311: The Business Case for Caring with David Barrett

[00:00:00] RepCap is proud to support Punk Rock HR. We're B2B content marketing consultants that combine a journalist's curiosity with a marketer's creativity to tell clear human stories that connect. From strategy to execution, we partner with brands to turn ideas into thought leadership and get real results. Want to learn more? Head over to RepCap.com.

[00:00:22] Even in this time of kind of great redesign of work and what are tasks and what are skills and automation and AI and bots and whatever, it still remains true that the highest performing companies economically also had very strong multilateral and multilayered connectivity between stakeholders, be they senior leadership, middle management, frontline workers.

[00:00:48] And they're being very fluent lines of communications and understanding between these groups. Hey, everybody, I'm Lori Rudiman. Welcome to Punk Rock HR. My guest today is David Barrett. He's the founder and CEO of Waliba.

[00:01:06] They're an HR and employee experience technology company that uses AI and behavioral science to analyze workforce sentiment and provide insights into employee experience and organizational health and health. And strength. David is here today because Waliba just completed one of the largest studies ever done on employee experience across the entire S&P 500.

[00:01:29] That's 25 million public data points, no surveys, no asking employees to fill out anything. And the results of that study show the importance of focusing on EX and what it means for your bottom line. And so David is on the podcast today to talk about that report, talk about Waliba, and also just to tell stories with a great Irish accent.

[00:01:53] So if you're interested in all of that data, research, science, employee experience, making a difference in your organization, helping your company be profitable and helping your employees do meaningful work, well, sit back and enjoy this conversation with David Barrett on this week's Punk Rock HR. Hey, David, welcome to the podcast.

[00:02:23] Thanks for having me, Laurie. Oh, it's my pleasure. Listen, before we get started talking about all the good data and research and just the operations of your organization, why don't you just very briefly tell us who you are and what you're all about? So, Laurie, I'm David Barrett. So I'm a psychologist by my background. I'm the first psychologist in my family when I went off to college to begin with. My dad said, that'll be great when you come back at the holidays or Christmas, you can give us all the massage. And I said, well, that's a physical therapist or a physical therapist.

[00:02:53] So, you know, I have a novelty in my own family in that respect. I worked as a psychologist for about maybe a week or two. And the first company where I worked did a lot of interactions with directly with people trying to evaluate their personality or cognitive style or their attitudes or personal characteristics. And then being expected to write up extensive reports on a laptop is like pre-internet days. Often there could even be pencils and paper and acetates all involved.

[00:03:22] And while this is all very worthy work and important in its own right, I decided that this was much better suited to computers and databases and the Internet ultimately being involved in. So I kind of spent the last 25 years developing platforms and technologies that are able to directly or indirectly measure and understand people in the world of work and then able to analyze them against models to do with the human and organizational form.

[00:03:47] And then that data being used to help make decisions around how to hire people, how to develop people, how to train people, how to organize the workplace to get the best productivity and outcomes for people in business. So tell us about your current organization. What is it and what does it do? Yeah, so my current organization is Waliba. I'm the founder and the chief executive.

[00:04:08] What we do is without having to use any surveys that people have to answer directly, we're able to alternatively use all the data that's in the public web that's been pushed out there by people and organizations and analysts and commentators in order to gather large reservoirs of information that we can get.

[00:04:29] We can then run content analysis on in order to then form kind of numerical ratings and scores and explanatory information about what's happening against different factors in the organization and what could be done in order to remedy or improve these things. So for example, we can measure the perception of leadership or rewards or equipment technology or communication or work conditions in hundreds of thousands of companies all at the one time.

[00:04:57] And we can do that all in an apples to apples standardized way against our model and then run that up against a load of predictions about how it impacts sales or revenue or stock price or absenteeism or like unwanted attrition, things like that. So we can do that in a couple of minutes, whereas if you use consulting firms or you do run internal programs, it takes months and costs hundreds of times more.

[00:05:21] So I think there are a lot of HR professionals who listen to this podcast who would say, well, how do you know the information out there is reliable and valid? And are you telling me that just by looking at public data available on the web, you know my organization may be better than I do? It's not that it's necessarily better, but it's certainly similar and to a large degree the same in what it can tell you.

[00:05:46] So we are gathering, say, 100,000 data points on, say, a large retail bank in the US. Say 65,000 of those data points will come from individual workers who currently are in a given timestamp period are actively working in that organization. So it's what they're saying in the public space.

