Wednesday June 28th - 6:00 PM (UTC)

Conquering the Chaos: Harnessing Compensation Intelligence in Volatile Markets


Time Stamps:

Intro - 2:39

Who is Southern Glazer's Wine & Spirits - 4:35

Who is Lightcast - 5:01

Agenda - 6:04

Economic Chaos - 7:42

Business Use Cases - 18:55

Compensation Intelligence Framework - 23:28

Use Case #1 - 27:46

Use Case #2 - 29:12

Use Case #3 - 34:41

Use Case #4 - 36:11

Putting it All Together - 38:44

Q & A - 40:03

Compensation leaders have suffered unprecedented challenges in the last three years, forcing them to evolve. But how can we support our businesses with impactful compensation decisions in the midst of acute and unique job market nuances? What if the surveys we deploy don’t reflect our immediate realities. Join us to learn how Southern Glazer’s Wine and Spirits has used Lightcast’s real-time labor market data to navigate those questions and more, and consider how you can apply our approach in your organization.

Lightcast Webinar

Joe Fusillo, CCP, GRP, leads Compensation for Southern Glazer’s Wine & Spirits. In this role, Joe is responsible for unleashing the potential of every employee by encouraging development and rewarding excellence through employee engagement by supporting management in motivating performance and maintaining internal pay equity based on job and performance.

With over 20 years of compensation experience, prior to joining Southern Glazer’s in 2017, Joe worked in diverse industries for global companies in transition including NCR, Motorola Solutions, Westlake Chemical and Global Payments, in addition to consulting with Mercer. Joe specializes in broad-based compensation, sales compensation, executive compensation, and technology solution implementation.

Elizabeth Crofoot is a Senior Economist at Lightcast. With 20 years of experience assessing US and global labor market data, she researches business responses to labor and talent shortages and works with global enterprises to address this challenge. Most recently, her research has focused on worldwide demographic shifts and implications for global labor supply. She also works with companies to identify rising skills and occupations in their markets, build skills-based hiring and training plans, and help business leaders make geolocation decisions.In prior roles, Elizabeth was Senior Economist at The Conference Board and a Supervisory Economist at the U.S. Bureau of Labor Statistics. She has extensive experience in global labor market competitiveness, including evaluating labor cost competitiveness across countries.Elizabeth has appeared as a guest economist on Yahoo! Finance, the TD Ameritrade Network, and NPR’s Marketplace and has authored numerous reports and blogs on labor shortages and workforce training and development. Elizabeth holds an MA in economics from American University and a BA in political science and economics from the University of Washington in Seattle. A West Coast transplant, she currently lives outside of Washington, DC with her husband and two young children.


Justin Calvin: 

Hey everybody. Welcome to our Lightcast webinar. Happy first or second week of summer. Not sure what it technically is, but glad you guys could make it. We'll get started here in just a bit. We're just going to give people, I don't know, another 30, 60 seconds to trickle in. So glad you could join us.

Looks like more are joining. Welcome, welcome. Thanks for coming. We'll give people, I don't know, 15, 30 seconds left.

All right. We can get started. Hey, so glad you guys could make it. Welcome to our webinar. I'm so excited to take you guys through it and introduce you to your panelists in just a moment here. Quick, by way of a quick intro, my name's Justin Calvin, I'm a director of client services here. Been here for about four years. 

I'll introduce Elizabeth and Joe here in just a moment. Today, you guys all know our webinar is titled Conquering the Chaos. We're going to be discussing how to utilize compensation insights in this current volatile market. 

Some housekeeping items before we dive in. You guys will have the recording in your inbox within 24 hours, hopefully by today, but if not by tomorrow. So feel free to take notes if you'd like, but you guys will have the recording as well, so no urgency to do so. And then, as you guys have questions, we will reserve some time at the end here for some Q&A with Joe and Elizabeth.

Feel free to throw your questions into that questions chat throughout the whole time. And we'll hit those or feel free to do it at the end, but yeah, no need to wait until the end to throw those questions in. Some of you guys might know a Lightcast representative, either an account executive or an account manager. Also feel free to reach out to them after this call if you'd like some insights as to how this content applies to your guys' roles, your guys' industry, your guys' regions. We'd be happy to expand on those things as well. 

Okay, into the meat and potatoes of it. I'm joined here by my colleague Elizabeth Crofoot, one of our senior economists, and industry leader Joe Fusillo who leads compensation at Southern Glazer's Wine and Spirits.

With that, I'll kick it over to these two for some intros and then take us through some content. Also Joe's webcam is not working right now. It was working yesterday. It might pop on magically throughout. Just a quick heads up there. Elizabeth, do you want to go first and then we'll get into it.

