Пълният препис на Rewrites, Rebuilds, and Reality Checks: Greg Laney on Workday Implementations, Better Data, and Smarter Decisions

sudden pivot to applying for graduate schools and I started a job as a recruiter. While my applications were still out there, I worked for a recruiting company. I recruited telemarketers for a famous three digit phone firm that has an and in the middle of it and in South Florida. And I recruited for that until I started grad school. From there I recruited for a three letter delivery service company. Then I pivoted eventually to generalist type roles. 7 00:03:18.000 --> 00:03:43.000 Well, I'm so glad that you escaped the recruiting world and let's tell about it. So and again we'll talk about really different aspects of your entire career. So obviously when I met you, you were over systems at I think at a workday customer and you've done that at a couple of workday customers if we're going to get workday century. But you've been across responsible for all different kinds of systems. So what kind of got you into that kind of role? 8 00:03:43.000 --> 00:05:12.000 It got me into systems. So it was actually funny. I was at a company and I'd been doing compensation from 2003 to about 2011, 2012 or so. And I was actually at a point where I was interested in trying something different. I was leveraging a lot of technology and I was always drawn to technology by using things like VBA for Excel and using access databases and web database design. So I was always doing techie type things. But I do not have a computer science degree and so I was approached by someone to work on a. It was an internal data mart system that looked at HR analytics. And so I got into that about 2012 and a little later after several months my boss approached me and said we'd signed a contract with Workday and you know, at first it was no harm, no foul. Few months went by, I was still doing my analytics. Then it turned out that who knew that workday is actually greater than all of us. And it took a lot of effort and they brought me in to actually manage a team of. We had HR and payroll people that had overnight transitioned into H R I S analysts and so we were heavily involved. My areas of specialty, I was heavily working on reporting because that was an area I was focused on reporting and then also security and then Also business processes. So heavily involved with, on a global scale business processes. 9 00:05:12.000 --> 00:05:23.000 So one of the things I want to talk about that because, and again, I'm going back to our conversation that we had before is you were talking about when you guys went live because you said what, 2014, is that right? 10 00:05:23.000 --> 00:05:25.000 It was 2013. 11 00:05:25.000 --> 00:05:44.000 We went live 2013. Okay. So that's still kind of early on in the days when, you know, you're starting to see all these people that are implementation partners, new implementation partners and things like that. And I think you said that, you know, it's kind of maybe the blind lead the blind or it was like doing the implementation and leaving and stuff like that. Kind of expand a little bit on that. 12 00:05:44.000 --> 00:07:20.000 Absolutely. I'll give a shout out to one of my colleagues named Kathy. One of her favorite sayings that fits this, that hits exactly what you were saying is it's like we're building the airplane while we were flying it. And so that's really what it was. So it was interesting. So we had a team of people that were familiar with ADP Enterprise, they were familiar with the systems that we had, and we were familiar with the processes that were used within the company. So how things had always been done was what we were familiar with. We had workday consultants that came in and this was very early in the implementation. So I think everybody was trying to figure out what they're doing. So you had someone that was, you know, the senior person was always 20 years experience in all these other systems. And oh, by the way, they just got into workday because it was the new kid on the block. And then they had a bunch of consultants that were typically two to three years out of school that had done one or two implementations. And the challenge that we ran into, and I didn't really recognize it at the time, but the challenge at that point was they would say, this is how you have to do it. This is how you have to do it in the system. And it was always, workday is configurable, not customizable. And we kind of knew this is what we wanted to do. And they knew, well, this is what you should do. And then we just kind of had to battle back and forth. Now the funny thing is wake, go down the road a couple years and you start to learn, oh, workday has other functionality that we could have done. It was just a consultant that we implemented with maybe wasn't familiar with that process, which that goes on to a whole other conversation of experience within the field versus certifications on specific processes. But I won't go down that path unless we do. 13 00:07:20.000 --> 00:07:23.000 That's a whole other podcast. 14 00:07:23.000 --> 00:07:38.000 Oh yeah. And honestly, one of the things I loved about our conversation previously, and this is you, you are definitely a storyteller. But you alluded was like the Greatest American Hero. So for many people will not even remember, was it not a suit? Tv. 15 00:07:38.000 --> 00:07:40.000 Tv? It was a TV show. 16 00:07:40.000 --> 00:07:49.000 Yes, but explain why you said that. You know, because this is really happening over and over and over again. But why you related it to that. 17 00:07:49.000 --> 00:07:59.000 Well, first of all, I'm a little embarrassed to remember that. I am actually old enough to remember the Greatest American Hero, so. And I used to watch that every, every week. 18 00:07:59.000 --> 00:08:02.000 I remember the song was a. I. 19 00:08:02.000 --> 00:10:06.000 Could absolutely relate to that show. I mean, and that's what it was. It was funny because we would build out a process and then two years later we would see that it wasn't the best way

