Effectively Mitigate Bias In Performance Reviews With Just-in-time Training

(0:07) Hello. All right, Randall, Jennifer, Janine. Hey, everybody.

Welcome to our session today. (0:24) We’re here with Shane Lloyd, who’s the Chief Diversity Officer at Baker Tilly. Shane, (0:30) I’m so delighted that you could join us today.

Welcome. (0:34) Thanks for having me. It’s great to partner with all of you and to share some of the insights that (0:38) we have gathered together.

So before we jump into it, Shane, I love working with you. I think you’re (0:45) an extraordinary leader. I want our audience to get to know you a little bit.

So I’m just going (0:53) to start. You graduated from Brown with a master’s in public health. Is that right? And then you went (1:02) and you’ve worked in roles consulting in diversity.

You’ve worked at Amazon in diversity. And here you (1:11) are now at Baker Tilly doing amazing, amazing work. What can you tell us about, you know, (1:18) a little bit about your experience coming up through DEIV and, you know, what led you to (1:27) participate and be a leader and advocate in diversity research at Baker Tilly? (1:33) Sure.

So oftentimes people will look at my resume and think, wow, he’s lived many lives given some (1:39) of the industries that he’s spanned. And I would say that the connecting thread between all of my (1:45) experiences is actually some of the skills that I’ve developed in my public health degree program. (1:51) So within public health, we tend to apply a systems thinking lens that helps us consider (1:57) what are some of the circumstances or factors that help or hinder people’s ability to obtain (2:02) their optimal health status.

Now, if you substitute optimal health status for academic thriving and (2:10) cultural thriving for students from underrepresented backgrounds at elite institutions, (2:15) systemic lens, different goal. If you look at it from the perspective of the work I did as a (2:20) DEI consultant, or even the work I’m doing here now at Baker Tilly, or even the work that I did (2:24) at Amazon, it’s really looking at the overall systemic picture of an organization and what (2:29) helps or hinders people’s ability to thrive across a variety of diversity dimensions. So in many (2:35) instances, as I continue to go through different organizations, although I’m not leaving Baker (2:40) Tilly, so I hope my Baker Tilly colleagues don’t hear that.

Next up. No, that’s not what I mean. (2:47) Just across different industries, applying that systemic lens, but then also trying to figure (2:53) out how do we, knowing that in corporate America, Amazon was also a research heavy organization as (2:59) well, even though it’s large and corporate.

But I think that in order to do diversity equity (3:05) inclusion work effectively, we cannot just leverage some of the best and leading practices (3:10) that have been tested out in certain companies or in different environments. We also have to follow (3:16) it up with our own internal studies to say, does this best leading practice work effectively from (3:21) my organization’s context within our population and within the policies, protocols, and procedures (3:27) and culture as we have it? And I think that added layer of research exploration becomes really (3:37) important to ensuring that when we talk about the value add of some of the programs and (3:42) interventions that we deploy under diversity equity inclusion within Baker Tilly, that we can (3:48) also back it up with our own research and not just, you know, what we know from what’s said by (3:53) McKinsey or Deloitte or EY, all amazing organizations, or Lean In or Catalyst. There’s a lot of really (4:00) good research out there and we still want to stress test it within our organizational context.

(4:04) So that’s the thread that kind of pulls things together. You know, that’s super important because (4:11) we’ve had, there was a lot of enthusiasm a couple of years ago for DEI and I think people just (4:17) threw everything at it. They just, you know, threw spaghetti at the walls and now we’re going (4:23) through an area where there is a lot of pushback and taking, there’s two approaches that I think (4:32) that you’re taking here with us.

We’re partnering, so for those who don’t know, (4:38) EMTRAIN is partnering with Shane and Baker Tilly to test bias interrupters training in the (4:46) performance management process and so we’ll get to that in a moment. But what’s really important (4:51) here is that we’re taking a very scientific approach. So we’ve got a doctoral candidate doing (5:00) studies and using a very traditional research protocol to test the effectiveness of this type (5:09) of training.

So we will talk about, you know, we had samples and we’re doing comparisons and, (5:15) you know, it’s a pretty heavy lift. Now I’m not saying that everybody has to do that, but (5:20) I think your point there, Shane, is that you can’t just take a one-size-fits-all approach. You’re (5:28) probably going to get a lot more pushback, you know, from organizations when they do that and (5:37) stress testing it and taking the approach where, you know, we’re seeing how managers react, how (5:45) cross-functional leaders react.

