Put End Users First: Vermont’s Data Modernization Approach for Workforce Solutions

Transcript

Michael Schmierer [00:00:03]:

Why do workforce development efforts often feel fragmented and siloed? What if we could revolutionize the way we develop and support our workforce, using data and technology to bridge skills gaps and drive economic growth? As director of workforce and economic development here at Resultant, these are the questions that I ask myself frequently, which is why we're here. I'm Michael Schmierer, and this is my takeover of Data-Driven Leadership. In this four-episode miniseries, I'll be joined by several industry experts as we discuss how data and technology can transform workforce systems, enhance job matching, and support workforce readiness. The goal is to provide you with valuable insights and practical strategies that can help drive transformational change, inspire action, and foster collaboration among stakeholders. You won't want to miss this. Let's dive in. 

Hey guys, excited to launch our workforce miniseries podcast. Our first one gets some great insights from Commissioner Michael Harrington from the Vermont Department of Labor.

Michael Schmierer [00:01:03]:

We talk about both opportunities and challenges in the workforce and unemployment space, but then also innovative solutions using data, technology and even some AI to see how both government, employers, and individuals can help further their skills, their educational attainment, and get to meaningful work. Looking forward to the conversation. Commissioner Harrington, welcome to the podcast.

Michael Harrington [00:01:28]:

Hey Michael, good to see you again and talk to you again.

Michael Schmierer [00:01:31]:

Likewise. So there's a lot going on in the workforce and unemployment space these days. So let's just start high level, what are the prominent workforce challenges facing states across the U.S. when we start to think about labor shortages and skills gaps?

Michael Harrington [00:01:46]:

Part of it is we all recognize there is a workforce challenge and a workforce shortage. Here in Vermont, we feel it the same as other states do across the country. There just aren't enough workers for the number of jobs that are available. And the workers we do have don't necessarily have the particular skills we're looking for. So it is a national challenge, it's a global challenge. When we talk about the issues, though, I think we have to look holistically. So a lot of the things that impact workforce really have very little to do with the department of labor or workforce specifically. So we can talk about having enough people or providing them the right skills and training opportunities to upskill or reskill them.

Michael Harrington [00:02:29]:

But I think what we're finding in Vermont, and I think this is true elsewhere, is that the things that are either driving our workforce or hindering our workforce are really at the community level. So think of the fact of how much housing prices and costs have risen in the past five or ten years. Think about how hard it is to find child care and then be able to afford child care. Think about health care related issues and the fact that it's hard to find a primary care physician or to even afford the health care we and our families need. So here in Vermont, our biggest roadblock to expanding our workforce is in the housing sector and elsewhere. But really, there aren't enough housing units. Whether it's a single family home or a multifamily dwelling or condos or whatever, the units just aren't there to support the workforce we need. And when we think about the units that do exist, they're way outside people's price range.

Michael Harrington [00:03:32]:

So for us in Vermont, if we want to be increasing our workforce so that we can meet the needs of our employers, we're having to make foundational changes at the community level to really drive our economy.

Michael Schmierer [00:03:47]:

Yeah, I mean, you hit on a really good point about the workforce system is not just the Vermont Department of Labor, it's other state agencies. Your local and regional economic development partners all play a role in this. And obviously, the outcome that everyone's hoping for, both for the citizen being economic mobility, increased wages, increased educational attainment, and businesses finding employees that can drive that. Can you talk a little bit about the impact on the businesses, and what does that look like if we are not able to solve some of these challenges that you just hit on?

Michael Harrington [00:04:20]:

Businesses, I think, are feeling it, and we see that in either the time we have to wait if we go to a business. So you might go to a grocery store, and instead of having ten lines open, you have two, or we may go to a restaurant and realize there aren't enough servers, or they might have off hours, or we have employers that are having to pay more in wages to either attract new workers or retain the workers they have. So we're also seeing prices increase as well. So, again, when we talk about things that are really hindering our workforce, but also employers, it's everything from inflation to the types of services we see. And we expect, we've come to expect on a regular basis, I think what probably happens behind the scenes that we aren't always familiar with is the supply chain issues, right? Which are heavily driven by workforce or the lack of workforce.

Michael Harrington [00:05:12]:

So where I might be able to order something online, and traditionally, I could get it in two days, it might take four or five or six days now. And that's a direct result of maybe not having enough drivers to deliver the products to my home, or it could be that there's a waiting period for the products needed to make the end product. So again, it's having a ripple effect that we are feeling. We may not always attribute it to the workforce, but we certainly are feeling it in our day–to–day lives. And I think businesses are as well. They're having a hard time keeping up with demand. And here in Vermont, they're struggling to meet the needs. And I hear often about businesses that could actually be making more money if they actually had the workforce to support the demand for their products and services.

