary, and I'd sayit's owned by people, enabled by
process, supported bytechnology. The technology is
the tail on the dog here. So ifyou can start with having clear
ownership and make sure thatpeople understand what is their
role to play in defining thevalues, the attributes, the
reasons that you might want toupdate it. The whole classic
(28:26):
move, add, change, delete. Whogets to do those things right?
If you can get that part right,the rest will follow. And I
think sometimes in HR, you know,a COE or a functional lead will
say, Oh yeah, that's, that's thesystem teams problem. That's the
work day teams problem, or thesuccess factor teams problem, or
whatever, pick your technology.
Which isn't true. The people whoneed to really feel ownership
(28:49):
are the people who arecollecting and using that data
and understand its purposebetter than anybody else.
Dwight Brown (28:56):
Well, and organizations need to also
understand and have in placeoverall data governance
processes, because, and itdepends on the size of the
organization, what that lookslike. But where I was
previously, we were a 60,000person organization. We'd
literally had hundreds ofdifferent systems out there, and
(29:19):
in that case, you know ourstarting point to your question,
David was all right, we need tocentralize this data governance
function right in some way oranother, and then let's take
stock of the systems that wehave out there, get the right
stakeholders around the tableright now for a large
organization, that makes sensefor smaller organizations, it
may Be a little bit differentthan that, but that's the and it
(29:43):
kind of gets back to what wewere talking about at the
beginning of the conversationwith what you what you said,
Danielle, that not only is theHR system doing HR data, but you
may have finance data and otherdata systems in place. And so.
So to the extent possible, beingable to bring together
everybody, so that you've gotcohesive data governance
(30:06):
processes, whatever that lookslike in the organization, it's
just it is hard to find thatstarting place and who owns it.
So.
David Turetsky (30:15):
I think that's the one of the big issues there,
is who's the data owner. And toDanielle's point, you know, who
is the one who gets to make allthose decisions? And how do you
make that as a team? How do youhave those? I mean, do you have
committees, Danielle, where yousit down with your colleagues
from across the company and say,you know, this is yours, this is
(30:36):
mine. This is yours. This ismine. I mean.
Danielle Bushen (30:39):
We kind of do, yeah, there's those. We do have
an enterprise data office, andso there are standards of care
for how data gets stored andmanipulated and moved into
warehouses and everything else.
Those are great foundations andtools that we can leverage in
each function in each businessline. But each function and
business line has its ownaccountability and for framework
for data governance in peopleand culture, we have a data
(31:01):
Council, and you get into thosedifficult conversations around,
well, who gets to define what apromotion is? Is it comp? Who
decides grading and gradingstructures? Is it talent
management? Who says, well,lateral moves with this kind of
change in scope would be reallyhelpful to call a promotion, or
is it because the person movedfrom one division to another
that that's considered acrossme, but these are all the
(31:24):
conversations that you have toreally go through. What does
promotion actually mean? Whatdoes demotion actually mean in
our organization, right? And itmight be different than somebody
else's organization. Yeah,right. But if you can clarify
that you get to a great place,you know reasons for departure.
Is it voluntary? Is itinvoluntary? Well, what do we
mean by constructive dismissal?
(31:48):
There's legal components tothat. There's labor law
components to that. There'sactual conversations with the
person and what you want to sayto them, and what that means in
terms of whatever theirtermination paperwork where it
looks like in the countrythey're in, right? Getting all
of that put together iscritical.
David Turetsky (32:05):
Also, if they're part of a labor Labor Council or
labor union, and you know, whodo you have to go to once those
kick off, once those processeskick off, especially if you're
terminating someone,
Danielle Bushen (32:16):
yep.
Dwight Brown (32:16):
Hm.
David Turetsky (32:18):
yeah. And thus start Interesting, yeah,
exactly, start somewhere, andthen, and then go through all of
these processes. I think that'sone of the overwhelming things
about this, though, Danielle,and that's the reason why I kind
of asked the where do you start?
Is because this is reallycomplex, and it gets, it has so
many there's foundationalelements, yeah, but then there
(32:41):
are also these elements thatexist in the fringe, all over
the place, all over the world,like learning systems and reward
systems. They're just, they're10, they're not only tangential,
but sometimes they're built in,you know, commission systems,
yeah, where it's owned by sales,ops, you know, it's only owned
by HR. It's not owned bycompensation. It's sales ops.
Danielle Bushen (33:03):
All three of those examples have come to my
desk just in the last like twodays.
David Turetsky (33:10):
Sorry,
Danielle Bushen (33:12):
but those are the right conversations to be
having. Right like you want tohave a sales compensation
calculation engine thatunderstands profile based
information, based on on the jobyou were in, the function you
are assigned the territoryyou're working in the market
opportunities. You're bringingtogether sales data and product
data and HR data all in oneplace. And it's actually doesn't
(33:34):
matter who sponsored that work.
Yes, it might be owned by salesops. What role does it fill?
What data is it being populatedwith? Who has governance of that
data, but may not all be salesops and figuring out how to have
those conversations in aconstructive way together? To
say here at the guard rails, iswhat matters most. It's not, not
all we I mean, I said it's allabout ownership. It is all about
(33:55):
ownership, but it's also allabout partnership, making sure
you understand those guard railsand who owns which piece, and
it's rarely an all or nothingconversation.
