Workforce Data for a People-Centric World

Episode Summary:

Today’s workforce market is shaped by the need for accurate and detailed data. Lightcast Vice President of Strategy, Skills and People Analytics Mark Hanson shares how data helps determine where, when and how to find talent. Data points for emerging markets, skills-based hiring and compensation rates are just the beginning for organizations to make the workforce decisions to reach their goals.

Transcript:

Bruce Morton: Allegis Global Solutions (AGS) presents the Subject to Talent podcast, a hub for global workforce leaders to unleash the power of human enterprise. Listen in as we explore the most innovative and transformational topics impacting business today.

Bruce Morton: Hi, I'm Bruce Morton, the host of the Subject to Talent podcast. Today I'm delighted that I'm joined by Mark Hanson. Mark is the vice president of strategy over at Lightcast. They're a global leader in the labor market analytics space. Mark leads the strategic initiatives of people analytics, skill, products, and partnerships related to their open skills' taxonomy. Mark, welcome to the show.

Mark Hanson: Thanks so much for having me. Appreciate it.

Bruce Morton: Great, thank you. Those regular listeners will know, we always ask the same first question, and that is how did you get into this wonderful industry of ours? Quickly give a synopsis of your journey to date?

Mark Hanson: Happy to. The short answer is I fell into it. I had no career aspirations. Didn't even know what this world was when I first started out. I was an accounting and finance major in undergrad, and so quickly realized that I love data and I love solutions. Through a series of dabbling in management consulting for a few years, jumping over to help run people analytics at UnitedHealth Group for about five years, I got introduced to this crazy company called Lightcast that was working with labor market intelligence data. I was like, "What's that? They have some things about skills and what is the skills trend?" I said, "Hey, this data is way too cool. The things that they're building around skills intelligence is way too interesting," so I jumped over to their side.

 After being a customer for five years, I joined Lightcast and helped build some products and help run just our general data strategy for skills and for our skills products and consulting. But I've been here about five years at Lightcast, and it's just been a wonderful way to tap into the HR tech world as well as work with all of our wonderful corporate customers, and management consulting customers and our 75 HR tech partners as well. We get to cover a lot of areas and get into lots of interesting situations with our customers in trying to bring the best data forward that we can for making the solutions better and hopefully answering a lot of their problems and different questions that they have. 

Bruce Morton: Awesome. Here at AGS, we've been partnering with Lightcast for about the same amount of time as you actually, for just over five years. We've seen many iterations of the organization in different names and how the organization has grown. If you would please share with the listeners that journey that what's now Lightcast has been on and how you're positioned in the marketplace

Mark Hanson: Absolutely. We rebranded about two years ago, and that was the result of a merger between Emsi and Burning Glass Technologies. Both of those companies have been around for 20 plus years doing a lot of the same things. Actually, I looked back at some of the data. I think Allegis has been a part of the Emsi customer base for 10 plus years in its different iterations. It's been a long-standing partnership. It's been a really fun journey of taking two powerhouse labor market intelligence companies and pushing them together and really brought the best of both worlds of some rich taxonomy work that Emsi had been doing in the past.

They had open sourced their skilled taxonomy and their title and occupation libraries. Then when Burning Glass came into the mix, they had some rich parsing technology and just ways that they were sourcing data, different ways that they were modeling the data. Pushing these two powerhouses together has really been a great match to really be the market leader for talent intelligence and labor market information. We realized that Emsi Burning Glass would be a mouthful as a brand name, so Lightcast... The people smarter than me that chose a new brand to go with, and it's been a good journey.

Bruce Morton: Yeah. Awesome. I think it's a great name by the way because you are certainly casting light on intelligent intelligence.

Mark Hanson: I love it.

Bruce Morton: I guess that's where I came from, so I love it. In this world now, as you were just talking about earlier, the data has become so important for organizations from a talent perspective, but it's also become global. Back in the day, I've been in this industry 45 years for my sins, and it used to be domestic. I was in the UK and then the US, but that was good enough then. Give me your data and how many states do you have data for? Now we're truly in a world where organizations are at rethinking how they get work done. They want to put the work all over the world, therefore they want to know where they should be putting it, how much they should be paying. What's the journey that Lightcast have been on to expand your global reach, I guess?

