Data Driven Leadership

Workforce Recommendation Engine Empowers Indiana Job Seekers

Guest: Josh Richardson, Chief of Staff, Indiana Department of Workforce Development

In this conversation, Indiana Department of Workforce Development Chief of Staff Josh Richardson shares how data can shape employment strategies and personal career paths.

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Data-driven decisions are the future of employment.

In this conversation, Indiana Department of Workforce Development Chief of Staff Josh Richardson shares how data can shape employment strategies and personal career paths.

Josh shares his journey of working on the development of Pivot, an innovative tool designed to empower individuals experiencing job loss. He explains the importance of data sharing, collaboration, and feedback in launching the tool.

Throughout the conversation, we explore the intersection of data, leadership, and public policy in Indiana's approach to workforce readiness.

In this episode, you will learn:

  • How Indiana's DWD is leveraging data to connect people with jobs
  • How to manage skeptical feedback (and why it’s actually a good thing)
  • How to minimize the effort required by users to achieve meaningful outcomes

In this podcast:

  • [4:00-12:00] How Indiana’s DWD uses data to connect people with jobs
  • [12:00-17:30] Using data to help people envision potential career paths
  • [17:30-28:00] The importance of user agency and autonomy
  • [28:00-34:00] Possible future uses of the workforce recommendation engine
  • [34:00-39:14] The value of skeptical feedback

Our Guest

Josh Richardson

Josh Richardson

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Josh Richardson serves as Chief of Staff with the Department of Workforce Development. He returned to DWD in March of 2018, having previously served the agency in various capacities in the administrations of Governors Mitch Daniels and Mike Pence. Richardson is now in his second stint as Chief of Staff, previously serving in that role for Commissioner Fred Payne.

Richardson previously worked for the National Association of State Workforce Agencies' Integrity Center where he advised state agencies on various methods to reduce fraud and improper payments in their unemployment insurance systems. He has also served as the Director of Indiana's Unemployment Insurance System and in the office of Governor Mitch Daniels as a Policy Director.

Richardson was raised in Blackford County. He graduated from Ball State University and the McKinney School of Law. He is licensed to practice law in the State of Indiana.


Jess Carter [00:00:01]:

The power of data is undeniable and unharnessed. It's nothing but chaos.

Speaker 1[00:00:06]:

The amount of data, it was crazy.

Speaker 2 [00:00:08]:

Can I trust it?

Speaker 3 [00:00:09]:

You will waste money.

Speaker 4 [00:00:11]:

Held together with duct tape.

Speaker 5 [00:00:12]

Doomed to failure.

Jess Carter [00:00:13]:

This season, we're solving problems in real-time to reveal the art of the possible. Making data your ally, using it to lead with confidence and clarity, helping communities and people thrive. This is Data Driven Leadership, a show by Resultant.
Hey, guys, welcome back. It's Jess Carter with Data Driven Leadership. And on today's episode, we're going to be talking to Josh Richardson, who's the chief of staff at the Department of Workforce Development in Indiana. Side note, if you ever listen to the news in the beginning of each month, you might hear them talk about the wage report, the wage data coming out that is federally mandated as a collection of data from the states to the feds that is usually managed by the Department of Workforce Development in your state. Josh works in that department and he has spent over a decade thinking deeply about the data that they have and the unique data that they hold and how we could leverage that to better serve citizens.

Jess Carter [00:01:11]:
I think this is an opportunity for anyone in leadership to think about what data they have in their organization. That is an asset that's unique to their own organization and think about how they can better leverage that creatively to serve a purpose or to help meet a need, either in the organization or with your constituents or clients, customers even. And so as we get into this, you'll kind of hear more about how Josh unpacks his idea and you'll get to hear it from idea and vision to fulfillment. And I think the other thing that's neat, too, that Josh highlights is there are a lot of people around him that helped bring this idea through fruition. And so it's also looking at the greater picture of what you're trying to accomplish and recognizing who's around you that you need to be for you and for this vision and how do you pull them in and help them get excited about it? I hope you enjoy this episode. Let's get into it.
Jess Carter [00:02:16]:
Welcome back to Data Driven Leadership. I'm your host, Jess Carter.
And today we have Josh Richardson, the Chief of Staff at the Indiana Department of Workforce Development. Let's get into it. Welcome, Josh.