[00:06:07] The other third of the information might come from academic papers, might come from journalist commentary, analysts, might come from Reddit conversations or Twitter, where people are talking about the company and working there, but they might not necessarily be workers. But we know that the same contributors are providing the content. They're pushing it in the public space.

[00:06:28] We run many validation studies whereby we'll take all things like the Gallup data or the Glint data or the Pecan data, which is like, you know, a typical internal survey that's run by a company. And we're able to run, in effect, a reliability study between the two to see is the stack ranking, the ordering or the pattern of data the same between ours and what tends to come from a classical internal survey.

[00:06:54] And even though the information has been gathered from two totally different sources, we see, like we say, 0.7, 0.8 reliability between the scoring in both modalities. So different methodology, but certainly measuring ultimately the same thing. Boy, that's really fascinating. So with this data, what does a company do with it? Well, it depends on the company.

[00:07:19] But the company will usually use it in order to, first of all, develop the business case around what are the most important things to put emphasis on in terms of like people, culture, context, organizational factors that they would need to potentially fix or address if they're poor or that they can amplify and use to good effect if they're strong.

[00:07:49] So most companies, if you're a chief people officer, what you'll do is you will get our platform to run on your whole organization or say on your salespeople or your managers or your early stage talent. Or if you've got 50 big sites across the world, you might like break it down and say, run it on these 50 instances and tell me what's going on in general in my organization or in these different pockets. And they can run it themselves or they can get us to run it.

[00:08:16] And then what they'll typically do is they'll stack rank themselves against other peer companies. So say like if you're using classical surveys, you can't get the direct survey data from the survey vendor to look at the other company's information because they'd have a data processing agreement and an NDA with their client. But in our platform, you're able to run them against the exact same model as yourself.

[00:08:39] So you're able to know where you're strong or where you're weak, not just internally, but against your competitors for talent or people that you operate in the same sector as with the exact same typology of staff. That's the most common use case is that companies will want to use it to quickly understand themselves, be able to compare themselves and learn by being able to be benchmarked against others really rapidly.

[00:09:06] So like oftentimes they'll want to compare against like best performers, you know, in a niche or a cluster where they either admire the other party and want to learn from them or they're competing avidly with them for business or for talent. And that's where they see the kind of uniqueness of what we do is that you can run all that at once rather than only looking at yourself. What happens when employees behave badly?

[00:09:31] Boy, we could we could do an entire TV show, maybe maybe a Netflix special on that. Well, Ryan and I sat down and recorded episodes for FOMA and we asked practitioners, give us your most outrageous story. You know, the sales leader that brings cocaine to work, you know, whatever. Just bring us the outrageous and it is funny.

[00:09:56] So if you need a laugh, which we all do from time to time, search for workplace misconduct wherever you get your podcast and you'll find it. And trust me, you will laugh and cry, but you'll definitely laugh. All right. Thank you. Well, I just wonder why you do what you do, because it sounds like you were a pioneer in your family going to university and pursuing this kind of background. And you could have gone a lot of different ways.

[00:10:24] And it sounds like, well, OK, you like computers. But what is it that drives you to do this work? Although, well, the other people in my family have done much more interesting things, particularly my... Oh, have they? Yeah, my dad left school when he was 13 and he got a job as a stonemason making gravestones, tombstones. So he then ended up in his teens becoming an entrepreneur making these gravestones. And I used to work with him when I was a little kid.

[00:10:52] And obviously he had a lot of freedom to, you know, choose his own hours, you know, work out who'd be his customers. There's a pretty like endless and ongoing unlimited market for gravestones. And he then expanded into owning a late night fast food joint and was a licensed gun dealer. Well, he used to run all these three businesses. I was saying these are great synergies, dad. You sell guns, you have a fast food joint that's open late at night and you sell gravestones.

[00:11:22] So this is a really good combo business. And you bury them. Yeah, it makes sense. The full life cycle. It's like food to grave services. I liked the idea of being allowed to, you know, choose what you're doing yourself and to come up with, you know, the way you wanted to build your own type of business and to be kind of free and able to meet a lot of different types of people and doing that. When I was leaving high school, I didn't want to go to college myself. I wanted to sell advertising billboard space. I didn't want to do the bit about making the advertising.