I think that that is probably the best, the leading practice, but (5:54) I think it is also hard for organizations to do so. What do you think is, what are the conditions (6:02) at Baker Tilly that even enable us to come in and do something of this complexity? You know, (6:10) what’s special? What’s different? Oh, sure. I will answer.

There’s a thought that your statement (6:17) just made and I’ll make sure to answer your question as well. So I think one of the additional (6:21) advantages of a research mindset is that it also allows us to better identify what I would call (6:30) the curb-cut phenomenon insights. So by curb-cut phenomenon, I mean you can have a targeted (6:38) intervention designated for a particular community, but as you take this, you know, 30,000-foot view (6:44) from a research perspective, you might find some additional added benefits where this targeted (6:51) intervention actually works in a variety of different contexts for a lot of different (6:55) communities that allow everyone to see the benefit, even if the initial exercise was to either address (7:02) inequity or to target a particular community.

I think one great example is, you know, the common (7:09) one that we talk about are curb cuts in the street. You know, it’s not just designed for people in (7:13) wheelchairs, but also works for people pushing strollers, riding bikes, or temporary injuries. So (7:17) how do we, when we talk about DEI interventions, how do we understand the broader application (7:22) that would actually support everybody thriving in the workplace? And to your question around what (7:27) makes Baker Tilly special, I would say that part of what makes Baker Tilly special is that within (7:33) our value system as a company, we have belonging as one of the five values within our company.

So (7:39) very, very high ranking, take it very seriously. So from entry-level employees all the way up to (7:44) executives, we have to live up to that standard. And then I would say the other part that’s (7:49) particularly important is one of our other values is collaboration.

So when we think about even this (7:55) project, it is a very cross-functional project where it’s spanning different teams within Baker (8:01) Tilly, and all of us are thinking about how do we structure this effectively so that way we can (8:05) learn the information that we need to, to better unleash and amplify our talent across all levels. (8:13) Okay, awesome. And that the curb cut effect is technically, I think they call it universal (8:19) design for learning.

Yes. UDL for our design. John Powell, yes.

(8:26) I hope it’s okay to give a shout out to the job you just posted, by the way, for all, (8:32) for anybody who loves DEI, operationally focused, research-minded, Shane is hiring a senior manager. (8:41) So heads up, look for that. Shane, where are they? Can they find that on LinkedIn or where is that? (8:46) Yes, it’s on LinkedIn.

It’s on our careers page. If anyone has any questions about where to find it, (8:55) reach out to me on LinkedIn. And then before we dive into the results, just one more thing.

You (8:59) also commissioned or supported this study with Sarah Mount. Do you want to just briefly (9:06) talk about the results of that before we jump in? Because I think there’s a lot of folks who (9:11) are afraid to go full force with DEI right now. Oh no, thank you so much for providing the (9:17) opportunity to bring some awareness and attention to that work.

So the study that Dr. Pereira is (9:24) referring to is Baker Tilly was the lead sponsor on a study with Sarah Mount, diversity best (9:29) practices, looking at diversity, equity, inclusion, backlash, and what employees think. (9:35) Part of what made that study particularly enticing is that when we think of the national conversation (9:40) around anti-DEI backlash, there is a heavy emphasis on the perspective of politicians. (9:47) People have definitely heard about the litigation.

There’s also both mainstream media interest and (9:53) also social media influencers weighing in and offering their perspective. And with this (9:58) particular study, it centered one of the most important of the many stakeholders that are (10:02) important to an organization. It centered some of the most important stakeholders being our (10:08) internal employees.

So making sure that with a sample size of over 3,000 across different (10:14) industries, how do employees within our organizations think about the diversity, (10:19) equity, inclusion strategies that are implemented? How do they rate, you know, (10:24) the performance of their leaders today in 2024 compared to 2020, 2021? And where do they see (10:30) the work progressing? And despite what’s frankly, despite what’s conveyed in the media, (10:37) most US workers are actually very supportive of diversity, equity, inclusion, and remain committed (10:43) to fostering inclusion and combating racism. And then there are also some interesting nuances (10:50) in the sense of how is it that employees are thinking about inclusion? Is there a standard (10:55) definition within the organizations or a standard set of metrics? Or is it that team members are, (11:00) team members or employees are thinking about inclusion in the context of, you know, what’s (11:05) in it for me, which may not be as expansive as how people might’ve been talking about it in 2020, (11:10) 2021, 2023. And then also talking about, you know, when it comes to organizations that are (11:17) trying to balance a commitment to inclusion and belonging with increasing pressures to (11:23) speak up or engage in societal issues, this research also offers a set of recommendations (11:31) for companies to figure out how do you navigate some of those politically sensitive (11:39) dynamics that also create belonging and inclusion challenges for employees and could challenge a (11:47) business’s ability to operate.