Josh Richardson [00:02:22]:
I'm so happy to be here. Thank you, Jess. Let's get into it.

Jess Carter [00:02:25]:
So Josh is maybe the first person on the show that I have had the pleasure of knowing for nearly ten years.

Josh Richardson [00:02:34]:

Jess Carter [00:02:34]:
It's been a minute. I remember you walking into a room with the commissioner, with Scott Sanders at the time, to talk to the PMO about the unemployment insurance system that was going live. And that was the first time I got to meet. I remember the exact moment when I got to meet you. I'm sure I was as memorable as you.

Josh Richardson [00:02:50]:
I do remember it. I would have had trouble remembering the rest of it, but. So here you are, promoted the way up to podcast host, and I'm still doing the same thing.

Jess Carter [00:02:58]:
It's great to be with you, Justin. Yeah. Lots of good stuff over there. Sure. Chief of staff. You've also been promoted to something that's a little more so important. Okay. This is also difficult.

Josh Richardson [00:03:09]:
Let's go.

Jess Carter [00:03:10]:
So when I first joined DWD or was helping as a consultant, I had never heard of the Department of Workforce Development. So when you pitch that to someone you meet or at a kid's sports game or something, what do you explain about, give me the elevator pitch for what is DWD?

Josh Richardson [00:03:25]:
So it's a good question. And the thing is that that explanation almost switches a little bit depending on the economy, because we have two real main things that we do from an overarching perspective. One is that we administer the state's unemployment insurance system. So that's more than half of the employees at the agency. But so really, that's everything from collecting the employer taxes that go into collecting the trust fund, all the way to paying out those benefits to insuring fraud. We hold appeals within the agency, but the other side of the agency is really workforce training. And I think largely that is how you would connect individuals that were unemployed to work. But it includes things like upskilling existing workforce.

Josh Richardson [00:04:05]:
But a huge part of it is data. Right? We collect so much information about the workforce through both sides of that system, information about what's available, what skills are in demand. And so it's kind of that nexus that joins the two sides of the agency.

Jess Carter [00:04:20]:
Okay. And to your point earlier about the economy, whether it's really great or really not great, one of those sides of your agency sort of ebbs and flows. Is that fair?

Josh Richardson [00:04:30]:
It's an interesting piece where when we've gone through periods like the Great Recession or certainly during the pandemic, really everything that we do at the executive level, so much of the focus is on unemployment insurance. But now the pendulum is almost the entirely, entirely in the other direction, where so much of the focus is on workforce. Because really, across our economy, from frontline work all the way up through the highest skilled jobs that we have, everybody needs skilled workers in order to run their business, and so lots of focus there. We're still cleaning up some of those issues. But, yeah, it is really interesting how the conversations change at that executive level.

Jess Carter [00:05:09]:
So few people in my career so far have been as passionate and innovative in their space as I would argue that I have observed you. I realize that you're not going to toot your own horn, but I will for you that there is a passion that just comes out of the work. Was that always there? How did you become so passionate about DWD?

Josh Richardson [00:05:29]:
I don't know, because we probably won't get into it on this podcast, but it was kind of an accident that I'm here. I will say that I've always really been in love with public policy. The idea of having big puzzles to solve that actually lead to real outcomes for real people. So I think that's always been there. But it has been interesting that the Department of Workforce Development has been a really good mix because so many of the things that are my interests, from economics to data to law to politics, sort of all of it, has ended up being able to there are things that I get to do every day in many of those different areas, and I think it's helped drive the passion. So, yeah, I hope so. You're right. I think maybe I won't talk too much more about that, but that's right.

Josh Richardson [00:06:13]:
It's been great for me, and it's easy to find the passion to do this work.

Jess Carter [00:06:17]:
Okay, well, so that's fine. We will get into sort of the interesting thing to talk about here that I'm really excited about is, and I want to talk about how it kind of came to be, because I have this memory, another memory that's a really particular image of me sitting across a lunch table from you in 2014, 2015. And on a napkin, you drew out the concept for this project that—and I'm not even sure, what are we calling it?

