Women at Work - Ground Your DEI Efforts in Data
Episode Date: August 12, 2024How do you know how diverse your company’s workforce is, how equitable its processes are, and how included people feel if nobody is using any metrics? DEI strategist Lily Zheng explains the power of... data to track a company’s progress, fix unfairness, and hold people to their promises. They have advice for measuring and improving diversity, equity, and inclusion even when you don’t have a budget or you’re starting from scratch.
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You're listening to Women at Work from Harvard Business Review. I'm Amy Bernstein.
I have a couple of questions for you. How are your company's DEI efforts going?
How do you know? What data does your company collect and track that shapes those efforts? To strategist Lily Zhang, data-driven efforts are everything. The way people make
lasting progress on diversity, equity, and inclusion is to measure outcomes. And I couldn't
agree more. During this year's Women at Work live event, Lily explained the opportunities
that data, when used ethically, of course, can create for DEI. Lily will give us examples from
their consulting with different companies, like the one that found out where exactly its recruiting
efforts, which started out fair, took a turn, and how the company fixed the problem.
Lily also has advice for making a difference even when the company is tiny,
even when you're starting from scratch, even when there's no budget.
Lily is someone who always makes me and Amy G think and laugh, and we're delighted to share this conversation with you.
Hey, Lily. Hi, Lily. Hey, folks. Great to see y'all.
So we're going to get to data in a sec, but first I want to hear about the decisions you've observed
business leaders making in response to the backlash against DEI. Can you take us through
one of them? Yeah, yeah. So, you know, just to provide some context for the folks listening in, we are currently
experiencing a backlash against diversity, equity, and inclusion work where perhaps folks
are being misled by misinformation or are otherwise, you know, not as enthusiastic about
it as they have been, perhaps compared to five years
ago. And in response to it, I think we're starting to see companies diverge pretty substantially when
it comes to their approaches to DEI, in the sense that whereas in 2020, or 2021, you saw a very consistent approach to DEI. Many companies started employee resource groups, organized voluntary DEI committees and councils, made commitments, made donations, published a whole bunch of DEI positive articles on their websites. to see that diverge, where some companies are continuing to stay the course or double down even
and say, no, this is actually what we care about. This is our brand. These are our values. We're not
going to stop whether or not it's popular. And we're seeing other companies start to withdraw
that support and say, okay, now that it's not popular, we're going to cut our DEI staff. We're going to withdraw our DEI funding.
We're going to quietly be less vocal about our support or call it something else or quietly put it into another department or otherwise take actions to deprioritize DEI, both in language and in commitment.
And so I think that that divergence is the big thing that we're seeing
right now. Yeah. And are you seeing companies having to dial back because of this or choosing
to dial back? Give us an example of a conversation you've had with a leader, with a group of leaders
about this backlash and how they're navigating it. Absolutely. So I think what's consistent across
most companies that I've worked with, and most leaders that I've spoken with in the last year
or so, is that everyone is anxious. Now, what people do in response to that anxiety is very
different. Some folks say, I'm anxious, but I have a lot of confidence that we're doing things
that are having an impact. And so I'm going to push through that anxiety. We're going to keep
doing what matters because I know that this is effective work. Other leaders, on the other hand,
are perhaps leaning in, I would say a little too far into that anxiety and saying, you know what,
suddenly this feels risky. Suddenly even something like starting an employee resource group feels risky. Suddenly, even saying the word diversity or inclusion or equity feels risky.
And so maybe we just don't do that. So I've talked to a couple leaders who said, what if
we just call it other things? What if we find other terminology so that no one sees that we're
talking about DEI? Or what if we just say inclusion and
drop the diversity and drop the equity? Or what if we just not only don't talk about it, but we just
stop doing it? I'm sure no one will notice. And now we're in this twilight zone of backlash,
where not only do all of those problems that I just talked about exist, now some leaders are being swayed by folks who think that there is concrete proof that DEI is causing harm.
And I'm like, where is that?
There's not concrete proof of anything you're doing, let alone harm, right?
So I think we're so far behind.