Elizabeth Crofoot: 

Sure. Thanks so much for the intro. Really excited to be here today and give these insights. And just for a little background, part of this content today is from a presentation that Joe and I gave at a conference on total rewards and benefits recently. So I really wanted to just share this information to the rest of the Lightcast community and to other compensation professionals out there or anybody who's interested in just wages and benefits and how that's been evolving over the last several years. So my name is Elizabeth Crofoot, senior Economist here at Lightcast. I actually started my career at the Bureau of Labor Statistics, working with the compensation data. So I'm very familiar with government sources of comp and benefit data. Also spent about a decade at the conference board working with C-Suite executives on their labor shortage challenges. And most recently here at Lightcast, I work within the consulting arm of the organization. And I work with big and small clients on their strategic workforce planning needs.

Joe, do you want to chime in here? 

Joe Fusillo: Yes. Thanks Elizabeth. I'm Joe Fusillo and I hope to have my webcam come up at some point here. I've been working in compensation for more than 20 years in various industries and several companies like Global Payments, NCR, and Motorola. I even did some consulting with Mercer at one point, and Elizabeth, if you could go to the next slide. For the past six years I've been with Southern Glazer's Wine and Spirits. We're privately held, and we are the largest distributor of wine and spirits in the world, representing about 7,000 plus brands with 24,000 employees in the US and Canada. 

Elizabeth Crofoot: 

Great. Thanks Joe. And just to give people a little bit more information about Lightcast, so we are a big data company and specifically a big labor market data company. We also provide professional services. I'm on the consulting side, as I mentioned, so we're really helping our clients use this information to harness the workforce to increase labor market mobility, using data from job boards, from company websites and online resumes, employee profiles, really putting that all together to give the most comprehensive and up-to-date picture of the labor market that is available. 

So let's dive on into this content. Today's agenda, we are going to talk about today's objectives. We're going to also describe this economic chaos that we have been describing, right? That's the title of our webinar today. So we want to talk about some of the recent labor market trends that have created this chaos, especially in pay and benefits. Then we're going to talk about some of the use cases of Lightcast data. So using-real time labor market information to anticipate shifts in wages and benefits. And then we're gonna wrap up, provide a summary, and then give time for Q&A of course. 

So today's objectives first we're going to discuss what the primary compensation challenges have been over the last three years for compensation professionals. We're gonna talk about some of those volatile trends in the labor market that have been driving a lot of this uncertainty.

Second, we want to understand specifically how Southern Glazer's Wine and Spirits has evolved its compensation practices. So that's why Joe is here today. He's really going to give us some insider information about how he has used Lightcast data with his company over the last several years, and his story about how it has really changed the way that his organization approaches their compensation strategies.

Third, we're going to learn about the specific use cases for real-time compensation data and how it can help organizations really adapt quickly to this changing compensation landscape. 

And then lastly, we want to give you all a chance to evaluate, to think through, are your organization’s current compensation practices also agile enough for a lot of today's volatile markets? For the black swan events that we've seen, right from a pandemic to a banking crisis more recently? So just to give you space to think about all of these issues and where you fall into all of this. So economic chaos. Joe, it's over to you.

Joe Fusillo:  

All right, so this started for me back in 2009, 2010. I'm guessing about 30% of you on the call were in compensation at that time. So I'll provide a little bit of context.

At the time we were coming out of the global financial crisis and I was with MCR, which if any of you know is an ATM manufacturer and at the time probably not the best place to be. Unemployment had peaked to 10% in October 2009. When we received the survey data that year, there was an increase in pay similar to 2006 or 2007, which kind of left me scratching my head.

The reason why is the providers did exactly what they should have, which is they surveyed people that had jobs. We knew the rates had decreased. I was getting calls from HR asking me to decrease hire rates. In addition, we could see jobs that were recovering were recovering unevenly, and both the types of jobs and based on location. There just had to be a better way to understand supply and demand for specific talent in a local market.

I ended up being introduced to an early version of Lightcast back in 2016. And in 2019, I was able to convince my boss we were due for a market shift and we needed to supplement our surveys. I might have understated that. Remember back in 2019 and how tight we thought that labor market was? I think we all can agree that the labor market's been pretty chaotic over the last three years.

Next slide, Elizabeth.

So for Southern Glazer's, we were fortunate to be an essential business, but we lost all the business from restaurants and bars as soon as the pandemic hit. We laid off workers just like many of you did. Many of our workers went remote., many had to continue working on site. Tech companies started to hire from anywhere without regard to geographic differentials. Employees ended up moving anywhere and everywhere.