Josh Richardson [00:06:44]:
Well, so I think the Workforce Recommendation Engine is sort of like this all encompassing tool that covers all of it. And then Pivot is really the name of the tool that thus far we've launched.

Jess Carter [00:06:54]:

Josh Richardson [00:06:54]:
So that's the interface that people are interacting with. But I do think just as this broad concept, the workforce recommendation engine, probably covers everything there.

Jess Carter [00:07:02]:
Okay, you drew this out for me at a really high level. Can you kind of, again, elevate your speech of what that high level was? What was the idea?

Josh Richardson [00:07:12]:
I mean, there are a couple of different things that all come together at once. One is at the Department of Workforce Development, we are privy to a significant amount that we mentioned this earlier, like, a significant amount of data about the workforce. One of the biggest pieces of that are unemployment insurance wage records. And so, just quick version, every quarter, every employer in Indiana is required to report at that individual level the amount of wages that they've paid to an individual that they employ over the years. Researchers often ask for that data, so they come through the Bureau of Labor Statistics, and they come to us with a request and do all sorts of really interesting research topics using these wage records. And so that's one, two is on the workforce side of the house. There's often so many acronyms, so many programs, so many different baskets of funding that it gets really difficult, even for our staff, let alone the people that we serve, to figure out how to connect those.

Jess Carter [00:08:16]:

Josh Richardson [00:08:17]:
And so I think as I started to learn a little bit more about the data we had access to, and also as technology changes and more focus on data-driven-type decision making, I think really looking at this saying, I wonder if we can use wage records, if we can use this data that we have access to that the private sector really can't get. Again, a lot of this is confidential by federal law, and for good reason. But what if we could use it to help figure out how to match up the services we have with the people that would be most likely to benefit from them? And it really kind of grew from there. And technology has changed a little bit, too. I mean, I love the idea that I drew this out on the napkin largely. Yes, that's true. The vision has stayed the same. But what's happened is that I think as the technology has advanced, it both made it sort of more tangible, but it also has allowed us to do it in really a way that I think probably exceeded even what I was hoping for at that point.

Jess Carter [00:09:16]:
Well, and so for right now, just to get really pragmatic and make sure I understand, because I've been on a lot of projects adjacent to this one, but not on this project. So, if I understand at brass tax here, if I'm on unemployment in Indiana, I have the opportunity to leverage this Workforce Engine to the, I hope I don't get this wrong here. The most effective things I could be doing, skill sets, education to gain, to skill up, essentially get re-employed.

Josh Richardson [00:09:44]:
Right. So, where we're at right now is really focused on occupational change.

Jess Carter [00:09:51]:

Josh Richardson [00:09:51]:
So we're going to add more and more elements to this as we move forward. And obviously, this is still a work in progress. Again, think about it this way. So about 3.2 million Hoosiers in Indiana's workforce. And every quarter, those individuals are having those wage records reported. And so what we can see is sort of career transitions. We can watch people as they move through and as their jobs change and as their industry changes, the place where they work changes, their wages change.

Jess Carter [00:10:19]:
Got it.

Josh Richardson [00:10:20]:
And so by using that, when an individual files an unemployment claim, so should also say this, there are something like, at a higher level, we can kind of classify jobs into 830 different occupations.

Jess Carter [00:10:34]:

Josh Richardson [00:10:34]:
So, obviously, it gets more specific than that when you drill down. But I always think for a lot of people, if you gave them a pencil and paper and said, write down as many occupations as you could think of, I don't think they'd get that.

Jess Carter [00:10:47]:

Josh Richardson [00:10:47]:
And I think what we have is you have a person that's filing an unemployment claim. That can be a really stressful, that can be a scary time. And their first question is, how do I successfully make a transition back to work? Yeah, I like the job that I had, and I'm really disappointed it's gone. Maybe I didn't like the job that I had, and I'm ready for something new, but trying to be in that spot where they've got to figure out what to do next is tough. Well, so the idea is that what we can maybe do is leverage these wage records, leverage this information that we have to figure out where we've seen people make a successful transition that were in that same position before. So, a factory worker in Richmond, Indiana, who lost a manufacturing job after 20 years with a high school education. We can look at many of those same factors and see, okay, of the people that were in that similar spot that made a career change, which ones were most effective? Putting that as an option in front of that person.