David Turetsky (34:08):
I love this conversation. We can have it all
day. I think one of the problemswith a conversation like HR data
governance is that for many ofthe people who are listening,
it's something that they have todeal with, and it's in a
mountain of other priorities.
And one of the problems is, isthat if you don't deal with it
and deal with it quickly, it canbecome its own big problem later
(34:32):
on, right? I mean, there are youmentioned analytics at the
beginning, and I've gone intoanalytics projects and said,
Hey, how? What? What's the shapeof your data? And they go, Oh,
it's great. Okay, well, whyaren't using analytics today?
Well, our executives don'tbelieve the data. That doesn't
mean that it's great. It meansthat, you know, we need to do
(34:53):
some work to earn back theirtrust. And so one of the things
I always think about when we gointo. Projects like this is what
are the major issues that wehave to solve? And let's try and
start there, first solve thoseproblems and then work on the
hygiene issues afterwards.
Danielle Bushen (35:11):
I fully agree.
I am actually working on a HCMcore remediation project right
now that is focused on the supersexy topic of worker types and
subtypes and contract types,great, but it's foundational
work. It's about making surethat those definitions support
the business requirements, whichwill then allow us to do much
(35:31):
more interesting work aroundautomation of onboarding and pre
boarding and improving theemployment experience, which is
what we want to do, yeah, butthose data elements are the
prerequisites for that, and it'sabout understanding why it's
worth doing that work and whatit's going to enable and unlock
in terms of value for theorganization, and also what it's
going to prevent. Like, how muchtime do you want to spend
(35:53):
investigating data breaches likethat? Is, like, the last thing
on my list that I want to spendtime on if I can stop that from
happening? For you, exactly.
David Turetsky (36:01):
Exactly.
Dwight Brown (36:01):
Yeah.
David Turetsky (36:03):
Well, I think I know what our next topic is
going to be. Danielle,
Danielle Bushen (36:06):
which is
David Turetsky (36:07):
it's going to be those worker types.
Danielle Bushen (36:09):
oh, great topic.
Dwight Brown (36:12):
I can imagine the number of downloads.
David Turetsky (36:16):
It'll be in the millions. Dwight, it'll be
millions,
Dwight Brown (36:18):
exactly.
David Turetsky (36:28):
Well, no, I'm serious when I say this, that
that it is such a pleasuretalking to you, because, you
know, we could geek out withyou, you know, pretty much all
day on this, but it's just sowonderful to speak to someone
who speaks our language andthinks the way we do. So thank
you very much for being onDanielle,
Danielle Bushen (36:45):
thank you for having me.
Dwight Brown (36:46):
Great having you here,
David Turetsky (36:47):
and thank you, Dwight
Dwight Brown (36:48):
thank you. Thanks for being with us like David
said, we could, we could geekout on this stuff for ages. I'm
not sure what that says aboutus, but that's all right. I'm
okay with that.
David Turetsky (36:58):
I think that's the reason why people listen to
us now, Dwight, is that we getto have conversations with
brilliant people like Danielle,
Dwight Brown (37:04):
Exactly it. Yeah,
Danielle Bushen (37:05):
I'm into my third decade of doing some
version of this kind of work,and it's still interesting, and
I'm still learning new thingsall the time.
David Turetsky (37:11):
Yeah, we're with you well, and thank you all for
listening. If you're stilllistening to this after this, we
love you. You are our people,take care and stay safe.
Announcer (37:24):
That was the HR Data Labs podcast. If you liked the
episode, please subscribe and ifyou know anyone that might like
to hear it, please send it theirway. Thank you for joining us
this week, and stay tuned forour next episode. Stay safe.
The world of business is more complex than ever. The
world of human resources andcompensation is also getting
more complex. Welcome to the HRdata labs podcast, your direct
source for the latest trendsfrom experts inside and outside
the world of human resources.
Listen as we explore the impactthat compensation strategy, data
and people analytics can have onyour organization. This podcast
(00:24):
is sponsored by salary.com Yoursource for data technology and
consulting for compensation andbeyond. Now here are your hosts,
David Turetsky and Dwight Brown.
David Turetsky (00:38):
Hello and welcome to the HR Data Labs
podcast. I'm your host. DavidTuretsky, alongside my best
friend, partner in crime andco-host from Salary.com, Dwight
Brown. Dwight, how are you?
Dwight Brown (00:50):
David Turetsky, I am wonderful today. How are you
David Turetsky (00:53):
You're wonderful. And I'm I'm freezing
doing?
my butt off here inMassachusetts. It is a cold
spell from hell, or, you know,if hell, if hell or cold? I
won't rub it in what thetemperature is here, don't. But
today we have with us a evencolder, but brilliant person,
(01:14):
Danielle Buschen and Danielle,how are you?
Danielle Bushen (01:17):
I'm good. I am chilly. I hope I'm not cold. No,
no. Your personality
David Turetsky (01:21):
is certainly not cold, but you are potentially
colder because you are comingfrom the great white north of
Toronto,
Danielle Bushen (01:29):
north of the border, and it is very chilly
here today. It is well into thedouble digits below zero
Celsius.
David Turetsky (01:37):
For those who can't convert that to
Fahrenheit, we'll actually putthe equation in the show notes.
Dwight Brown (01:44):
Equals cold as hell.
David Turetsky (01:45):
I think it's minus 32 times five divided by
nine, something like that.