Then the distribution industry just blew up. Seemed like there was going to be a new warehouse opening in a different spot every week. Then we had the great resignation and quiet quitting. And you can see on this chart kind of the ebbs and flows that were occurring during that period. At the height of our turnover in the last three years, it was elevated. A little bit, it wasn't as extreme as some individuals had it, but it was acute in specific locations. Others had it much worse. They would struggle to maintain a culture, especially with remote work with that level of turnover. Next slide.

For us during this time, our management team was searching for answers. Where are the workers? What's our competition paying? And what are the pay trends now? The market was shifting very rapidly, and our surveys could not provide the insights. What really happened in a lot of these local situations is demand simply outstretched supply. There was no price equilibrium for us to measure. 

So what were we as compensation professionals supposed to do with that? The key to coming out of this pandemic stronger as a compensation function was to take a different approach. We really started with just, I don't know. Something that was very difficult to us to admit, but it built bridges that we were all in this together, and we could work together with the business to find a solution.

Lightcast helped us give direction that we could share with the business. Our local contracts were able to give us ad hoc data on what they were seeing locally. Then we could work together to come up with ways to address the issues and evaluate shortly after. Sometimes we had to adjust, sometimes we didn't, but we worked together on the solutions. And I believe that was really what gave us success coming out of the pandemic.

Next slide.

So other issues in the job market included boomers moving up to retirement age and finally retiring, and then even some Gen Xers retiring as well, as you can see on this slide. Next. The labor force participation rate cratered at the beginning of the pandemic and has not fully recovered. If you look on the right, you can see that these percentages are small, but any imbalance between supply and demand is going to feel pretty drastic at this point.

Elizabeth Crofoot: 

Yeah and just to chime in here really quick about some of the reasons that we're seeing this trend.

So this labor force participation relates to workers that are 16 to 64, but a lot of this reason is due to workers ages 55 and older. So these are the individuals that are retired from the workforce. So we saw a lot of early retirements. We obviously have an exodus of baby boomers that are retiring.

A lot of that happened because of the pandemic and it was gonna happen anyway also because of the demographic forces that we're seeing. But we don't expect older workers 55 and over to necessarily come back to the labor force. So we are going to see these participation rates remain lower for some time.

And on the other end of the age spectrum, we have younger workers, ages 20 to 24, that also have seen their labor force participation not recover. And if you remember, these are individuals that essentially came of age during the pandemic and right afterwards. And they have a very specific idea of what their work relationship is or what they're looking for.

So remote work opportunities, a lot of work-life balance and other factors that they're trying to evaluate when it comes to, should I work or should I not work? And they also have their baby boomer parents that have acquired a lot of wealth, so they don't necessarily need to work.

So there's a lot of dynamics on the lower end of the age rectum as well. So we're really relying on this core workforce ages 25 to 54 to try to get this through some of these labor force challenges.


Joe Fusillo: 

Recently the market has started to cool and we've had tech layoffs. We still have a huge number of job openings and talent shortages. But, I question if this is real. I think we're closer to balance or even tipping toward oversupply in specific jobs than the numbers are indicating.

This is a difficult thing for me to reconcile right now knowing what our talent acquisition teams are experiencing versus six months ago. Just not sure that it's real. Next slide.

In 2021, inflation started to spike and most companies moved up slightly on the merit increase as we did. But none of us seemingly could meet employee expectations. This is the reason for the increased turnover, in my opinion. Employees were feeling the pinch and they needed to move jobs to maintain their standard of living.


Elizabeth Crofoot: 

Yeah. And just to give a little bit more context about this, that wages really did chase inflation and not the other way around. I feel like a lot of the media was hyping up this idea of a wage price spiral where prices are increasing very rapidly, and then workers are demanding higher wages so that they can afford those prices, and then employers increase their prices further to fund those wage increases.

But we really didn't see that happen, and you can see that in this slide, right? Inflation is accelerated much more rapidly and to a higher level than wages and salaries did. And as inflation is coming down, however, wages and salaries remain sticky because as we all know, once you increase a wage rate, it's really hard to take that back. Or that's not a popular move that a lot of compensation functions want to go there. We are going to see elevated wages and salaries, I think for some time.

Joe Fusillo: 

So remote work stayed in place for many, but flexible work schedules are extremely prevalent at this point. Employers also looked for ways to support the employee population through benefits. Elizabeth.

Elizabeth Crofoot: 

Yeah, just to highlight that these are data from Lightcast from our job postings. So these are actual benefits that we see advertised in those job postings.

