Is your benchmarking built for a market that keeps moving?

[00:00:00] [SPEAKER_00] Join us on a journey where we unravel the latest trends, tackle your burning questions and explore innovative strategies that are shaping the future of compensation, all with a coffee in hand. Hello and welcome back to another episode of Comp and Coffee. I'm Ruth Thomas, Chief Compensation Strategist here at PayScale and today I'm going to be joined by our Chief Product Officer, Pay Tane.

[00:00:25] [SPEAKER_00] Now, Pay has been on the podcast a couple of times before. We've talked about some of our roadmap launches, but today we're going to have a slightly different conversation. I've asked him to come onto the show to talk about his observations of the compensation management market, the work that we do in compensation and how that's been changing in the time that he has been with PayScale. So Pay, many of you will know, came from a technology background, so he hasn't spent his career in HR tech or in compensation management.

[00:00:55] [SPEAKER_00] He definitely brought with him a fresh perspective on how compensation works and how technology could rethink some of the processes that we've been doing for a very long time in compensation. And it's been very exciting to partner with you, Pay, over the two and a half years that you've been here at PayScale and really just kind of like share like some of the thoughts and processes that you've brought to how we approach compensation.

[00:01:20] [SPEAKER_00] That's been something really exciting. I've enjoyed it. I wanted to share some of those insights with the audience today. So Pay, welcome back to Kompon Coffee. Let's remind the audience, what is your go-to morning beverage? Are you a tea, coffee or something else person?

[00:01:35] [SPEAKER_01] Coffee. I'm definitely a coffee person. Now I am going full black. That's about it. Nothing on it is black coffee.

[00:01:43] [SPEAKER_00] And how many of those do you need to have in the day to get you going?

[00:01:47] [SPEAKER_01] Too many. Too many. I try to restrict myself to not more than two, but that is the few that kind of keep the day going. But it's good. I've been building up that habit for too long.

[00:01:57] [SPEAKER_00] Well, as we record this, where are you based, Pay?

[00:02:00] [SPEAKER_01] I'm in Indiana. I'm in the Midwest of the United States.

[00:02:04] [SPEAKER_00] Yeah. And obviously I'm in London. So it's definitely afternoon tea time in London as we're recording this podcast. And so coffee and tea, that kind of makes sense. All right. So let's start with what you saw when you first got into this space. Compensation professionals understand how complex the work can be. But when you took a look at it with fresh eyes, you maybe noticed things that people working within that process every day had learned to accept.

[00:02:30] [SPEAKER_00] So when you first joined PayScale, what struck you most about how organizations were managing compensation and maybe what surprised you in that?

[00:02:39] [SPEAKER_01] Well, first of all, thank you, Ruth, for welcoming me back to Comp and Coffee. I'm glad to be here and has been two and a half years working together. Really happy that we get to do that. I think a couple of things. When I first joined PayScale and being new to the industry, when I was talking to different folks, folks like Ruth, some folks in the team, and also a lot of our customers, every single time the word benchmarking, job matching, it's kind of core front and center of everything that they do.

[00:03:07] [SPEAKER_01] And they have always been asking for better tooling, workflow, software to help them make it more efficient so that they can do it faster and get more up to date. After a while, looking through that, I think I come to quite a slightly different conclusion in terms of what they actually are looking to solve. At the end of the day, if you kind of look at why we're doing all this benchmarking and all those, they are trying to make a decision.

[00:03:33] [SPEAKER_01] They're trying to basically use market data, benchmark data, structure it, create whatever composite that is aligned to their organization so that they can actually make a much more high-confident decision about their compensation for their organization. That is the problem they're trying to solve. Benchmarking, job matching, it's just along the way that they need to do that. But ultimately, applying the science and the art to be able to create and make the right decision is the real problem to be solved.

[00:04:01] [SPEAKER_01] And I do kind of see the industry has been very much focused on the operational technical part and might have not invested enough in helping solve the real problem. The first principal problem is to make decisions.

[00:04:15] [SPEAKER_00] And as you spent time with customers, because I know you spent a lot of time on the phone with customers here at PayScale, what did you hear about the challenges? What challenges were you hearing consistently from them? Did that align with your initial observation?

[00:04:28] [SPEAKER_01] I think the challenge is fairly aligned, but sometimes it might not be fully articulated correctly. I think I can draw an analogy that I was just sharing with someone early on. A lot of times, in order to kind of figure out what the compensation that you want to build for your organization, the first thing that you want to do is you need to have a job architecture. And then from the job architecture, you want to be able to benchmark it. And then after benchmarking, you need to create a structure for it and then subsequently operationalizing it.