Danielle Bushen (01:52):
Oh, you're right. I just know that some
things, I'm a Canadian, right,so I'm almost up. Some things
get measured in Celsius, but mypool temperature gets measured
in Fahrenheit.
Dwight Brown (02:02):
Go figure. Wow.
Oh, interesting. Well,
David Turetsky (02:05):
if it's like exchange rates, it's like point
six to the Fahrenheit orsomething, exactly. So,
Danielle, tell us a little bitabout you. I know you're a
repeat offender on the HR datalabs podcast. You were with us
for the HR data labs podcastfrom the HR technology show.
Danielle Bushen (02:22):
I was running Vegas together. At the time, I
was working as a data governanceleader for Sanofi, and I still
at Sanofi, I'm now focusing onour HR technology strategies.
I'm the Global Head of peopleand Culture Technology Strategy
at Sanofi pharmaceuticalcompany. Globally scaled
(02:44):
footprint in about 70 pluscountries. Wow. And close to
well more than 120,000 people inour total workforce, including
both our employees andcontingent workers. So, big
footprint,
David Turetsky (02:56):
yes,
Dwight Brown (02:57):
wow.
David Turetsky (02:57):
Big job too. So Danielle, we actually ask every
one of our guests what's one funthing that no one knows about
you. So you have to come up withsomething different from the
last time.
Danielle Bushen (03:08):
Oh, that's not fair. I'd forgotten this
question. That's okay.
David Turetsky (03:11):
I'll tell you that's something that I
remembered from the last time.
Danielle Bushen (03:15):
So last time, I think I told you that I make jam
of practice archery in my sparetime. Today, I will share that I
spent the New Year's in LA andwas so fortunate to get a chance
to see that part of the worldand spend time in Pasadena and
Altadena and Malibu. Rightbefore everything went I was
(03:35):
literally I got on a plane tocome home. I took off, and
everything was fine, and Ilanded and the news was just
exploding, so enormouslygrateful that I got to spend
time in a greater LA area andfeeling really badly for
everything that's going on inthat part of the world right
now.
David Turetsky (03:52):
Yeah, and our hearts go out to all the people
who are our regular listenersand even the people who aren't
our listeners, for how this isaffecting you. It's really
horrible. And I can't make anyjokes about it, because it's
just so terrible. No, but
Danielle Bushen (04:05):
I will tell you the bucket list item. I got to
go to the Rose Bowl parade whileI was out there. Really nice,
fantastic. Highly recommend thisas something to go and spend
your time on if you have theopportunity.
David Turetsky (04:17):
That's really cool. Nice Rose Bowl. Who played
in that this year.
Danielle Bushen (04:21):
Oh, now you're asking me a football question.
The Rose Bowl was there? No, I'mpretty sure it was Ohio and
Oregon. Okay, well, but you areat the far limit of my American
football knowledge. Now,
David Turetsky (04:39):
it's okay.
That's okay. When you tested usever about the Canadian Football
League, we'd probably have lessknowledge. So,
Danielle Bushen (04:46):
yeah, I would also have less knowledge. No,
there's not a league thatanybody follows,
David Turetsky (04:50):
but maybe we can talk hockey a little bit.
Dwight Brown (04:52):
I have to admit that I couldn't even have
answered that question. I don'tI like watching football. I
don't pay attention to who'sdoing. And what? So I had no
idea who was in the Rose Bowl,
David Turetsky (05:03):
but if I asked you if the Toronto Maple Leafs
are doing okay this season,would you know?
Danielle Bushen (05:07):
Oh,
Dwight Brown (05:08):
I'd say, is that a basketball team?
Danielle Bushen (05:12):
If you really want to upset me, you can tell
me their an ice hockey team, asopposed to a hockey team. And
there's only one kind of hockey.
Dwight Brown (05:24):
Big differentiator in there,
David Turetsky (05:26):
one kind of hockey, although my friends who
actually play field hockey wouldbe upset with me if I said that.
So today, we have a phenomenaltopic to talk to our friend,
Danielle about, because it isone of those things that are
near and dear to the hearts ofDwight and myself, HR Data
Governance.
(05:54):
So Danielle, from your currentrole as well as your past role,
what is HR data governance? Whatdoes it actually mean?
Danielle Bushen (06:02):
It's a great question. And I think people
often think about datagovernance as a bunch of data
lineage, tracing and technologystuff, and deploy a bunch of
tools and talk to the ITdepartment and get the data
office involved and worry aboutprivacy. Yes, that is a piece of
the story. It is not the pieceof the story that I find most
(06:24):
compelling or that adds the mostvalue for me. HR data governance
is about making sure that yourdata reflects the business value
propositions of the company, thepeople that work there, the
processes that you want totransact. And it is all about
getting that story right. It'sabout digitizing the HR function
in a way that you can automateit. It's about making the
(06:46):
experience of work as seamlessas possible. And we talk about
HR data probably two ways mostof the time. One is
transactional HR data and theother is analytical HR data, and
when you're talking analytics,directionally correct is great,
probably good enough. You canhelp people understand lots of
(07:08):
good things about what's goingon in the function, and it
doesn't have to be exactlyright. But when you talk about
transactional HR data, guesswhat? It makes a huge difference
if one of your person's genderis wrong or their salary was off
by a zero, or the yourtermination date was in 2525
instead of 2025 which actuallyhappened in a colleague system
(07:29):
just recently, they found thedata error. But this is the
stuff of exactly right. This iswhat data governance is all
about. And when I talk aboutdata governance, I always say to
people that it is owned bypeople. It is owned by the HR
function itself. It's not an ITthing. It is supported by
process, and it is enabled bytechnology. And it's all those
(07:52):
three pieces coming togetherthat makes data governance so
interesting and so impactful.