We're so far behind that I don't even know how they can conclude that, you know, the AI is somehow making things worse. Yeah. Maybe perhaps you collect some data. And then we can see if it's
actually causing harm, because I think it's just essentially going nowhere with a lot of companies,
right? And this backlash, I could be. Okay, do it. Wild hot tape. I love a Lily hot take. Oh yeah, I'm full of them. A hot take could be that
part of this backlash could be maybe a distraction from the possibility of collecting data. And so
people are so scared of the possibility that they could be held accountable, that they're buying
into this narrative that suddenly everything is too risky, right? Suddenly DEI is evil,
suddenly DEI is bad. And so that's why we're just never going to collect data ever. And we're going
to move on and hope this all goes away. I do want to know, do you work with any companies
that are based in a state where government has banned DEI initiatives or offices? And if so,
how are you advising them to keep up the work? You mentioned
some of the things that people are considering, let's drop the diversity and equity, let's stop
altogether, let's call it something else. How are you advising them to keep going, despite the sort
of I would call hostile environment? Yeah, yeah. So I am currently working with a few companies
that are based in states where DEI is risky,
maybe where there's been proposed legislation to ban it, which I believe hasn't passed yet
for the companies that I'm working with.
But I'm definitely working with several global companies that are operating in these states.
And those companies have to be careful, right?
Because of course, they're not going to change their entire global policy to align with the
laws of one state, but they are tiptoeing, I'd say, right?
They're walking on eggshells.
For those companies, a lot of them are saying things like, well, maybe we should just stop
doing it.
And to them, I say, look, what matters beyond all else is that you're actually achieving
the outcomes that you say you
are. And so what I care about is, are you achieving diversity? Are you achieving an
inclusive workplace? Are you achieving workplace equity for everyone involved? And if you have to,
if for some reason someone's made it illegal to say the word equity. That's rough. What can we do to work with
that and to make sure that we're still achieving those outcomes? Because those outcomes matter more
than anything else. I've been working with some of those companies on, you know, for example,
I gave someone the exercise the other day to design a workplace equity initiative around pay
without ever using the word equity. It's not actually that
difficult, right? So let me come up with one off the top of my head. We are taking efforts to correct
disparities in pay by gender to ensure that the processes we're using to pay people are fair
for everyone. Done. Right. I didn't even say the word equity. I didn't say diversity. I didn't
say inclusion. But if you actually follow through on that, you should be achieving something like
greater equity at scale. Yeah.
What does the future hold for business? Can someone please invent a crystal ball?
Until then, over 40,000 businesses have future-proofed their business with NetSuite
by Oracle, the number one cloud ERP, bringing accounting, financial management, inventory,
and HR into one platform. With real-time insights and forecasting, you're able to peer into the
future and seize new opportunities. Download the CFO's Guide to AI and Machine Learning for free at netsuite.com
slash women at work. That's netsuite.com slash women at work.
Hey listeners, if you want to hear from more leaders to help you answer questions like,
should I talk about my anxiety at work?
Or how do I claim my leadership power?
Then you should listen to TED Business, hosted by Columbia Business School professor
Madhupe Akinnola.
The show features TED Talks about everything from setting smart goals to the latest on
DEI in business, followed up with a mini lesson from Madhupe
on how to apply these lessons in your own life.
Listen to TED Business wherever you get your podcasts.
So I have a question for you, Lily.
If you notice that your company is pulling back on its DEI efforts, or whatever
it's calling those efforts, and you believe the work was making a measurable difference,
there's data. What can you do? Have you seen employees actually reverse that pullback,
or at least in some way, affect a change in that policy?
So your if is very interesting, because the number of companies I've seen that have extremely
good measurement and are pulling back on their DEI efforts is very low.
I'm trying to think of one right now.
Usually what companies are doing is they're doing a lot of movement around DEI.
They're doing a lot of actions, a lot of initiatives, but very little impact tracking.
And they're proposing reducing some of those initiatives.
And so we're, you know, as practitioners and proponents of DEI in the tricky position of
saying, well, simultaneously, I don't think you should be doing initiatives just for the sake of
doing initiatives, but also you shouldn't be taking them away just for the sake of taking them away.