to do the process or and I've got a story for this that will exemplify this even further, that will expand on this. But we would do something and then after a year or two of pain, painful results, we'd go back and we'd rebuild it. I can give you example of one instance where I went into an organization and they had a 12 page performance review process on paper. They did it in the Word document. And the first year what they did was they loaded the 12 page Word document into workday. It's like, well, you know, workday has a performance review process and you can do that. So then what they started doing? Well, the second year is really where I came in. They were then taking the 12 page process or what they'd done, you know, forever and ever. And they were putting that into workday. And so it's like, let's build out a 12 page performance review process in workday. And it's like instead of asking the why are we doing this? It was, what do we need to do? Well, we need to get this 12 page document into workday so that managers can have what they have. It wasn't necessarily of, well, why are performance reviews not completed on time? Why do managers hate performance reviews? If a manager ever goes back and looks at a performance review, what do they go back and look at? They'll look at people that are maybe getting promotions or if a situation where there's maybe there's a lawsuit or something like that and do they want the answer to all 12 pages of questions? And the answer typically is no, it's what did the person do that year? How did they do it? And then we need some sort of degree of rigor in order to be able to compare apples to apples with the people in the organization. And I think that was actually one of my bigger wins within workday was taking a process that was on paper that turned out to go into workday and then just blowing it up and rebuilding it to say, you know what, let's just have an easier process that a manager can go in and instead of doing one performance review over a two week period, maybe they can do three performance reviews in a day. Because it's just a one page document. 20 00:10:06.000 --> 00:10:22.000 No, I mean that's what the systems are for. Absolutely. You know, it does happen so much where it's like, let's just take what we were doing and put it in a new system as opposed to, as you were saying, why are we doing this? You know, why are we doing this process in the first place? And could it be better before we even try to get it into a system? 21 00:10:22.000 --> 00:11:19.000 Exactly. When you're building these processes, you really have to stop and you have to have people that can reimagine what that can do for the business. So you can't think of it like, I can't think of it as I'm an HR person. I'm going to implement whatever the HR business process is. I need to think, what are the pain points for the managers? Like, why are we purchasing this tool? Like, to be honest, it's funny because I love systems, but I will be

the first person to say, no, we don't need to pay for the system if it's going to add pain and heartbreak and cost. And we can do it for near free with like Excel. And I'd be the first one to say don't do everything in Excel, but because I love what workday does and I love all these other systems. But you have to have the buy in from the team, you have to have the desire to change and you have to have. There's a lot of have to, have to, have to haves before you're at a point where you're like, okay, now it makes sense to pivot from Excel or whatever the tool is to the better tool. 22 00:11:19.000 --> 00:11:38.000 No, that's so true. And I'm just going to go ahead and throw this out there for the people that don't remember what the greatest American hero was. It was actually a guy. Let's see if I have this right. He remember or he ended up having these superpowers. Is that right? Or he had a suit that had Superpowers. But he didn't have an instruction manual. Is that right? 23 00:11:38.000 --> 00:11:39.000 Yeah, yeah. 24 00:11:39.000 --> 00:11:40.000 Learn as you go. 25 00:11:40.000 --> 00:12:06.000 I remember at the very beginning where, like, he had a briefcase or something like that, and you saw the. The instructions manual fall out of the briefcase. He was walking off. And then from what I remember, the show was. The entirety of the show was he was trying to figure out how to do it. Like, there would be an episode where he didn't even realize he had this particular superpower. But then all of a sudden, it's like, wow, there it is. And then it was, how do you harness that superpower to solve that episode's challenge? 26 00:12:06.000 --> 00:12:12.000 And that is a world that everyone that does system implementation lives in. 27 00:12:12.000 --> 00:12:17.000 Anybody that's in HR systems is living the Greatest American Hero. 28 00:12:17.000 --> 00:12:23.000 We'll see how much on Netflix. All of a sudden, that's going to get all this streaming. Everyone's going to be watching Greatest American Hero. 29 00:12:23.000 --> 00:12:26.000 They're going to wonder what. 30 00:12:26.000 --> 00:12:28.000 Any royalty involved with that. 31 00:12:28.000 --> 00:12:32.000 Will you get a cut if they do? You know, Greatest American Hero goes up by four points. 