Mark Hanson: It's been quite the journey because like you said, for the many, many years, probably the first 15 years of existence, we were really focused on the US labor data. But then as you work with larger organizations and the world became more global, you had to go beyond the US borders to be able to get at ‘where are those new talent pools?’ How do we understand what talent’s available and where is the demand? The customer base just expanded rapidly. For the last 10 years, we've been on a mission to keep expanding country by country as much global data as possible, and it's really driven off the demand of the insights that our customers need. No longer are people tied to a desk and focusing on office strategies. That's still the case for some industries. But for the most part, we can hire workers wherever, and that remote strategy is really critical. Especially when labor costs are tight and with shrinking labor pools that we're trying to tap into, we have to go global to find the right talent at the right price. That requires a global data set.

Bruce Morton: How have you stood up to that challenge and faced that challenge of gathering data. We know that the further you go from developed countries, the harder it gets to get that data. What are some of the tactics you've deployed to continue to grow that?

Mark Hanson: We've always started with a government data foundation, even when we started deep into the US and Canada and the UK. Those are some very mature nations that have rich history and lots of mature data gathering practices and have just wealth of data points to rely on. Even in the US we have data.gov, which pretty much has everything you could think of from the Bureau of Labor Statistics (BLS) and census data and everything. But that's not true as you go across the pond to different areas in different continents, they're just not as mature in terms of the data gathering. They've never had that. The systems weren't in place. What we've tried to do is go after say which are the countries that have the best government starting data? Then we go after two big data sets that we always focus on is the demand data. Where is all that rich job posting data going?

Is there a series of equivalents that are similar to Indeed and Career Builder and Monster where there's these job board sites that are housing a lot of this or is it distributed across many? Then we go after profile and resume data to say, "Are there LinkedIn equivalents at different countries?" We try to get this mix of government data, supply data through resumes and getting that granular data, and then going after the demand data. That's a country-by-country practice because every country has its unique available information. What's the breadth of the information? What's the depth of it? What languages are being used? Our team over the last four years has been really focused on expanding our language capability. What can we translate to expanding our partnerships with different vendors in each of those countries that are running those job boards and different supply data sets? Trying to bring that all together and harmonize that data through our data structure and our taxonomies.

Bruce Morton: Yeah. I guess what you're saying, you can't take a global approach. Although you're trying to create a global database, you're actually having to go country by country and make it very specific and very localized in that situation. I think to my mind, a good indicator of where work is starting to get done now more and more around the world is when organizations start asking for data in particular regions or particular countries. That's a good barometer of where's next for the talent. Can you just talk to which are some of the hot countries or regions right now that you getting asked about?

Mark Hanson: Yeah, absolutely. It's been a really fun journey with our customers because we get some really interesting requests on, "Do you have data on Chile or Argentina." One of the latest conferences we just spoke at was a presentation to the World Bank. The number one request was data on Uganda in Africa, and so we're like, "Whoa, that's interesting." Then when they started talking to some of the participants at the conference, and sure enough, most of the participants were from Uganda, and they're really seeking how do we understand our labor market in some of the adjacent countries that we work within? Then those global firms are saying, "How do we reach some of those untapped markets that we haven't gone after?" Because often what companies do is they'll start to look at “I heard that there's really good software engineering and tech talent in Poland,” and all the companies rush there because they heard a couple of success stories.

Well, by the time that you get some of that information, if you're not an early mover, you've actually missed out on some of the cost benefits maybe of some of the available talent that's there. Then that quickly has wage inflation after you get more competition for all of that talent. That market isn't really a rich market anymore because either tapped out from a competitive standpoint or the costs are too high. Our customers are constantly looking for what are those new emerging markets where we can tap into some of that wonderful talent that exists? But it's certainly going to be cheaper than trying to hire someone down the street in Silicon Valley where the wages are astronomical, and so we got to really spread out for our talent strategy. Where do we find the best talent at the right price to keep all of our initiatives running at an optimal speed?