So to those organizations, I would say, why are you removing these? Give me a good reason. And
we can use this also to say, why are you doing them? Why do they exist in the first place? And some of the
folks who I talked to behind closed doors will say things like, honestly, Lily, we have no idea why
we're doing these. We're only doing these things because some people asked for them in 2020. And we
don't, we don't really know. And now people are asking us to take them away. So I guess we'll
take them away. And I'm like, wow, that is,
thank you for being so honest. But also that is the least rigorous thing I've ever heard.
This isn't how we run workplaces, right? It's like, oh, you know, why did you,
why did you hire this person? I don't know, because someone told me that they wanted it,
right? Like, no way. No way. Like we, we run organizations because there is a need, because we're trying to do something to create some sort of impact. That should be why we organize any initiative,
any intervention. And if we want to take one away, it's because it's not having the desired
impact that we want it to have. So frankly, I don't mind if some companies get rid of some DEI
initiatives that are not working, that they have data to show aren't working. If they don't mind if some companies get rid of some DEI initiatives that are not working,
that they have data to show aren't working.
If they don't have data in the first place, I think that's the problem, right?
Like you need to be able to show the value, the impact of every DEI thing you're trying
to do.
And then if something is working right in the scenario that you said, then there better
be a really good reason why you're getting rid of something
that's working. Are you going to replace it with something that's going to work better?
Or are you just being pressured by external sources? If it's the latter, then I don't know
what to tell them, right? Like, you're, you're ignoring the data to cave to political pressure.
So maybe don't do that, right? Like, then that becomes something a consultant can't fix. And I'm just like, well, I sure hope you're ready for folks to be very mad at you for a long period of time.
That's right. Yeah. That that situation is pretty rare for all the reasons I named Bethany. She asks, having data requires
self-disclosure, how do you get more people to opt into self-disclosure efforts?
Hmm. I think it's because people view data as, what is it? People are scared that data will
force them to be uncomfortable. And I think that's accurate, right? Like in the same way where if you never take a COVID test,
you never have COVID, right?
In the way that if you never do an audit
of your cybersecurity,
you never have any cybersecurity issues, right?
Like I didn't coin this, but I say it a lot.
It's FOFO, fear of finding out, right?
People are scared.
They're scared of learning something
that they might know intuitively, but can deny.
And then when they see the data,
then they're like, oh man, I can't deny this anymore, right?
So I think what I tell people is that fear is very normal.
It's very human, right?
But we can view the possibility of having data,
having transparency as an opportunity to grow and as an opportunity to improve. Progress is quite literally impossible unless you're able to measure your present state. you know 20 dei initiatives i actually tell them you are honestly wasting your time with these 20
initiatives unless you can show what it is they're trying to achieve right like the potential of
these 20 initiatives only comes about if you're actually measuring how impactful they are
otherwise they're just there because they're popular or they're just there because someone
wanted them to be there but wouldn't it be cool if you had your 20 initiatives and you could say these 10 initiatives
are increasing the belonging of these marginalized groups by 25% year over year?
Like that'd be incredible. Do you know how many folks you could brag to if you could say that?
Do you know how incredible that would be if you could use that data to attract candidates but instead
all you're saying is we have an erg right and all of your competitors are like well we also have an
erg wouldn't it be cool if you could say our erg is different than our competitors because ours
actually meaningfully increases people's chances of career progression can our competitors say that
i don't think so they're not collecting right? Like data gives you that opportunity. Yeah. You wrote in an article for us about how
imagine if we ran other business initiatives with metrics like we participated in a sales webinar,
right? Like, no, you measure sales by dollars. Why would we not measure DEI initiatives with
the same rigor? Right. And that article, you go through sort of we not measure DEI initiatives with the same rigor?
Right.
And that article, you go through sort of different areas of DEI and talk specifically about the outcomes that you could measure, which I think is so helpful. And I think our audience
will find that.
Yeah, I actually, I want to pull the camera back and sort of, you know, you just spoke about
the persuasive power of data. What are the other reasons that you advise your clients to ground
their DEI efforts in data? Accountability. That's perhaps the most powerful one,
being that every leader wants to feel like when they make a commitment that they can be celebrated
for it, right? Like leaders want to feel good. Everyone wants to feel good. You can't feel good unless you can feel
like your promises are being kept
and that you are delivering on what you have told people
you're going to deliver on.