[00:04:58] [SPEAKER_01] But it's easier to kind of talk about it from the perspective. I kind of draw the analogy to like the stock market, right? You kind of have the stock market S&P 500, the Dow Jones Index and so on and so forth. What you're trying to do for your organization is really creating a composite of different jobs from different market data that you want to use to benchmark against the standard index that's out there that works for you, for your organization.

[00:05:25] [SPEAKER_01] The complexity, the challenge is coming to define the composite, make adjustment to the composite, make tweaks, because every job within every organization is a bit different. And how do you actually systematically apply that and keep that composite consistent when you use the benchmark is key. And a lot of the things that is being built in the software is to help you do that more effectively and more efficiently.

[00:05:50] [SPEAKER_01] And I think as we all kind of see in the world today, there's a lot of AI that is being tossed around. That is a technology that can unlock to make that much more concrete and useful and make the life of creating the composite and benchmark easier, more up to date and more real time.

[00:06:07] [SPEAKER_00] If we're honest with ourselves, there was an awful lot of the work that we were doing on a day-to-day basis that really deserve to be automated. And AI has really helped facilitate that with the processing, like large volumes of data, making workflows more efficient and effective. And I guess, I mean, something probably you also observed coming in, which, you know, I've observed for a long time, was that still so many people were managing compensation on Excel or on spreadsheets.

[00:06:36] [SPEAKER_00] And, you know, that had been a long-held kind of status within this segment of compensation technology. Did you have a solution of like, how was I going to get people off Excel?

[00:06:47] [SPEAKER_01] I think the main thing is, to a certain degree, people see compensation management as almost like a tax that they do periodically. So having it in Excel that I need to revisit only once every six months and once every 12 months is not good, but maybe acceptable. But as you kind of look at the market today, information is readily available at the fingertip.

[00:07:12] [SPEAKER_01] The employees, the organizations can get information fairly quickly with ChatGPT, Claude, or whatever that might be. So having it in Excel and lock it without having a tool that you can continuously manage and keep up to date is now becoming a blocker for you to be able to do the work effectively. So as you kind of think about how things is actually getting evolved, there's multiple things that are changing.

[00:07:37] [SPEAKER_01] The user or the employees have way more access to data, way easier, and they're asking a lot more questions. Information is now not organized or locked in certain Excel. You have multiple copies of it, and they create a lot of additional overhead to kind of unlock the insights and value to help the organization move. By having those information in the system that you can manage effectively is going to be key for you to basically keep up with how things are evolving in the market.

[00:08:05] [SPEAKER_01] So from my perspective, I think Excel is sufficient, but as fast as how the workforce is transforming because of AI and how much customer or employee have information at their fingertips, it will no longer be sufficient if you want to compete effectively in the current market.

[00:08:22] [SPEAKER_00] And we're going to come on to talk about always on, which I agree with you is kind of like one of the key reasons we think leveraging technology has to be the answer here. But I guess coming back to your initial observation, what was the magic moment that the compensation or HR professional was trying to do? And that was like really making a defensible decision. Now, you told a story at conference. So we just recently here at Payscale had our annual virtual conference. I'm sure many of you probably attended that.

[00:08:51] [SPEAKER_00] We had a great reception this year. If you didn't, check out Payscale.com and you can find access to conference and all the sessions that took place over three half days. But Pay was in the product keynote, obviously, and you told a story there which really resonated with the audience. And I'd love you to tell that story again, just because it was a fantastic story.

[00:09:11] [SPEAKER_01] Yeah. So I think it is a story that I actually read on LinkedIn. And when I read through their story, it resonated really well with me. And I think that is worth sharing in terms of the work that folks in the HR and compensation space do.

[00:09:27] [SPEAKER_01] I think this story revolves around a company where the CFO walked into the HR director's office and basically say, hey, we need to take $2 million out from our budget this year, given the trajectory of how the business is growing. And we need to do this so that we actually come out as a much healthier company on the other side. And we need to do this quick. You have to do this Wednesday or this Friday to get it done.

[00:09:57] [SPEAKER_01] You have this week to get it done. And if you kind of think about it, $2 million is a lot. That is somewhere depending on the organization, between 9 to 15 people that you actually have to take out to basically be able to kind of make that a shortcoming in the budget.