[00:11:51] You've got to remember, this is like the late 1980s, early 1990s. I didn't want to like make the ads or do the creative work. I wanted to find all the places on the highways and the gable ends of buildings that you could rent out and rent them to the advertising company, which turned out, I think, to be quite a good business, like Comcast Your Channel and companies like this. But my mother wouldn't let me do that. And she said, you can do advertising in college or whatever. And she says, but I think you should be a medical doctor. I don't want to be a medical doctor.

[00:12:21] I'd hate that. I wouldn't want to do that at all. You can get my younger brother to do that. And actually, he does do that. And he was a cardiologist in Scripps and in Columbia in Harlem. So he'd do the short straw of having to be a cardiologist. So the compromise was that I'd become a psychologist because she told me that would certainly have something to do with advertising and billboards. So she tricked me into that whole pursuit.

[00:12:46] And I think that's what happened then when I ended up in that job where when I was sitting down having to write all those reports, you know, by physically meeting people and then analyzing them and writing the report. I didn't like that because you had to kind of be physically in one place all the time. So that's why I wanted to get into the idea of selling all the software and building a globalization of what you could do with the Internet and data, because it allowed me to go around and do whatever I wanted to.

[00:13:14] It took me from everywhere from Kazakhstan to Sakhalin to Brazil and everywhere in between and Congo, you know, selling these services. So I love the freedom the same way as my dad loved his freedom with the guns, the gravestones and the French fries. Amazing. Well, as I think about the organization that you've built today, can you tell me about it? What's the size? What's the scope? Where are you located? What's it all about?

[00:13:39] So we've about 40 people in our company and it's half the people are, we'll say, very technical, mathematical, scientific software AI engineers, because they're building all the work on the LLMs and the generative AI and all the MCP and RAG systems and all the requisition systems and the pipelines, the tokens and all this stuff. So there's a group that have to build and affect all the engineering and the UX and the product part. That's about half the company.

[00:14:08] They're divided mainly between Ireland and Germany. And then there's the other side of the business, which are more like business advisory, commercial development practitioners. And they're usually kind of management consultants, enterprise salespeople, or they're like IO psychology type people. So we've colleagues in, say, Minneapolis, New York, Atlanta, London, Brussels, Amsterdam, you know, and the UAE, Singapore.

[00:14:35] So all that group is dotted around where the clients are because it's easier to work with the clients, even though it's a software enabled, you know, AI product, building relationships and understand what's going on in that person's, you know, country, legal system, culture, business agenda. You know, it's better for us to have people who can build those relationships, you know, in close proximity with the customers.

[00:15:01] So one of the things that struck me by the research that you do within your organization is that you found there's a 5% shareholder return gap between companies that get EX right and those that don't. And so I wonder what that means for an HR leader in 2026. Can you talk to me about that? So maybe that's worth unpacking a little bit about what we did to generate that insight and that evidence.

[00:15:28] So what we did, Laurie, was we got our platform Accelerate, which is able to measure all these people and cultural and context factors in the firms. And so we measured all the S&P 500 organizations, except we ran it on them for 2020, 21, 22, 23, 24, 25. So we had all the data sets around what was going on around these characteristics in the firms across kind of a longitudinal period.

[00:15:53] And then we had all the stock price movements and the total returns on each year that are looked at as being anteceded by certain factors being present in the people, the management and the culture.

[00:16:05] And we were able to identify that the top 100 firms in terms of EX, our measurement on Accelerate, had outperformed in stock price growth by 11% over the rest of the S&P 500 and 5% in total returns, which is like the growth minus dividends, because some of the slower growing ones have larger dividends. So it's like it's 5% returns, 11% growth.

[00:16:30] And the experimental design for that is really good, because we're better able to say it's like cause and effect, because we're able to track it in a very good experimental design, rather than just a snapshot with a correlation that's there. Now, what I would say to HR leaders is that most of the HR leaders have trouble being able to show the economic merits of when they want to go and do an intervention or work on a particular topic.

[00:16:58] But with these agentic systems that work with all this kind of public data at a massive scale that you can run an X and Y axis on, you know, you can take any business outcome, like say your JD Power Score with your customers or your revenue per employee or your, you know, your regretted attrition or whatever it is.

[00:17:18] And because you're able to run up all the characteristics of your company that are maybe present alongside that, you're able to, with a strong level of certainty, work out which things are definitively and with the largest impact connected to either the problem or to remediating the problem or solving the problem.