David Turetsky (07:58):
I think one of the complications is it's
actually also owned by theemployee and by the manager and
by everybody else in the valuechain, that, or I mean, even
candidates have a have a hand inyour HR data governance, right?
Because they're enteringinformation into a system. Might
be your candidate, application,system, contracting, closing,
(08:19):
Yep, yeah. But, but theneverything they enter could be
right or wrong or could becomplete Baloney, and that's
getting into your analytics andyour transactions which make
them wrong.
Danielle Bushen (08:31):
So users have an obligation, duty of care, to
try and give you as complete adata set as you can they also
have rights to choose to giveyou the data or not. Yes, right?
And that's really important tounderstand as you're thinking
about what data am I collectingfor what purpose? How do I want
to use it? Have I informed theowner of that data about how I'm
(08:52):
going to use their information?
But it's also sort of a duty ofcare when we think about process
design, to encourage people togive you the data in the easiest
and most complete way possible.
Yeah, if you're collectingpostal code as a consumer, I can
put my postal code in all inlower case with no spaces, and
it's a Canadian postal code, soit's got letters and numbers in
(09:14):
it. And guess what? Amazonfigures out right away.
Absolutely did. I mean capitall6, capital L, etc, right? It
tells you that. And I think whenHR thinks about data and data
capture and data governance, weneed to bring that sort of
consumer grade experience tobear and help the user to your
point, the user who's providingthat data at the top of the
(09:36):
funnel to give you the bestquality data they can. That's
about a guided experience. Andit's about thinking through
what, what things are likely tobe problems down the road.
Dwight Brown (09:45):
You know, I think back historically, and it's
amazing how quickly thelandscape has moved with this.
The to your point about theabout Amazon being able to sense
those things, it wasn't long agothat there's. Just wasn't the
technology available to be ableto do that, yes, and so, you
know, being able to have thosestops in place that confirm the
(10:09):
information or whatnot, there'sa lot of that stuff in the data
governance arena that wasn'tthere even two years ago. I
mean, you look at where we arerelative to that, done. But it
also underscores the need forboth solid data governance as
well as changing in the waysthat that we administer it. You
(10:30):
make
Danielle Bushen (10:31):
a really good point, right? And when we, when
we think about technologydeployment in HR, very often our
budgets are sort of with a onceand done flavor, yeah, implement
it, carry on. But the reality isthat all of the major HR systems
are making releases every sixmonths, maybe more often.
(10:51):
They're continually upgrading.
They're bringing in newcomponents, adding AI that may
be helpful. May just be a datavalidation rule that's being
checked in the background, ifyou don't stay on top of those
things, then you fall behindthat consumer experience very
quickly, and that makes the HRprocess owners need to be much
more attuned to technology thanperhaps they were in the past.
(11:12):
It's not something you can justthrow a defense to it and
ignore. You really have to begreat partners as a function of,
in terms of continuallydeveloping, how is a, how is the
technology supporting theexecution of the organization?
Dwight Brown (11:29):
Yeah, so many people still like to try to toss
it over the fence to it, becauseit's just easier. Like, yeah,
you guys can program it. Youcan, you can make something to
happen, right? Yeah, exactly,exactly, your jobs are easy.
David Turetsky (11:47):
Well, there's another issue with HR data
governance. And I mean, there'sanother explanation about HR
data governance that touches onso many things across an
organization. HR data governanceisn't just HR data governance,
it's also it's ties to all theother pieces of the value
proposition of a company. Sowhether that's security, whether
(12:07):
it's finance, whether it'severything workforce planning,
all those things aren't just HR.
They're everything else. And sowhenever I deal with my
colleagues from the finance andfinance group, and they say to
me, Hey, I have an accrual thatI have to create for the bonus
program. Well, you need, can yougive us some numbers? Well, that
(12:27):
kind of takes it out of therealm of HR, and now puts it
into the realm of finance. Sonow I have to interface with
them and the things that I doand the decisions I make, I now
have to lay out all myassumptions for them, because
now my data is being used insidethe context of finance, and they
have rules for this stuff. It'sbeyond just us right now. They
have rules. So you know, HR datagovernance is also how do we
(12:51):
interface with other teams,isn't it? Or am I? Am I just
trying to make my arms a littlebit bigger and try and grab
more.
Danielle Bushen (13:03):
I don't think it's about grabbing anything.
It's I think it's aboutunderstanding that the
accountability of HR is tostructure the people data of the
company that may sit in HRtools. It may sit elsewhere.
Head count generally, doesn'tsit entirely in an HR tool.
There's a whole bunch of financecomponents to that. You're in
the middle of hiring somebodyfor a global role in a
(13:25):
multinational Guess what?
There's going to be transferpricing, pricing behind the
scenes. You want to structurethe real estate footprint for a
hybrid workforce. You need tounderstand how often are those
people on site, and that'spartly badging data and partly
security and partly contracts.