Jess Carter [00:11:40]:
Right. So it gives in that moment when there might be some high emotions because we are unemployed and we don't want to be, it gives somebody some sense of a shortened, more data-based menu of where other people have gone in case they haven't thought of that, or consider those as options that are easily attainable potentially. Right. Is that fair? Right. Okay. And is this the only place this is happening? I mean, I know that workforce agencies are federally mandated. They're in each state. Are we doing this in other states?

Josh Richardson [00:12:10]:
I mean, as far as we know, this is the only one like it. Now you'll see as we're adding AI to essentially everything that exists, there are tools out there that try to use artificial intelligence to match people with jobs. A lot of times, those are skills based and those are exciting, too. It'll be interesting to see how they develop, but where they'll do things like, you tell us about your prior jobs, we'll try to identify skills. Then we're going to look at job postings, we're going to try to identify the skills and match them. So it's an interesting component. But what's really different about ours is that we don't actually have to ask this person for any additional inputs. And we're using these administrative wage records. And so instead of someone having to sit down and try to match these skill pieces and try to figure out what's relevant, we can just see what's worked for other people.

Josh Richardson [00:12:55]:
And so nobody that we're aware of has figured out how to use these state data sources as the driver of this kind of information.

Jess Carter [00:13:04]:
That is so cool. This is a tool. This is data as an asset to the agency that has not been utilized in an effective way like this before. And we can start from here.

Josh Richardson [00:13:13]:
That's right. And like I said, I think that the other tools are really exciting, too. And with all this AI, really excited to see where it goes, but I think they require a decent amount of effort from that individual. You usually have to try to drive them to a standalone website or something, encourage them to participate. And sometimes it's hard for them to sort. There's so many different tools out there. We talked about this before. How do I know which one to use? And so we really love the idea that this is just a part of the unemployment claims filing process.

Josh Richardson [00:13:44]:
Essentially, they sort of can't avoid it. They're going to see these options. And so it's a low effort from that standpoint. But obviously if they're going to get much out of it, we want them to interact. And a big part of this is the autonomy of that individual. I'm excited about the skills-based stuff, but in our case, we almost skip that step, right? Instead of having to say, look, we know that there's some skills mapping. When we see people move from one occupation, we see these successful careers into another, there absolutely are going to be some skills there. But with this tool, we don't really have to define them.

Josh Richardson [00:14:18]:
We just know that we've seen them be successful. And I think that's really cool. And I think.

Jess Carter [00:14:26]:
You mentioned this or alluded to it earlier. The, call it customer experience of UI, can be tricky, right. Because it is a bunch of different federal or state programs depending on where you are, and then they get enrolled in one or the other, and it can be a little confusing to navigate. And the fact that you're giving them an additional service through this unemployment experience, right?

Josh Richardson [00:14:48]:
Yeah. So, the tool itself is absolutely the additional service. I think one of the interesting things about these problems are, almost in every case, we can help, but the work is going to be on that individual. At the end of the day, they're going to be the ones who have to take this leap towards a new occupation or, in many cases, enroll in the kind of training that will better their outcome. So we can't do that for them. Right. This is going to take their work. It always will.

Josh Richardson [00:15:15]:
But I think that the key point is trying to reduce the level of effort that it takes to figure out what that path looks like and also increase their confidence because this tool helps them better understand the outcomes they can expect. Again, based on people like them who have made that transition.

Jess Carter [00:15:32]:
I love that concept of you're almost immediately helping them envision where they might go. That can be a real gift to people that are in the middle of this process. It's not exactly a confidence-inspiring moment in general. And the fact that they can immediately start to see what might work is a real kind of a gift.

Josh Richardson [00:15:47]:
Yeah, well, and I mean, you've slowed me down a couple of times already to talk through this just because of how many different things that are happening. And I think it's really easy to take for granted on our side. Like, I've now spent 15-16 years in this world and so kind of know where these programs are at. But for someone who's just been working, this is an unexpected job loss. They haven't done any of this background work. And so really being able to cut down on the amount of effort that it takes in this stressful time to see what might work, I think the best thing that we're doing with the tool.

Jess Carter [00:16:19]:
Yeah. Okay. So question for you, in this whole process, from ideation to—it's live, right?

