AI's Secret: Data-Driven Career Frameworks for True Pay-for-Performance.

Welcome to the Built by People podcast, where we share the stories and insights of the world's top HR leaders. Join us as we dive deep into the minds of HR executives, uncovering their strategies, challenges, and triumphs in shaping today's workforce.

I'm excited to welcome Nick to the Built by People podcast. Nick, thank you so much for joining us today. And as a starting question, I always like to ask if you could share a little bit more about your career journey.

Thanks, Dave, and thanks for having me. So right now I'm the VP of Total Rewards and Analytics for PowerSchool, which is a leading software provider in the education space, specifically K-12. I landed here circuitously. I started as a mathematician economist by trade. I was starting in the finance space. That was my bread and butter was the finance space. Got introduced to HR by a headhunter that said, do you want to come and do data science in HR? And I said, I don't know what data science is, and I certainly don't think I belong in HR. But luckily for me, they were persistent and they let me come in and fail and fail fast. And I learned a lot along the way.

So.

Started on the East Coast in government and in that space, super helpful, really fulfilling. And we were figuring things out together. So analytics in HR specifically was really a burgeoning field. There hadn't been a ton, obviously, outside of maybe the Googles, some of the enterprise groups that had started analytics in that space. They brought me along. I learned a lot from my mentors and it's been progressing through there. So data and analytics has been the big focal point, but that has obviously brought me into the world of compensation quite a bit in my current role. That evolved into just taking on both data and analytics. Of course, that's my bread and butter, my DNA, the space of compensation data analysis and planning, competitive salaries and benchmarking, and then the introduction of benefits. That's been the journey over the last year and a half.

Nick, last we talked, you mentioned implementing a career framework at Powerhouse, a 1,000-person company that never had one before. What challenges were you facing without this framework? And why did it become a priority for your total rewards strategy?

Yeah, good question. So at PowerSchool, we— when I started here, we didn't have a great way to talk about our leveling or our structure, right? We knew that we had individual contributors. We certainly knew that we had people leaders and everything else was piecemeal. If you wanted to know how many directors we had, how many VPs we had, you're just looking at individual titles and trying to manually sort. And I really do mean manually sort to assemble What do these populations look like? It made reporting super difficult for one. It made like organizational leverage and structure really difficult. It made it hard to even talk about succession planning in a meaningful way because you don't know who are viable candidates. All if you're trying to get some sense of like level and experience and progression, you're looking at salaries. So you don't even have this real backing of, okay, are you a director? What does that mean? Are you an individual contributor? What level of individual contributor? Entry, or have you been doing this for a few years? Are you more experienced? Are you a thought leader? Are you excellent in your field? We didn't have any of that. And so on that space, it made it really difficult in the compensation area to know if we're paying well or not, right? Because like titles could have huge variability in pay, and that's because the titles were almost meaningless in a sense. We didn't really know what their core business type or their core like job title was, their profile that they fit into. So we hadn't just put guardrails around it, structure around it, and we didn't have that. And for a company that grew very fast, it was an in-demand ask on the manager space. They want to know who do they have in their organization? What's that leverage look like?

How did you approach building this career framework from scratch, and could you walk us through your process of combining data analytics and compensation practices to create a solution?