And so sure, leaders can make a promise like,
in 2025, I will commit to racial equity.
So I guess sometime in 2025, you could say like,
hey, everyone, I committed to it., you could say like, Hey, everyone,
I committed to it. And then people can say, yay, that's great. Wonderful. But if you said in 2025,
right, we are going to meaningfully close the racial pay gap or the racial gap in promotion
rate, or the racial gap in access to opportunity, we're going to commit to closing that by 50%. And then by the end of 2025, you can
say, okay, we gathered the data. Turns out we closed it by 20%, which isn't exactly what we
promised. So I didn't quite meet that promise, but we're at 20. Next year, we're going to make
sure to keep on closing it. There's a very different kind of feeling around that, right?
Where even if you don't quite meet your goal,
the feeling in the workplace isn't, well, there's another empty promise that I can completely
ignore. It's, wow, I actually think we're doing something. Well, I actually think that this leader
that made a commitment isn't just, you know, spewing hot air there. They're doing something.
I'm working in a company that's doing something. Most companies don't do
that. And that creates an incredible sense of loyalty, of commitment, of engagement,
of satisfaction. It's running a good organization, right? It's running a healthy organization. You
do what you say you do. Collecting data gives you that potential to be truly accountable.
Yeah. I mean, Lily, in that
response, there's so many reasons to have data, right? Accountability, retention, persuasion,
I mean, bragging rights, and I think actually even buy-in. There's an article we published
called Data-Driven Diversity written by Joan Williams and Jamie Dulkis, who are both at
California College of Law. And they talk about how sharing the data
helps get buy-in from people inside the organization. So if you want to sort of
decrease some of the internal backlash, share the data and be honest about it. I'm thinking
about an organization I did some work with. They were measuring the pay gap. And unfortunately,
their annual measurement showed that the pay gap for gender got greater, not smaller. And so they, you know, had a big question of how do we spin this to the
organization? And it's like, no, there's no spin. You're disappointed, you know, and just be honest
about it, right? Well, in fact, I wonder if you can give us an example of an organization that
did the measurement and then, you know, in disappointment, went back and
redesigned processes. If you can talk us through how that worked. Yeah. Yeah. Yeah. I, I have
worked with some good organizations as it turns out. Yeah. So, so I worked with one that was a
couple of years back. They found that their that their hiring processes had a lot of folks falling through.
So they actually did a really good job recruiting.
They had close to equitable gender representation in their initial stage of recruiting and decent,
I won't say perfect, racial representation in their initial recruiting.
But we actually got data showing that the further
along they got in the hiring process, right, the phone screen, the interview, second interview,
they started to see women and people of color falling off very rapidly. And there was a big
disparity there. And so they found that data, decided that it wasn't enough data, and actually
did a whole bunch of
interviews with their hiring managers, and with their recruiters and their interviewers,
and found that there there were some not necessarily individual biases, but sort of
procedural biases in the process, where, for example, they lacked hiring rubrics for their second stage interviews. And so they had developed this sort of informal process where they essentially said, okay, well, it's not really in a rubric, but if the candidate is very confident about this specific thing, then that's a good sign that we're going to move them forward. And it turns out confidence for that specific thing was very racialized and
very gendered. And they ended up having a lot of their women candidates and their people of color
candidates fall through that gap. And they didn't even know it because they weren't tracking and
they didn't have a rubric. And so one of the ways they fixed it, obviously, right, they created a
rubric, but they also implemented hiring panels. They learned about ways in which folks were falling through the gaps and said, how can
we correct for this?
They went through the resume screening and said, okay, actually, what are the criteria
that are required for success in this role?
And how can we pass through folks who meet these criteria?
There's also a problem where I think they were doing the thing where they had a lot
of applications. And so someone somewhere was like, you know what we should do? We're having a
lot of difficulty parsing these. Let's just make it so everyone with an Ivy League background just
immediately goes through and we toss out the other ones. That's a very explicit bias, right?