Michael Harrington [00:05:59]:

But it's actually the confining nature of the limited workforce that's holding them back.

Michael Schmierer [00:06:04]:

Yeah. It hurts the economic development as well, of bringing in jobs and expanding companies within states as well. We talked kind of at a high level. I'm wondering if there's any specific things that Vermont Department of Labor or Vermont itself is kind of focused on to solve some of these big challenges.

Michael Harrington [00:06:21]:

We are, and I think some of it is what I've talked about. And that is really, we have to think about the root cause, right? So we can focus on the symptom, which is maybe a business not being able to find the right worker or a worker with the right skills, or there just aren't enough workers. But again, the root cause of those symptoms we're seeing are things that are actually preventing either people from coming to Vermont or people from staying in Vermont. And I often use the analogy of, imagine a bucket that you're trying to fill with water from a hose, but there's also holes in that bucket. Water represents our labor force. We can sit there and turn the spigot open all the way and try to put as much water in that bucket. But depending on how big the holes are, we may never fill the bucket.

Michael Harrington [00:07:10]:

And so it has to be a two-pronged approach. We have to be thinking about what are the ways we can either grow the size of our workforce… so, how do we introduce more people into our workforce, which is the hose in the water, but also how do we plug some of the holes? So when someone graduates from high school or college or a certificate or degree program, are they choosing to stay in Vermont? If I'm a working age adult and I've lived in Vermont for the last ten years, am I choosing to go elsewhere because it's more affordable somewhere else? Or, again, one we often see, is it just too costly or too difficult and I'm forced to have to leave? We can look to grow the population from within. So how are we fostering growth from the individuals and the population we already have? I think what we've also recognized here in Vermont is if we look at our projections about people entering the workforce, if we look at the number of people that are unemployed at any given time in Vermont's workforce, there's typically two jobs for every one unemployed person in Vermont. And so we could put everybody back to work, and that's assuming they all have the same skills and they live in the right area for the job. But at the end of the day, we still wouldn't fill all the jobs. So I think from our standpoint, we've got to be looking at other ways, grow our workforce, attract people.

Michael Harrington [00:08:36]:

And so the question becomes, why would you choose Vermont? Or why wouldn't you choose Vermont? And to me, those are the things that we have to be focusing on. So at our most basic level, it's affordability, it's child care, it's health care, it's education, it's housing, transportation. The things that really drive community development and foster population growth.

Michael Schmierer [00:09:01]:

Yeah, really good points there. I think demographics show across the country with baby boomers retiring and all of them reaching retirement age by the end of this decade, it's something that states are going to have to focus on now in order to make sure that they're ready for that in the coming five or six years. We're on a podcast called Data-Driven Leadership. So we’ve got to talk about data and technology. I know Vermont's done some work with your UI modernization. Just wondering, what role does digital transformation play, not only in unemployment insurance, but what it means to your department as a whole?

Michael Harrington [00:09:35]:

So before I became commissioner and even before the last job I had, I worked for an organizational development firm. It was my family's company. And so, doing a lot of work, both not only in data, but the idea of continuous improvement and how we use data to improve. So the data is important to have, but it has to be usable data. And then you have to have the culture in the organization to actually have people use the data, right? So, again, really thinking about the humanistic side of that, I think a couple things. One, we have to begin with the end in mind.

Michael Harrington [00:10:09]:

So if we don't know where we're going, we're not going to know how to get there. I think the other piece that we're seeing is when we think about data, a lot of the data that state labor departments collect is really designed for the federal government, right? So I think you have to decide, like, what is the data that's actually meaningful to me? What actually tells me that what I'm doing is good, and how do I know when it's successful, right? And if I can't answer that, then I'm not collecting the right pieces of information. So we have to, you know, there's a lot of data we're required to capture. At one point, we looked at the number of different data points we collect in our workforce development division, and it's like over 400 different data points. My guess is there's five data points, or maybe less than ten, that actually mean something to somebody. And so we have to be also thinking about what is the most meaningful data we collect. The other piece is that we have to think about data in real time.