32 00:12:32.000 --> 00:12:33.000 Holy cow. 33 00:12:32.000 --> 00:13:12.000 It's going to be funny when you open Netflix and it's like, top ten, number one. That'll be great. Oh, my goodness. But it really is true. And I mean, a lot of what you said, too, is, especially with these launch implementations, you know, everybody here's fast and, yeah, that sounds good. And I'm up and going. And you're having companies that maybe specialize in that, but they've never seen the full workday implementations. And we're hearing from contractors that we've had with clients that they've had to push back, going, you know, you have an implementation partner saying that functionality doesn't exist. The same thing that you just said, you know, workday. And our contractors are like, yeah, it does. You just haven't seen it. 34 00:13:12.000 --> 00:14:17.000 And, you know, I mean, one of the challenges. And it's funny because I almost come across as combative or adversarial with technology, especially in my compensation role. In the earlier days before workday, we'd have consultants that would come in and they would show these perfectly manicured data sets, and they would, like, push buttons, and all of a sudden these beautiful graphs would pop up and this stuff. And then, you know, your executive team would be like, oh, that's fantastic. Let's buy it. But what you have to remind them is, okay, well, our data set does not look like the data set that's behind that model. We don't have our organizations designed that way. We don't have our roles assigned the way that they have their roles, so it will not do what they do. So most likely we're either going to have to like, blow up our entire organization and start from point zero to create what they created for that tool to work, or the tool's just not going to work. And I think that's one thing that a lot of people don't take into account when they see whether it's, I don't want to say workday because, you know, everybody, it's everybody, but these tools can do fantastic things, but they're built in very specific instances to be successful. And you just have to be willing to make sure your company data aligns with that for it to work. 35 00:14:17.000 --> 00:14:24.000 Oh, yeah, no, definitely. I mean, it doesn't matter what the technology is. It's still all the base foundation, you know so well. 36 00:14:24.000 --> 00:14:49.000 And you're mentioning compensation, and I know that's a huge part of your background, current role. Just wanted to dive in a little bit there, Greg. Obviously we've put out the workday compensation report. You know, in your opinion, what's something good and also maybe something bad that organizations, you know, are modeling or thinking about from a compensation perspective. What have you seen kind of the good and bad side of comp. Structure? 37 00:14:49.000 --> 00:16:27.000 Well, I think good starts with that second word you just said there is structure. Anything with structure is good. I mean, before we went on the air, we were talking about AI and all this stuff. And you can't really do AI and all this other stuff without structure because what it's doing, you know, AI is built off of LLMs or large language models, which is basically, it's a model which, to build a model, you have to have, like, consistent patterns and whatnot. And so I think any organization that has that, like, has a grade or bam. Structure, has market ranges, has this stuff, I think they're automatically moving in the right direction. The other thing is, even if an organization is based off of, you know, bases their job ranges off of market pricing, I think there's always value added to some sort of internal equity or internal

market pricing. So from a standpoint of a manager in this area and a manager in this area, are they the same level, are they not the same level? Bonus eligibility, you know, what qualifies you to be bonus. So anything. We have those structures there that makes compensation that much easier. I think the biggest challenge for compensation is when you try to move too fast. And what I mean by that is, I mean, you're always moving at the speed of business. So I think from a standpoint of organizations, when they don't follow the processes, when they don't create the structure or maintain the structure, the structural integrity, I think that's usually where you run into the most pain points within compensation. I think companies are usually, I think they give a good faith effort most of the time. And I don't think there's any intentionality or very little intentionality to do things poorly. I think they're all trying to do the right thing. It's just the right thing that they know how to do is where you run into, I think most of the problems. 38 00:16:27.000 --> 00:17:31.000 All right, so let's talk a little bit about AI and comp. Because there's so many things that we've seen out there where people are, you know, they're googling which now you have AI results and things like that, or using AI to research what should salary be and then they're taking that and going in and then you're seeing companies are like we're having crazy numbers that are being brought to us like this is what we expect. We also know that AI, it's been proven that AI is biased towards minorities and it tells them if they're negotiating compensation to accept a lower rate. And that's one of the reasons, I mean we always fitting out the COPS survey that now with WD Beacon having the interactive compensation dashboard where you can get real time data and we still audited and it's workday centric so it's not these generalized things because I've gone out and played with it just to see. So you know, what would be your advice given? You know, you've got direct hire but you've also got contract. Now if you think about it, the majority, not the majority, but there's a huge increase in people that are their own companies now and what they should charge and things like that. So what kind of, you know, how do both sides deal with that? 39 00:17:31.000 --> 00:21:14.000 So it's a little bit of a challenge. I think one of the challenges with using AI for even pricing jobs and whatnot is all the valuable data, I'll say the really, really good data is typically behind firewalls and not really accessible to it. That said, you could, you know, corner office consultants could use setup like Microsoft Copilot or something like that to look at your data within your system. And I've built agents