Yeah, absolutely. A lot of things came into play. We contract with a salary survey group called Radford, and there's many. I know Mercer does plenty through CompTrix. There's a whole handful of resources and tools that let you get a lens into what does competitive pay look like, and they have their own leveling structure. So we adopted that. Better, better just bring that wheel in-house. And so we brought their structure in and cascaded it into our organization. Now, how do we get people into the right level was the real challenge, especially in those first 6 months. So before we even get into educating our workforce and making sense of what do you do with this new tool, We had to get people started. Data analytics came into play big time because we can use salary as a proxy. If you're paying somebody kind of entry-level wages, presumably they're entry-level. If you're paying somebody more mid-level wages, you can get this schema of where folks fit and where they exist within your organization. So that was our first quest, making sure that we definitively knew where folks were and we could use clustering out of data analysis to do some of that. The next piece is once we got everyone slotted into things, we borrowed from Radford. We created job family groups, job families. It's not an organizational structure, but it mirrors it. So within like HR or finance, you have HR roles, finance roles, and then you have families that exist underneath there. Finance, you have accounting, tax and treasury, FP&A. So you got to get all these subsets. And then within that, you have levels of individual contributors, managers, directors, VPs.. And so we could cascade people into an initial match and you help us validate that folks are in here and you're not matching by person, you're matching by job. And that was the real educational arc we had to take that you're not talking about, does Nick have 20 years of experience and should he be at this IC6 senior level individual contributor? It's what job is Nick doing regardless of his experience? What job is he bringing to the company? Okay, that's an IC4 and that's that leveling that we borrowed from Radford, our individual contributor 4 level. Radford calls it the professional track. So we adopted and put people in these profiles, and then we had our business partners over the course of months validate. And so they worked with managers to say, is this right? This is the, the goal, this is the horizon, this is where we're trying to go, and this is why. And so once they were bought into the value proposition and understood kind of the framework, they helped us do the validation. But it was like a 12-month journey to get folks slotted into these these job levels and to make sense of that they're in the right family, that they're in the right family group, and the value as to why we would do this at all. So it was essential. That partnership with the business partners was essential. And I could recommend that for every HR team in the world, right? They're the arms of impact. You have all these like COEs, whether it's us in total rewards, whether it's your global mobility folks, if that's the angle for your company, whether it's talent development, learning and development, everybody brings value. And yet the success of all of those independent camps is the business partner. That's the approach we've taken. So they helped us do a host of that validation, get people slotted into the right things, and it's iterative. As knowledge has increased, validation has increased. And so we really wanted to hone in first on this framework and the value it brings to managers and to leadership before we turn it to the value that it also brings to employees, because of course it does.

Nick, you leveraged AI to scale your team's capabilities during this implementation. Can you share specific examples of how you use prompt engineering and AI tools to accelerate your work and what initial challenges you faced?

Yeah, so right off the back of my last answer was we needed to bring value to the employees. You put Nick in a profile and you know what that profile should pay, you can see my salary and say, yeah, we're on target. We're paying Nick what we should be paying him. We can understand progression. And that's obviously important for the employee as well, but it's most important for the manager to understand competitive salary ranges. For the employee, the value really comes in understanding career progression. What are the lateral moves I can make? What does it look like to get promoted to the next level? How much time? What are the skills and competencies that I need to develop? And skills and competencies is really where we leverage AI because we need to understand the skills for every single one of these job families at every single level. What does the mastery look like? What does the proficiency look like? So we had to roll that out. Now we can go to the Lohmingers of the world, the Kornfairies of the world. We can go to the Lightcasts, all these places that have banks of skills and competencies, and that's great. We need to take that structure, cast that DNA into our organization to make sure it resonates with our managers, our people. We need to define it and explain like something like data analysis. That's a skill, right? A technical skill. I need to know what that looks like at an IC level 1. I need to know what data analysis means at an IC level 4. I need to know what it looks like at a director level. I need to know what it looks like for data analysis at a VP level. And of course, it mutates and changes. Mastery means different things.. But for an individual's progression, they need to be able to look at a skill or a competency and say, okay, that's what I'm missing that's stopping me from taking that next level jump. That's what's stopping me from progression. That's what I need to work on. And it helps managers recommend training and learning, et cetera. When it was all said and done and we came up with it, we had 700 and above skills and competencies we wanted to be part of our library. We wanted to define all of them in the context of our organization, and we wanted to have a definition. Now, not a huge definition, 3, 4 sentences of what mastery of that skill or competency looked like at every single level. And that is over 3,000 inputs. And if we can buy it off the shelf, that's great, but we can't. That wasn't in our budget, in our cards, especially the personalization that needed. So we leveraged AI and the that we prompted AI to more or less say, I want you— and this is hacks of AI, right? I want you to take on the role of a talent development advisor. I want you to define the mastery using this job schema, and I want you to produce definitions of all of these competencies at each of these mastery levels. And so something that could have taken us a year of a few folks working on the definitions and tweaking took us less than a week of just populating that initial view of all definitions and mastery levels. Now, that's not to say it's fully baked. Of course it isn't. Now we can take that draft that has populated entries for every competency skill at every level for every definition. We can take that to the business and say, poke holes in it. What do you want us to change? What is missing? What skills or competencies are missing? What do you think we've misrepresented in any certain level? And that's not to say we're just going to take whatever the business says at face value, but it turns it into a collaborative discussion.

