EP146: WageScape - How to Compete with Real-Time Labor Data

All-In Recruitment is a podcast by Manatal focusing on all things related to the recruitment industry’s missions and trends. Join us in our weekly conversations with leaders in the recruitment space and learn their best practices to transform the way you hire.

This transcript has been edited for clarity.

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Lydia: Welcome to the All In Recruitment podcast by Manatal, where we explore best practices, learnings, and trends with leaders in the recruitment space. If you like our content, please subscribe to our channels on YouTube, Apple Podcasts, and Spotify to stay tuned for our weekly episodes.

I'm your host, Lydia, and this week we have Cary Sparrow, who is the founder and CEO at WageScape. Thanks for joining us, Cary.

Cary: Hey, it's a pleasure to be here.

How Consulting & Military Shaped a Tech CEO

Lydia: So you have got 35 years of experience spanning engineering, military consulting, and operations leadership. How have these very impressive and diverse experiences shaped your approach to leading WageScape or even founding it, Cary?

Cary: In terms of leading it, I have had the benefit of working with a couple of hundred organizations when I was in consulting. We did lots of work with different types of companies in different types of situations. I got to see many different approaches. I get to work with people all over the world. I learned how to work virtually very quickly.

That was one of the things that I did when I set up WageScape. I set up a virtual organization. I founded WageScape ten years ago. This was well before the pandemic, and I deliberately set it up to be a global virtual organization. This was before remote work was even recognized. My experiences leading up to that time involved working with global teams.

We did not really have much video conferencing, so we had to learn how to work together very effectively without being face-to-face. That was one of the things. The other thing was creating a learning organization, recognizing that it is more important to go fast and correct than it is to get things perfect before you move forward. I saw that both in the military and in consulting. Then, when I was in the corporate world, I saw the opposite of that, where in the corporate world, you are really paid to manage risk out.

So you err on the side of taking a little bit longer and getting things as right as possible, but in a technology world, that will kill you. So you had a kind of bias for action that was instilled from the other parts of my career.

Flying Blind: The Hidden Risks of Outdated Labor Intel

Lydia: So what initially drew you to the labor market data space? I mean, that is the area in which WageScape operates, right? And what gaps did you see that WageScape was created to fill?

Cary: I had been working with companies to help them get the most out of their workforce for about 20 years and took a very analytic approach to looking at where opportunities exist and how to link operations and organization to strategy. I took a very business strategy approach to that as well.

One of the things I noticed was that the availability of data about what is happening with jobs and pay, and skills, who is available, and who is hiring is really poor. It is a little bit better now than it was ten years ago, but it is still not nearly what it could be. The lack of information really gets in the way of companies creating an environment where they can unleash the talents of their workforce to drive competitive performance.

I saw that as a real opportunity because many of the root causes for why the information is so poor have, over time, been going away with better advanced technology and changing behaviors. For example, being able to share data across organizations, having systems that do that, and so forth.

I saw there was a pain point that most people simply lived with, which is that their information about how much to pay people, who is hiring, and where to go to get talent is so out of date that most people were just flying completely blind. They thought they knew the market, but they did not really know what was going on in the market because there was no good information about it.

That, coupled with the fact that there are now better sources of information that could be tapped into that had not been tapped into before, is what led me to found WageScape. I founded it ten years ago, and ten years ago, nobody was looking at real-time hiring and pay the way that we envisioned it. We very quickly set up an operation and a technology stack that allows us to capture what the hiring situation and pay situation look like worldwide every single day.

In the ten years since, other people have gotten into that business. It is not to say that we were literally the first, but I think we had a vision that took it a bit further and saw the usefulness of that information in the talent acquisition space. This really came to a head in the pandemic when the supply chains of talent were completely fractured. What was needed for talent was completely turned upside down because certain things you could not do anymore, and certain things were now critical that you did not have enough staff for. Companies started paying to get the staff, and they were paying at a really fast rate.

Between 2021 and 2022, advertised wages were going up about twenty-five percent a year. That is remarkable when you think about it because every one of us is used to wage inflation between two and four percent a year, especially here in the United States, but also in other parts of the world, predominantly as well.

It really caught everybody off guard. We were sitting on top of the data that showed, yes, in fact, wages are going up that much, but they are not going up that much consistently. They are going up in some cases, many times that in certain markets or for certain jobs, and they are not going up at all in other markets and for other types of jobs.

The need we had originally envisioned ten years ago really came to the forefront right after the pandemic. That is when people started to invest in what is going on in real time with labor market intelligence.

Lydia: So, how do you find the scenario now, post-pandemic?