[00:17:39] And that means that when you go to your colleagues, it's really easy to put a dollar value on if I fix this by 1% or if I do this like other companies and we do this with our company, we'd expect to see some kind of a net improvement within 12 months. And we know that that is worth, you know, X hundred thousand or X million dollars in a large company. And it's worth tackling.

[00:18:06] So that means that your business case is really solid to support your investment of time, effort and resources. This is William Tencup and I'd like to direct you to a wonderful limited series podcast that Ryan and I recorded live at the ERE Recruiting Innovation Summit. We sat down with 20 recruiting and TA leaders from around the world to hear what today's best recruiters are doing to stay sharp, stay relevant and stay ahead. It's called the talent shift. You'll love it.

[00:18:36] You'll find the podcast wherever you get your podcasts. Listen, like, review, share. Do you. Well, David, you know, you've got a lot of good examples of where it's gone right in your research. Where has it gone wrong? There's so many good intentioned investments that go on within the organizations we serve to do with learning, development, well-being, transformation, upskilling.

[00:19:00] But very few of them are supported by evidence around why in the first place that was worth addressing. And then even fewer of them are ever validated around did that make a difference in terms of the dependent variable or outcome variable that you wanted to turn the dial on.

[00:19:19] And that means that when things are going well and money is in ample supply, people do care, but they don't care that much because they're happy to, you know, throw money at the interventions in order to try and work well with the people.

[00:19:33] But when the kind of boot is on the other foot, which it is a bit at the moment where the employer perceives themselves as having quite a lot of power and the employee isn't in the driving seat that the way that they were in 2022, the value for money case is really expected in a strong way now. So I think that what happened was, say, for example, in the pandemic, enormous amounts of money were thrown at interventions around health, well-being, employee supports, talent, learning, development.

[00:20:04] Most of it was never kind of audited properly or judged properly around its merits. People were just trying to do good things to kind of stay on the right side of their employees. Whereas now, if you went and asked for a load of money to buy stuff for employees, you would be expected to bring a proper business case.

[00:20:19] And companies and practitioners in HR who've continued on with the pandemic mentality around, I want to do this for employees because it's good for the employees and it might be good for our organization, are receiving short shrift from their finance departments. Well, and your research has shown what actually kind of works and what doesn't. And I think there's nothing more in HR than we love than a program. We just love it.

[00:20:45] And so we'll throw money at like perks and benefits if we can, because also we're employees too. And we think, well, we need it. That benefits us. But I think your research shows something different. The importance of a manager and employee relationship. Can you talk to me about that? Yeah, well, I could talk about that all day long.

[00:21:04] I think that what our S&P 500 research threw up, Laurie, was that even in this time of kind of great redesign of work and what are tasks and what are skills and automation and AI and bots and whatever, it still remained true over the period 24, 25 and into 26,

[00:21:27] that the highest performing companies economically also had very strong multilateral and multilayered connectivity between stakeholders, be they senior leadership, middle management, frontline workers. And they're being very fluent lines of communications and understanding between these groups.

[00:21:47] So even though companies are hugely keen on, I want to maximize my revenue per employee or I want to like have less employees maybe if I'm going to have the same size business. Regardless of this kind of brutalist mentality about that ratio, the companies that are succeeding the best have this really strong multilateral tightness between the people and the cons.

[00:22:12] And that was the biggest indicator of high performance on the stock price stuff in the S&P thing. Out-predicted technology, out-predicted rewards, out-predicted methods of working, out-predicted policies. Anything. Nothing was as strong a predictor as that dynamic between the people. Wow, David, you know, we have a lot of people looking for work. So can you name some names of companies that are really just outperforming it and killing it in this way?

[00:22:39] I'll give you one company that, you know, that I think is an interesting company that has very high scores on that. You know, if you go to our website, you'll see the whole 500 of the S&P companies together. But if they're in the top right, the company I thought was very interesting is Moderna. You know, they're quite radical in that they're combining their HR and IT function. The person who's the leader of that is now the CPO. So that function is combined. They've really good, you know, agility.

[00:23:09] They were brilliant, performed brilliantly during the pandemic into the era of the vaccines for them and have continued to perform, you know, well. And they also have been an AI first type organization. So they've seemed to marry the concept of, you know, being technology orientated, an innovator, good with people. I give them a thumbs up to begin with anyway.