Josh Richardson [00:16:27]:
Right. Yeah, we're up.

Jess Carter [00:16:28]:
What surprised you about the process?

Josh Richardson [00:16:34]:
I think that there are so many different surprises as we move through this. You asked the question earlier about what their other states were doing this. I think one of the things that's become clear is that Indiana has really done some things to set the stage to make this possible. And I think that there have been some times through this where I've realized, you know, like, we're actually in really good shape. The conditions were right to do this here. And I think that the truth is, and again, I'm not an expert at truly what every single other state has, but between our Management and Performance Hub and between these data sources and sort of the maturity of these data sources that we have, the relationships with other state agencies, we've been able to do. So, when we look at other states, they're just starting different components of this process. And so that's been exciting for me to see Indiana's real leadership in this data-driven world.

Josh Richardson [00:17:25]:
And so that's been interesting and exciting. Yeah, I think maybe that's the biggest surprise.

Jess Carter [00:17:31]:
Well, and when you say that, so, I'm going to non-public sector translate some of what you just said, and you tell me if I'm right. So some of the themes of what I just heard is we did go through this unemployment insurance modernization, so the system, we went through that in 2014.

Josh Richardson [00:17:46]:
It was a long period, 14 launch, but yeah, started many years ago.

Jess Carter [00:17:50]:
So kind of new system with new data access that we have, and then we have the Management Performance Hub. And so data sharing, data privacy protection that as we pull data from different agencies, there's protection, but there's collaboration that's possible with interagencies. And so when you talk about workforce, so the wage data, my data will be Jess Carter Resultant, blah, blah, blah blah, right, every quarter. But then you have the unemployment data. So, you know, if I'm unemployed, too, but you don't have the education data that comes from IDOE, right?

Josh Richardson [00:18:23]:
Or the commission for higher ed or another state partner.

Jess Carter [00:18:24]:
This is, it's necessitating that kind of a collaboration across all of those datasets. Is that fair?

Josh Richardson [00:18:31]:
That is correct.

Jess Carter [00:18:32]:
Okay. And that's where MPH plays a critical role.

Josh Richardson [00:18:35]:

Jess Carter [00:18:35]:
Okay. And so it's sort of like you have these modern systems and this interoperability of data that's flowing between these entities, that's protected, that is timely as much as it can be, knowing that the quarterly data, et cetera, some of that seems really important to me. When I say IDOE, I mean Indiana Department of Education, you have to remember to get your tough year acronyms and MPH is Management Performance Hub, which we already talked about. Okay, so to your point, you're saying we didn't just build this, it was built on a foundation of the commitment to data and technology advances we've already been making.

Josh Richardson [00:19:09]:
That's so true. So, I mean, just going back to the earlier question, sketching this out on a cocktail napkin, I think we could say, hey, wouldn't it be fun if we could take all of this data and use it in a way to help positively inform people about outcomes? But the reason why that's possible is because of a history that Indiana has with its state longitudinal education database. SLDS is the acronym, and I don't even know Jess exactly what the acronym is for, but it's essentially where we're able to link up a lot of these workforce and education-related records together. And then MPH allows us to do these data matches where you've talked a lot on this show, and your listeners hear you talk about data silos, and everyone is familiar with this. But essentially to allow this agency, to allow the data that these different agencies possess, a lot of it very sensitive. A lot of it is confidential. A lot of it needs to be protected. But MPH has really allowed a secure place to do this record linkage that allows us to make smarter decisions based on this data in a way that protects people's privacy and security.

Josh Richardson [00:20:13]:
And so, from the back of a napkin to launch in November couldn't happen without those things being in place.

Jess Carter [00:20:22]:
Yeah. So you've kind of already explained the difference, the experience for somebody who's on unemployment or going through the process compared to before, that they wouldn't have had these kinds of recommendations or suggestions. I want to emphasize or ask you to emphasize the importance of agency here. We're not telling them these are your only options or these are your options. We're saying this is what the data, we're just presenting information to them.