So I highly encourage people to check out that research (11:53) because not only does it say DEI is still important to employees, which is important, (11:57) it also weighs in on some of the more complex and murky situations. So that way, (12:01) organizations can find their footing. Awesome.

Thank you very much. And we’re also releasing (12:07) our culture report today. And I think we have quite, we have a couple of hundred thousand (12:14) data points across the country, almost perhaps a half a million saying the same thing.

People think (12:19) DEI is really important. So check out the Emtrain culture survey available today. Okay.

Let’s jump (12:26) into the findings, y’all. Nick, show us the findings, please. All right.

Let’s start here. (12:35) Let’s go to the next slide. All right.

All right. So the writing is a little small, (12:44) y’all. So let’s talk about it.

This is what we wanted to do was use evidence-based (12:51) bias mitigation techniques in the performance review process to increase diversity and partner (12:57) track eligible employees. That’s a lot of words. Managers were given just-in-time bias (13:04) interrupters training before the performance review, and we designed it to be industry (13:09) specific.

So first of all, that’s a point. Shane, I think when we went in there and the teams did the (13:19) training, they loved it. They found it very relevant.

Do you want to, can you say a little (13:25) bit about the feedback, the initial feedback we’ve gotten so far? Sure. So first I’ll say that (13:32) we were actually quite surprised by the initial feedback, because when you think of the conversation (13:36) around bias training or even anti-DI backlash, there is oftentimes the question of, are these (13:43) particular kinds of training still useful? Are they just either, you know, widely popular, (13:50) commonly described, but mixed in their results and execution? And we’re also dealing with people who, (13:56) you know, in the realm of professional services, they’re, you know, strapped for time. So we were (14:00) actually quite delighted and surprised by the enthusiasm, but here’s why the participants were (14:06) particularly enthusiastic.

In our framing of the concept of bias, we actually leveraged the (14:16) descriptors provided by Joan Williams, who is a legal scholar who does a lot of work around (14:23) creating systemic inclusion within organizations, and then also thinking about the appropriate (14:28) interventions to create equitable outcomes. And how she boils down bias is in some pretty key (14:38) categories that are essentially identity agnostic, but can help surface when those (14:49) bias dynamics are deployed disproportionately for people of different identity markers. (14:53) So as an example, one of the bias categories she discusses is this idea of prove it again bias, (14:58) where despite your time, tenure, or proven track record of success, you’re still finding that (15:04) people are either surprised by your accomplishments and achievements, or still asking you to do more.

(15:09) And that can be deployed commonly against women, caregivers, working moms, and specifically people (15:16) who are the first in their families to enter a profession, or first in their families to have (15:20) gone to college, or people of color. So when we use that language of the prove it again bias and how (15:25) that could be deployed inconsistently, when it comes to groups of different demographic groups, (15:32) that really, really resonated with the participants, as did this concept of (15:38) the tightrope. How do you manage being seen as effective and assertive and authoritative within (15:44) context and working effectively with groups without being hit with, you know, bossy or other (15:51) unflattering language? And how do you manage some of that professional identity management, (15:56) which could be deployed across a variety of different categories of diversity and difference? (16:02) And then I also think of tug of war being a very powerful phenomenon, whereby you would have (16:09) junior professionals seeking mentorship from more senior professionals and thinking that the (16:17) indicator of connection would be an affinity group, whether it’s shared gender, shared race, (16:22) or shared geography, or, you know, shared background with socioeconomic status, or (16:28) being a part of a particular religious or faith community.

And that did not work out as well. (16:32) And finding that that ended up being a source of, you know, competition and challenge. So when we (16:38) look at these broad categories, not just tied to, you know, racial gender biases alone, while (16:44) also looking at that, that provided the participants with a degree of language that (16:50) they hadn’t had before.

