S4 E94 | eXpertease: Eve Lewis talks about using the Mansfield rule

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Chris Hoyt, CXR 0:17
All right, Hello fellow romantics. Chris Hoyt, CXR’s president today’s matchmaker for the next 15 minutes as you find a professional love match, courtesy of this eXpertease segment of the CareerXroads podcast, if you haven’t listened, watched or been part of the eXpertease segments before, this is the speed dating of podcasts. And this is sort of how it works. CareerXroads is connecting you with an industry leader almost every week so that they can share with you one thing they’d like to make sure you know about their career or their professional journey. Now, if you’re fortunate enough to join us live, then you can jump in the chat channel and drop in a question of your own for our guests. And if I swipe right on it, should there be enough time we’ll get it covered today. But if time forces me to swipe left, don’t worry, it’s me, not you. And you’ll find it posted in the free and public forums we host over at CXR.works/talenttalks. Now, if you didn’t already know, the focus of our topics, were actually built from the results of our 2021 CXR talent acquisition priorities research. And this is where hundreds of verified team leaders and practitioners weighed in on what was most important to them this year. Now you can find that report for free within the research and report section of CXR.works. So turn up the volume and lean way in. We’re getting started today with our first time guests Eve Lewis, who is the global inclusive recruiting director at Uber. I got it, where they’re using something you may have heard about the Mansfield rule to guide their diversity recruiting and their retention efforts. Now, Eve Welcome to the show. How are you?

Eve Lewis, Uber 1:44
Thank you, I’m doing well thrilled to be here. Been I’ve never actually been introduced in speed dating context. So this is the first three I’m super excited to be here this afternoon.

Chris Hoyt, CXR 1:53
If you may be very fortunate could be the last time you’re introduced that way.

Eve Lewis, Uber 1:57
As long as everyone swipes right, I guess right?

Chris Hoyt, CXR 2:01
That’s right. Everybody’s gonna swipe right on us today. I always like to start these sort of rapid fire segments with a little bit of background on our guest team. So can you can you tell us a little bit about yourself? Can you give us sort of the escalator pitch about Eve Lewis and the work she does at Uber?

Eve Lewis, Uber 2:17
Yeah, so I’ve been in diversity. I won’t say recruiting, but some segments and capacity of diversity, outreach, recruitment, evangelism for my entire career, I started at Microsoft, about for there for about 15 years. And then from there, I was with Oracle and IBM. And then now I am thrilled to lead the function at Uber. Essentially, I’ve done everything from marketing, to outreach to candidate engagement, pretty much everything on the spectrum from initial engagement through to hire. And then now at Uber, I lead a team that specifically tasked with enabling and driving interest applies and hires among all diversity constituency groups globally.

Chris Hoyt, CXR 2:58
I love it. And I love the fact that these are not small organizations that you’ve been at, right. And you know, the old saying, you know, the bigger the wheel, the longer it takes for the revolution. So it’s so it’s really interesting that you’re pushing to sort of make an impact here. Now. We’re talking about the Mansfield rule. And my understanding is that this came around out of out of Women’s Law Firm, hackathon. Exactly. Back in like 2015 2016, something like that. Exactly. And the math on that, I think, please correct me is that it is, it is about ensuring that 30% of women, LGBTQ people of color, and disabilities, are considered for roles in leadership positions?

Eve Lewis, Uber 3:42
Correct. So in the loft space, and by the way, Uber is Mansfield certified. So there’s an organization called diversity labs that will certify corporations, but they only certify in the legal function Ubers, legal certified with Mansfield, and what it did is it realized that if they looked at the data, they saw that true diversity penetration, true inclusion was seen when companies realized that there is a trickle down effect. And they looked at senior level roles within the organization and first focused efforts on driving penetration of all diversity segments there. And then what you’ll see is it goes top down, bottom up. The other thing I saw was that you can’t just focus on one segment. You know, I think a lot of companies think of Rooney Rule. And when when various companies think Well, we’re going to start driving some diversity strategy, the knee jerk reactions, typically Rooney Rule, which is a good first start, but the problem

Chris Hoyt, CXR 4:36
I’m sorry to interrupt you. For those who don’t know, can you can you give us sort of the the bullet of like, what’s the Rooney Rule? And what what’s the difference between Rooney Rule and Mansfield rule?