Like Joe mentioned, you can really see the increase in the trend in tuition benefits, in retirement, remote work, and signing bonuses are still something that we see at much higher levels than we did pre-pandemic.

Joe Fusillo: 

All right. In the middle of all this, a few state governments decided to implement pay transparency laws. I found this slide to be extremely interesting in that there was a spike in job postings in New York City in this example, when the law was enacted, but we're nowhere near compliance. Maybe it's gotten a better place since the last measurement.

But this is an interesting slide to me, Elizabeth.

Elizabeth Crofoot: 

Yeah, this is definitely an issue that people are really keying in on. In that conference that I mentioned, wage transparency laws was a key theme that many compensation professionals are very concerned about and want to make sure that they are addressing it appropriately, legally. In terms of our data, we've seen salary ranges have not really expanded that much. So in the chart on the right hand side, you see that the top end of the wage range is about 27% higher than the low range before the law went into effect in New York City. And then afterwards it ticked up to about 31% higher. 

So there's not a whole lot of movement there in those ranges. Which is a good thing. That means that those wages that are being advertised are meaningful, right? They're not these huge ranges that aren't helping anybody find a job or make a better match.

So let's jump into those business use cases now. So how are we going to use some of Lightcast data? But before that, let's just recap the challenge, right? Joe just went through a lot of his own story, his challenges pre-pandemic, during the pandemic, and it really boils down to: how can we more effectively monitor labor supply and demand so that we can better anticipate these shifts in labor rates, wages, and compensation more broadly? 

There are essentially two sources of labor market data that we all use. One is official government data, and this is definitely the gold standard, right? These are data from the BLS, from census, from other government statistical agencies that really have the most representativeness and coverage.

However, they really are reliable during times of stability and not times of economic change. For that, we have real-time data on the labor market, and this is best for identifying those inflection points and the magnitudes of change in either direction, so that you as a compensation professional can really make those business decisions that you need to in order to react in real-time, to what's happening on the ground in the labor market. 

And again, this is best for times of rapid change and economic shifts. So how do we actually do this at Lightcast? What we do is we aggregate data from online job and networking sites and from government sources. So we have access to over three billion current and historical job postings, over 300 million global online career profiles and resumes, and over 18 billion data points from government sources. 

So we collect all of this, we de-duplicate it, and then we run it through our parsing methodologies, and we harmonize it using our open source taxonomies on titles, on occupations, and on skills, and we generate these detailed data around job titles, occupations, specific employers and industries.

Skills, skill, skills, all types of skills that you can think of, certifications, educational requirements, experience levels, and most relevant to today's webcast - data on wages and salaries, and also benefits. So real-time compensation data helps organizations make data-driven decisions, and it does this in three different ways.

First, it helps us understand what matters most, and the key here is about identifying those inflection points, like I mentioned before, you know what is happening here and now, and how can I react to what's happening in the labor market? But what we need is historical context to make that have meaning, right?

What's happening today really is a reflection of perhaps what has happened in the past as well. So we do track historical wage and benefit trends, and we can also detect wage expectations of our talent pools. 

Number two, it helps us plan more strategically. So essentially this is all about analyzing supply and demand, right? Having both sides of the market. We have the job postings, which is the demands from employers, and then we have resumes, online resumes and social profiles that help us have a sense of what the supply is, what type of workers they are, who they are, what type of education do they have? 

So marrying that together is our secret sauce and how we deliver or at least generate a lot of these insights. Other ways or other aspects that we can plan more strategically around comparing incumbent and market wages. And also establishing build versus buy models. So this is where strategic workforce planning comes in. So are you going to build a skill internally, for example, by training it, or are you going to buy it on the market? 

And then finally, we put these two pieces together, right? You have the information, you're understanding it, you are developing a plan, and now we can adjust our pay practices to make sure that we are competitive and equitable across our pay structures, we're optimizing pay across all of our geographies, and that we're rewarding skills and capabilities appropriately.

So here at Lightcast, we have this compensation intelligence framework that we are using to help our clients really understand where they fit in all of this. What are the pain points that they're seeing when it comes to compensation and benefits? So on the left hand side or on the Y axis, two big broad challenges, right?

Retention and recruitment, I think we can all say that’s something that we deal with on a day-to-day basis. And then on the X axis, we have a timeline, right? There are short-term and also long-term challenges. So I would say our number one use case or concept here around compensation is this competition angle.

Many of our clients come to us asking, what are my competitors offering for a particular job in a particular location? So that's, how am I gonna get these new hires in the door? But thinking more in terms of retention in that aspect, in that short term aspect, alignment has really come into play recently as well.