Bruce Morton: You mentioned Africa. Obviously, I think that is inevitably going to grow if you look at the demographics. We're just going to have to get better at sending work to Africa is my view because that's where the world's workforce is going to be in the future, a large percentage of it. What other areas? I guess Latin America is still hot for near shoring. Southeast Asia is coming online now. You mentioned Poland, Eastern Europe as well. Are those the hotspots?

Mark Hanson: Yeah. Absolutely. Asia, specifically the Philippines, has just been a wonderful booming area. It continues to grow for a lot of our customers in terms of especially call center workers and being able to have native English speaking there. There's some of these countries where they're easier to get into in certain respects for logistics and maybe some of the labor laws and things like that. There's others where the more connectivity there is, specifically in Africa, the better mobile technology is, the better that the internet connectivity. That just unlocks a whole new world of available labor forces there.

I'd say there's really not a place that our customers haven't explored. There is the unique scenario where you do want some concentration of labor where you're not the first mover to go into some sort of place. You do want a few competitors there just because there is the skills that are being trained there. The infrastructure is already built in terms of the local labor laws and being able to work within some of those countries. There are some of those countries that are more difficult to work in that different companies avoid. But for the most part, it's around the globe, people are looking everywhere they can.

Bruce Morton: I think it's fascinating that we start seeing these trends of countries being known for specific skill sets almost. It used to be, well, Scandinavia are known for design, hence Ikea. Then now we think about even Egypt where there's some real, real cool cyber security stuff going on. It'd be interesting to see how that pans out. That whole areas of the world become known for certain skill sets as opposed to it used to be just labor arbitrage. It was just about, well, the cost of labor is lower there, so send the work there. Now I think it's not just that, it's even perhaps in front of that is, well, where is the talent?

Mark Hanson: Yeah.

Bruce Morton: If you tap that into universities, what are the universities producing around the world as well? What are they doubling down. It’s a big challenge for governments of course, where should they be investing education?

Mark Hanson: You're hitting on really the combined strategy of the regions and countries that we work with is behind the scenes, the mission of Lightcast is to bring educators and government and private organization enterprise together to be using the same data so that we can create the right incentive structures. Because businesses need the new, fresh talent with specific skill sets, and they need to be partnering with educational institutions around the globe to say, "Are you training for the things that we need?" There needs to be that connection between them. Then the local governments are saying, "How do we incentivize and bring the right tax incentives or the right programs and learning and development initiatives to bear?" If we can get all three of those groups working together, it creates economic prosperity for everybody in those regions. It's definitely okay to have some specialization because what makes your region unique and allows you to invest more dollars in the concentrated areas of where you're the best at.

I think that's a great thing if we can find that because it creates meaningful employment, it creates growth opportunities, it attracts these multinational companies that can say, "Yeah. We have our payroll services over here, and we have our technical teams over in this country, and we have concentrations here." I feel like it brings the best of the entire world together to diversify that talent, but also diversify sourcing that talent. Because globally, if you're just focused on a singular country or small region strategy, you're going to have problems finding all of the unique talent that you need to run your business, especially as technology changes and as your business initiatives change. We do need that global perspective to make sure that we're finding the best, especially when talent markets are shrinking.

Bruce Morton: That's right. What a great mission and purpose for an organization like yours to have. Of course, the other thing we haven't mentioned, it's not for this podcast, but the AI work. Obviously, that's going to influence, and impact as well, which skills organizations and countries and universities build. What are those skills we really need for the future as we move into more of an AI world? But that's for another day. If we bring it back home for a second here in the US, what has been the impact for your organization on the new legislation around organizations having to be more transparent with what they're paying? I think the bizarre example would be they're using these crazy broad range – $50,000 to $2 million – but I'm assuming that getting past that it's actually helping you the more transparent organizations are.