And that's a bias that dramatically impacts the demographics of who makes it through.
So all of these little fixes, right, like apply all of these at once. And then we started to see
a year or two later that it wasn't entirely fixed, right? But they were actually improving
the pass through rate of these marginalized candidates. So I still need to check back in
with them. I don't think they have fully fixed it by the time I stopped working. But that is an
example of them identifying these challenges and doing something
to address it and seeing some movement on that front. Right. Love it. Thinking about the reason
to collect data, there's a great comment from Shahida Foster, who says, one thing that cooks
my grits is the need, which is such a good use of that term, is the need for us to show the data to justify the need for DEI.
I think it's wild.
We have to commodify DEI and show how it's profitable to do something about structural and systemic oppression and exclusion, not because it's the right thing to do.
Meanwhile, companies have mottos and corporate values based on the right thing to do.
Any reactions to that comment?
Yeah, I think it's
complex. So I agree, right? We shouldn't need to rationalize DEI and we shouldn't need data for
companies to feel like it's the right thing to do. I think I see it less as finding data to show that
DEI is profitable, which a lot of it exists. And frankly, I don't like it. It turns out the so
called business case for diversity, right, this idea that hiring more people of color and more
women is good for the business, actually has some pretty substantial backlash effects associated
with it, where the more you say it, the more you actually turn away marginalized candidates,
because they feel like they're going to be commodified within the organization. So even this comment itself, I think reflects exactly what this data found,
which is that like, you know, we, we shouldn't be using data to show that, I don't know, if you
hire one more Asian person, or if you hire one more black person, you'll make 20 more bucks this
year. That's extremely dehumanizing and a terrible use of data. What I'm hoping we can get towards
is less in justifying the need for DEI through data, but in recontextualizing DEI as whether
or not it's the right thing to do, right? It is something that organizations need to do full stop
and the data helps them hold themselves accountable to doing it.
And so I don't usually use data to try to prove some sort of why. I use data to demonstrate the
how and the what, right? So I assume that leaders have their own reasons for doing DEI, but I say,
look, I couldn't care less whether you're doing DEI because you think it's the right thing to do
or because it's going to make you more money. I'm here to make sure that
if you promise to do it, you're going to do it and it's going to work. Right? Like that is,
I think, what we should be using data for. Yeah, that makes sense. So let's dig into that a little
bit, Lily. Molly in our audience asks, what type of data do you track to show whether DEI efforts are working?
And then she asks, what if your company is smaller and the N of any sort of diversity is very small?
What are your thoughts?
Oh, that's so interesting.
Okay.
Well, two different questions.
And I guess my answer will differ slightly for each question.
So first, how do you track the effectiveness of DEI interventions? A-B testing
is a really great way to do it. You can also do longitudinal measurement. It's a little less
precise compared to the A-B testing, but you can measure how the outcomes that you're interested in
are changing over time for a target population after you're applying these DEI initiatives.
You can also do things like pre and post testing. So for things like DEI training, which I think is people's go to intervention, and perhaps it's not
always as successful as we want it to be, we can, on a very basic level, pre test people on their,
let's say usage of particular skills on their awareness of certain concepts on certain behaviors,
and then test them on the on the exact same things on certain behaviors, and then test them on the
exact same things after the training, and then several weeks or months after the training as well
to see what's changed over time. We can also collect great qualitative data from things like
employee engagement surveys, or employee surveys in general, around the effectiveness of different
DEI initiatives. So that also gives you really useful data.
Of course, it's not quantitative data.
It's not the same, but qualitative data is just as valuable.
It gives you different insights.
So a whole bunch of ways we can do that.
The second question is, how do you do DEI work that's impactful when you have small n within a small organization?
You just widen the aperture of the group that you're looking for.
So instead of looking at, for example,
gender and race, intersectionally, maybe you don't have enough people to do that, right? Maybe your
entire company is seven people. And so rather than saying, Oh, what's the belonging of your
men of color versus white men versus women of color versus white women, there might only be
like one person in each category. So you can't do that, you can say, okay, how can we increase belonging for the entire organization of seven people?