Are your compensation structures for new and incumbent employees aligned internally and with the market? We've seen a lot of wage compression issues recently. With new hires coming in at elevated wage rates, and then our more seasoned employees not seeing those same types of compensation increases. So we want to make sure that it is aligned. 

More long-term, many of our customers come wanting to benchmark their competitiveness in terms of their wage rates. Are they offering competitive wages and how can they maintain their competitiveness over time? A lot of that boils down to longer term trends, right?

And labor supply. Are there gonna be workers in the area that I need them to be in? What's happening with overall benefits, right? Remote work changes the game a little bit. And inflation, how is that affecting our workers take home pay? So all of that is, is really wrapped up in, in your overall competitiveness.

And then sustaining, right? Sustaining transparent and fair structures of compensation. And this is so key now, especially during these times of wage transparency laws and asking yourself, do similar roles at similar pay levels require similar skills. So ensuring that your job architecture is in place, that job profiles have skills attached to them. That's going to help you establish those pay ranges and be able to explain to employees why a certain role is paid at the level that it is. 

So before we move on, just think to yourself like, where are you fitting into this framework? Do you see some of these challenges? Where do you see yourself in your organization?

So the compensation use cases, there are really four main ones that we’d like to walk through here. The first is when organizations just need more timely data, and they want to see those real-time fluctuations in compensation. The second is when they need more granularity. So you can slice data by geography, by industry, by occupation, by specific competitor, really to get to the nuts and bolts of your market and your challenge that you're trying to address.

Another aspect of granularity is estimating the salary premium or the salary cost associated with specific skills or years of education or years of experience, et cetera. The third use case is around identifying emerging skills. So what are those future ready skills in the market that are gonna increase your competitiveness? 

And fourth is calculating ROI. A lot of compensation professionals also need to be talking to their finance team on a regular basis or other parts of the organization, and we want to make sure we're speaking their language, right? Putting things in dollar terms and saying, what is the estimated labor cost?

Or what are the savings potentials of certain workforce initiatives in terms of expanding talent pools or skills-based hiring or other initiatives that are affecting our build versus buy decisions. Alright, use case number one. Joe, you want to chime in here?

Joe Fusillo: 

Yeah, this is one of our most recent use cases.

We opened up a new warehouse in Fort Worth, Texas, and we need to hire a large number of warehouse workers. And as you move a warehouse, you tend to lose a lot of warehouse employees. This chart and the data on the next slide helped us to really determine the new hire rate. You could see the distribution of advertised wages in this particular one and how it clustered around that.

$17 an hour range area. Now if you go to the next one, we can also see the advertised wage rate trend. And as we look at this, you can see it, it was going up pretty sharply at the beginning, and now it leveled off even though it became unpredictable, a little bit more varied at the end here. If you drew a trend line, you'd see it go up and then level out a bit. So this, putting the data together helped us to decide where we wanted to put those rates.

Elizabeth Crofoot: 

Yeah, and these are some of the most classic use cases. I think the most popular use cases from our clients is just knowing what the lay of the land is in terms of the overall wage rate.

So moving on to use case two, when you need more granularity. And here we're looking at the data by competitor. This is another Southern Glazer's example, but just to give you a sense of the metrics you're looking at here. So this is job postings for drivers in Louisville, Kentucky by a competitor. So Southern Glazer's identified actually 10 different competitors in this example, only looking here at five due to space issues. But you have data on total postings, unique postings, and that gives you a posting intensity metric. So how fierce is the competition in this area by these competitors, and how long is it taking them to actually fill those positions? And then you also have the advertised salary histogram here at the bottom, so you can see what the wage range is from your specific competitors.

Joe, you want to elaborate on any of that? 

Joe Fusillo: 

Yeah. You could see the bimodal range that you've got there at the bottom. And the reason for that is as we dug into this we looked at those employers that were at the far right end there, and they were showing a total compensation or a total annual ratings rate in their postings versus the ones on the left that were showing an hourly rate.

So the point of that is, is, data's great. You've gotta look down to understand what the data is and order to action it though. And this is no different, and I'm sure you guys have seen it as wage postings have been put on and you've been able to get to your transparency laws that different companies have interpreted them differently, and this chart simply reflects that.

Elizabeth Crofoot: 

Yeah. And Joe and his team are very informed users of our data. Yeah it's a really good point to make. So another example here, we're still on use case number two with needing more granularity, but here we're looking at a specific role, right? This is going to answer the question, how successfully can I recruit workers in a particular geography?

So what we have here are metrics for data scientists in the Dallas Metro area by county. So we can get pretty granular in terms of the geography. And you have information like, how much are these workers making in this location? How many data scientists are currently working there?