to look at data within our own particular systems to do that. But that data is not typically readily available to the applicant or whatnot which is going to lead them potentially to some faulty decisions. If I were to break this down to a few different questions from an employer standpoint, I think the purpose of AI is really to build out structures. And I am going to caveat this because I've built some market pricing agents within AI, within Copilot, and I did till like the fourth or fifth time I built it until the AI model caught up. Like, you know, they have like GPT3 and GPT4 and GPT5. GPT3 isn't as good as GPT5, and GPT5 is not as good as what GPT7 or 8 is going to be. And so I built out models that have lots of hallucinations. And so that's why it's important to have someone that has the skill set to know when AI is doing something right or wrong. And so I will start there. The second thing is, as you build out those models, you have to make sure that you build it out correctly. And prompt engineering is a real thing and there's a right way to build out your framework for your prompts and whatnot. And if you do that, that could actually get you, if you have access to the data, will get you closer to the data. But I think employers challenge isn't necessarily. I think the employers, they still have to get over the basic function issues that they had before AI, like compensation. The issue is going to be communication and companies, it's going to be communication. Communication to managers, communication to candidates, communication to whatnot. I think for candidates, the challenge goes back to exactly what you're talking about, is candidates will often look at one or maybe two numbers if, let's say they're a commission job, but one or two numbers and focus specifically on what they saw on, you know, ChatGPT told me that that job pays $60,000 or whatnot. So as a candidate, you really have to think of the total picture. And AI can help you. But what I do in those situations, if I were a candidate, knowing that the data in AI may not be ideal because the good data is behind firewalls, what I do in that situation is I don't ask it to solve my problems. What I do is I ask it to help me think more strategically. So ask a question like, I'm considering this job. I don't have a lot of great data on this. Help me, you know, like, what am I not thinking of? So I just did a presentation with our IT director last Friday on prompt engineering, and we were talking about it, and one of the things that I saw is when you Start using prompt techniques like, I don't want to go too far down that path of crit or, you know, tree or whatnot. Entering a standard prompt versus entering the, you know, a very tailored and specific prompt where you're identifying a role, you're creating a task, you're providing context, you're asking it to evaluate its own recommendation and then recreate the recommendation to a more advanced recommendation. What I found was typically it was 50 to 80% better when you had a more detailed and structured prompt than just asking what's the best option. So I think what I would tell people is, and I know I was babbling there, but I think if I tell

people, what do you need to take away from it is always have AI evaluated. So critique itself and provide an answer. Critique that answer, figure out what may be good, what may be bad, and then come back with a better answer. Or, you know, another thing I've done too is I've asked AI to come up with three solutions and then grade those solutions on a scale of 1 to 10. Then only give me the solution that rates the highest based off of reliability, accuracy, and whatnot. 40 00:21:14.000 --> 00:21:33.000 I like the, the way that you angled it, kind of using it as a coach or as opposed to because you're right so many times it's like you're googling something. It's just asking a question that's not the right way. And then if you're not going to have all the context of a good prompt, like you said, and have it evaluated, then tell me what I'm missing. That was good. 41 00:21:33.000 --> 00:22:20.000 I like that my AI doesn't have to pay my water bill. My AI doesn't get my merit increase. I get my merit increase. So I'm ultimately responsible for what I put into AI. But what I tell people is AI is not here to replace you. You are. The value added AI is more like an exoskeleton or a bionic suit that you put on. So if you run the wrong direction at 100 miles per hour instead of, you know, 5 miles per hour, AI isn't really helping you. It's helping you do something bad much faster, you know, so you need to be the expert on what to do. Do the right thing, and then AI will help you be more efficient at it. You can do more at it. And I think that's the big takeaway that I think a lot of people need to keep in mind is AI is not going to take my job, but it's going to make me better. Or it could make me Worse at my job, depending on how I use it. 42 00:22:20.000 --> 00:22:56.000 And obviously, you know, you are all about teaching and training and sharing. Just what you just did there is just, you know, bringing ideas and different ways of thinking. I know that you taught at, was it Georgia State. You're teaching classes on comp. You have a YouTube channel with lots of followers. I think there's salary school. So there's a lot of stories and tools and insights you share and continue to share. So that's important to us is, you know, your stories and helping people and sharing ideas. I was just curious, where did that start? Or why is that so important to you and starting all these different angles. 