Mark Hanson: Absolutely. Yeah. Some of the new law changes in the different states for pay transparency have really helped us because it's bringing to bear data that's been long hidden for a long time. Pay ranges and stuff were very secretive, and now, if you were in certain organizations, but you couldn't really compare that across different companies, different regions. That was a hard data set to get at, and you'd have to do some complicated surveys and rely on sample data and things like that. But now through our data processing and aggregation that we pull that data through, we're able to see many more observations. We have to do some data modeling to make sure we kick out the outliers, like you mentioned with some of the obscure cases that get through. But for the most part, people are in a good enough range where we can get the relative median ranges and percentile comparisons between the different areas.

I think that helps from one standpoint, from just the broader transparency so people know, but it's also really helpful for just the intelligence that needs to be there to how do we supplement our current talent management strategies and acquisition strategies and compensation strategies? How do we start to understand the different complexities of the different markets we operate in? We need those signals from every spot that we can get and pay has been one that's just been hard to nail down. This offers an opportunity to supplement some of the rich work that our compensation partners already use and in those teams. They have something else that can be a daily number that they can see some of those immediate trends, and they can start to adjust the short-term strategies to complement their other survey and different methods that they're using.

Bruce Morton: That makes sense. I'd just like to touch on the partnership between our organizations where we're really geeking out in a good nerd way all around the skills-based hiring, skills-based organizations and that model. I think that we've seen that coming for a while, but now it's getting very real. Of course, you can't do any of that unless you have that data and really understand what's behind the job and what's behind the individuals. Can you just share a little bit about the approach for skills-based hiring?

Mark Hanson: Absolutely, we can. Yeah. We made the push about five years ago to go deep into skills because that's the underlying data structure that gets us the most granular insights we can between learning, people and jobs, and so we love the skills-based world. Because of that, we need to move beyond a lot of the vague job titles that have been used in the past, the vague job descriptions that are written for different jobs. We need to get more precise in our language, and we need to get down to what we like to call the building blocks of learning and work to understand what skills do we actually need to drive our business? How are we screening and recruiting? Are we asking for the right skills? Are we pushing the right learning content that's relevant for our jobs today?

A lot of learning content's extremely old, and it doesn't get checked very often to see if it's still relevant. Our companies are pushing us to look at unique career paths, and how do we think about talent mobility within our organization? Skills gives us that lens to look through our jobs to say, "Well, where are there skill overlaps? Are there unique career paths that we're missing? Is there interventions we can take through learning? When we do need to go buy talent externally, where do we find that talent?" That's where a mixed strategy of organizing your internal data and mixing it with external labor market intelligence really brings a holistic approach to say, "We can understand what's shifting in the labor market. We can understand how our business is shifting at that more granular detailed skill level."

It gives us something to anchor on. Kind of a connective tissue that speaks the same language that we can search more effectively for the right pockets of talent, be screening and looking for sourcing from the right markets and the right different areas of the world that we can pull in this talent. Skills is really that connective tissue that binds all of this data together really well. It's going to be needed in the future for how dynamic the businesses need to be to pivot into new initiatives and new strategies and new products that they're rolling out. How do they need to shift their workforce, and how do they be strategic with some of that build, buy, borrow strategies that we love to talk about. Skills gives us the mechanism to be able to make precise decisions in that area.

Bruce Morton: How can organizations who are just starting that journey or thinking about going on that journey... How do they start to understand and shift that mindset of how work gets done compared to who should I hire? What would your advice be there?

Mark Hanson:  We love to talk about this with our customers because there really is a shift in what used to be a job-centric mentality for HR and saying, "Everything is around this job, and we got to hire for this particular job." Well, it's pushing more towards a people-centric world where people are not just static anymore. They don't sit in a job for 20 years and then retire or move on to this something similar. It's really about we're learning at a faster pace than ever through multiple means on our phone and through YouTube videos and TED talks and whatever it might be. People are just very dynamic, and the projects are shifting so fast within companies that you might get hired into one particular job, but you end up supporting all of these different adjacent groups based on the most critical items. People's work is also flexing beyond this artificial constraint of a job title, and they're picking up more project work on the most important. We saw this through COVID, every company had to shift their strategy to what was most important.