How many postings are there for these workers? How many employers am I competing against in these areas? How long is it taking them to fill these positions and actually at the very bottom, this line on net commuters. That gives us a sense of the flow in and out of these geographies as people cross borders to take a job or living in one location and working in another.

And highlighted are some of our concentration metrics. So, the idea there is that any values greater than one indicate that there's a greater concentration there than the US average. So you can see in Collin and Dallas counties, for example, there are more data scientists in those areas, and there's also more demand, or more job postings in that area compared to the national average.

Whereas in Denton County, those values are less than one, so there's less. Both fewer workers and less demand. So the idea here is to find that sweet spot for your organization based on your needs. Like, where are you going to be most successful in recruiting workers at the rate that you want to offer?

If you're a small fish in a big pond, maybe you don't want to necessarily compete against the Googles and Amazons of the world, right? And you want to pick a market that you know that you can be successful in. One last one on use case number two, needing more granularity. Again, this is by geography and this is an example from a manufacturing company I worked with recently and they were trying to identify a new optimal location for an IT talent hub.

And obviously workforce cost is a huge factor in determining where to open a new facility, whether it's a production facility or office workers. So what we did is we looked at a basket of IT roles and also specific metro areas that had the talent and the skills that they were looking for.

So this is a snapshot of those results. So most people would only look at the wage range, right? What is the actual wage level that certain workers are making? And you can see that in the black bar in this chart. But you can notice that if you just looked at the black bars, the rankings would be different right from top to bottom of the cheapest to the most expensive metro areas.

Once you account for bonuses, paid leave, legally required benefit,s and voluntary and collectively agreed upon benefits that ranking order changes. And it could also change your decision making in terms of where you ultimately want to open those new facilities. The New York Metro area at the very bottom is obviously the most expensive one here for these IT roles that they were looking at. They would pay about $140,000 per year just in base wages. But when you add all the other components, you're looking at more than $200K to hire someone in that area. 

All right, moving on to use case number three, and this is when you need more information about emerging skills.

So this is an example from a digital payments company that I worked with recently, and they were trying to identify the future skill needs in their industry because they wanted to develop training programs to help workers really navigate their careers in digital payments and to grow into this industry.

So they wanted to know, what are the skills that workers are going to need? What are the projected growth rates, right? And how much is the premium for hiring a particular skill? So this is how we define disruptive skills, specifically here at Lightcast. So those that are very expensive and also are projected to grow very quickly over the next couple of years.

So here as an example for data engineers in finance and payments. At the very top, for example, you have a AWS Kinesis, so someone in this industry could make an additional $20,000 a year by learning this skill. And you can also see that it's gonna grow at about a hundred percent over the next couple of years. So this is great from making those build versus buy decisions internally. And just knowing how much am I going to have to pay to acquire the skills that I need to be competitive in the future? 

Use case number four. So this is our last one. When you need to calculate ROI on workforce initiatives, again to speak the same language as your finance department or operations or strategy, this is really going to help communicate with other parts of the organization. 

So this example is from a manufacturing company that I worked with recently, and they were trying to optimize their skills-based hiring approach. So the larger challenge they were facing was that they were losing competitiveness in their market and they were also trying to shift from being more project focused to being more product focused. And in order to make this strategic shift, they needed to make some changes in their overall workforce. 

So we were able to quantify to them, or for them, that if they built certain skills internally, so train and upkill their workforce, they could save about $20,000 to $35,000 per employee rather than hiring these skills on the market. They could also save $7,000 per hire by eliminating certain certification requirements and save $10,000 per hire by eliminating four year degree requirements for certain IT roles. 

And just to really dig into this example this is an actual job posting for a cybersecurity analyst, and we worked with the finance company recently to help them reduce their hiring requirements so that they could actually recruit cybersecurity positions and this is really hard to come by in the current environment.

So you can see, for example, that they were requiring a bachelor's degree in IT or cybersecurity. So by removing that requirement, they saved $16,000 and it also expanded their entry level candidate pool by 61%. They also were requiring advanced skills and API development and software development, lifecycle processes, and security automation. So by eliminating these skills on the job posting and instead upskilling or training them on the job, they could save about $10,000 for each of these skills. And then lastly, eliminating specific certifications around cloud or security could drop those salary costs by $9,000 per hire. 

So let's put it all together now. We've thrown so much data at you, a lot of weedy examples but hopefully you can come away with some takeaways, right? So real-time data helps businesses make data-driven decisions, and we talked about some of the reasons for that, right? Helps you understand what matters, helps you plan more strategically, especially when it comes to strategic workforce planning.