[00:10:13] [SPEAKER_01] So the whole story revolves around the HR director going back and then figuring out how to actually build an organization that delivers that kind of $2 million savings. At the end of the day, because they have actual data, they know how things are going, they are able to make slightly different decisions that actually help move the organization forward. The HR director was able to kind of look at it and say, hey, maybe we can not fill these two roles.

[00:10:44] [SPEAKER_01] We can move these three people into revenue generating position. And then we can allow these two or three people to have early retirement. And then we can cut certain contractor or consultancy spending. At the end of the day, he's able to reduce the number of headcount that needs to be reduced from 15 to like six people and able to save that nine additional headcount that might be on the list because of the budget constraint.

[00:11:14] [SPEAKER_01] And that is done because they have the data to be able to make the decision. But the main thing that kind of really resonated really well with me is no one, literally no one will ever find out the hard work that the compensation director or the HR director has done to make sure that they minimize the impact.

[00:11:33] [SPEAKER_01] They sit in between the business and the employee and have to manage and basically show the professional face to both sides to help minimize the impact for the employee and also help the organization towards a much healthier state. If you kind of think about it that way, it is a little bit of a thankless job.

[00:11:54] [SPEAKER_01] But we all here are glad that there is someone that is doing that to actually protect the workforce and make sure that whatever thing that needs to be done is done in a very, very empathetic way and also very humane way. So from that perspective, I think the story that I share is an appreciative story.

[00:12:17] [SPEAKER_01] Thank you for all the HR director out there who has gone through this, I'm sure, a couple of times, if not multiple times. And thank you for the work that you have done and you make it easier for the employees, even though they might never know that all this work happened behind the scenes.

[00:12:33] [SPEAKER_00] It was a lovely story. And we just again reiterates that we're here to like value people in the organization, which is a very difficult and sometimes sensitive thing that we have to do. And I guess, you know, you said at the time in the product keynote, that's essentially who we're building for here at PayScale. And we know, obviously, the pressure on them is only mounting with demands around pay transparency, pay regulation, and as you said, like shifting work. So let's move to that point. We know that the world of work is changing rapidly.

[00:13:03] [SPEAKER_00] People's jobs are being disrupted by AI. New data sources you mentioned earlier are available on a more frequent basis. We are going to talk about data. We talk about this kind of like the always on scenario. So, I mean, I've obviously been doing compensation for a very long time. Traditionally, our whole life revolved around an annual cycle. And now the decisions are happening much more frequently outside of that cycle.

[00:13:29] [SPEAKER_00] So give me your perspective on always on and how we should be thinking about that in the future.

[00:13:35] [SPEAKER_01] If you kind of think about why compensation is being done on a yearly or bi-yearly cycle, I think it comes down to a few things. It comes down from the legacy where surveys that is being used to benchmark data, the benchmark jobs are only being published or being collected and made available once a year. And then second, budget is also being made available and planned once a year so that you can kind of upgrade that.

[00:14:03] [SPEAKER_01] If you kind of think about even when those things are true, when you do all this planning once a year, there is so much email, Slack messages and other messages that happen along the way throughout the entire operational of the year that forces you to go back and revisit constantly, right? There are a lot of adjustment, compensation, benchmarking and activity that happen along the way that is outside of the yearly process. Why? Because the jobs are moving.

[00:14:32] [SPEAKER_01] You're hiring from different markets. People are coming in with higher expectation. Jobs are collapsing. All those things are changing very, very rapidly. Whether we acknowledge it or not, the once a year process might be there because of legacy, but no longer sufficient in the world of how quick the workforce is transforming. So the always on part of it is something that we already do. We are just not doing it in the proper systematic way.

[00:14:59] [SPEAKER_01] We are doing it in email and Slack and being reactive towards it. So what I truly think about is as data become much more readily affordable, budget is being managed through where there is ability to kind of make adjustments to kind of adapt to the workforce. Always on should become front and center where you update your process with the data to be able to do it very consistently so that you are able to keep up and compete effectively.

[00:15:26] [SPEAKER_01] And when I say keep up, this is more around what you are already doing, but formalizing it to be much more proactive about acquiring data that is real-time so that you can actually make an informed decision and then continuously keeping it up to date so that you're consistent throughout the entire year or multiple years rather than, well, let's look at it this year and let's wait for 12 months, come and look at it again.