And in thinking about it that way, they were, they could actually (16:57) think of a number of examples where these concepts came to life. And now that they (17:02) had language could say, what are the ways that I can further inspect to make sure that I am (17:08) noticed, recognizing, addressing, and course correcting within the context of how I run my (17:13) own performance management process? Yeah, let me just double tap on that. So (17:18) Joan describes five different types of biases that to Shane’s point, it doesn’t matter what, (17:27) it’s not political, it’s not tied to your race or anything, it’s prove it again biases.

Did you ever (17:33) have to prove yourself over and over again to get the same level of recognition as your peers, (17:40) you know, so it’s that type of thing where there’s five different types of bias, it gave, (17:45) we gave people to something to really noodle on. And, and I think that they really appreciated that. (17:52) Okay, let’s go to the next slide, please.

And we were running out of time. So we’re going to have (17:59) to jump through these pretty quickly. But this goes, this one just talked about the cross functional (18:05) team.

There’s the executive sponsors, we had people solutions trainers, we had, you know, (18:13) a director of the team be part of our core team, we had a senior manager of performance management (18:19) as a systems advisor, we had a legal advisor, we had our research team, including a doctoral (18:25) student, and then we had Emtrain’s client success team. So it was no small team, even for the pilot (18:31) and Shane, I guess this is a testimony on a test of collaboration. And it was it was just (18:39) so smooth and easy.

And I don’t know if that would always be the case, but I really enjoy. (18:47) So let’s go to the next one, please. And this is a timeline, just we don’t want to get into (18:56) the details too much here.

Just to say that we started, we started onboarding in May. (19:03) And then, you know, here we are in October, and we’re, we’re getting ready to present the (19:10) the final packet of, of the study. But most of this stuff has most of the training took place (19:19) within a very short period of time, it was June and July.

So it doesn’t have to be a ton of time (19:27) to do something. A lot of thought went into cohort development upfront. And again, I don’t (19:36) want to spend that much time.

I’m sorry, Shane, I’m just gonna jump. Okay, awesome. And so we’ll (19:44) go to the next slide.

So the research design was simple. We have the leaders, we broke them into (19:50) three conditions. One where they got no training at all.

The leaders got no training at all. (19:58) One condition where they got eLearning only. And the third condition, we did eLearning plus a one (20:04) hour instructor led training, ILT is an instructor led training.

We did that right before the (20:11) performance review process. I think it was a week before they were due or just a couple of weeks. (20:19) And, and then we had them can they conducted the performance review process as, as, as usual.

And (20:27) then we surveyed their direct reports on their experiences of bias. So Shane, I do want to pause (20:34) here and talk about embedding this training right before performance reviews and how I think it’s (20:43) important for DEI leaders to be in the operations of things. Absolutely.

So I think that oftentimes (20:51) when it comes to weather, I’ll start here. I think it’s not uncommon for DEI interventions to (20:57) sometimes be deployed in a manner that’s bolted on where you either are trying to just latch (21:02) something on in a manner that it’s going to sound illiquid, but it’s a little intrusive and doesn’t (21:06) fit with the natural process. And that was not the case with this particular deployment, which I think (21:11) is vitally important.

The extent to which we can piggyback off of some of the operational cadences (21:16) of the organization, such that the intervention seems like a natural aspect of what is getting (21:23) done becomes really important. So with this instance, what was really helpful is that whether (21:30) or not people had been really thinking about developing the, you know, using, taking the whole (21:37) performance review cycle and really thinking about the evidence and what they were going to put (21:41) together, or if they were kind of dashing through the process, because they got the HR reminders, (21:47) were able to catch a broad swath of people. And when they received the intervention, it was (21:54) that the emphasis on just in time being particularly important.

It was right around (21:58) when people are thinking about, okay, now that we’re almost at the end of finalizing these results, (22:04) how can I do my best to make sure that this is a fruitful process for all parties involved? (22:09) And I would also emphasize to you, the opportunity to talk to our team members about the experience (22:15) and have that survey is really useful, because then we get additional insight around, you know, (22:21) how did people experience it? What kinds of questions do they have? You know, what level (22:26) of confidence might they have to even challenge some of the insights that are shared to ensure that (22:31) they get a fair shake within the process? Those are all very, very useful, because we know that, (22:37) you know, depending on the size and scale of an organization, you know, the performance (22:40) management process, it’s coming and it’s experienced, but we may not always be consistent (22:45) around finding out how do our employees really feel about or what insights did they gain (22:52) from the experience? (22:56) Yeah, this is not for the faint of heart, y’all. It takes a little bit. It’s amazing, because (23:05) it’s not easy to face these responses and yet to make traction and to do so, you really do have to (23:15) open up a little bit of a can of worms.