And then it helps you adjust those pay practices based on the information that you have and your strategic objectives here. Trying to, there we go. Hold on. There we go. Joe, I think this is you.

Joe Fusillo:  

It is. So this all comes back down to fundamentals. What is the supply and demand for a particular skill within a defined market? With the help of Lightcast Southern Glazer’s was able to get local timely data in a chaotic market.

As you look at the future, how will you help your business navigate these chaotic markets? And do you guys have any questions for us?

Elizabeth Crofoot: 

Yeah. So happy to take any questions.

Justin Calvin: 

Yeah, perfect. No, thanks a ton, both Elizabeth and Joe. Super helpful. We do have a couple questions. So I think this one was for Joe. What was the most challenging part when it came to communicating to your leadership what needed to change? I think in reference to increasing costs.

Joe Fusillo: 

Yeah, the most difficult part. Wow. I'm trying to think whether it was the market or the leader. The most difficult part, I guess, with working with our leaders was managing with finance. As the market for warehouse workers and warehouse management started to really increase there was definitely some consternation from finance as to whether that was the right thing to do to increase those costs. 

We were able to convince them that it was, thank goodness. And I think that across the landscape of different operations areas it was challenging because we ended up having to go one by one because every one of those was a local, unique situation. And that was probably the most difficult part.

Justin Calvin: 

Actually, this one has a part two and you teed it up nicely. Were there any ROIs, or KPIs outcomes that you had to present to your finance team to get that buy-in?

Joe Fusillo: 

Yeah, the ROI was pretty easy because we were having a hard time retaining employees in specific areas. We became more proactive over time. I would say we became more aware when we were getting on the front end of turnover versus on the back end. At the beginning, it was on the back end and by that time many employees had left already.

And that ROI was easy to put into play because we had to get cases out, right? Had to service our customers. So that was easy. On the latter side, when we were on the front end of starting to lose employees, we were able to use those earlier cases as a reference point in creating an ROI.

Justin Calvin: 

That's awesome. Love that. Here's another question actually. I think it'd be cool to get Elizabeth, your perspective on what our data is showing. And then Joe, your perspective from what Southern Glazer's is seeing. Do you guys see increased competition for the entry level talent more so than senior level roles?

Elizabeth Crofoot: 

Yeah, that's a really good question. No, I would say that the competition, I would say that was definitely true earlier in the pandemic, and I think we've seen those entry level wage rates starting, at least the level of increase, has come down. We are still seeing that frontline workers are still seeing elevated wage rates compared to what they were making pre-pandemic. But at least those increases have started to come down a bit. When it comes to more senior level positions, I think it really depends on the role, right? IT related, cybersecurity related. There are specific areas that have seen greater demand.

So I think it's more role by role.

Justin Calvin: 

Awesome. Joe, anything to add to that?

Joe Fusillo:

I completely agree. Yeah. As we were going through this, you could see the retirements ramp up. That was a big part of those higher level roles that needed to be filled and that were seeing a little bit more stress on the supply and demand.

The other side was at the beginning of the pandemic, you had so many government supplements that were potentially coming in on the lower end as well as an increase in demand from our customers. Not only our customers, but every other customer that was in the market looking for any type of product. 

It was coming through some sort of internet provider or coming through a click on the worldwide web, no one was going to a store. So as you were looking at the supply for warehouse workers was nowhere near what the demand was. And yeah, that provided a struggle, but as of right now, I do believe we've leveled down on both of those and we're back to a little bit more of the specialty roles. But Elizabeth, you can chime in on this, the question is how much is it going to shift back?

Elizabeth Crofoot: 

Yeah. I don't really have much to add. I think that you nailed it. I think the other companies have seen that experience as well. 

Justin Calvin: 

Awesome. Another question here. It sounds like we saw a little bit of this, we saw a little bit of pay transparency inflating salaries. Do we anticipate that as more states follow suit and more cities follow suit and start requiring pay transparency in job postings, do we expect wages to rise commensurate with that?

Elizabeth Crofoot: 

Joe, I think you could speak from your own experience at Southern Glazer’s, but largely what we've seen in our data is we haven't seen a huge increase in wage rates because of the pay transparency laws.

We've seen that wage ranges have expanded a little bit, so that the top end has gone up slightly, but it hasn't been significant enough that I would say that it's actually causing wage increases overall. I think the wage transparency laws, for the most part, are doing what they've intended to do, which is just create more transparency and give workers a little bit more leverage in terms of how much, what they're worth, and what their options are.

Joe, I don't know if you feel differently about that.