Eve Lewis, Uber 4:44
Yeah, so Rooney Rule was established in the NFL, and it was established because they were very limited black and brown execs at both the general manager leadership level and coach level within the NFL. So the thought was if we put one or two black or brown individuals on this slate will drive representational drive greater penetration in the senior upper level office space at NFL Well, it was implemented about I think we’re 1215 years in now. And when it was implemented, there were three black coaches, guess what, today there are three black coaches.

Chris Hoyt, CXR 5:15
Looks like they are really killing it.

Eve Lewis, Uber 5:17
Yeah, terrific investments there. But it’s been a failure in the NFL. And the reason is because it doesn’t address the root problem. It’s not a matter of putting individuals on slate, it’s a matter of looking at the systemic inequities that persist that didn’t allow black and brown individuals to matriculate up the ranks within the NFL. So the challenge is, yeah, you can place a few at the final stage. But until you’ve addressed those issues, and allowed individuals to get the exposure and the experiences, and normalize different backgrounds, you know, the challenge to within the NFL is they’ve got very strict criteria, much like we see in tech managers want to hire certain criteria, NFL coaches, or NFL owners want coaches that come from certain backgrounds. Well, just by virtue of access, you’re not going to see a lot of brown people and black people, they get access to those experiences. So until you normalize different experiences and expand the aperture of what strong talent looks like for those roles, you’re not going to see penetration. And similarly, in corporate America, when we started implementing Rooney Rule, it became challenging because first of all, the burden was on TA, I mean, you’ve got to find that female on the panel before you can extend the offer. So it became very reactive, very one rec by one rec, the burden was on to find that person, it oftentimes just became a checkbox, as long as you found a female who was interviewed, it didn’t really matter the outcome. And the other thing is it fails to recognize human behavior. If you have one individual on a panel, who’s different, what does your mind do? it normalizes all of those that are similar and kind of pushes the edge cases to the edge. So you’re not driving strong results, because you’re not normalizing that different experience, you’re

Chris Hoyt, CXR 6:51
looking for subconsciously, the they subconsciously become the token candidate.

Eve Lewis, Uber 6:55
Exactly. And so as a result, you don’t drive the hires. And the other piece to that is, you’re not driving holistic diversity wasn’t when when I came to Uber and looked at how we operate operationalizing Rooney Rule. In a lot of cases, it was only focused on female, it wasn’t consistent across levels. If you’re truly driving inclusivity. And diversity, you’d want to go across the entire aperture, you’d want to look at MVP candidate diverse females, you’d want to look at African Americans, Latinos, we were only really looking at females. And so it’s just a very narrow way of driving and it’s not scaled or sustainable. I mean, ta cannot police and manage rec by rec, you’ve got to have a sustainable framework that allows you to drive holistic diversity across all functions, not just rec by rec.

Chris Hoyt, CXR 7:37
Yeah, yeah. And it seems to me, you’ve got to make sure that it doesn’t just sit with ta it’s not the candidate police, right?

Unknown Speaker 7:43
Varied accountability. Yeah. And with Mansfield, we specifically elected to implement at the business phone screen just for that reason. We wanted to make sure to have an accountability of driving pipeline. But we also want to make sure that the manager is accountability when they get that inclusive pipeline, that they are, that they’ve got metrics around how they transition and assess that talent. So it’s a shared accountability and business don’t spin it all doesn’t just sit on ta.

Chris Hoyt, CXR 8:08
Nice. And how does in a time when organizations are struggling to get some transparency or even some visibility into candidate diversity? How does Uber handle that? Because typically, that’s hidden from most recruiters, even though they’re held accountable to building a diverse slate.