You know, who's who's on a fullyremote contract, who's supported
(13:46):
for their tax treatment of that,you're bringing in so many
departments that all need totalk to each other and learn to
speak a common language. And Ithink the opportunity for HR is
to be that translator,particularly around the people
do it. I mean, we need to lookto others to be the experts in
certain things, but we also needto bring that conversation
(14:07):
together. Last week, Ifacilitated a conversation
between our single sign on,team, our service now team, our
work day team, our Microsoft 365team and our CUPA procurement
team, sure, because we weretrying to solve exactly one of
these kinds of problems, and so,you know, there's five functions
represented around the table,and we're talking about, what
(14:27):
portion of our workforce, ournon employees, do they still
need network IDs? What's theirsingle sign on identifier? Do
they have a work day identifier?
What's our regulatory obligationto those people? HR is at the
heart of that conversation, butwe can't do it without all those
other people at the table.
David Turetsky (14:45):
Oh my God, there's such a compliance issue
there, too, with all the rulesthat California had created, or
that had been started inCalifornia, about what is an
employee and what is the if youstart putting putting them in
the HRIT. What does that mean?
Danielle Bushen (15:02):
Co-employment risk, super interesting, data,
governance topic,
David Turetsky (15:06):
exactly, important, yeah,
Dwight Brown (15:08):
yeah.
Danielle Bushen (15:09):
And these are the things that create a lot of
anxiety within an organization.
You know? This, this tribal myththat, oh my gosh, we can't touch
that. It's a regulatory problem,right? One of the things that I
focus on a lot with in thosekinds of conversations is Tell
me more, what regulation, whatexactly are we trying to comply
with in what part of the world?
(15:30):
Because if you can articulatethat, then you can figure out,
where's the room for creativeflexibility. How do you create a
seamless model? At Sanofi, we'rein the process of looking at
bringing our total workforceinto a single set of systems.
And for years, we had a beliefwithin the company that we could
not put contingent workers intowork day. Anybody who's a
(15:52):
workday user knows that'spossible. It's just about how
you think about theconfiguration of that profile.
Make sure that you've got theright kind of data for the type
of worker that you're lookingat.
David Turetsky (16:02):
I think one of the other complications is that
when you're trying to balanceall those different regulations
you're talking about, forexample, California has
regulations on pay transparency.
Illinois just created paytransparency legislation that
says you need to keep five yearsof history on how you paid, and
the decision points along theway, and the posting
(16:22):
information, so you might havean employee comes along and
says, I want to be forgotten. Sowho are you going to follow? You
going to follow California'srules. You're going to follow
the EU's GDPR. Are you going toallow them to be forgotten? And
then now, kind of break the lawin Illinois if they're an
Illinois employee. So, you know,there's so many things that you
have to comply, have to worryabout from a compliance
(16:44):
perspective,
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David Turetsky (16:58):
That's kind of lends me into our next question
of, what's the problem with HRData Governance? I mean, I guess
we're talking about it rightnow. It's complex, right?
Danielle Bushen (17:09):
It is, and people want a clear answer, and
there isn't always time. So, soyour example is a perfect one.
If you look at the deployment ofAI in HR, New York City has its
own rules for this stuff. Therange of jurisdictions that you
might be looking at, the waysthat you look at how your
(17:30):
technology and your dataretention plans and all these
other things fit into theconversation, are going to be
varied. So there's not going tobe one clear answer. And I think
it's incumbent upon HR leadersto think about thoughtful risk
management. Yes, you need togive the employee the ability to
ask to have their data removedafter they leave the company so
(17:50):
they want to be forgotten, butyou have to balance that with we
may have obligations to you as afuture retiree. We may have
components of tax treatment thatneed to be managed. And so those
those different regulations area little bit in conflict with
each other, right? Which onetakes precedence? And as long as
you can demonstrate that you'vetaken a thoughtful approach to
(18:11):
removing data that's nonessential, retaining things that
might have a specific obligationfor the company or for the
individual that they're just notthinking about, then you've got
a leg to stand on, then you'vegot a way of justifying your
approach. And most regulatorsare quite receptive to that.
They will look at us through alens of, have you done your due
diligence? Have you thoughtabout reasons for retaining that
(18:33):
data, and have you been clearwith the individual? Yes, I've
asked to have my data removed.
No, we haven't removed all ofit. Here's why that's fair and
reasonable.
David Turetsky (18:43):
I think there's also the expectation of privacy
that may not actually existanymore, given things that they
posted on LinkedIn or that theyactually applied using LinkedIn,
but they put their entireemployment profile, even from
your company, on it. And so youknow, how, I mean, how do you
balance that too? Because thedata is in the public domain.
Danielle Bushen (19:05):
And a lot of people aren't very astute or
aware about their digitalfootprint. The amount of
information that could besourced about me from the public
environment is probably akin towhat we store in your hrs, a lot
of the time, until you get tothings like, you know, we just
had a conversation about healthdata being stored in the HRIS,
(19:26):
and why would you need healthdata in your HRIS? And there's
two really interesting usecases. One is understanding
disability or ability, which isactually a health status.
There's a diagnosis attached tothat right and it is really
relevant and helpful for theright people within the HR
(19:46):
organization to be able toprovide accommodations. So
there's a real good reason tostore that data in a
constructive way. But of course,the risk is that data is going
to be misused. It's going to bemisinterpreted, it's going to
create. Bias, and so now you'reinto a conversation about who
has rights to that data for whatpurpose. How are we using it?