Joe Fusillo: 

No, I don't necessarily feel differently. I think what you're going to see though, is I think you're going to find the employers that were paying far below market, I think they'll move closer to the market in order to become more competitive. But aside from that, I don't think this will be the cause of wage increases.

I haven't seen anything. 

Justin Calvin: 

Okay, super helpful. And by the way for the audience, we still have, I don't know, five or 10 minutes, so if you have more questions, throw them in. We've got time for them while you do that. One last question and Elizabeth, I think this one's probably for you.

What report can you pull the average annual labor cost from Lightcast?

Elizabeth Crofoot: 

Oh gosh, off the top of my head, I don't know if I can answer that question, Joe. You might have better, I know you're using those tools on a daily basis. Joe might know better than I do, but off the top of my head, I don't recall the exact name of the report and I wouldn't want to make something up that might not be true.

Joe Fusillo: 

Yeah. We normally look at things that are more specific. We're not looking at the larger, overall picture within Lightcast, although I know there's areas of the product that we should be leveraging more of. But I'm not familiar with that particular report.


Justin Calvin: 

And I can jump in there. There's actually probably a few that can get you there. Market comparison is going to be a good one. That's in both our Talent Analyst and our Staffing Analyst modules. You're able to pull in large swaths of occupations and look at those and actually see a time series of that for year over year as well. So that's at least a good place to start. 

I would say whoever asked that question, feel free to reach out to your Lightcast account manager, account executive, and they can point you in the right direction. Looks like we have one last question, although, again, feel free to keep them trickling in if you have them.

Are you seeing a shrinking gap in wages in like roles as more pay transparency and analytics are available?

Elizabeth Crofoot: 

A shrinking gap in like roles. So for similar roles, are we seeing that wages are getting a little bit tighter? From the data that we've seen, we've seen that those wage ranges have expanded just a little bit. So rather than compression, we're seeing a little bit of expansion, but not meaningful enough that it's going to shift competition.

I think what Joe said earlier that it's bringing below market players or offerings back up to par. So I think maybe that if we're seeing any increase, it's because that lower end is coming up probably much more than that higher end. We're just not seeing a lot of movement there in the data, at least.

Joe Fusillo: 

Yeah, and there's a case study here that probably goes back more than 20 years on nurses that you could probably leverage on this. And the case study would say that there is an artificial cap on how much certain companies are willing to pay for a particular job regardless of how hot the position is.

And the supply can, or the demand can far outstrip the supply for many years. And companies just have to figure out how to do without, because they can't reach and pay enough for financial reasons.

Elizabeth Crofoot: 

Yeah. And actually I think that's what we've seen with our clients too.

There was a chart that showed just that inflation and then wages started stabilizing a little bit. They're still elevated, but they've stayed at a higher level. That's because a lot of employers are saying, I can't pay any more. I've already given everything that I've got, I need to find other ways of making this position more attractive. 

So I think we've hit that. That's why we've seen wage inflation at least starting to slow down because many of those employers have hit their top end range. 

Justin Calvin: 

Awesome. That's all the formal questions.

Maybe I would just turn it over to you guys and say any lasting recommendations to the audience so far as to what they can do, what's one actionable piece or the first actionable piece they should do right now to make sure wages are competitive in this market?

Elizabeth Crofoot: Obviously Lightcast data is providing this type of insight, real-time insight into the market. We talked about a lot of the use cases and the tools that you can use. 

But even so just thinking about that framework. In terms of where are you in that spectrum of your challenges, long-term and short-term, and are you seeing more pain on the recruitment side or the retention side?

And just having that in your head and identifying where you fit and what are the specific tools that you could use for those to address those challenges. Just starting there and identifying those pieces, I think might be a good place to start. 

Justin Calvin: 

Thanks so much, Joe.

Joe Fusillo: 

From a Southern Glazer's perspective, our focus is on our local markets and our local business leaders and trying to have them call us and give us a heads up when they're feeling the market move. And then we use Lightcast and supplement with our surveys to really try and understand what's going on in the market and if something needs to be done or not. 

But my advice would be to stay close to your local business leaders. Try and understand it from what's going on, or talent acquisition is a great place to go as well. Try and understand at the local level because the market is not moving consistently across the US at this point. It is very local.

Justin Calvin: 

Perfect. Awesome guys. That's everything. One last housekeeping item for the audience. You guys will have the recording in your inbox within 24 hours. Reach out to us as you have any other questions. But Elizabeth and Joe, thank you guys so much for joining and all the insights and hope everyone has a good rest of your day.

Elizabeth Crofoot: 

Thanks Justin.

Joe Fusillo: 

Thanks Justin.