Josh Richardson [00:20:46]:
I think this is such a critical part about all of this. And so I definitely want to answer that. But I will say before we started to run this way, our agency has had a long history of looking at things like what are the most in demand jobs in an area. So you'll look at things like what occupations are growing, what are the wages. And so if you think about a predecessor to what we're doing here, they were posters, and they would be a poster that we would hang in a local office, maybe send to a school that would talk about the top 50 jobs in their area. But so, if you think about those, they were tough in a couple of areas. As one, they're very one-size-fits-all. And so it wasn't surprising to see a lot of those require things like higher education or master's degrees.

Josh Richardson [00:21:28]:
And again, those are absolutely still going to remain hot jobs for the future. But for a lot of individuals, again, if I've just lost this manufacturing job, the only job that I've known for 20 years, seeing a list that includes a lot of things that feel inaccessible to me, isn't that helpful.

Jess Carter [00:21:45]:

Josh Richardson [00:21:46]:
The other part about this is that people, of course, don't want to be told, like, here's what you're supposed to do, here's your only answer. And so I think what we're really trying to do with this tool is essentially have the approach, here's where others have been successful. We can see this. And so the way I like to think about it is that the algorithm that this artificial intelligence algorithm that we've built off of all of these wage records, we're really confident that it can show people good jobs, often better jobs than where they came from. But really they're the only one who can figure out what the best job is. And I think trying to have that humbleness here to know that we're not going to nail it, but we hope to facilitate their being able to nail it.

Jess Carter [00:22:25]:
Right. Can you expand on…when did it go live?

Josh Richardson [00:22:28]:
We went live on November 2.

Jess Carter [00:22:31]:
Okay, so we're still in kind of quarter one, if you will, of three months or so of collecting the data. Are you getting feedback from users of how it's been? What are you hearing?

Josh Richardson [00:22:44]:
So there's a handful of things that we're getting. So, the tool itself has a feedback mechanism. So we're asking people, when we show them an occupation for them to go ahead and let us know, no, this doesn't work for me yet. Maybe, like you're close, there's more they'd like to know or a yes. And we're seeing people use that tool so they don't have to. Right. That's an optional part of this process. But we've seen thousands of people respond already and give us yes answers.

Josh Richardson [00:23:10]:
The tool then allows them to go and explore that job further, where they can look for training providers that provide it. So we're seeing that. But the other thing that's really interesting is when we've done a lot of these campaigns before, if you do things like an email campaign, it's really hard to get people to open those emails. It's even harder to get them to click on it. But because this is really built into the process, we're seeing really high rates of people interact with this tool at some point during their claim. We're still building that out a little bit more. We want to add a lot more clarity to what we're seeing, but we're seeing a significant percentage on a weekly basis of the initial claims numbers turn into activity within this tool.

Jess Carter [00:23:50]:
Okay. And then I have technical questions or context I will try to provide. So, Uplink is the name of our unemployment system in Indiana. So, is it embedded within Uplink?

Josh Richardson [00:24:02]:
Absolutely. So, Indiana, again, we talk about Indiana almost for some reason, the conditions just being right here. But Indiana is essentially 100% online claims filing.

Jess Carter [00:24:11]:

Josh Richardson [00:24:11]:
And so other states still will use some paper mechanisms or maybe some phone center processes, but we're essentially all online. And so when that individual files that unemployment claim, they use the Uplink system. But so what we do is as they register for the system, as they file an unemployment claim, we're taking the information that we needed for their unemployment claim, and that's the information that we're using to generate the recommendation. So again, you could think about building this in a different way where we gave it its own URL, its own website, and we'd have to drive people there and encourage them to register and ask these questions. And again, a lot of these job matching tools do that. But we really like the idea here that we didn't need anything further from them to generate the recommendations. We need something further. Obviously, like we talked about this earlier, this is actually going to turn into a good outcome.

Josh Richardson [00:25:02]:
The individual says, yes, they enroll in the training, they get the job, the work is on them. Right. But we're just trying again to make it a lot simpler to find it. So, yes, all right. In Uplink, I filed my claim every week they're coming back, right? If they stay unemployed, they come back to make that next week's claim for unemployment benefits.

Jess Carter [00:25:21]:

Josh Richardson [00:25:21]:
And they would continue to see this recommendation, have the option to enter this Pivot tool and interact with these recommendations on a weekly basis.