How is it being aggregated? Andhaving good rules in place for
(20:10):
those kinds of analytics whichare all about the story of the
whole not about the individual,is really critical to a
successful Data GovernanceProgram
Dwight Brown (20:20):
And good security protocols too on top of it to
make sure that it doesn't getout.
Danielle Bushen (20:26):
Yep. And in the land of Excel, that is a running
rear guard bottle a lot of thetime.
David Turetsky (20:35):
Wait a minute, you're talking about the most
popular database program in thehistory of business.
Danielle Bushen (20:41):
You could all just get rid of Excel. Some days
we'd be a lot happier. Iunderstand why it's used. I get
it. It's easy. Yeah, it doesbring some baggage.
David Turetsky (20:52):
It's not even just that. It's easy. It's
prolifer, proliferate-able. Imean, you don't need, I mean,
you need a license for it, buteverybody's got a license, you
know, thank you, Microsoft,right? Everybody's got a
license. And it's not hard toactually be a database
programmer. If you can put avalue into a cell and then put a
(21:12):
field header at the top of thatof that column, it's ubiquitous.
It's everywhere. It is, it is,and digital skills in it suck,
but that's that's another issuecompletely, but
Danielle Bushen (21:24):
it's not a data governance problem.
Dwight Brown (21:27):
I heard it. I heard an interesting one a
client on I was working up with,up until a short time ago, half
of their HR functions were in anExcel spreadsheet, as opposed
to, they didn't have an HRISyet, or they were just
beginning, and it was littlemicro piece that was built out.
(21:49):
So I think, I think things likethat, and the data governance
side of me just goes, Oh my God.
Danielle Bushen (21:55):
But that may be completely realistic, you know,
for a small startup, but theydon't need to invest in the
fancy HR system, and it probablyisn't a good use of their
limited dollars. It's justbecause you can apply the same
principles of governance to, youknow, a spreadsheet that has
really clear, locked down,restricted rights that you've
understood who's able to editwhich fields, all the same
(22:18):
things that you would do in asophisticated tool with role
based security. You can do it inspreadsheet.
David Turetsky (22:24):
That's a huge assumption. That's a huge
assumption, though, Danielle,that you're going to have all of
those things locked down in a ina canvas. That's kind of what
Excel is.
Danielle Bushen (22:35):
Yep. Yeah. It's true, it takes forethought. It
takes, you know, the ability torecognize, hey, this data is not
generally available. Justputting it in somebody's
personal drive is not safeenough. How do we secure this?
What passwords do we put on it?
And there are good ways to applydata governance principles, even
in a lower tech solution likeExcel. I think the bigger
(22:57):
challenge is when we start toemail files around to each
other, and, oh, here's a copy ofthis. And David, you should see
this information about, youknow, retirement rates, and then
you realize that you've sent afile that has all the source
data of everybody's ages anddates or birth on it, right? Not
ideal.
David Turetsky (23:14):
Well, I can't tell you how many times I've
seen analyzes that have beenpasted into PowerPoint, but they
paste in the Excel object sourcefile which has exactly it has
the entire source file with allthe employee names in it, with
all their pay in it. And that isan absolute data governance
nightmare. So, yeah, I mean, ithappens. And I guess the other
(23:38):
thing I want to mention,Danielle, is you were talking
about, you know, sending anemail. Remember the days when we
used to send those manilaenvelopes with the extreme
security measure of that? I lovethis, of that little rope, a
little the little string, thered string, and then you'd, you
could even put a piece of tape,very secure. You put a piece of
tape across the front so itwould
Danielle Bushen (24:01):
put a squiggly line on it to see if anybody had
opened the tape.
David Turetsky (24:04):
Opened it. Yeah.
You'd stamp confidential. Soyou'd line up, and you'd make
sure that the c o n wasabsolutely perfectly aligned
when it came back to you,
Dwight Brown (24:15):
the beginnings of cyber security right there.
David Turetsky (24:19):
Yeah, let's see how you can hack that one
Dwight, but that, that's wherewe started with sending inter
office mail that had approvalson forms for people's pay. So,
you know, we're not too muchbetter than that right now.
Danielle Bushen (24:33):
I mean, I think we are. I think they
David Turetsky (24:35):
I'm being overly
Danielle Bushen (24:37):
the the reality is that the problems of data
governance are there's theobvious ones that we've just
been talking about, the issuesof continuity of care through
evaluation. Those things areimportant. I think the harder
ones are when we use thirdparties, which most companies
do, and now you have what'scalled a data controller. Is
(25:00):
changing hands. Somebody else isresponsible for the information,
right? And what happens at theirend? Do they use a
subcontractor? Are theypromoting good governance on it?
Did they, you know, have a hackand somebody got access to all
the credit card data for yourentire company, which happened
to include social securitynumbers, but no longer in your
control. But as an employer,you're still accountable.
Dwight Brown (25:22):
You think of the the Facebook debacle a few years
ago with the analytics company.
I can't remember the name of it,but
Danielle Bushen (25:29):
Cambridge Analytica,
David Turetsky (25:30):
yeah.
Danielle Bushen (25:30):
Cambridge Analytica, exactly yes, yes. And
everything that happened there,and you see that play out
company after company aftercompany. It wasn't isolated to
Facebook, but a lot of that getsback to that, that data
governance piece of things, andwhat is the data? How are we
using the data? What are therules we're putting in place?