Nick, what measurable results have you seen since implementing this data-driven career framework, and how has it transformed how employees understand their career journeys and how the organization approaches compensation?

Yeah, so it has really unlocked pay for performance here, and I know everybody talks about pay for performance. Of course they do. I think this is the real hack to it, though, because it gives us a prioritization framework. What I mean by that is I can take even people with even performance and I can understand that somebody is low in market versus somebody that's at market, and I can prioritize that person that's low in market. So it gives me an additional element to understand where I need to put my budget to reward my talent that I'm determined to keep employed with us and make sure that we don't create inadvertent risks by rewarding people that have already been rewarded, more or less.. And so it gives us a real kind of compass for where we're going as a company. So first and foremost, for managers, never before were we able to say, hey, this is a comp ratio and we can do that now. This is where they are in range. We've never been able to do that before except on a very limited case-by-case basis. So the fact that we can now do this at scale and talk about where we have challenges under market, where we have plenty of people over market, where we have promotional readiness and In our just recent focal merit cycle, we were able to give prioritization lenses to our talent. Here are the top performers and here are the top performers that are low in market. Let's fix that. Let's put our budget, the bulk of our budget in that camp so that we can keep them happy and satisfied and keep their talents here. So that was a huge thing for managers first and foremost. So for our employees now, again, they have that horizon. What does What do lateral roles look like? Where, what does growth look like? What does the next step look like? And so we've seen massive improvements in just the career conversations that our managers are empowered to have with their teams, the utilization of some of our internal resources like LinkedIn Learning, some of our talent development tools that can allow for self-service growth and skill and competency development. And it's seen improvements in routine survey scores on career growth and is that possible at our organization. So all those were the beginning. Now, the value to the employees, we're still, I wouldn't say at its infancy, we just put this framework in place a year and a half ago. So for our employees, the value is started. And I think the sky's the limit for where we can go with it. A lot more that we can apply to it, certainly in recommending and personalizing courses and learning paths and a whole host of things in partnership, just internally and with vendors like LinkedIn Learning. Lots to come, I think, is the answer to the employee value piece. Managers were already seeing a ton of that. And then at the board level, our executive level, it allows us to have a lens into structure. Are we underleveraged? Are we overleveraged? Where do we have quote unquote top-heavy organizations and/or functions and where we have more bottom-heavy democratized organizations, flatter hierarchies? So it gives us more of a schema that we just couldn't answer before except anecdotally.

Nick, what advice would you like to

share with our community? Yeah, I think that It's daunting. Creating something from scratch is daunting. And probably more than ever it feels daunting because there's so many priorities and we have so much going on. Whether it's a career framework, whether you're spinning up a new HR system, whatever it may be in your world, just do it. People are scared of a blank piece of paper, but they're less scared of a draft. Draft something. You'll get feedback on a draft more than feedback on a blank process that's undefined. So get started and you'll have so many people that will then chime in. Now, sometimes that's too many voices. I know that happens in our world in HR all the time, but open that door to just collaborate with something already given and people will iterate with you. So that's the first thing I would say. And obviously that's even easier perhaps now, to my point earlier about with AI, it can get you off of the blank piece of paper. It's not going to be perfect and it shouldn't be treated as gospel, but it's a great way to get started, especially in the HR space.

Nick, thanks.

Thanks, Dave.