Jess Carter [00:25:30]:
Okay. And then I am going to share an opinion when I ask this question. I don't assume you will share your own personal opinion. Usually, in some of these federal programs for unemployment, there is a requirement for a work search that can be pretty goofy, in my opinion. Where in the past, how you make sure an unemployment claimant is looking for work has not been super effective. I don't know the right word I'd use. And how you measure that is difficult. If they click through and they say, yeah, I was in this kind of manufacturing, I want to be in this one.

Jess Carter [00:26:06]:
Is there any automation into work search requirements?

Josh Richardson [00:26:09]:
Okay, so we'll talk through this here for a second. First, I agree with you. Work search is tough. I think it's a really important concept that someone is on unemployment benefits, that the idea is that it's temporary and a transition to their next job. And by the way, overwhelmingly, it is. Very few people exhaust 26 week unemployment. Most claim less than that. So we have this work search requirement every week.

Josh Richardson [00:26:32]:
And this has been with the unemployment insurance system since it started in the 1940s. But to a large extent, we're saying, hey, you have to go look for work, but we're not really telling them how to do it or how to be effective as we do this. And so that requirement remains. We want to see this tool be useful, and so we're waiting for this feedback. But I absolutely can see the world where these things sort of merge, right, where we're helping this person connect and say, look, the use of this tool would substitute for a work search, activity in this tool would satisfy these work search requirements. But I think what we want to make sure, again, is we want to be able to look at the data and see that we're actually achieving better outcomes when we do that than the traditional method.

Jess Carter [00:27:16]:
Do you have a hypothesis about, not just if the algorithm is helpful or not, as we sort of watch it play out, but is it possible that it helps reduce exhaustion of claims? Do you have a hypothesis about whether that would be the case?

Josh Richardson [00:27:30]:
Again, I hope so. We talk about this a lot. So we're in these early days, and so our measures of success are, hey, are people using the tool? Are they leaving us feedback? How much time are they spending on it? Are they entering at another time? The ultimate only measure is does it make people's lives better? Right? Can we drive action that leads to a better spot at the end of it? So the answer to that is, I very much hope yes, but I think that there are also a lot of reasons to believe that it could. Right. I mean, I just still think that if someone sat down and said, look, I know I'm ready for a change in occupation, but I've already got bills that are piling up. Unemployment insurance, I mean, it doesn't replace anywhere near their working wages, and in fact, it's really set to always replace less than half of their working wages. And so the pressure is really on.

Josh Richardson [00:28:19]:
I mean, if your family depends on that income. So even if you wanted to sit down and say, look, I really need to go through a process to figure out what I want my next job to be, it's just really exhaustive. And so here I think that by speeding up that process, by connecting that person with that next role, my hope is that it really does put them on a better path. We do different things within the tool so they can filter their recommendations by the amount of time or training and training that it would take. Right. So we show them that information so they could say, look, I'm interested in training, but only training that I can accomplish in six months. Or they can look at just that training, but they can also say, look, no, I don't want any training, but I'm just interested in an occupational change. And again, like I said earlier, I think if you ask people to sit down and make a list of all the different occupations that they could do with no additional training, people just don't get very far.

Josh Richardson [00:29:11]:
And thus I wouldn't get very far on it, either. And so I think this really helps that. And hopefully, by doing so, we'll reduce the amount of time that they're unemployment.

Jess Carter [00:29:19]:

Josh Richardson [00:29:19]:
Even more, I hope it makes it less likely that they ever need unemployment again, or at least in the near future. I mean, to me, that might even be the better metric. I've sort of said this before, if they needed to spend an extra couple of weeks on unemployment this round, but it resulted in them obtaining the kinds of skills they needed so that they were less likely to be laid off in the future. Yeah, it'd be a positive return to the unemployment fund itself. Certainly better for them and better for an employer out there who really desires that skill set.

Jess Carter [00:29:50]:
Yeah, I love it. I can imagine that there's a world where not just citizens on unemployment want this. Is there a world where that's possible?