[00:23:31] And the other company I really like who has super high EX scores and super high business performance in their sector is Delta Airlines. So they have brilliant scores in our system around the business strategy, the frontline colleagues understanding the business strategy and lining up with it. Whereas most of the other airlines have really poor scores on that.

[00:23:55] And Delta scores as well on our platform have them highly predictive of their CSAT score. So all of the data around Delta between the stock price, the CSAT, the way that the employees and the leadership collaborate, they're like a star performer. And I love airlines as clients. I find them really interesting organizations. But Delta is a bit of a rock star, especially in a U.S. context around how they've managed to navigate good with people, good with business, good with customers.

[00:24:24] Yeah, except they're taking my Biscoff cookies away on shorter flights. So we'll see what this number looks like next year. Well, maybe that's the tariffs. You'll have to get some American cookies. Right. I think they're Italian. Yeah, whatever the Paducah, Kentucky version of Biscoff is, that's what we'll start eating. Well, I'm so glad we're having this conversation. You know, we've talked about best in class and what that looks like. But you have this term that floats in your ecosystem called unhappy performers. Can you tell me what that is and what it means?

[00:24:53] Yeah, unhappy performers would be... And again, you're going to start asking me to call out names of companies in a moment. But like, it's up there on the website. People can read it. But it means that the company is doing well economically and their business model or maybe their product is excellent. And they're knocking it out of the park on their stock price.

[00:25:12] If you take our model at the moment about where we looked at the S&P 500, but they've got poor scores on a range of things to do with how their workforce maybe perceives the environment wherein they work. So that probably means they're winning economically. But the people who are, you know, riding the horse aren't that happy. Yeah, yeah. I mean, you don't need to name names because we can all name the names in our head, at least self-perceived of these organizations.

[00:25:38] So a lot of these companies have either done a lot of, not damage, but they have a lot of repair work to do maybe about how they're trusted by the public or they've been very brutalist to their colleagues. Oftentimes, these companies are very strong, you know, AI first, tech first, AI native transforming companies. And they might be very profitable, but they're shedding truckloads of their workforce. Many of them are household names.

[00:26:07] So you could say that they're interesting in that they show you can do great business and maybe not need to worry so much about all the characteristics about how your employees experience things. But there's also a group on the other side who are doing great with people and great with their stock price. You know, so you can do it both ways, I suppose. And the group who's doing the unhappy performers is much smaller, you know, in terms of the happy performers.

[00:26:36] So in general, it's much less likely to work. So if we look at our S&P 500 study, you know, when you go out across five or 10 years, I don't think that ultimately it's a sustainable strategy for most companies to say, I'm going to build a great business and perpetually have my people traumatized and unhappy. The evidence supports that there's way more in the happy performers. Well, as we say in my family, from your lips to God's ears, I mean, that's the goal, right?

[00:27:03] To make sure that more people are moving to that upper right quadrant and that the workforce, the conditions, the overall just sentiment around capitalism and the directionality of it moves the correct way. But I think there will always be this group that just is profitable and is growing, but tries to do what it can to minimize the cost of labor, doesn't really prioritize the experience of labor and doesn't care. Doesn't care, right? It's also a bit more nuanced than that.

[00:27:32] And I think any of the companies, whether they're in, you know, the top right quadrant or the bottom, whether they're being painted as good or not so good or high performing but not great with the people, it's worthwhile them kind of click it onto their dot because it brings up how they measured on each particular characteristic out of the 24 things in the model. So what you could have is you could have a company that is an unhappy performer, but they could be exceptionally good at certain things about people understanding their strategy.

[00:28:01] They could be great at career progression, great at learning. They could be exceptionally high performing. And maybe it's bifurcated that maybe a third of the workforce think they're great and two thirds are extremely unhappy. Now, I would expect that probably to be the case because we're looking at an organization in its totality. So those high performing companies almost certainly have a subset of people who are really enjoying things. But it's not ubiquitous because they're going to be good at certain things.

[00:28:30] It just means that they're probably good at certain things like that maybe are to do with execution or alignment around the mission. But like they could be horrendous at things like flexible working or kind of taking care of people or the way people feel un-listened to maybe, you know, because maybe the company isn't really that interested in listening to their opinion because it's so busy doing what it wants. You know, but it doesn't mean the company won't be successful.