[00:15:52] [SPEAKER_01] You will manage a much bigger drift and much bigger problem to address down the road rather than continuously keeping it up to date. Always on is something that we already do. If you talk to any hiring manager, they are already doing it, managing the employee, asking for promotion and everything. It's not something new. We have just not talked about it and think about it in the context of compensation across the entire way that we have done it historically.

[00:16:16] [SPEAKER_00] And I mean, it's just speeding up. We have a product called PayCycle or our compensation planning tool. When we look at our customer base, we see 42% of that customer base, I think, do two cycles a year. So we've got over half of the customer base, you know, knowing that they've got to keep pace with the market and doing two cycles a year. And I think we're just starting to see from our customers that demand is happening more frequently than that. Let's stick with the PayCycle product. Let's talk about Always On because that is the new strategy of PayCycle.

[00:16:45] [SPEAKER_00] Do you want to talk about the thinking behind that?

[00:16:47] [SPEAKER_01] So the new PayCycle product that we launched, I'm so excited about the thing that we have built. We kind of realized that what I was just talking about, Always On is here, people are doing it in very bespoke tools like email, Slack and other channels that is outside the system. And then towards the end, you have to reconciliate that and say, hey, what happened to this employee? How come this thing changed and you have no history? Especially if someone leaves, you have to dig out the email and all those.

[00:17:15] [SPEAKER_01] It's super complicated to do. What we have to build, PayCycle, Always On, is to solve that problem. Compensation is now Always On. It's not just once a year or twice a year cycle. You have a budget. You have rewards. You have retention. Everything is in it that is in one single tool that you can allocate your budget.

[00:17:35] [SPEAKER_01] You can specify and managers have the information about the employees, when is the last promoter, what is the performance and so on and so forth in a single tool. So when you actually need to request a retention bonus or out of cycle promotion and all those, you are not going through 17 different emails to 10 people asking for budget, asking for approval. You look into a single tool, what is the history with all the justification that is needed about that employees,

[00:18:05] [SPEAKER_01] whether budget is available or not available, locate, and then go through the tools for systematically approving it. And you can do all this yourself continuously to scale your organization towards an Always On compensation planning and compensation operation. That is what we have built.

[00:18:23] [SPEAKER_01] And we have built this from the ground up with that in mind so that compensation just become part of the operating system of your organization that you drive throughout the entire organization, rather than a process that a select few focus on and do once a year and revisit every single period of time.

[00:18:44] [SPEAKER_00] Yeah, because what we were hearing from our customers was, and then maybe you're listening in and you are a pay cycle customer. What we were hearing is that the managers of the main user on that platform, they're coming into that platform to make pay recommendations. They would get access for maybe two weeks a year. Some of the large organizations, they would have like a six-week cycle.

[00:19:04] [SPEAKER_00] But then when that was switched off, they lost all visibility into that kind of peer-to-peer relativity and the depth of information around pay history, promotion history. And they lost sight of all of that. And that was what we really wanted to think about making available to managers year round so that every time someone's coming to them with a challenge about a pay decision, they're able to make a much more informed decision. And that is kind of really one of the key goals of pay cycle Always On.

[00:19:32] [SPEAKER_00] The challenge there is, this is part of another theme I know that we've worked a lot on pay, which is like democratizing who has access to pay data. That's been a big theme of yours. And you want to pay intelligence, compensation intelligence to be the connective tissue. Do you want to talk a little bit about that and why you think that's an important development?

[00:19:53] [SPEAKER_01] I think historically, depending on the organization, the pay information is being transparently shared. Sometimes it's actually hold fairly tightly between a small group of folks. I think the big changes that is happening is the information is now readily available, right? Someone can go into ChatGPT, Claude, or even just Google and say how much we should pay for someone. And ChatGPT or Google will show you this is the range, these are the sources and all those things.

[00:20:21] [SPEAKER_01] But that might not be what is reflective of your organization's comp philosophy or the role that your organization is actually hiring that person for. So instead of allowing folks to go to public sources that might not be authorized, that might not be reflective of how the compensation philosophy work and how they actually are getting benchmarked and autos,

[00:20:45] [SPEAKER_01] one key important thing that I always believe is build a compensation intelligence platform that actually exposes the right contextual information, not just to the comp pro, but also to the employee so that they actually can tell and know where they sit within their range and how their role get valued. Because every organization define a role differently.