(25:51):
And unfortunately, a lot ofcompanies have to learn it the
hard way to really get there.
And I think the opportunity forHR is first to really have clear
ownership of your definition. Sowhat kind of data are we
collecting for what purpose?
What's our pick list? How do wechange it? And that's really
setting the rules of engagementfor the HR function itself,
(26:11):
which, if you're thoughtfulabout it, you can have enormous
impact and really enable a greatprocess for your employees. Then
it that the challenge is toteach those data owners, who own
those different processes andall the different functional
areas, how to think holisticallyabout contracts and engage their
procurement specialists andtheir legal specialists at the
(26:34):
right time for those pieces ofthe process. And they don't
always know to do that. Sothere's, there's an education
campaign around saying you don'tneed to know everything about
all of this, but you do need toknow when to ask for help. Yeah,
David Turetsky (26:49):
Hey, are you listening to this and thinking
to yourself, Man, I wish I couldtalk to David about this. Well,
you're in luck. We have aspecial offer for listeners of
the HR Data Labs podcast, a freehalf hour call with me about any
of the topics we cover on thepodcast or whatever is on your
mind. Go tosalary.com/hrdlconsulting to
(27:11):
schedule your free 30 minutecall today.
One thing that stabs me in theheart right now though, Danielle
is there's a lot here. So wheredo we start? Because this is
what you've mentioned. Cutsacross and you're not 120,000
employee company, whether you'rea 50 employee company, whether
(27:34):
you're a five employee company,whether you're a 10,000 this.
This is a big deal,
Danielle Bushen (27:41):
and the range of obligations doesn't change.
Even if you're only doing it for40 people, those obligations are
still there. So where do youstart at? You start with
ownership, and you start withthe actual concept of
governance. Who gets to make thedecisions on data fields. And if
you can get that part right,then you're having the right
business conversation. Whattechnology you put behind it is
(28:03):
truly secondary, and I'd sayit's owned by people, enabled by
process, supported bytechnology. The technology is
the tail on the dog here. So ifyou can start with having clear
ownership and make sure thatpeople understand what is their
role to play in defining thevalues, the attributes, the
reasons that you might want toupdate it. The whole classic
(28:26):
move, add, change, delete. Whogets to do those things right?
If you can get that part right,the rest will follow. And I
think sometimes in HR, you know,a COE or a functional lead will
say, Oh yeah, that's, that's thesystem teams problem. That's the
work day teams problem, or thesuccess factor teams problem, or
whatever, pick your technology.
Which isn't true. The people whoneed to really feel ownership
(28:49):
are the people who arecollecting and using that data
and understand its purposebetter than anybody else.
Dwight Brown (28:56):
Well, and organizations need to also
understand and have in placeoverall data governance
processes, because, and itdepends on the size of the
organization, what that lookslike. But where I was
previously, we were a 60,000person organization. We'd
literally had hundreds ofdifferent systems out there, and
(29:19):
in that case, you know ourstarting point to your question,
David was all right, we need tocentralize this data governance
function right in some way oranother, and then let's take
stock of the systems that wehave out there, get the right
stakeholders around the tableright now for a large
organization, that makes sensefor smaller organizations, it
may Be a little bit differentthan that, but that's the and it
(29:43):
kind of gets back to what wewere talking about at the
beginning of the conversationwith what you what you said,
Danielle, that not only is theHR system doing HR data, but you
may have finance data and otherdata systems in place. And so.
So to the extent possible, beingable to bring together
everybody, so that you've gotcohesive data governance
(30:06):
processes, whatever that lookslike in the organization, it's
just it is hard to find thatstarting place and who owns it.
So.
David Turetsky (30:15):
I think that's the one of the big issues there,
is who's the data owner. And toDanielle's point, you know, who
is the one who gets to make allthose decisions? And how do you
make that as a team? How do youhave those? I mean, do you have
committees, Danielle, where yousit down with your colleagues
from across the company and say,you know, this is yours, this is
(30:36):
mine. This is yours. This ismine. I mean.
Danielle Bushen (30:39):
We kind of do, yeah, there's those. We do have
an enterprise data office, andso there are standards of care
for how data gets stored andmanipulated and moved into
warehouses and everything else.
Those are great foundations andtools that we can leverage in
each function in each businessline. But each function and
business line has its ownaccountability and for framework
for data governance in peopleand culture, we have a data
(31:01):
Council, and you get into thosedifficult conversations around,
well, who gets to define what apromotion is? Is it comp? Who
decides grading and gradingstructures? Is it talent
management? Who says, well,lateral moves with this kind of
change in scope would be reallyhelpful to call a promotion, or
is it because the person movedfrom one division to another
that that's considered acrossme, but these are all the
(31:24):
conversations that you have toreally go through. What does
promotion actually mean? Whatdoes demotion actually mean in
our organization, right? And itmight be different than somebody
else's organization. Yeah,right. But if you can clarify
that you get to a great place,you know reasons for departure.
Is it voluntary? Is itinvoluntary? Well, what do we
mean by constructive dismissal?
(31:48):
There's legal components tothat. There's labor law
components to that. There'sactual conversations with the
person and what you want to sayto them, and what that means in
terms of whatever theirtermination paperwork where it
looks like in the countrythey're in, right? Getting all
of that put together iscritical.