43 00:22:56.000 --> 00:27:26.000 I've always been interested in sharing information and training because the thing is HR systems, HR technology is. It's not a field that's been around for thousands of years that just say, just follow the process. This is something that's evolving. Every stuff that I was Learning in the 90s is now like, I don't even know if my kids are even going to know. They're going to read it in a history book, not necessarily in a business book, you know. So technology is improving so fast that I thought it would be important to grow and expand on it. This inkling actually hit me back probably around like the late 90s or early. Yeah, late 90s probably. I decided want to write a book. And I was in compensation at the time. I wrote about 60 pages of the book and it was all like, interesting thing, like, what do employees or colleagues always kind of wonder about but they don't know the behind the scenes. It was kind of like a Paul Harvey ask the rest of the story, like, why did you know? I asked my manager for a raise and they said no, why? You know, and then it's like, well, these are the reasons why. But the way I wrote it and everything, you know, because I'm more of an analytical brain than a writer per se, was that I had 60 pages of material and I bored myself to tears. And I was like, this is not anything that will. I won't even sell a copy to my mom. So at that point I shelved the idea. But I always had the intention to keep training and providing and whatnot. I participated in the Atlanta Area Compensation association, which I was, you know, like the VP of programs. I became the president of it and I still attend on a regular basis, well, semi regular basis today as I'm able to just to share. I've presented and whatnot. I had a buddy that was actually, he was an HR professional And he also taught at Georgia State and said, hey, I'd love you to come teach to my class. I taught to the class. The dean talked to me about teaching total reward systems. I taught several semesters of undergraduate and even a semester of graduate level total reward systems or compensation at that level. And I loved it. I mean, it's not about the money in that situation. It's more about the bucket list thing of, hey, I actually talked to people that are interested in this particular field or not, but I got to talk to them about the processes. And it's great because you talk about the textbook, but because you have the business experience, you also share this process. And then I got into analytics and you know, the analytics and then workday and after the workday implementation. Because if you look at it and you think about it from a workday perspective, you don't have just. It's not just workday anymore. It's workday recruiting, workday performance, workday compensation, workday reporting, workday integrations, work day. So it's like, there are so many different areas. Instead of me talking about compensation, I can write about an implementation. So I thought, what could I do? And so what I did was I took a different approach and I created this is the Book. It's not a big read, but what I did was I was like, you know what I'll do? I'm gonna do. Like, one of the things I really loved when I was in school was the One Minute Manager, you know, and I was like, I love the One Minute Manager. And then they had like the One Minute Manager meets the Monkey. And they had all the Ken Blanchard books. I was like, I really like that approach because it told a story, basically. And in the story was what they did to solve

the problems, whether it's bottlenecks or whatnot. And I'm like, I'm going to take a one Minute manager approach and write the story. And so what I did was, you first you go out and you start, okay, well, what are the things I can talk about? And so then it was mapping out, okay, what do you do in an implementation? And it's like, okay, well, I can't just start there. I have to start a little before then. The system has to be blowing up. You know, the world's on fire. Executives got embarrassed in front of a big presentation, you know, because the reporting was wrong and all that stuff. So I created a storyline and then they went to a new system and it was all about Sally and her team and what they were going to do. To implement this new system. And it was the struggles of, we don't have the money to do this, or we, you know, this is a challenge. Or these people don't like this new system because this person's going to retire in two years and they just want to be done with everything, you know, and it's like all the challenges that you had. And I got to make it more of a story perspective, which was cool because I got to. Instead of just being in the weeds constantly, I had to sometimes back out and say, well, what would an IT manager say in this particular situation? Or what would an employee. If I was an employee and I don't like new systems, what would I say? You know? And so I had to take these different perspectives in writing the book. And that's how I had the most success. The book itself, like, once I sat down and decided to actually write it, probably a year and a half time. But the from the start of, I have a concept that I want to write a book to actually having a success. Well, having a book that successfully is published, that probably took over 20 years to do. 44 00:27:26.000 --> 00:27:55.000 Oh, wow. Oh, wow, wow. That's one of the things I actually read it. It was very good. And I just love that you took a how to and ran it through a storytelling format as opposed to a simple how to kind of thing, like you said, when I pick this up and read it. And yes, that executive was definitely upset that she presented wrong data. So glad that Sally was able to take everything going forward. But what is that, though? That, I mean, if you think about. 45 00:27:55.000 --> 00:27:59.000 It, spoil it for me. I haven't read it yet. 46 00:27:59.000 --> 00:28:03.000 So someone who had. 47 00:28:03.000 --> 00:28:06.000 I read it too many times. 