Cary: Well, it is interesting because there are several different aspects when you say the scenario. In terms of the labor market itself, things have settled down. We are not seeing the same kind of wage inflation. One of the things that really became apparent, which was probably true all along, but now we have the means to see it, is that there is no single labor market.

Everything is local. The labor conditions locally can be materially different than the conditions even in a metropolitan area just a couple of hours away, or between what is happening within a city versus what is happening in a more rural area, even within fifty miles of each other. There are material differences based on your location, and there are material differences based on the kind of jobs that you are looking at. Even within the same kind of job, there are material differences between the requirements for certain kinds of skills.

For example, many people know that the demand for long-haul truckers has gone up dramatically over the last several years. You see that in the hiring data and the pay data. One of the things that is interesting is that over the last couple of years, the median advertised pay for truckers has flattened out, but the average pay has continued to go up. The reason is that there are certain skills for truckers that are so in demand they command much higher pay, and that is driving the overall average. Even within a job, you have to understand which skills are in demand.

All of this is important because within talent acquisition, if you are basing your pay decisions off of published pay rates for your state or the country for a standard kind of job, you are putting yourself at a disadvantage. You are not getting precise enough about what you need. You could be paying at an uncompetitive rate, which means you are not accessing talent as quickly as you need, and you are not getting the quality of talent because candidates know what is out there too. They probably know it better than most companies.

The other way you could be disadvantaging yourself is the opposite. You could be paying too much if you are going on an average rate and you are hiring in relatively low-cost areas, or if your skills requirements are not nearly as demanding as what some others are. You could be paying too much. In today's environment, especially with inflation, cost pressures are still very high. Uncertainty around the economy, especially in 2025, is causing companies to take a close look at costs.

You do not want to be paying too much, and you also do not want to be paying too little. That is some of what is going on in the labor market itself. Companies are responding to that. They are changing the way they manage pay. They are changing their information sources to stay on top of things. They are paying much closer attention to who their actual competitors are.

The traditional approach to competitive analysis for any area within a company, prior to just a few years ago, was to look at who the business competitors were. In most cases, if you asked somebody who they compete with for their talent, they would list their business competitors and a handful of companies. Even in a specific metropolitan area, there are dozens, and in some cases hundreds, of companies that are competing for exactly the same talent.

Also, because lower-end wages have come up so much, if you are in a business that is intensive in terms of an hourly workforce, who you are competing with just got a lot bigger. Most people, if they are making even a modest wage, will look very closely at moving to another organization, even if it is a different job, if it is nearby, and it pays a couple of hundred dollars more a month. That is enough to bring people away. The people who manage large hourly workforces know this firsthand. They are getting more sophisticated about how they pay attention to these things.

Why Most Companies Are Still Flying Blind

Lydia: Cary, let us talk about the technology itself. Your patented AI technology says it collects data from 5.6 million hiring organizations across 210 countries. What technology challenges did you have to overcome to build this kind of data infrastructure?

Cary: It was really interesting because when I went to college, I studied computer engineering, and I loved designing computer systems and thinking through problems that computers could solve. Then I went into several different careers that you mentioned, where I did not have to do that anymore.

When I founded WageScape, we actually built our own technology to go out and get data from millions of different sources. It is operating at scale. What we started doing, and we do more than this now, was going out to every website we could find that posted job openings, and we had a special way that we developed to figure out what those openings were going to pay.

That was very useful. We just run that twenty-four seven. We go everywhere we can find jobs, we capture that information, and we update our picture of the entire world every single day. It is a 24/7 operation, handling very large-scale and very large amounts of data.

We had to learn how to scale that. We had to learn how to build in operational controls. We had to learn many things. My academic background included some research in artificial intelligence, so I was able to look and see where we could apply AI to help with how we process data.

There are some areas where...

Lydia: This was 10 years ago?

Cary: Yes. So, it was, and we still use AI a bit today. Not as much as people would think we do. But we still use it to do things like translate languages, translate job titles, interpret from job listings, what industry the hiring organization is in, mapped to some standard occupational codes, things like that. AI is particularly well-suited for. So we do that.

Lydia: So now, Cary, let us discuss “flying blind,” as you mentioned earlier. When companies make hiring and compensation decisions, what does this actually look like for a company when they make those decisions? And what critical information are they missing?

Cary: Traditionally, when you talk to recruiters, hiring managers, operations leaders, and so forth, most of them would tell you that it is their job to understand the market for talent, and they feel like they have a pretty good handle on it. Then you ask the next question: what is that based on?

It is often, “Well, I talk to a certain number of people every day,” or “I know my competitors,” or “I know what it takes to hire people.” When you peel it back, what you are really talking about is anecdotes. You are talking about anecdotes that have shaped people's perceptions and influence their sense of what is going on, but it is not based on any statistically meaningful fact base.