Michael Harrington [00:11:10]:

Right? So the fundamental flaw in the data we often collect is that we get to the end of a period. So let's say for us as a state, we have to report quarterly to the federal government on our progress. Different programs. Well, if we only take a snapshot in time at the end of each quarter, we don't actually have the ability to course correct to achieve our goal. We only know whether or not we won or lost at the end, right? So imagine playing a sports game but not knowing the score till you get to the end, right? And then you're like, well, great. I learned that I lost, but I have no way to fix it, right? I have no way to change my strategy to make sure I win in the end because I don't know the score till I get to the end. So we have to think about what data can we be collecting in real time? So if we're needing to meet a certain benchmark or threshold by the end of the quarter, how are we collecting data at the daily level, the weekly level, the monthly level, that ensures that we're actually on target to reach our quarter goal? And if we can't do that, then what you find is most states go, I don't know.

Michael Harrington [00:12:21]:

We'll see what we get when we get there. And that's where I think a lot of them fall short. From a data perspective, we have to be thinking and framing it in the right way. I know that doesn't answer your question about modernization, but I think those are some really important things that I've tried to share with my team here, which is, how are you collecting the right data, and how are you using it to actually achieve the end goal?

Michael Schmierer [00:12:45]:

No, I think that's a very good response. Just having data doesn't mean anything unless you can get it in the right hands, to the right people at the right time, and having some sort of early warning indicator, whether that be through a data–science–type approach or just some sort of agile methodology in order to make sure you're getting those interventions or those pivots at the right point.

Michael Harrington [00:13:09]:

To hit those targets for us here in Vermont, we are going to modernize our unemployment insurance system. We're also modernizing our workforce development system. Both of those programs are many years old. Our unemployment insurance system, the actual code we're using now was developed in the eighties. The first electronic processing of a claim happened in the seventies. And it's really been that core system that's been here the entire time. But, to the point about data, is that if we want to pull data from our mainframe, we actually need a mainframe developer to run a query and pull the data each time. And so it's a very manual process and we don't necessarily have a way to automate that process right now or get real-time data, right?

Michael Harrington [00:13:54]:

So, there's very limited reports that we can even run on the business side. So the idea of having a modern system where there's automatic reports that get generated on a daily, weekly, or monthly basis, but also then the ability for our team to say, here's something we often don't see it need or see on a regular basis, but I need to pull it real quick. So the ability to pull ad hoc or manual reports from the system I think will be incredibly crucial for us to be able to again make sure we're moving in the right direction.

Michael Schmierer [00:14:27]:

Yeah. And then just going back to your earlier point about the end user in mind, a modernized system is just a lot easier for your citizens to help to navigate as well. And people that are applying for unemployment insurance, there's a lot of disadvantaged populations that might have a hard time with some of the older technology. So getting that interface right and entry points can also be a big help to the citizen.

Michael Harrington [00:14:50]:

That's been one of our key pieces. You know, we can talk a lot about modernization, but at the end of the day, who's actually using it and what is the method they feel most comfortable using? And so when we think about it, here in Vermont, we'd love to do everything online. We'd love to do electronic fund transfers right into somebody's bank account. But we still have people, as many states do, that either aren't comfortable using the Internet, they don't have a computer at home, they have no connectivity, they don't maybe use a bank, and a lot of their stuff is done with cash. So again, there's just a lot of different variables. So we have to be thinking about the entire workforce or the user population and how do we make sure we're building a system that meets their needs?

Michael Schmierer [00:15:35]:

Yeah, no, some really good points there, I think. Not just in workforce or labor, but any government project that involves technology, that's critical because you have to serve everyone, not just a specific population. Want to maybe pivot a little bit. Still talking about technology and data, artificial intelligence, it's been talked about a lot in the workforce space, both from how can we leverage artificial intelligence to better our systems or our programs, but also maybe a fear of is artificial intelligence going to take away jobs? So just general thoughts. How does data analytics and AI transform workforce development?

Michael Harrington [00:16:13]:

So there's obviously a lot of theory out there, a lot of conversation about the future of AI and how it will change the world we live in. I don't argue any of those points. I agree. But, you know, we're really talking about how do we use it as a tool for the purposes of this conversation, certainly we need to be mindful of how it's impacting our workforce, either for the good or for the bad. I was thinking about this question, and what I really came up with was how do people use AI? How do businesses or employers use AI, and how can government use AI? So from the people perspective, it can be everything from helping them draft a letter or a resume. If they're a job seeker, it could be helping them to better discern what career path they want to follow. So by putting in some simple trigger words or content, they can maybe get a better concept of what lies ahead of them in terms of a career path or what training would be needed. How do employers use it? So how do they build it into their systems to, again, meet the demand without maybe needing as many employees? And again, I think you can look at that two ways.