48 00:28:06.000 --> 00:28:32.000 No, it was good. It was really good. But that's the thing is, like, honestly, in a lot of things that you do, you use storytelling. You know, there is something with the power of storytelling, and, you know, that's something that we're saying now more than ever. Kind of in AI generated world, storytelling is so important. You know, what is that just naturally you? Or is it, I guess you said the one minute manager? Is it something that resonates with you or, you know, what kind of got you with that approach? 49 00:28:32.000 --> 00:29:20.000 Yeah. So, I mean, most of the tasks I always look at, you know, so let me step back in this story. I've always been an analytics person, data person. And so one of my big faults, like in my early interview days, what your biggest fault is I get too far in the weeds. I get too far in the weeds and whatnot. And so I think one of the training things and AI is actually great at helping me do this is help me tell the story. And so from that standpoint, working with executives over the years, one of the things that was really, you know, about the PowerPoint slide is you're not putting together a PowerPoint deck or a presentation deck just to show a whole bunch of graphs. It's like, you got to tell a story. It's like, what was broken? Why did that break happen? Or what can we do to fix it? And what will that fix take to get implemented? And then, you know, what's the cost? And all that stuff? And then, you know, you've got a story you can tell. 50 00:29:20.000 --> 00:29:21.000 Yeah. 51 00:29:20.000 --> 00:29:49.000 And. And they can get on board with that, you know, because I. I've done my fair share of presentations in my early years of, here's a whole bunch of graphs. I was like, well, what does all that mean? It's like, well, here it's 2%. Here it's like, but it's not a good story, you know, and it's not a compelling story. And so it's like, over time, I had to learn how to tell the story. So it's one of those things where it's like, no, some stuff you just. You're naturally good at, and some stuff you learn from experience. I learned that from more. From experience. That was not my natural capability. It was more developed over time. 52 00:29:49.000 --> 00:30:11.000 You know, you're seeing more people. Analytics folks actually say storytelling, and they're literally using that now. And that's really what it is. Like you said, it's not just crafts or, you know, here's what happened. It's the whole transformation, you know, dashboards or whatever. So writing the book, I mean, in all of this, all this stuff that you've always shared in teaching and stuff, what is that given you? 53 00:30:11.000 --> 00:32:35.000 A few things. So writing the book was something I always wanted to do, so I was always just excited to do that. It was one of those things where I said, I don't care if I sell, like, a single copy. I just want to be able to write a book and be able to hold up, like, an interview, hey, I wrote a book, you know, or show my grandkids, hey, I wrote a book. You know, it's just one of those accomplishments. And so that's what it did. Now, one of the things that happened to me between last year and this year, I did get into an accident, had a bunch of stuff that happened to where I was, like, out of commission for, like, a couple months, physically and that was like right after I had released the book. So the marketing and everything kind of went out the window. But one of the cool things

was, you know, it was like as I was talking with friends and whatnot, it was still something that was still brand new that I could talk to my friends about and I could still carry on. Now I'm at a point now where I've gone through physical therapy and I'm back 100% or 100% plus the extra 40 pounds of cookies that I ate. So, so I'm 78% now, but I was 100%. And so the book is, I still keep the book on my desk as a reminder and I still talk to my friends about it. And it's one of those cool things that I use. Now. It's funny because I still see like the Amazon royalty, like it comes in, it's like, okay, $3, you know, and it's, I'm sure it's small dollar amounts, but I really use it more for a motivator of, hey, you know, in order for you to be successful at something, you need to taste success. I think in order to be successful. And so that's where you'll see, like a lot of motivational people will talk about, you know, envisioning yourself shooting that three point shot, you know, make that basket, make that free throw and just picture yourself doing that. And so I can actually picture it. I can come sit at my desk and I can touch the book and I can read the book. And so it's like I successfully did that. So now when I work on these agents and I actually got my plus membership for ChatGPT and I want to say it was December of 2023, so I've had it for a couple years now. And so all these agents that I'm building and I'm sharing some agents on ChatGPT and I'm doing a lot of like silly videos and so on, stuff like. But knowing that I've done something successfully helps me with leveraging this. I mean the fact that I got asked to participate in a company wide AI presentation on prompting I think is a huge credit, you know, to the fact that not that I'm a computer scientist or I'm brilliant or anything like that, it's just I keep working at it because I've had those successes that have keep pushing me. And so from that standpoint, I'm extremely grateful. 54 00:32:35.000 --> 00:33:12.000 That's a story right there. Another story. And I was just going to say with the royalties, Greg, obviously more than Just your mother bought the book, so that's, that's a plus, like you said earlier. And then secondly, I was going to say that there's just so many different learning styles. You know, some respond by reading the book, some by the YouTube videos that you put out there, your website and, and LinkedIn posts. So you never know who is listening and what resonates and how that resonates. So good on you for continuing to put that content out there in so many different capacities and of course, teaching at the college as well. So lifelong. Lifelong educator. 55 00:33:12.000 --> 00:33:13.000 Yeah, no, absolutely, absolutely. 56 00:33:13.000 --> 00:34:01.000 And that's the thing. It's like eventually I will want to get out of the corporate world, you know, no doubt. But at the same time, I think like a lot of people, I think all of us probably just because I got out