[00:21:08] [SPEAKER_01] And because they're different, you searching for a software engineer publicly that gives you a different range doesn't mean that they are the same job. They just have the same title. And that is what creating a lot of, not confusion, but more around the discrepancy between what the employee expect and what the organization want to do. And connecting all this and make a single source of truth that you can expose to your employees will help build morale, transparency,

[00:21:36] [SPEAKER_01] and be much more helpful as you kind of drive the organization and workforce forward.

[00:21:42] [SPEAKER_00] Now, you talked about a little bit about data and the availability of data. Data is obviously something that you've had a focus on as well since coming in to Payscale. And we've, you know, we've kind of evolved our data strategy there. We had a long pedigree, the Payscale history, you know, the two decades of, like, managing pay data. When you joined Payscale, what did you think the industry needed to get right about compensation data? And what have you learned since, I guess?

[00:22:11] [SPEAKER_01] I think one of the major things that I've learned since I joined the industry is very much what I just described, right? The data from a lot of the trusted sources or through the survey provider is at least a year old. You're using a year old data to try to make a decision, today's decision for a future workforce. That seems to be partially broken for me from my perspective. It's also not the lack of more real-time data.

[00:22:38] [SPEAKER_01] There is real-time data or near real-time data that is available by different providers. And the way that I kind of think about it is you want to use survey as a way to form your structure. And then you want to use the real-time data to inform you directionally, are you on the right track? Historically, most of the folks just age the data forward, right? Just draw a line across and see how that will look like in the future.

[00:23:03] [SPEAKER_01] But with job and workforce transforming so significantly in the AI world, that might not be good enough. And having real-time data that reflective of the market today, allowing it for you to plan for the future is critical for you to be successful.

[00:23:17] [SPEAKER_01] So I do see there is a place for survey data that is also a much more important phase that is becoming much more real for real-time data to kind of work hand-in-hand to basically build a much more market representative of your benchmarking and help build a con philosophy that reflects the market reality.

[00:23:38] [SPEAKER_01] So I think that is the key component that makes data much more valuable than ever compared to historically, especially when jobs are moving so fast and they're quickly decomposing and recomposing as roles are morphing and merging.

[00:23:54] [SPEAKER_00] It's about to that kind of always-on challenge. We need data that's fit for the always-on world. Obviously, that's what we've done. We focused on the peer data asset, which is our HRIS reported data. And we've kind of like really focused on honing in on amplifying that data set, growing that data set, improving the quality of that data set, and also how we deliver that to our customers to solve the different problems that they may have around data.

[00:24:23] [SPEAKER_00] And you've been kind of really instrumental in architecting that peer data strategy. Let's talk about AI. We can't have a conversation nowadays without talking about AI. We've talked about how compensation has changed. We've talked about the need for better data and how technology is making teams make more informed decisions more frequently. But let's look ahead. There's a lot of conversation about AI and automation right now. And in the world of compensation, that's obviously no exception.

[00:24:50] [SPEAKER_00] You have some strong views on how AI can help solve the compensation challenges. Do you want to talk through your model of the different ways in which AI can help with the work that we're trying to do every day?

[00:25:02] [SPEAKER_01] 100%. 100%. 100%. AI is my favorite topic at this moment, that you cannot open any website. You're not looking at the word AI showing up. So the way I kind of think about it is we are now entering the phase of leveraging AI to be the intelligence part of the whole entire compensation.

[00:25:19] [SPEAKER_01] I think at the earlier stage, AI is basically being seen and used as an efficiency mechanism to make your workflow more efficient and help simplify the workflow that you have created across the board. Now we are entering an era of intelligence. If you kind of look at how PayScale has evolved its AI first strategy, we have reframed from putting a text box and let you chat with your data and call it AI.

[00:25:48] [SPEAKER_01] We think that at least from my perspective, that is a very good demo where, but on the day-to-day activities, it doesn't seem like it's a thing that actually accue value towards it. Where I see that changing and evolving is AI is going to be the component that you leverage to turn and minimize the work that you need to do to actually enable this always-on compensation that we have been talking about.

[00:26:13] [SPEAKER_01] Historically, a yearly cycle, you have to go in, benchmark, create structure, and so on and so forth. Imagine a world where you have an AI agent behind the scene that has taken what you have created over the years and then start monitoring it for drift, for changes, for adjustment with real-time market data.