[00:28:56] But if they click on their own dot, they can bring up like the high level data of what goes on at subscale level. Well, I think we're all tracking on the nuance and I really appreciate that. I really appreciate the fact that you drilled down on that because if somebody listening to this podcast wants to know where their company actually stands, what should they go look at first? Where should they go? Well, if you're in that S&P 500 group or you want to understand how we work,

[00:29:24] like you just need to go into waliba.com and on the top of the web page, it has the S&P research. And you can go and look at any of those companies there and start to see, you know, what kind of things are driving good or less good outcomes for any of the organizations. And then we've loads of other studies where we've ran this on the Nikkei 225, the Euro stocks. We've ran it on the top 100 retail banks in the US, the top 100 global airlines.

[00:29:52] We've ran it on all the hospitals in the United Kingdom. We've run it on loads of US. Like there's loads of data on how, I know it sounds a bit anachronous, but we've got loads of factors that are connected to profitability of hospitals. You know, with things like readmission rates and litigation. You know, like I know that the primary thing about a hospital should be like patient care and clinical outcomes.

[00:30:19] But that's one of the, if you're running hospitals, they're expensive places to run. And they tend to run over budget and make losses very easily, as we all know. So like, you know, the owner and operator of a healthcare network would be very interested in, OK, what's the kind of characteristics in my people that tend to lead to keeping the car on the road? You know, when I'm trying to run the hospital as well as take care of all the patients, you know, that I'm not going to lose my shirt while doing. We all watch the pit here in America.

[00:30:48] And so we're all acutely aware of the drive for profitability and the ability to fund things well and unwell in organizations. I think that conversation is in real time in many of our families just from that show. So that's really fascinating that you focused on some of that data and collected that. And I'm just so excited for people to head on over to your website and learn more about you. Why don't you tell everybody where they can go and what they can find?

[00:31:12] So if you go to waliba.com, you will find like a very easy explanation of how our platform works. You'll be able to sign up for a demo. You can see the white papers, the scientific models, and you can get live access to that S&P 500 research. And if you're in there, you can learn quite a lot about your own companies and your peers in the sector or competitors.

[00:31:34] Or you can use the platform in order to kind of understand the principles yourself of how, you know, public data, generative AI, agentic systems are all used to kind of in effect now do in minutes. You know, what historically had taken management consultants and HR departments months.

[00:31:52] It's a big disruption and a transformation, but in a way that maybe makes, you know, the information more democratized and available to everybody, you know, without needing enormous systems. Yeah. Well, if people want to learn more about gravestones and fast food and advertising, where can they connect with you? Well, you can find me, if you put in David Barrett into LinkedIn, you'll find me. Yeah. So if you put in, there's a lot of David Barretts in the world.

[00:32:22] There's two other chief executives of other, two other technology companies called David Barrett as well. One called Expensify, another one called Intercom. And they're both quite biggish companies. So I'm David Barrett, Lockray, L-O-U-G-H-R-E-A, or else Galway, G-A-L-W-A-Y. Wonderful. We'll make sure we include the URLs in the show notes. And I was just so pleased to spend some time today and hear your story and learn more about what you're doing to fix the world of work. Thanks for being a guest.

[00:32:52] Thank you, Laurie. It was lovely being with you here today. Hey, everybody. I hope you enjoyed that conversation with David Barrett. Here are three things that stood out to me from our chat. The first is that I didn't quite realize how much publicly available data there is out there, not just on the S&P 500, but on most companies.

[00:33:15] The second thing is that while EBA's data showed that the biggest EX driver isn't perks or flexibility, it's still the manager and the coworkers. That's always going to be important, sometimes more so than the benefits and programs that you're excited about. Finally, I'm really struck by the companies making money but burning people out.

[00:33:38] David called them unhappy performers, and that language is going to stick in my head probably for the rest of my life. I really love this conversation with David. I hope you connect with him on LinkedIn and check out Waliba and their really awesome S&P 500 study on EX. Punk Rock HR is produced by RepCap. They're a B2B content marketing agency who help organizations tell clear human stories that connect.

[00:34:07] Whether you need strategy, customer interviews, or full production support, RepCap turns complex ideas into compelling content that moves business forward. Learn more at RepCap.com. Punk Rock HR can also be found on the Work Defined podcast network along with hundreds of other work-focused shows. To listen or learn how to advertise, head on over to WorkDefined.com.

[00:34:34] That's W-R-K-Defined.com. And finally, if you enjoyed this episode, please leave us a five-star review wherever you stream it. It really helps the show. Now that's all for today. I've got some advice for you. Be safe, be kind, and don't sell out.