Eve Lewis, Uber 8:26
Yeah, great question. So one of the challenges and honestly, even as we implemented Rooney, initially, we were challenged because we didn’t have good data coming in. One of the first things we had to do with kind of step back and align our data infrastructure. So we’ve implemented self ID, which sounds so basic and simple. But I really would be interested even among your the people on this call, I’m sure a lot of a lot of these companies don’t have really good candidate data we definitely didn’t. So we implemented self ID first in North America and Canada. And now we’re rolling out globally across the rest of the world. But that will allow us to do is pull in analytics, all of this needs to be database and data driven. We do not provide disaggregated data to our recruiters so recruiter can’t go in and look at candidate x, but what a recruiter can do and we actually only provide access at certain levels. So there will be a couple of folks on each team who have access to the full pipeline data at an aggregated level. And it can tell them, for example, for my back end development role, what does the candidate pipeline look like? What percentage of African American what percentage of female what percentage of MVP candidates have applied to that? So based on that a recruiter can go back and say, Oh, they can let them know hey, for that role, you might want to go back and do some additional sourcing your light on specific segments, they will not tell them you know, for example, candidate j is a male or female, but they will tell them overall with their candidate pipeline looks like for a specific role. And then based on that, we would expect to see similar throughput at every stage. So we also are looking at data by stage for a candidate. So if I see that, for example, back end engineers, white males are progressing through To business phone screen at twice the rate of African American females that lets me know, you know, I’ve got a problem, I need to go back and look at the data. Is it a sourcing issue? Is it a bias issue? Is that a process issue? Why is there such a gap there? The idea is to have similar throughput rates by candidate by stage by diversity demographic, all the way through to higher so, you know, a lot of people will say, well, it really was great because I could make sure diversity represents is represented at the offer stage. Well, technically, if your process is equitable, you don’t have inequities that are disenfranchising diverse communities, you should still see that same pipeline representation at the offer stage.

Chris Hoyt, CXR 10:38
Yeah, yeah. Well, let me ask you, when you talk about doing something like this on a global scale, and using data, Well, the first thing that comes to mind for me is my North America team’s definition of diversity may not be the same or certainly isn’t the same as my EMEA team’s definition of diversity or even geographies within the EMEA specifically, are you guys accounting for that? How does that work at Uber?

Eve Lewis, Uber 11:02
We are so I’m really insightful comment there, because what we found is, as you know, there are different privacy rules across every country in EMEA. And so what we’ve had to do is develop different self ID forms per country based on those rules and regulations. So each country, each region does have different access. And we’re building dashboards. So that, as I said, when they go in and look at aggregate data inputs, they can see what is allowed in that country in terms of reporting, and then they can see what their their diversity looks like, you’re right, every country is going to be different. You know, if you look at last time, a lot of those countries have persons with disability quotas. So we’re going to be focusing on those issues in those countries worse, whereas in Europe, there’s different requirements in Germany, for example, with Alexi report an app. So we’ve modified our outputs in terms of we’re asking candidates to supply and how we’re driving the pipeline based on those specific country requirements.

Chris Hoyt, CXR 11:54
I love it. I love it dashboards and data and DE&I It’s fantastic. Let me let me ask you, if I’m listening, or watching, and and I want to get started in my organization, and we don’t we don’t have anything in place yet. Is there anything you’d recommend for someone to use data as this point to move into sort of a Mansfield rule commit? Can they leapfrog the Rooney Rule? And what can they do to just start making a difference now, right, not just have the the idea or the interest to make a difference, but let’s start moving the needle now.