That means people needed to flex outside their comfort zone because business was not running as we normally had it. Skills-based approaches help us to get people tied to the right things that are important, whether it's projects or it's newly developed jobs that are critical to run our business. We need to have that flexible architecture to say, "Well, people are learning new skills on the job. They're learning and flexing beyond their normal day-to-day career path that they're sitting on currently. We need to start to align that." The beauty of a lot of this technology, the reason why there's been such a push the last couple of years into skills-based is really the artificial intelligence, the dynamic processing capabilities of all the technologies that are being used to run HR. We're actually able to get to that lower level without such a manual lift, so that's accelerating a lot of these conversations that we can be much more strategic in our workforce planning, in our talent management strategies.

Bruce Morton: That's a great point because without AI, this stuff is almost impossible if you've got thousands and thousands of employees, you just never get to it. Do you have an example you could share just to bring that to life for how when one of your clients is thinking differently about who to hire and the work to get done and so on?

Mark Hanson: Yeah. Absolutely. We've seen a lot where in what was called kind of the great resignation the last couple of years where people were just leaving, it actually was more of a great shuffle. People were moving and getting poached by different companies because when they went out to look in the market, the supply was really low, and so you'd have to start poaching folks. Our customers have been really creative of saying, "How do we look at adjacent labor pools that we maybe have never looked at? We should look at it from more of a skills-based perspective instead of just, okay, we got to find someone with that exact job title and let's move them over to this position." One of my favorite stories, and he's still a good friend of mine at UnitedHealth Group, we had an opening for a data science lead on our people analytics team. It was an HR job, very specific to analyzing all the rich people data that we were trying to model things like predicting retirement and predicting turnover. Creating all those fun models.

We started looking, and we looked everywhere. It was just tough to find someone that had exact data science HR experience. It just is still relatively new and the labor market's small, and so we expanded a little bit and we started saying, "We should just take a skills-based approach and look a little bit broader." Well, we found a guy that he was an epidemiologist at a children's hospital and we're like, "Okay. On the surface, this doesn't look anything close." When we interviewed him, we're like, "Wow, this is the perfect candidate," because he had all of the core underlying data analysis skills. He's like, "Yeah, analyzing health outcomes in kids is the same exact models that I would use to predict turnover within this particular division." We're like, "Oh, my goodness. You're exactly right." Sure enough, he was a wonderful hire and built a whole team around him. That's just something that we don't think about of what are those unique talent pools that we could be tapping into that we would've been blinded to if we were dead set on one particular type of job we were thinking about?

Bruce Morton: It just dawned on me that you yourself are great example as well, the way that you got to Lightcast.

Mark Hanson: That's right.

Bruce Morton: You came from a completely different industry. The skills were there.

Mark Hanson: I started off as a financial planner with my accounting and finance degree, and I quickly ran away and saw the light.

Bruce Morton: There you go. Yeah. They'd have never found you by doing a search on your job title on a job board. That's a certainty. That's a good example. As we think about that, and I know the journey we're on together and we're partnering with in terms of helping continues to grow that database of knowledge. I've got a great question for you. I'm going to put you on the spot here because the two different terms that are used are taxonomy and ontology. I'd love you to have a crack at explaining in layman's terms the difference between those two, and are they interchangeable?

Mark Hanson: They're not interchangeable, although our customers interchange them a lot because it is nuanced. But no, they're really valuable for different purposes. I always love to talk about taxonomies as something that's very structured and hierarchical. Everything fits together, and it has a one-for-one relationship of what category it fits into. I don't know where I heard this but it resonated with me is a taxonomy is like a hardware store. Everything is in sections, and you know exactly what's in the plumbing section, you know what's in the whatever it might, a fixture section. Everything is in order, and it's categorized, and you can find things quickly. When we reverse that and compare it to an ontology, ontology is really a flexible structure where there's organic relationships. You can have many, many relationships connecting to different things at once. It's a free for all sort of cluster of things connected. There's not always a logical reason why they're connected, but there are anchoring node points where things are connected.