Right. And last year, we found that only two out of seven people felt belonging above 50%. And so
we want to get that higher to four out of seven people. demographics get a little tricky when you
have small n, right? That's a whole nother question, but you can at least make some pretty substantial progress
if you just look at the entire group.
Yeah, and I love that you don't have to be an n of seven.
You can be an n of 70,000 to think about
how do we increase the belonging of everyone?
I like that focus you take of these efforts
are not targeted just for marginalized groups.
They are also beneficial to the whole
organization. You should be measuring that. What does the future hold for business?
Can someone please invent a crystal ball? Until then, over 40,000 businesses have future-proofed
their business with NetSuite by Oracle, the number one cloud ERP, bringing accounting, financial management, inventory, and HR into one
platform. With real-time insights and forecasting, you're able to peer into the future and seize new
opportunities. Download the CFO's Guide to AI and Machine Learning for free at netsuite.com
slash women at work. That's netsuite.com slash women at work. That's netsuite.com slash
women at work. You've also written for us about how demographic representation isn't the only
important outcome to measure. We've been talking about this, but people can measure employee
career progression, for example, or social impact or conflict resolution, something dear to my heart or environmental impact,
you know, within all of those options, have you found there to be outcomes that are better to
prioritize before others? Hmm. Better to prioritize. Or more impactful. If I'm thinking about, okay. Um, pay, pay is, pay is a huge one,
right? Like everyone wants to be paid fairly. I think that that's a good place to start.
I think pay in some ways is even more important than satisfaction because I would much rather
someone were paid fairly and dissatisfied than very satisfied and being paid horribly.
Let's see what else.
Enablement.
So people feeling like they can do their job.
They're given the resources to actually do their job.
Respect.
Inclusion.
These are similar things.
So feeling respected and valued by members of their team.
I think that's a very important outcome.
It's a good predictor of other ones.
And psychological safety.
That's also really high up there.
So people's feeling of comfort in taking risks, in making mistakes, and doing so without feeling like they'll be punished by the folks around them.
I can imagine how that one cascades to so many other outcomes you would measure.
Do you want to go to another question? Yeah, I want to ask Inaga's question because it's a good one for this conversation because
she's starting from scratch. She says, I'm a DEIA associate at a nonprofit where my supervisor and I
are building our DEI foundations from scratch as a new department that was created due to a
significant need for equity and anti-racism at our organization. What if you don't have much data to go off of? Where do you start?
Okay. So if you are starting off from nothing, it's honestly a really exciting place to be
because you have enormous opportunity to shape how things develop. I'd say, first, you need to learn how your
organization is functioning to begin with. So if your culture is good, what makes it good? What
processes are good? What aspects of your culture are powerful? What is helping people feel good
within your organization? And then how can you operationalize those? How can you create norms, processes, sometimes policies, requirements, expectations to ensure
that the things that are working really well continue to work well?
This is something that I talk to a lot of startups about.
You know, the thing where a lot of startups say, well, we don't need any formal structure
because everything's working really well already and everyone's great and we're all buddy,
buddy.
And suddenly they add another 50 people to their team
and then it's a dumpster fire
because they never took the time to operationalize
what made their culture good to begin with
until it stopped existing.
So I think you can do the same thing.
Understand how your organization is functioning well
and put in processes to sustain that
and maintain that over time.
Then also try to understand where your organization is not working well.
So this comment mentioned a very strong need for equity.
What is that need?
Why did that happen?
Who's falling through the gaps?
What are the disparate experiences?
These are all things that you can do.
Data helps.
Data helps enormously.
But even if you can't collect quantitative data, I would argue already that you have
data.
If you said there's a strong need for equity, you're telling me that you have collected
some data, maybe qualitative data, maybe comments, maybe feedback.
You're already using it, right?
Qualitative data is just as valuable as quant data.
And if you take actions based on that feedback, I would argue
you're already using a basic, you know, data driven DEI approach. Yeah. One of the things
about collecting data is that it's most helpful if you have consistent data for a long period of
time, right? So you can say we've improved this. But I think about that question. And because
they're starting from scratch, they might collect certain data the first year, but then reconsider what they collect second year, third year. Do you recommend that,
that people are constantly rethinking what data they collect? Or do you hope for that consistency
over a long period of time? I think eventually, I want orgs to get to that consistency, right?