The way that pay levels are set, the way sources of talent are targeted, the way positions are defined — these actually do not take into account any meaningful view of what is really going on in the market. It is based on conventional wisdom. It is based on individual experience, which is very limited and not that useful in a very dynamic environment.

This really became clear in the pandemic when you could read news articles on the same day, even in the same morning, with some people saying we were in a recession, others saying we were going gangbusters. Some were saying there was no talent, others saying we had too much talent. When you looked at what people were saying and compared that with data, such as from us, it had no bearing on reality.

Those kinds of anecdotes, however, carry the day in actual conversations around how to set pay levels, how to go about recruiting, what messages will resonate with people, and whether to look at remote versus only where you have operations. It is those conventional wisdom and personal experience points of view that carry the day.

When I say a lot of companies were flying blind, it is because they were going off an accumulated set of experiences that were no longer relevant or were not connected to any kind of fact base about what is going on in the labor market.

Savvy organizations have begun changing that. Savvy organizations recognized a few years ago that they need to equip hiring managers and recruiters with an up-to-the-minute view of what is happening in the labor market. They need to be proactive about how they shape their hiring practices and their pay practices and policies.

There is a big gap, I would say, between the organizations that have really embraced the idea that the labor market is dynamic and that they need to be on top of exactly what is going on to be as effective and competitive as they need to be, and everyone else. That gap is still there. More and more people are adopting that view, but we are still in the very early days, and it is the most savvy organizations that take that perspective.

Lydia: How would you define a savvy organization?

Cary: In the context of what we are talking about here, it is organizationally recognizing that they have to create the capability to understand what is going on. They have to constantly evaluate what they need in order to compete from a talent standpoint, and then where they can go and get that.

They have to use actual fact-based information on what they should be paying people, what is worth paying for, and what is not. They need to operate at a much faster cycle rate. Annual pay reviews do not work anymore. National pay reviews or international pay reviews definitely do not work anymore. Things need to be much more localized and much more frequent.

Savvy organizations are making those changes. They are creating much more dynamic approaches to match the dynamism of the labor market.

Speed, Cost, Resonance: The Triple Advantage

Lydia: Now, going into the actual competitive advantage, what are those competitive advantages that your clients may have gained by having more accurate or timely labor market intelligence?

Cary: I would say speed, cost, and resonance. Speed means you can react to changes in the markets that you operate in much faster. Those changes could be driven, for example, by one of our clients, a very large retailer that pays attention to the hiring practices of every other retailer, large and small, in every market that they operate in.

They use our data to do that because that is the scale we track at. As soon as they see a pay change with any one of those competitors, and these are competitors for talent, not just competitors from a business standpoint, they immediately alert the local teams.

This company has made this kind of change, and they need to evaluate how to respond to it. In some cases, they do not need to respond. In other cases, they begin to make a shift in order to move in that direction, but they do it very quickly. Within a matter of days, they are able to adjust their local pay approach.

That is an example of speed. Having real-time information allows you to more quickly determine what matters to you and your team and then take action on it. To do that, you have to have an aligned organization that understands this is the information to pay attention to.

Speed is one thing. Cost is another. Having a handle on what prevailing rates are in the marketplace and what is driving those prevailing rates is essential to stay competitive, not just from a talent acquisition standpoint but from a cost management standpoint.

Go back to the example I mentioned. All the major companies that were hiring long-haul truckers were increasing their advertised pay rates by more than five percent a year, and in many cases, much more than that. Starting in 2023 and continuing into 2024, you started to see a number of those same companies not raising their advertised rates. By 2023 and 2024, you were starting to see those same companies decreasing their advertised rates for drivers.

Instead of everyone across the board raising rates to attract talent, now companies were taking a much more nuanced view. When you did the same analysis, looking at individual locations, you saw the markets. Three years ago, rates were going up across the board. Now it is a much more nuanced view where rates are going down in some markets, staying the same in some markets, and going up in other markets.

This is a direct result of having a better sense of what the right equilibrium point is for right now, which is appropriate to pay this critical talent and then move forward.

Turning Labor Data into Strategic Foresight

Lydia: With data like this, Cary, how far can you forecast? Things are changing so fast. What is the furthest you can look?

Cary: There are certain questions where you can look reasonably far out. There are other questions where the horizon is maybe a quarter. If you want to know where pay is going in a certain market, a real-time view of what is being advertised by all the competitors in that market will show you what pay rates are probably going to be six to nine months out.

It takes a while for people to come into an organization. You have to hire them, get them on board, pay them, and so forth. So, six to nine months is a reasonable forecasting ability. Keep in mind that is compared to zero. Using prior methods or prior data sources, you could not reasonably predict anything at a local level or at a job level based on those sources. It was just not precise enough.