Unknown Speaker 12:26
So So there’s a couple things you could leapfrog Rooney, but you could also take the basic constructs of Rooney if your organization doesn’t have the ability to really operationalize a broader, more holistic, more strategic rule. And what you could do is look at your data, take the data you do have, I mean, clearly, you have higher data. So look at that, clearly, you should have some sort of information on the candidates that are applying and showing interest in your roles. Look at that, we looked at all of those factors, we wanted to see what our existing candidate pipelines externally, were looking like, what our hire data look like, what market availability look like, we triangulate it all back to set our aspirational ranges. But that was a very long and involved rigorous process, if you don’t have that, start with the data you do have and see where the gaps are. For example, if you know that you have real big gaps around people with disabilities or people that are differently abled focus on that focus on a few of the segment that you realize you you probably need to drive enablement on and then expand from there. Um a huge piece of this that was also educated and managers, right. And so as you expand, the managers are going to see different profiles of candidates come in, they’re not going to stick with this nearly maybe preferred profile that they’d like to hire against, as we saw Uber, as you expand it. And as you bring in more candidates, you’re going to have to show in quantify the value of different experiences to your managers. So the beauty of that is once you start doing that, I mean, I think we’ve all had the example where manager is adamant that the candidate has to have x, y, z, and you bring them ABC, and then all of a sudden, they’re like, ABC is the best candidate I’ve ever hired. Like, I never realized what we were missing until you brought in something new that illuminated that. So it’s an education piece, both for TA and for the business. But I think once you’ve done the initial groundwork, once you’ve looked at the data, once you’ve spent the time educating the business that should allow you to enable you to drive a different type of candidate which hopefully drives more inclusion more diversity across

Chris Hoyt, CXR 14:18
Nice and do you guys have within Uber or even just within your peer base you guys have talked about and we see this often is that hiring managers and this one comes from the audience but hiring managers often combat that type of sleep build with the argument of speed that they’re trying to actually we don’t have time to wait on a on a diverse slate. We’ve got to do this. Now. We don’t have time to do the training and the investment on the back end of the hire. We need somebody now is there sort of a standing, standing argument or standing response to that that you can sort of share?

Eve Lewis, Uber 14:54
Well, if you do what you’ve always done, you’re going to get what you’ve always gotten and there is a bit of a ramp there is going to be changed is challenging, right. But ultimately, I just don’t see any compromise there. I do think, in our case, we aren’t seeing really a slowdown in hiring because if you’ve got a strong sourcing function you’ve enabled sourcing, you’re going to be building that pipeline. And because it’s holistic, you know, for example, in the case of North America, we’re targeting six distinct candidate segments, you can’t tell me that recruiters cannot find strong talent across six segments. The beauty is it’s not just looking for African Americans, Latinos and women, you’re expanding across all diverse segments to drive representation. And so if anything, I think by looking at Mansfield, and something that’s holistic and scalable, you’re enabling your sources to drive better diversity of confidence going to be faster. But in the event, you know that you’re in a market, for example, Germany, where it’s more narrow, and you’re only focusing on a couple of dimensions of diversity, that’s the education piece that the managers have to understand. And in Ubers case, I’ve got to say, I’ve been super impressed because I have managers that are so conditioned now, if they don’t see the visual representation of diversity on their final hiring panel, they will say, I’m gonna wait, I’m going to pull back and wait until you bring me an inclusive slate before I offer this hire. And so they’ve been trained to do it. So do the work upfront, it may be painful initially, but the ultimate outcomes are going to certainly be way more beneficial than any short term pain.

Chris Hoyt, CXR 16:21
You’re saying that hiring managers are trainable.

Eve Lewis, Uber 16:24
I know Yeah. Who knew? Right?

Chris Hoyt, CXR 16:28
Oh, my gosh. Well, thank you so much for giving us your time today. We really, really appreciate your insight. Thank you.

Eve Lewis, Uber 16:33
Thank you all. It’s been a pleasure.

Chris Hoyt, CXR 16:35
All right listeners next week, you’re gonna want to be here. I think that’s May 25. As we connect with longtime industry friend and shake weight fan, Martin Burns. Martin is the editor in chief of recruiting news network that is a pretty fantastic industry tech news resource. If you haven’t already been there. He’s going to talk with us about what we’re seeing in the space right now. With regards to unprecedented mergers and acquisitions activity for vendors. So it’s sort of a tech versus services and why you should be paying attention to this you’re gonna want to jump on with us and you’ll be glad you did, I promise. So if you haven’t already, be sure you subscribe to this videocast for podcasts anywhere you listen to your other favorites and we’ve made it super easy by sharing those fancy little subscribe buttons as well as a vast library of previous episodes and CXR.works/podcast so until then, we’ll see you in the active forums and talent communities over at CXR.works Thanks

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