Like every big organization needs to have that, like it's a requirement. I think if you're a very
small organization, I'm not going to say that every startup of like 10, 15 people needs to have that, like it's a requirement. I think if you're a very small organization, I'm not going to say that every startup of like 10, 15 people needs to have a longitudinal,
you know, employee engagement survey of 100 items every year, right? Like that's not something that
you can do every year. And it's not the right environment for it. But I do think that so long
as you're being intentional with how you use that data, and I mentioned qualitative, so long as you're being intentional with how you use that data, and I mentioned qualitative, so long as you're consistently collecting a lot of qualitative data, I think that's good enough,
right? So maybe in lieu of that quantitative yearly survey, you instead have an open feedback
form that you collect comments for. And every quarter, or maybe every month, you review all the comments
you get, announce it during your team meetings, and make changes based on those recommendations.
I would say that that's essentially longitudinal data-driven DEI work, right? Even if it's all
qualitative. And so the consistency is the most important, regardless of what the actual form of the data is.
Yeah. So, you know, you've talked about the importance of DEI as an accountability tool.
I wonder if you can share one specific example that our audience can learn from a company that is using it and using it well. Hmm. So I had a company that I worked with last year
where they used their employee engagement survey
to understand it was belonging
they were really looking into within the organization
because they had gotten a lot of reports the year previous
that lots of folks did not feel a strong sense of belonging
within the organization,
specifically disabled folks, women, and LGBTQ plus people, I believe. So this organization used data
to find out that the belonging gaps were because their managers had extreme variation in their
ability to provide support for their direct reports. And so they found that some
departments and some managers were really good for pretty much everyone. And some departments
and some managers were really bad for specifically women, disabled folks, and LGBTQ plus folks.
And so what they did is they use that data to focus on improving those experiences, but
because they were able to isolate
it to managerial support within a few departments, they were able to focus on those departments.
Imagine if you didn't have the granularity of that data and just saw we have low belonging for
LGBTQ plus people in our company. Let's bring in a pride month speaker. A pride month speaker
is not going to fix a department whose managers are all homophobic, right? Like, so you see how
unless you understand the challenge, your solution, right, your one size fits all solution may not
actually solve the problem. And so this organization was able to use that data to uncover
that root cause, or at least, you know, some root causes. I'm sure there were other problems as well that weren't captured by data. And we're able to design a solution. In this case, it was targeted manager training, and specifically more guidance for the department manager, the department head of that department to address their problem. So is that sort of what you're looking for?
Yeah, exactly.
Examples of how to use data in this way.
Yeah. And also how to hold people accountable, right? Like that's, I think that in terms of
what needs to change, right? It's accountability and investigating the root causes.
But also the follow through I find so interesting, you know, just understanding
the nature of the problem before you leap to a solution.
Yes.
Yeah.
Right.
And data help there.
There's a comment that I want to briefly make because earlier on you talked about kind of building buy-in and using data to build buy-in.
Right.
And I think this example that I shared is a good example of that because a lot of leaders that I talk to say, you know, DEI isn't my problem.
Right. It's the HR leader's problem or it's the DEI person's problem. And what you can do is you can actually say, well,
let's see, because you're responsible. So you're right, you're not responsible for the entire
organization, but you lead a department. So when you can show me that your department's DEI outcomes
are peachy, doing great, then you can tell me that you've got it handled.
But if they're not looking good, then that is your problem.
That is your responsibility.
So let's see.
And I think giving people that data, not just everyone's data, but the data that pertains to the area of the organization that they manage is one of the most powerful ways I've found to build by it. Because
now suddenly it's personal. No one wants to be leading a poor performing department.
Right. And your point that a Pride Month speaker is not going to fix that department, right? Like
it's such a vivid example of why it's important to get to the granular level and understand the
root cause. I'm hoping for a really hot take here because
one of the other questions I have is, what's a popular practice that you see lots of companies
using for DEI reasons that you've come to learn either through research or personal experience
just is not effective and you wish everyone would stop? Okay, well, these aren't hot takes. These are research driven insight.
