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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? 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 the 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 effort, 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 an Amy G.
think and laugh, and we're delighted to share this conversation with you.
Hey Lily. Hey folks, great to see you 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 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 website.
Now we're starting 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.
So I think that divergence is the big thing that we're seeing right now.
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 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 employer 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?
Or if we find other terminologies 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.
A little alarm. Right? So I think we're so far behind.
Right. We're so far behind that I don't even know how they can conclude that DEI 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.
And this backlash, I could be okay.
Do it. I love a lily hot tape.
Oh yeah, I'm full of them.
A hot tape 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.
Yeah. 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.
Just 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 a 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, we'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, 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 inclusions.
But if you actually follow through on that, you should be achieving something like greater equity at scale.
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So I have a question for you, Lily.
If you notice that your company is pulling back on its DEI effort 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 survive. 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.
They're proposing reducing some of those initiatives.
So we're 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, really, we have no idea why we're doing these.
We're only doing these things because some people ask for them in 2020 and 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.
It's like, oh, why did you hire this person?
I don't know. Because someone told me that they wanted it.
No way. No way. 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 have data in the first place, I think that's the problem.
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 in the scenario that you said, then they're 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.
You're ignoring the data to cave to political pressure.
So maybe you don't do that.
And then that becomes something that consultants can't fix.
And I'm just like, well, I sure hope you're ready for folks to be very managing for a long period of time.
That's right. But that situation is pretty rare for all the reasons I named.
Like the lack of measurement is often the major problem there.
Yeah. We have a question from a participant named Bethany.
She has having data requires self-disclosure.
How do you get more people to opt into self-disclosure efforts?
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.
In the same way, if you never take a COVID test, you never have COVID.
In the way that if you never do an audit of your cybersecurity, you never have any cyber security issues.
I didn't coin this, but I say it a lot.
It's a faux-faux fear of finding out.
People are scared. They're scared of learning something that they might know intuitively but can deny.
And then when they see the data, they're like, oh, man, I can't deny this anymore.
So I think what I tell people is that fear is very normal.
It's very human. 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.
And so for those organizations that are doing 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, 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 saying, 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 data.
Right. And then, what do you think about the ERG?
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Collecting data gives you that potential to be truly accountable.
Yeah. I mean, 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 Dolcus, who are both at California College of Law.
And they talk about how sharing the data helps get buy-in 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 had a big question of how do we spin this to the organization?
Oh my gosh. And it's like, no, there's no spin.
You're disappointed. 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 about how that works.
Yeah, yeah, yeah. I have worked with some good organizations as it turns out.
So I worked with one that was a couple years back.
They found 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 and 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 interviews, 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 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 an rubric, but if the candidate is very confident about this specific thing, then that's a good sign that we're going to move on 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 their 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 wow 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 past 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 stop working, but that is an example of them identifying these challenges and doing something to address it and seeing some movement on that front.
All right, love it. But thinking about the reason to collect data, there's a great comment from Shaheeda Foster, who says one thing that cooks migrates is the need, which is such a good use of a betterm, 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 models 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.
So it'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?
So I think that organizations need to do full stop and the data help 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 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.
And 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 end 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 the I 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 target population after you're applying these DEI initiatives.
And also do things like pre and post testing.
So for things like the I training, which I think is is people's go to intervention and perhaps is not always as successful as we want it to be.
We can on a very basic level.
We test people on their let's say usage of particular skills on their awareness of certain concept on certain behaviors and then test them on the 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 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 and 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 say, 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, OK, how how can we increase belonging for the entire organization of seven people.
Right. And last year, we found 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 and 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 end of seven.
You can be an end 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.
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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 resolutions of the 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.
Better to prioritize or more important.
Yes. If I'm thinking about, okay, pay is pays a huge one, right?
Like everyone wants to be paid fairly.
I think 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 enablements.
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 and making mistakes and doing so without feeling like they'll be punished by the folks around them.
I could imagine how that one cascades to so many other of the outcomes you would measure.
Do you want to go to another question?
Yeah. I want to ask Anaga's question because it's a good one for this conversation because she's starting from scratch.
She says, I'm a DEIA associated 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? 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 talked 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.
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.
And then also try to understand where your organization is not working well.
So this comment mentioned a very strong need for equity.
What does that mean? 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 DDI 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 or it's 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 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 consistently collecting a lot of qualitative data, I think that's good enough.
Right. So maybe in 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 of the comments you get announced 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 is an accountability tool.
And what if you can share one specific example that our audience can learn from a company that is using it and using it well.
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 their organization because they had gotten a lot of reports the year previous that lots of folks did not feel a strong sense 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 used 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.
So you see how unless you understand the challenge, your solution, your one size fix 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 some root causes, I'm sure there were other problems as well that were 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?
Exactly. How do you use data in this way?
Yeah, and also how to hold people accountable.
Like that's I think that in terms of what needs to change, right?
It's accountability and investigating the root causes.
It also the follow through I find so interesting.
Yeah, 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 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 your 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 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 found to build on 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 I, 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 inside.
Yes, so 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 statements.
As part of your hiring process that actually results in substantially fewer members of marginalized groups higher, 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.
It 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 like, you cannot bootstrap and inherently, you know, racist or sex is hiring process just by having one comment saying like, we love diversity.
Right. You actually have to fix your hiring process.
Another practice is the identification of demographic characteristics, which I myself was calling the best practice.
Explain what that is. 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 through the resume itself.
The prevalence of studies finding bias against people with racialized names or feminine sounding names has led a lot of organizations to say, okay, got it.
We're going to strip all identifying information from these resumes and 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 makes 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 raise 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 the AI, the HR training and evaluation efforts take resources we do not currently have?
To do more with the really interesting, I would say DEI is not about doing more.
It's about achieving more.
And so I don't care what you do.
I care 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.
How are 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.
And I think I would apply this in 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 the better outcomes.
But be creative about it.
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 the cause, manage the risks involved in pushing for change and ultimately how to get buy-in.
Women at Works editorial and production team is Amanda Cursey, Maureen Hoke, Tina Toby Mack, Rob Eckhart, Erica Trucksler, 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 womenatwork.hbr.org.
I'm Amy Bernstein. Thanks for listening and take care.