David Turetsky (32:05):
Also, if they're part of a labor Labor Council or
labor union, and you know, whodo you have to go to once those
kick off, once those processeskick off, especially if you're
terminating someone,
Danielle Bushen (32:16):
yep.
Dwight Brown (32:16):
Hm.
David Turetsky (32:18):
yeah. And thus start Interesting, yeah,
exactly, start somewhere, andthen, and then go through all of
these processes. I think that'sone of the overwhelming things
about this, though, Danielle,and that's the reason why I kind
of asked the where do you start?
Is because this is reallycomplex, and it gets, it has so
many there's foundationalelements, yeah, but then there
(32:41):
are also these elements thatexist in the fringe, all over
the place, all over the world,like learning systems and reward
systems. They're just, they're10, they're not only tangential,
but sometimes they're built in,you know, commission systems,
yeah, where it's owned by sales,ops, you know, it's only owned
by HR. It's not owned bycompensation. It's sales ops.
Danielle Bushen (33:03):
All three of those examples have come to my
desk just in the last like twodays.
David Turetsky (33:10):
Sorry,
Danielle Bushen (33:12):
but those are the right conversations to be
having. Right like you want tohave a sales compensation
calculation engine thatunderstands profile based
information, based on on the jobyou were in, the function you
are assigned the territoryyou're working in the market
opportunities. You're bringingtogether sales data and product
data and HR data all in oneplace. And it's actually doesn't
(33:34):
matter who sponsored that work.
Yes, it might be owned by salesops. What role does it fill?
What data is it being populatedwith? Who has governance of that
data, but may not all be salesops and figuring out how to have
those conversations in aconstructive way together? To
say here at the guard rails, iswhat matters most. It's not, not
all we I mean, I said it's allabout ownership. It is all about
(33:55):
ownership, but it's also allabout partnership, making sure
you understand those guard railsand who owns which piece, and
it's rarely an all or nothingconversation.
David Turetsky (34:08):
I love this conversation. We can have it all
day. I think one of the problemswith a conversation like HR data
governance is that for many ofthe people who are listening,
it's something that they have todeal with, and it's in a
mountain of other priorities.
And one of the problems is, isthat if you don't deal with it
and deal with it quickly, it canbecome its own big problem later
(34:32):
on, right? I mean, there are youmentioned analytics at the
beginning, and I've gone intoanalytics projects and said,
Hey, how? What? What's the shapeof your data? And they go, Oh,
it's great. Okay, well, whyaren't using analytics today?
Well, our executives don'tbelieve the data. That doesn't
mean that it's great. It meansthat, you know, we need to do
(34:53):
some work to earn back theirtrust. And so one of the things
I always think about when we gointo. Projects like this is what
are the major issues that wehave to solve? And let's try and
start there, first solve thoseproblems and then work on the
hygiene issues afterwards.
Danielle Bushen (35:11):
I fully agree.
I am actually working on a HCMcore remediation project right
now that is focused on the supersexy topic of worker types and
subtypes and contract types,great, but it's foundational
work. It's about making surethat those definitions support
the business requirements, whichwill then allow us to do much
(35:31):
more interesting work aroundautomation of onboarding and pre
boarding and improving theemployment experience, which is
what we want to do, yeah, butthose data elements are the
prerequisites for that, and it'sabout understanding why it's
worth doing that work and whatit's going to enable and unlock
in terms of value for theorganization, and also what it's
going to prevent. Like, how muchtime do you want to spend
(35:53):
investigating data breaches likethat? Is, like, the last thing
on my list that I want to spendtime on if I can stop that from
happening? For you, exactly.
David Turetsky (36:01):
Exactly.
Dwight Brown (36:01):
Yeah.
David Turetsky (36:03):
Well, I think I know what our next topic is
going to be. Danielle,
Danielle Bushen (36:06):
which is
David Turetsky (36:07):
it's going to be those worker types.
Danielle Bushen (36:09):
oh, great topic.
Dwight Brown (36:12):
I can imagine the number of downloads.
David Turetsky (36:16):
It'll be in the millions. Dwight, it'll be
millions,
Dwight Brown (36:18):
exactly.
David Turetsky (36:28):
Well, no, I'm serious when I say this, that
that it is such a pleasuretalking to you, because, you
know, we could geek out withyou, you know, pretty much all
day on this, but it's just sowonderful to speak to someone
who speaks our language andthinks the way we do. So thank
you very much for being onDanielle,
Danielle Bushen (36:45):
thank you for having me.
Dwight Brown (36:46):
Great having you here,
David Turetsky (36:47):
and thank you, Dwight
Dwight Brown (36:48):
thank you. Thanks for being with us like David
said, we could, we could geekout on this stuff for ages. I'm
not sure what that says aboutus, but that's all right. I'm
okay with that.
David Turetsky (36:58):
I think that's the reason why people listen to
us now, Dwight, is that we getto have conversations with
brilliant people like Danielle,
Dwight Brown (37:04):
Exactly it. Yeah,
Danielle Bushen (37:05):
I'm into my third decade of doing some
version of this kind of work,and it's still interesting, and
I'm still learning new thingsall the time.
David Turetsky (37:11):
Yeah, we're with you well, and thank you all for
listening. If you're stilllistening to this after this, we
love you. You are our people,take care and stay safe.
Announcer (37:24):
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