[00:26:32] [SPEAKER_01] And anytime that it detected a consistent drift, it notifies you and tells you that, hey, we have seen a shift in this particular role, especially in Sacramento, California, that impacts seven different employees. You might want to review and take an action around it. And then if you do take an action around it and adjust this, this is how you're operationalizing it with a pay cycle or whatever a comp planning tool is.

[00:26:58] [SPEAKER_01] That kind of turns compensation into an always-on use design. And there is an AI behind the scene that's continuously monitoring, identifying drift, informing you rather than wait for 12 months or 24 months when you lose some employees and say, hey, you need to make some adjustment. It's too late now. That is something that is not available historically. Technology wasn't matured yet.

[00:27:21] [SPEAKER_01] AI now can deliver that to you and then remove the need for you to continuously go proactively look at certain things, let AI do that for you and inform you when there are changes that needs to be done. That is how I kind of see AI in compensation that is going to truly transform the potential grant towards task of making always-on compensation into something that you don't even think about.

[00:27:45] [SPEAKER_01] And you just have a helper behind the scene working on your behalf continuously and drive towards a much, much more market-driven compensation philosophy for your organization.

[00:27:56] [SPEAKER_00] We obviously spent a lot of time focusing on the core workflows in our products, which we now know. Those of you that are pay scale solution users, you know that we call them smart workflows. So, you know, we've introduced different smart workflows. But this next phase is really like once the work is automated, what are we doing with the outputs from those workflows? And how are we keeping up to date with the drift? Like that often was having to be monitored manually.

[00:28:24] [SPEAKER_00] Now we're going to monitor that for you. And then you get to the point of like making a decision or what's the right strategic thing to do to fix things that are being highlighted in this drift.

[00:28:34] [SPEAKER_01] The decision is always going to remain with the human and the structure. This is a tool that just make it easier to highlight the things that you need to pay attention to versus all the noise that you do not need to pay attention to. And I think that is where this will evolve towards and make this whole thing come to life.

[00:28:54] [SPEAKER_01] And it will become almost like a table stick because I think the point in time that you wait for someone to leave the company before you make adjustment or someone to escalate because they are unhappy will become a thing of the past once you implement some of this in your organization.

[00:29:10] [SPEAKER_00] And so comp leaders who are trying to prepare for this shift, what's one thing you think that they should start thinking about or doing now to get themselves ready for this always on era?

[00:29:20] [SPEAKER_01] I think a lot of organization is going through some sort of AI transformation. You should think about this in terms of your organization, in terms of how do you actually modernize your compensation practice? I think when I say modernize, there is a couple of things that is involved. First, get your job structure, job architecture. Before you benchmark what you hire, you need to know what jobs you have and are they up to date. If you have not updated your job profile for the last three years, it's time to dust it up and kind of do some work there.

[00:29:50] [SPEAKER_01] Then the second component is make sure that you are adding the additional data set for benchmarking. Like, for example, you should definitely continue to use survey, but augment it with real-time data so that you know if the market is shifting faster than the survey that has been produced a year ago. Because wrong data in, wrong data out, right? There's no option around it.

[00:30:13] [SPEAKER_01] And then once you have both your job done correctly and you have the data source, now it's the investment in the process, the organizational process and workflow to be able to adapt to this always on information that keeps coming rather than once a year practice. And then kind of build towards that. Those are the three major things to look into to modernize your compensation practice moving forward.

[00:30:37] [SPEAKER_00] Great. Thank you. Well, thanks for taking the time today to join me, Pay, and sharing your perspective with the audience. We'll be interested to hear what you thought, everybody listening in to Comp and Coffee. I think you can tell that, you know, obviously, Pay spends a lot of time thinking about the work that you're doing and how he can help to improve and augment that work. If you're a customer and you haven't had a chance to meet with Pay, you can always raise your hand.

[00:31:02] [SPEAKER_00] You'll come and have a discussion with you about maybe the future of how you're thinking about compensation. But just really appreciate you taking the time to share your perspective today. We know the pace of work is changing and the information that you need as compensation teams are changing. And having someone like you around to help us get ready for that future is really encouraging. So thank you, Pay.

[00:31:25] [SPEAKER_01] Thank you for having me. Thank you, everyone.

[00:31:26] [SPEAKER_00] Thanks for listening in. If you've got any questions or a topic that you'd like us to explore in a future episode, then do let us know. You can reach out to us by email at coffee at payscale.com. That's coffee at payscale.com. Love to hear from you and what you're thinking about. Until next time, thank you very much.