Michael Harrington [00:17:26]:

Either you're using AI to cut jobs, which is nothing necessarily a good thing, or you can say, listen, we don't have enough people to meet the demand, and so we have to use AI to help us meet the demand with the workforce. We have.

Michael Schmierer [00:17:40]:

Sorry, not to cut you off there, but in many circumstances there, right, the AI might be doing, you know, smaller tasks, and then we can upskill our workforce and they can make a higher wage and take, take some of those jobs that technology can't do, that pays them more and increases their educational attainment with it.

Michael Harrington [00:17:56]:

Yeah. And so, you know, AI can be used from a training perspective, it can be used to help somebody. The department of labor here in Vermont, we struggle with workforce just as much as any other employer, right? So also, if we're thinking about how to best serve our constituents and our customers who walk through the doors of our job center. AI becomes a tool for us to be able to again link them with the resources they need without maybe needing a human interaction right at the onset. And I think when we think about AI from a government perspective, we should be thinking about it in terms of service to the customer or service to the constituent, and that could be an employer or it could be an individual. But when we think about how do we provide better service, it might allow us to process unemployment claims faster.

Michael Harrington [00:18:45]:

We might be able to conduct our fact finding on claims in an automated fashion where there's an actual AI behind that, actually coming to some level of processing or determination with needing a physical touch from a human being to start. Or again, it could be in our job centers where we're using AI as a training method to provide virtual services. So there are a lot of different ways, I think, to use AI as a tool to increase productivity, to improve the quality. I mean, the ability for us to use AI to translate something into a different language for someone with limited English proficiency, or the ability to even look at the way we're communicating to certain members of our population, the ability to run that through an AI bot that can actually hone it, to make sure our messaging is on target to reach a better result. I think those are things that we, you know, we may not have the expertise in house to do that, and in the past, we would have had to find a contractor or a vendor and get their assistance, where a lot of this allows us to do it in real time to provide faster service, but also more complete service as well.

Michael Schmierer [00:19:59]:

Yeah, I mean, I think you hit on some really exciting things. I think there's trepidation about AI for good reason, and we need to make sure that it's being used in an ethical and moral way. But I think there's a lot of really cool use cases out there for the three groups that you talked about to explore; citizens, employers, and then the government itself. We talked a little bit about this earlier, and you alluded to some exciting things, I think, happening in Vermont with your workforce modernization and unemployment modernization and maybe some barriers that you have right now. Given the state of your UI modernization, your unemployment insurance system being so old, how do you envision using data to help inform those two large initiatives or any other initiative that the department's undertaking right now?

Michael Harrington [00:20:45]:

There's a couple different aspects or ways to use data. We were just looking at some data around job growth and job loss right across the state by particular county. The question really was, so here are these numbers. What does it actually mean or how can it be useful? We collect a lot of data. It's not all useful. So again, I think understanding how to use that data to help decision making or help inform decision making, there are two pieces. I think there's the data we use internally that helps us understand how effective we are in connecting with our customers and our clients, how effective our training programs are. So if somebody goes through a training program, what was their starting wage before the training program, and then what was their wage after the training program? And what was their wage they earned six months after training? So did we actually upskill them in a field that then pay dividends down the road by improving their life and their economic value, if you will, in some way, shape, or form? I think there's also the data we use to say, okay, how fast are we processing claims? Are people having to sit and wait too long? Or how fast, from the point that someone submits a workplace safety complaint, do we actually have someone in the field going to inspect that business? So there's that type of productivity data that we're hoping to be able to use and collect as well. But I think there's also the data that the public needs.

Michael Harrington [00:22:17]:

So, you know, one of the things is that our modernization project has been very well known and something I think Vermonters are eager to see. I know our legislature and our governor are eager to see it come to fruition. So we're also talking about how do we construct a public-facing data dashboard around the project in general? So how are we communicating updates and our progress to keep people engaged so that they understand where we are in the process and the process steps we're going through? What are the challenges or risks? What's the natural progression of the project from beginning to end? How close are we? Are we spending the money effectively? Are we going to run out of money? Are we going to have money left over? Are we going to hit our timeline? You know, that's all data that I think we can share publicly that hopefully ties the public to the project and our mutual desire to see it succeed.

Michael Schmierer [00:23:11]:

That's an awesome level of transparency for everyone involved in that type of project. NASWA, the National Association of State Workforce Agencies summit is coming up here in a couple weeks. You've had the opportunity to serve as the chair of that organization for what, the past year, year and a half? I want to give you opportunity to talk about your work there and how NASWA helps states in this space.