Okay, so direct reports performance score by leader study (23:21) condition. So basically, we train the leaders to mitigate bias and let’s and we wanted to know (23:27) what was the effect on the direct report score. So what we found was that direct reports received (23:37) slightly higher performance ratings overall when their leaders participated in the bias interrupters (23:44) training compared to the scores of the direct reports whose leaders were not trained.

But (23:50) there were no, the pilot, the condition was small. So this was not a statistically significant (23:56) difference, but the numbers are still there, right? I would still want a slightly higher bump. (24:01) I would want my leader to be in that training because I would want a slightly higher score.

So (24:07) this was, I think, the curve cut effect that Shane was talking about where it could potentially (24:13) raise all but but the story gets a little bit more interesting. So let’s go to over and look (24:20) at the distribution. So if now we’re looking at the direct reports performance score by training (24:27) intervention, meaning you know, we said there are three three interventions where you’ve got the (24:32) e-learning and workshop the e-learning only and no training and you’ve seen these bars are pretty (24:39) much the same.

So when you look at it by the intervention, we saw with this very small group (24:47) that there were no no changes really on the average performance review score. Now, where did (24:56) we see the biggest difference? And let’s come here. So this is this is this is what was really (25:04) interesting to me.

So if you look at these scores in the left-hand column, you have we we (25:12) did this by gender here. So in the left-hand column, you have the males and the right-hand (25:17) column, you have the female and then you look at the conditions. We found that in general, (25:25) if you look at the bottom two conditions, the e-learning and no training, the men typically had (25:30) higher scores than the women.

But when we added on that workshop, now you have the women having (25:39) higher scores than men. And there was a statistically significant difference here. And so (25:47) to me that that says that there’s that’s a number of things.

But let me pause and let me let Shane (25:55) comment on on this finding. What are your thoughts, Shane? Yeah, so I think that there are a couple (26:00) things that emerged. One, a greater sensitivity on the part of the managers to double check and (26:06) inspect their commentary in the performance rating process.

What we also know on the back end, too, (26:13) is that the receivers of performance feedback were also more rigorous in the sense of does this (26:21) insight have evidence to it? Is this actually just too succinct and generic and nice that to the point (26:30) that it’s not even helpful or effective? Even if I’m being rated effectively and told that I’m a (26:36) strong performer, even then I still want evidence to determine not just that I’m doing well (26:43) directionally, but I want concrete insights that can enhance. So for I think of it in a couple ways, (26:49) for those who need to do some course correcting to make sure that they are not having a bias impact, (26:55) the rigor being addressed. But for people who thought, oh, I can breeze through this performance (26:59) cycle because they’re a solid performer, they’re doing really well, I’m just gonna, you know, put a (27:04) bow tie on this and get this through the finish line.

That was not satisfying to our team members (27:10) either in the sense that all parties wanted really thoughtful, evidence-backed feedback, (27:17) and they did not want to be caught in, you know, either the conflict avoidant or the not to make (27:25) fun of people from the Midwest because there’s a lot of nice people in professional services, (27:28) but the Midwest nice phenomenon. (27:32) Right, right. Yeah, I think that as we looked at some of the other scores, we noticed that (27:38) there was, in general, there was, for the leaders who received training, their trend was that (27:47) some groups were not getting, it wasn’t, the variation in the scores wasn’t as great.

(27:55) There were, they were a little more conservative in general, but it was notable that (28:03) in this condition that the women were getting higher scores. And again, this was the pilot, (28:11) we want to, we’re going to be running the main study next year. We’d like to validate some of (28:18) these trends there, but that is, that’s what we were going for, right? The purpose was to (28:23) increase the number of women, the performance ratings and the visibility of women in the (28:30) partner track.

So, so far, promising. Question, did the employees know who received training? (28:40) I, we didn’t, I don’t recall us telling them, Shane. No, because regardless of the (28:46) quote unquote treatment group, all of the employees got a survey on their experience (28:52) in the performance process.

So no, they were not aware. Okay, so let’s go and look at that, (29:00) the results of that. So in the pilot study, the direct reports of leaders who were trained (29:10) reported experience more bias, experiencing more bias than those whose leaders were not trained.