of the corporate world doesn't mean that I'll stop doing AI or compensation or even HR system. Like, I haven't been using Workday for the last year, but I'm still researching Workday. I'm still talking to people that use Workday because I'm passionate about what they're doing in the direction of Workday, you know, whether they acquire new clients. And so then I then try to figure out, okay, that acquisition, what does that mean for Workday, two, three years down the road? I think it's more about being a hobby and being a passion. And oh, by the way, I happen to get paid for it right now. One day I'll choose not to get paid, or maybe I'll get paid on a perfect. On a consulting basis, but it'll be doing something that I really truly do enjoy. 57 00:34:01.000 --> 00:34:16.000 You just never know. I mean, it can open up so many different things and really the angle that it goes. But I love that you keep the book and that's your visual representation of. That was my goal and I attained it. And that is just like an ongoing motivator. I absolutely love that because we need that. 58 00:34:16.000 --> 00:34:17.000 Absolutely. 59 00:34:17.000 --> 00:34:31.000 As we always say. I mean, that's why we were saying riding the workday wave. But it's any career is this, you know, and so you have to have those motivators, you know, all doing that. All right, so are we, Are we ready for the barrel rush? 60 00:34:31.000 --> 00:34:32.000 Sure. 61 00:34:32.000 --> 00:34:46.000 Greg, I think you said you mentioned you grew up in South Florida, you're from South Florida, so. Yes, a little bit of waves on the East Coast. So this is kind of that concept is in and out real quickly through that wave. 62 00:34:46.000 --> 00:34:53.000 In the barrel. All right, I think I'm starting. All right, one great Trait. Every HRS leader needs two traits. 63 00:34:53.000 --> 00:35:16.000 But I think I'll go with patience. And what I mean by patience is when everything starts blowing up, you need to take a second of calm, to breathe for a second and then reassess the situation and then act appropriately. You know, rather than running down the wrong path a million miles per hour, take a second, make sure you've got the right path, and then go. So patience is something I think everybody. 64 00:35:16.000 --> 00:35:25.000 All right, so you've led teams through all kinds of stuff. Project goes off the rails. What's like your go to move to get everything back on track, you know. 65 00:35:25.000 --> 00:35:43.000 My answer is it's actually going to go back to page. So what I do when the project goes off the rails, rather than immediately fix it, what I do is I, you know, stop the press, identify the problem, and then get going in the right direction. So there's a reason why I said patience and that's because it's applicable to many situations within what we do. 66 00:35:43.000 --> 00:35:51.000 Love it. I'll jump in on this one. So what do you think is more powerful for retention? More compensation

or a sense of purpose? 67 00:35:51.000 --> 00:36:45.000 So not to get into like Herberg's two factor theory, you know, and, and talk like hygiene versus motivators and stuff like that. I. They're both important. Compensation is more like a hygiene factor from the standpoint of once you get to a certain level. But at a point, I think the sense of purpose, like once you've been stable for a long time, I think the sense of purpose is much more powerful from the standpoint of I'm not going to go across the street for $25, but if I am aligned with what the person across the street is doing, they have the same philosophy on using AI to do something and whatnot. I'm going to stay with that person whether it's $25 less or $25 more. So the purpose is always the trump card or is the leading card in that situation. But I think money is like, it's a hygiene factor and it weighs in. People are going to leave for higher paying jobs, but I think the true, true core people of your team are going to focus on purpose. 68 00:36:45.000 --> 00:36:46.000 That's great. 69 00:36:45.000 --> 00:36:46.000 That's good. 70 00:36:46.000 --> 00:36:57.000 I agree. And so we'll close out the barrel rush with my favorite question. All right, Greg, so what is your, you know, pump up song, your motivational. Maybe I need a little oomph. 71 00:36:57.000 --> 00:36:58.000 Oomph. 72 00:36:57.000 --> 00:37:01.000 At the end of the day, what is that? Go to song for you. 73 00:37:01.000 --> 00:37:27.000 Anyone that's been watching me is probably not going to guess, but you may have like a slight inkling on this. So I'm very eclectic in my music. So whether it's Rock, R&B, 70s, 80s, 90s or whatnot, I'll listen to. But because of where I grew up and because of the DJs and whatnot that I listened to growing up, there is someone that still is on the air Today on Sirius XM. Live from the 305 is. His name is Lazaro Mendez. 74 00:37:27.000 --> 00:37:28.000 Oh yeah, Musician. 75 00:37:28.000 --> 00:37:53.000 And not a song per se, but he's a dj. And then he'll mix freestyle and you know, all types of music, like even any of the musics. And he'll mix them up and he does it in more of an upbeat tempo to where I can really jam out so that I'll get pumped up to most anything. But once a week, that's like my guilty pleasure is if I get to sneak into the car on Saturday mornings at 10am to listen to Live from the 305. 76 00:37:53.000 --> 00:37:54.000 Wow. 77 00:37:54.000 --> 00:37:59.000 I can see you going around 285 in Atlanta, like just in your car. 78 00:37:59.000 --> 00:38:02.000 That's when I go from the slow lane all the way to the left. 79 00:38:02.000 --> 00:38:06.000 Exactly right. Just cruising on by. 80 00:38:06.000 --> 00:38:15.000 And you're gonna have to share that station because growing up in Fort Lauderdale myself, I remember that name. So definitely that's exciting. 