Okay, so there's there's a few. One of them is quite old. In fact, there was a really interesting
research on diversity statements, essentially showing that when you make a very public diversity statement, as part of your
hiring process that actually results in substantially fewer members of marginalized groups
hired, which is very unintuitive and very strange. The reason being that having diversity statements
around like, oh, you know, we don't discriminate, this is a fair process, like we encourage diversity,
actually encourages your
candidates to hide less of themselves when they interview so they spend less time whitening their
names they spend more time being authentic which sounds really good yeah except that then opens
them up to more hiring discrimination during the hiring process themselves which results in fewer
of them being hired.
Right. Talk about unintended consequences, right? Exactly. So the idea being that you cannot bootstrap an inherently racist or sexist hiring
process just by having one comment saying, we love diversity. You actually have to fix your
hiring process. Another practice is de-identification of demographic characteristics, which I myself
was calling a best practice back in 2015. Explain what that is, Lily. Yeah, yeah. So you know how
resumes have people's names on them or their affiliations, and oftentimes those names are
gendered and racialized. And so you can infer people's name or their race or some other information about them just review the facts, right? So by taking
out this information, we're going to interrupt bias and that's going to fix everything. It turns
out it doesn't, it doesn't fix everything. In fact, sometimes it makes things worse because
what happens is that people from different groups have different experiences in society.
They experience discrimination, they experience marginalization. As a result, that has a substantial impact on the sorts of
career trajectories, the career opportunities, their educational opportunities, and so on and
so forth. When you remove the context of their demographics, it makes those disparities stand
out even more such that hiring managers will just say, oh, got it. Well, the only
thing I have is candidate A has more experience here and candidate B has less experience here.
So I'm just going to hire candidate A and it results in a dramatic, sometimes in a dramatic
drop of diversity and talent. And so the idea here being, we need to, instead of teaching people to literally not see race
or not see gender, we need to teach people to be more intentional and more mindful to
contextualize people's demographics within their career experiences.
Yeah, I love that.
Let me ask you one last question from our audience.
Here it is.
How can we find the resources to do more with DEI?
The HR training and evaluation efforts take resources we do not currently have. about what you achieve. And if this very expensive training doesn't help you achieve some sort of
change or help you achieve some sort of outcome, don't do it. Power to you, like literally do
anything else. Something I've said to folks before, is that I would much rather you take the
money you would spend on an expensive speaker that might not do anything for you long term and spend
it on pizza parties every month. Literally, if pizza parties every month would have a better positive impact on your team than a speaker, do that, right? And I
think I would apply the same philosophy here. Look at the amount of resources that you have to spend
and ask yourself, what is the greatest possible impact, lasting impact we can make with these
resources on the DEI outcomes that we care about? Go ahead and do that. There's so many creative things you can do.
There are programs you can invest in.
There are community events you can sponsor.
You could just take all that money
and just pay people a little bit more in the organization.
Maybe that'll translate to better outcomes, right?
But be creative about it, right?
Because the goal is to shift those outcomes,
not just to give the illusion of doing a whole bunch. Thank you, Lily. Thanks so much for joining us today. This has been
fantastic as always. Thank you for having me. Lily's latest book is DEI Deconstructed,
Your No-Nonsense Guide to doing the work and doing it right.
The accompanying workbook is called Reconstructing DEI.
If you have ideas for policies that might move DEI forward where you work, but you're not sure where to start, check out our 2022 episode, How to Push for Policy Changes at your company. In that one, Amy G and I talk with Lily and a union leader about how to build a coalition around a cause, manage the risks involved in pushing for change,
and ultimately how to get buy-in. Women at Work's editorial and production team is
Amanda Kersey, Maureen Hoke, Tina Tobey-Mack, Rob Eckhart, Erica Truxler, Ian Fox, and Hannah Bates.
We're taking the summer to put together a solid season 10 for you.
If there's a particular topic you'd like us to cover, email us at womenatworkathbr.org.
I'm Amy Bernstein. Thanks for listening and take care.