I like to liken that to... It's not a perfect example, but it works like Costco. You can walk into Costco, and you can pick up a hammer. You can pick up your vegetables, and you can pick up a new computer. It's all there and it's all connected, but there's not a lot of logic to it. There's not really clear sections either. You're just wandering around and you find all the things you need randomly, and it's all there. That's how I liken that. Really, ontologies are great for understanding meaning behind things. How are things connected beyond the specific question you're answering? Versus when you're working in a taxonomy, there's sometimes you want things structured because you're like, "I want to know which occupations are underneath this functional area, and underneath those occupations, which titles are most relevant."

We want to look at things that are closely related versus when we look at skills, oftentimes we'd love to talk about our ontology. We use our aggregate data at Lightcast for we call it our daily changing ontology because we're seeing these unique relationships of skills showing up in new pockets of industries and occupations that we never would've thought of because there's just technologies being used in different ways. If you think about looking at a ChatGPT or prompt engineering and anything with large language models, it started in a very tight technical group. Now that skill has branched out into marketing, into writing, into all these areas that people might not have anticipated. That's more of an ontological view. It's connected to many things. It doesn't always fit in a tight little box.

Bruce Morton: Awesome. Well, thank you so much for that. I'll remember those examples that will help me explain it in the future when people ask me. I appreciate that. As we're wrapping up here, I'll again put you on the spot, but we like to ask our guests the crystal ball question. How do you think... If we pick a date, five years, 10 years, whatever, how would organizations be using Lightcast type data in the future differently to how they're using it now? Or what would it evolve to, I guess?

Mark Hanson:  I think in the next five to 10 years, what we're going to see is an even deeper shift to that people-centric view of work. There's some great material out there that's called Work Without Jobs, and so how do we think about a truly flexible workforce that is built off of understanding people as a set of skills? Those skills can be deployed anywhere in the organization. They're not going to be tied down by functional areas or specific job families that they need to fit within, but they're going to be fungible. The work flexes based on a project basis versus a singular role that you do within a company. As technology expands with AI and the understanding of the underlying data components through a skills' lens, that is going to completely unlock how flexible an organization can be in the future. I think Lightcast's data set up perfectly for that because we're already mapping the global labor market from a skill perspective.

As organizations start to dabble in this and find the pockets of where this more Work Without Jobs concept would latch on, it's going to really not only help organizations flex to the most important things so that we hopefully can see less layoffs and things like that, and less knee-jerk reactions. We can redeploy talent much faster. But it's also going to be a wonderful thing for the employees and workers out there so that they can truly see how their skill development and where their skills are being deployed and what's the value of that. We should be able to see more direct compensation impacts as well as just longevity to be able to work on the most critical things and not be tied into one particular area where you might have a bad boss or you got put on a bad team under doing a certain role. It's like, "No, we can be more fungible. We can flex the team." That data connectivity is going to require a lot of horsepower from a data processing perspective, but also the rich taxonomies and ontologies needed to make those connections as well.

Bruce Morton: That's fantastic and so well put. Well, let's end on that positive note. I like it. Thank you so much again for your time today. Been great fun chatting with you. Love our partnership. Where can listeners go to find out more about Lightcast or even yourself?

Mark Hanson:  Lightcast.io. A little bit old school with not the .com. Get to Lightcast.io. Then you can find me on LinkedIn. Mark Hanson on LinkedIn, I pop up right away. If you search for Mark Hanson at Lightcast, I'll be right there and would love for anyone to connect. Bruce, it's been an absolute pleasure and been such a joy to work with your team over the years.

Bruce Morton: Great. Thanks, Mark.

Mark Hanson:  Thank you.

Bruce Morton: If you enjoyed this episode, please subscribe, rate and review us on Apple Podcasts, Spotify, or wherever you get your podcasts. And if you have questions, send them to SubjectToTalent@AllegisGlobalSolutions.com. Follow us on LinkedIn with the #SubjectToTalent and learn more about AGS at AllegisGlobalSolutions.com, where you can find additional workforce insights and past episodes. Until next time, cheers.