81 00:38:15.000 --> 00:38:16.000 He's still. 82 00:38:16.000 --> 00:38:30.000 It was 96 back then, but it's. It's on Pit Bulls Globalization, which I think right now is channel 13. They always move. They bring the Taylor Swift channel in or something. They'll bump one down and one up and stuff like that. But it's a pitbull globalization station. 83 00:38:30.000 --> 00:38:41.000 He's still spinning. Wow, that's fantastic. We have to check that out. I remember that this has been like a nostalgic. Let's say we started with Greatest American Hero and now we're talking old school. 84 00:38:41.000 --> 00:38:43.000 You said lost in space and then. 85 00:38:43.000 --> 00:38:44.000 We got lost in space. Exactly. 86 00:38:44.000 --> 00:38:45.000 Holy cow. 87 00:38:45.000 --> 00:38:46.000 This has been. 88 00:38:46.000 --> 00:38:51.000 Now all of a sudden I've turned into the Speed Racer. 89 00:38:51.000 --> 00:38:53.000 That's awesome. Good stuff. 90 00:38:53.000 --> 00:38:54.000 Good stuff. I love it. 91 00:38:54.000 --> 00:38:56.000 This is a lot of fun, for sure. 92 00:38:56.000 --> 00:39:24.000 No, it really is. And I mean, thank you so much for being part of this. And like I said, there were just so many different angles and will have to say of your background, you've touched so many different things. And I knew that we would have so much fun talking about that. I didn't know. I'm so glad that you were back even at 78%. So that's fantastic. We Will help with those royalty checks from Amazon where we will definitely be sharing the book. Putting there every quarter helps. Yeah, exactly. 93 00:39:24.000 --> 00:40:19.000 I appreciate, yeah, but I'll talk to people, friends from Vegas, friends from wherever and they're like, oh, I gotta get a copy of the book. And so I love talking to people about the book. And all my HR friends for sure have been, definitely been supporting me on it. And again, it's a hobby. Like if I make $0 off the book, I'm happy. I'm just happy I wrote it. And it's a motivation piece for me. So from that standpoint, it's more of a fun thing. It's a hobby, but I'm just glad I did it. And the thing is, who's there's is it, I want to say Eric Collins, there was an HR person, he worked for Pepsi. He started writing books probably like five or 10 years before I did. And it was just HR stuff and they're not like academic textbooks or anything, but he started writing them and it's like I was just so inspired by looking at what he did that if, you know, if someone sees my book as an extension of like what he did and says, you know what, I might write a book too on recruiting or whatever, if I can motivate one person, I think that's good enough, you know, and so I love it. 94 00:40:19.000 --> 00:40:21.000 That sounds, that's what it's all about. 95 00:40:21.000 --> 00:40:24.000 It's keeping the next generation going. Basically. 96 00:40:24.000 --> 00:40:45.000 You get so much, you can just tell, you get so much back from sharing. But I also love that you had said, you know, you're seeing again, these were goals that you had and you're using that as a visual motivator to hit new goals. And it's taking you places. You just never know where it can take you. And you're just writing that. That's what I love about it. 97 00:40:45.000 --> 00:41:12.000 I think most of us can do it. It's just sitting down and taking the time to find out what's possible. Like if you're in those walls and say, well, that's not possible, not possible, I'm not doing it. It like we're sitting here talking about AI improving the recruiting and figuring out a way to weed out AI based resumes and stuff like that. And it's like, well, that's all possible. We just, you know, we just have to really sit down and think through how to do that. And whoever has the patience to do that is going to be successful. I think so. 98 00:41:12.000 --> 00:41:13.000 Exactly. 99 00:41:13.000 --> 00:41:21.000 I hopefully I, you know, someone says, I read Greg Laney's book and he talked me into doing it. It was like, you know, that'll be my win. 100 00:41:21.000 --> 00:41:23.000 Yay. I love that. 101 00:41:23.000 --> 00:41:24.000 That is awesome. 102 00:41:24.000 --> 00:41:39.000 Well, thank you so much again and thank you. I look forward to continuing to watch you and read your post and the things you share. And you know, let's see, what was that four years? What will happen in another four years? 103 00:41:39.000 --> 00:43:04.000 Speaker E: Greg shared something on today's show that every workday professional knows is true. Compensation problems don't start with the number. They start with the structure behind it. The clarity, the data, the decisions being made without the full picture. And when someone with Greg's experience breaks that down, well, it resonates. Because we've all seen those gaps inside an organization and across a team. And that is exactly why we built the WD Beacon Compensation Dashboard. So our ecosystem has real data shaped by real workday professionals at every level. Not generic HR surveys, not AI guesses, but actual compensation data from the market you work in every day. And if Greg's comp insight made you rethink your own value, please take a moment to add your anonymous comp data directly on WD Beacon's interactive dashboard. It not only strengthens the data, but helps others in our workday community make smarter decisions too. Our goal would have WD Beacon is simple to help more professionals grow through real stories, real data, and real expertise from people working in our ecosystem. And please make sure to like, follow and share WD Beacon so more workday professionals can get that same clarity in building their careers too. After all, this is how we keep riding the workday wave together.