Michael Harrington [00:23:33]:

So I would say that NASWA, National Association of State Workforce Agencies, is a pretty unique association. So, you know, over my lifetime, I've belonged to a number of different organizations and associations. They're usually member-driven. They might have some policy work that they do, or they might have some very limited actual services or products that they provide some value to their membership. But I think what I learned, and I've heard this multiple times from multiple different state leaders, is that the National Association of State Workforce Agencies is probably one of those associations that is extremely heavily driven on membership value. So what do you get for your membership and actually providing direct service and direct products. So, for instance, yes, it is a way for different states to become members to go to different conferences and learn on different topics and engage with people of similar backgrounds from other states to learn collectively like that. But at the same time, NASWA provides all states an opportunity to use what they call their data hub through their integrity data center, which actually reviews all state claims, unemployment claims, and actually ranks them and flags them for suspicious fraudulent activity.

Michael Harrington [00:24:57]:

Right? So that's a direct service that's free to states where you take every initial claim that gets filed and every following weekly claim that gets filed, and you run it directly through their system, and they will send you a report back flagging claims that are suspicious. They have an extremely vast knowledge center and library of training. So they have entire curriculums that actually, like, I as an employer can have our staff, especially new employees, go through an entire training series through their learning system to learn the basics of maybe unemployment insurance or workforce development or even some subject matter expertise in a particular function or area, like tax and contributions or fraud mitigation and prevention. So I think those are two real tangible ones. But they also have an extensive staff that will actually go into states and provide direct service to states. So they'll do consultative work as well as some direct product support and work as well. They also manage, and I think this is probably a little-known fact and probably something that people aren't familiar with unless you're working in state government. They also manage, in partnership, the National Labor Exchange system, or NLX.

Michael Harrington [00:26:16]:

And that is amalgamation of many different sources that compiles data on available jobs across the country and within individual states, and they help feed that data into each state's labor exchange system. So think about indeed.com or Monster. Every state has to manage a labor exchange system where employers can post jobs and job seekers can post resumes. And so at NASWA, they manage the labor exchange system that actually compiles that data and will upload it into each state's job board. So again, there's a lot of different direct services that, you know, you get simply by being a state member. And I think that's a really great aspect of NASWA that I don't necessarily see elsewhere.

Michael Schmierer [00:27:03]:

Yeah, no, that's all really good stuff. And have heard some states thinking about how they can use that NLX data to further some other projects. I know you're handing off the baton of leadership after the summit, so I speak for ourselves and others. Thank you for your service there and appreciate your time on the podcast. We hit on a lot of things, but wanted to see if there's anything else that we didn't talk about today that you wanted to bring up before we wrap.

Michael Harrington [00:27:27]:

I think at the end, again, it's beginning with the end in mind and thinking about how data can be most meaningful, can tell a story to your staff, but also informs their decision making as close to real time as possible. And so for us here, we're constantly looking at different ways to improve our processes, but we can't do that if we're not collecting the right data to know whether we're actually making progress. I think overall, we can also use data to tell a story for our public customers. So I think I would also not throw away or minimize the power of visualization of data. So, it's one thing to have the numbers on a spreadsheet, but, really, we should be talking about how to communicate data in a meaningful way. So whether it's through graphs or charts or infographics, but again, numbers on a page don't really speak to people. But data can tell a really compelling and important story if it's communicated the right way. And I think that's where we're constantly saying we oughta data, right?

Michael Harrington [00:28:32]:

It's not about not having the data, it's about how do we take the data we have and actually put it to good use. That's our focus here. Appreciate, as always, the time on the podcast and working with you, Michael. So thanks for the time and the opportunity.

Michael Schmierer [00:28:46]:

Yeah, no, we greatly appreciate it. And to hear more from Commissioner Harrington, you can find him on LinkedIn. Additionally, you can stay updated on the latest workforce development initiatives by following NASWA on LinkedIn and the Vermont Department of Labor at labor.vermont.gov. As always, thank you for joining us on Data-Driven Leadership. Don't forget to follow Data-Driven Leadership wherever you get your podcasts, and leave us a rating and review to let us know how these data topics are transforming your business. Be sure to check out the rest of our workforce miniseries, where we will explore future workforce development and initiatives. Well, just like in today's episode. Thank you for listening to my takeover of Data-Driven Leadership.

Michael Schmierer [00:29:28]:

For more on me and Resultant, check out the links in the show notes.