There are other applications where you can predict even further out. One of the things we saw coming out of the pandemic was that we saw very clearly who was starting to hire again in certain industries right away, which companies were going to be more resilient coming out of the pandemic, because they started to loosen up hiring much earlier. We knew which ones were really struggling because their hiring went to zero. That had long-term implications. From a competitive intelligence standpoint, there are many uses for this kind of information.

Don’t Let AI Define Your Pay Narrative

Lydia: Cary, one more question about AI. In terms of the impact of advancing AI technologies on recruitment, have you noticed that sort of impact happening on the recruiter side or even the candidate side? We have seen more scenarios in which candidates are using AI, and so are recruiters, yet they have not really understood how advanced or how to manage the capabilities coming out of AI. What are your views on that?

Cary: You cannot have a conversation these days about talent acquisition without talking about AI. In fact, you cannot have a conversation about business without talking about AI, and it is changing so fast. One of the things to recognize is that the world today is not what the world will be in six months when it comes to AI. Talent acquisition teams have to be very diligent to recognize that the capabilities they do not think AI is suitable for now may be suitable six months from now. A year from now, there will definitely be more things that are suitable.

I think you are exactly right to call out both the recruiter experience and the job seeker experience. On the job seeker side, it is important to recognize that every recruiter is probably facing this right now. Job seekers are using AI tools basically as very smart search capabilities. When it comes to understanding what a company's culture is like, what a job entails, and how much they should be getting paid, they are going to AI models to tell them that. Those AI models, even though they give answers with high authority and great detail, are in many cases just flat-out wrong.

As an interesting exercise, anyone listening out there, if you want to do this, go look at the top three AI models that are available for free and ask them what the pay rate is for any position. You will get three wildly different answers. That is because they are not learning based on any reasonable or up-to-date fact base. In most cases, you have no idea how old those rates are that they are quoting. So there is a lot of inaccuracy, but the job seekers do not care about that. As far as they know, that is the right answer.

You have to equip yourself to re-level everyone with what the situation actually is. This is our understanding of what is going on, and this is why we offer this kind of compensation. It is also useful to stay on top of what AI is telling people, so you can bring in additional information. There is a whole question I get into with audiences sometimes: What is truth in a world with AI? Unless you are careful, the truth will be defined by the AI. At some point, it does not matter what the truth really is — if the AI says something different, then perception becomes reality from that standpoint. You have to stay on top of that as a recruiter.

The other thing is that there are many tools now available to recruiters. For over ten years, companies have invested in AI matching of candidates to job requirements as a way to improve fit and streamline the recruiting process. Those have had very mixed results. I would say every three years a new crop of companies comes out to do that, and there will continue to be more. But from what I am seeing, they often take a relatively superficial approach to what a good fit means. They look at position requirements and see who has the best match with those requirements.

The latest generation of tools starts looking at skills to see what underlying skills are required in certain types of work and who has the best match for those skills. AI is playing a role in figuring out what skills are relevant. But there is a whole dimension that has to do with how organizations work — culture, working style, work ethic, and so forth — that AI is not touching. From a recruiter’s standpoint, you cannot just abdicate everything to the results of an AI-driven search. You still have to know what allows people to thrive and succeed in your organization and what will set them up to fail. In most cases, that is not just a skill set; it has everything to do with the organization.

Don’t Get Trapped by Old Hiring Habits

Lydia: And final question, Cary, what advice would you give someone who is starting a career in this talent space? This nuanced, dynamic talent space that we just talked about today.

Cary: A couple of things. Some of it is just basic principles. Work hard. Put yourself in a position to learn as much as you can from the people around you. Put yourself in organizations that are in that savvy organization category, that bring a very aggressive and nuanced view of what is going on in the labor market. That is the biggest thing: choose your spot, work hard, and learn as much as possible.

If you are already in talent acquisition, guard against conventional wisdom and traditional ways of doing things because things are changing so rapidly. New technologies are coming online, and labor conditions are changing so much. If you are relying on the way things have been done in the past, you are setting yourself up to be uncompetitive.

Lydia: Thank you very much for your time and your insights today, Cary. For those who are listening in, where can they find you?

Cary: Thank you, first of all. You can find us online at wagescape.com. You can find me and WageScape on LinkedIn. If you reach out to us and mention this podcast, we have ways to accommodate you if you want to explore doing business together. Thanks again.

Lydia: Thanks again, Cary. We have been in conversation with Cary Sparrow, Chief Executive Officer of WageScape. Thank you for joining us, and stay tuned for more weekly episodes from All In Recruitment on YouTube, Apple Podcasts, and Spotify.