(29:16) And let me, let me just say that this goes to Shane’s point that they’re, they’re, this was (29:26) also statistically significant. And I, I actually don’t have a full reason why I’m still processing (29:34) this. It’s somewhat new and it could be to what Shane is saying is that there was more discussion.

(29:39) They are more critical, you know, they, but I’d like to, we’re definitely going to test that a (29:47) little bit more and perhaps, you know, have some, some additional findings to, to run that out the, (29:53) the next time. Okay. Brittany, were you able to look at the time spent on the review process (30:00) to potentially get a sense of how much deliberation was happening? Thinking of how biases thrive in (30:05) these fast environments and wondering if the training encouraged folks to move slower.

(30:11) So Brittany, we gave the hiring the, the leaders a worksheet to look through. And so we gave them (30:20) the five types of biases to the definitions of them and, and some pointers on what that might (30:27) look like. And then in the worksheet that they were supposed to use in conjunction with the (30:34) performance process, they were to look at their feedback and say, which of the five does, (30:40) does this reflect, might this reflect? So which of the five might my feedback reflect? Prove it (30:47) again bias, tug of war bias, maternal wall bias, and so on and so forth, or none.

And so there we (30:55) were trying to slow down and have them reflect on, on their feedback. Now, what we didn’t do was (31:02) bounce it back to them. So we didn’t look at their feedback and then send, send it back.

If there, (31:08) if it reflected bias, we did not, not none of that, but we did ask them to, to self monitor. (31:19) And what I’ll also say too is around, because I think I can imagine people thinking, wait a minute, (31:24) is bias really happening? And what we also have to understand too, is that as people might (31:30) be suspicious of bias taking place, that doesn’t necessarily mean bias was in fact taking place. (31:37) But I think that the heightened awareness of, wait a minute, let’s really like think back about it.

(31:42) And now that I have the opportunity to talk about it, because someone’s surveying my thoughts about (31:46) the experience also, also gives us insight that with this being, if we ask our team members about (31:53) it and raise this concern, how do we make sure that people understand that across the board, (31:58) this is what managers at the individual level and the firm at a systemic level (32:02) is doing to address those concerns where they’re real or perceived. (32:09) Yeah. And again, I mean, what, what’s it, what you can’t, you can’t do anything about something (32:15) that is not visible and ignoring it is not the right answer.

So, so the good news is summary, (32:23) just-in-time training on how to identify bias can mitigate bias in performance ratings. (32:31) You know, contrary to what we would have thought, they were very eager to learn. They asked to (32:36) learn more.

So it really, it did indicate a desire to learn more. And, and these folks, (32:42) I want to add are billable, high level billable partners in a professional services firm. So if (32:49) they can take the time, chances are most anybody can take the time.

Calibration training. So we (32:57) also got a few future directions that we may act on in the future. We may move to calibration (33:03) training before, before the partners do the calibration.

We’re talking about also looking (33:11) a little more closely at their rating system and, and trying to break that down a little bit more. (33:18) But I, I, unfortunately, I think we’re out of time. Shane, 30 minutes is just not enough.

(33:24) You know, there’s so much to talk about. Do you have any thoughts that you’d like to leave folks (33:31) with in closing? Absolutely. I would definitely encourage anybody on this call to really think (33:36) about what is the likelihood or opportunity for you to do some of these experiments to find out, (33:42) you know, are these trainings having the impact that you imagined? And what is it that you can (33:47) learn? I think one of the most powerful things that we learned from this exercise is our team (33:53) members are, they’re very curious to have their experience of the overall performance management (33:58) process solicited.

So not just maybe with their, you know, one-on-one HR business partner, or just (34:03) with their manager in a one-on-one conversation, but if there are some intervals where as cohorts, (34:09) people are having opportunity to provide insight to their experience, that could also help us (34:15) understand where we might have really thoughtful equitable processes that are not perceived as (34:21) equitable for whatever reason. And then how do we close that perception gap? All right. And yeah, (34:27) thank you so much, Shane.

Everybody go boldly into the world of DEI and test. It seems like, (34:34) you know, the climate is there in spite what, what folks may believe from the hype. And we look (34:40) forward to seeing you again soon.

Thank you so much, Shane. Thank you, everyone. All right.

(34:58) All right. Thank you so much, Shane. Really, Nick, are we still live or are we not live?