Josh Richardson [00:29:58]:
I really hope so. We're in the process of doing this and we're scoping this out, and the only things, there will be some slight differences. Right. Because the question is we're going to have to obtain that information from them up front. So in the unemployment insurance system, we're able to do this as a matter of course. But, yeah, we want to make this tool available to everyone. I think that it would be really great if we could use the data that we sit on so that someone could ask this question, look, if I wanted to make five dollars more an hour than I did today, what would the path look like to get there? And so not only to be able to answer that question, but to be able to show them the paths that people like them have made that successful transition to the five more dollars an hour. Again, I think that's something that almost only the state could do because others couldn't get access to that data.

Josh Richardson [00:30:47]:
So, yeah, we're working on that now. A different interface, sort of a different front door to it as we continue to try to improve the tool that's already in place.

Jess Carter [00:30:56]:
Awesome, because then it's not just a solution for unemployment insurance, it's a solution for wages in Indiana, which is good for everyone, right?

Josh Richardson [00:31:05]:
Absolutely. I think what you really want is for people to be able to meet their needs and their goals when it comes to their career. And the more that we can reduce the effort that it takes to figure out which path that would be, the more that I think it allows that. So absolutely excited to do that. And then so many other potential use cases of this. The way that we might be able to help employers identify where future talent pools come from. Those sorts of things are really exciting uses of it. It's too the same dataset.

Josh Richardson [00:31:33]:
It's just going to be different.

Jess Carter [00:31:35]:
Oh, great.

Josh Richardson [00:31:36]:
Sort of different approaches and probably different interfaces.

Jess Carter [00:31:41]:
That makes your earlier point land for me even further, of if it can allow employers to select the most right employees up front, would they stay longer? Would there be better retention? Would there be less unemployment in the first place?

Josh Richardson [00:31:54]:
Yeah, I think.

Jess Carter [00:31:54]:

Josh Richardson [00:31:55]:
Hopefully, just information to help them understand where we might be able to look at where their potential pool comes from and also where those workers might be going instead, just providing employers with hopefully better information that helps them attract the kind of talent that they need to be successful.

Jess Carter [00:32:11]:
Awesome. Okay, let me ask you this. When you look ahead the next, so I make you look back and look ahead. But we'll start with looking ahead. We look ahead the next five years. You've kind of had a pulse on unemployment and reemployment for, you said, 12 to 15 years?

Josh Richardson [00:32:27]:
Yeah, 15 plus.

Jess Carter [00:32:29]:
15 plus. Okay. All right, we're getting old.

Josh Richardson [00:32:32]:
I know.

Jess Carter [00:32:34]:
What do you anticipate is going to be the next big challenge?

Josh Richardson [00:32:39]:
I wish that we were better at anticipating those. Certainly, nobody saw the challenge that we were facing when we did. Look, I'm not one of these doomsdayers about AI. In fact, I'm really excited about it. But I do think that there are a lot of folks suggesting that what we'll see is sort of just more need for individuals to continuously upskill throughout their career, to stay employed, to stay gainfully employed, just to progress in their wages. And so I think that's one thing that we'll look at. Where that plays out. I'm not quite sure, but what we know is that skills and education are really in demand as we're moving through this phase where more and more can be automated.

Josh Richardson [00:33:22]:
And so I know that that'll be a challenge for the system, but I'm not sure that I can quite predict exactly what the effects will be. I think we'll definitely keep an eye on that to see if the types of occupations start to change that we see come through the unemployment insurance system.

Jess Carter [00:33:39]:
Okay. Looking back as a leader, that's kind of the point of half the name of the podcast, right? You've seen this through a whole bunch of phases, and I think a lot of leaders come in for a moment and are critical to one moment in a project's lifecycle. They don't get to see it through fruition. Do you have any advice for a leader that is embarking on a journey or something that you thought would be important to look back on and say, this is how the staying power I had some days was that hard, I imagine?

Josh Richardson [00:34:15]:
Absolutely. I like the question. At the same time, it's hard not to almost fall into cliche types of answers. We really tried to stay the course. I think so much of it. When you depend on others to buy in, to gain the support for something which isn't unique to government, I think there are maybe some components of that that are, but in any organization, and I think it's to continue to listen to the concerns and the objections of others and to try to make sure that you're reflecting on that as you make changes going forward. But it really has just been to continue to share the message and try to generate excitement around the potential of the tool. That's really been, I think, what ultimately turned us from an idea that just kind of sat for a while into an actual tool.

Jess Carter [00:35:02]:
You know, I know that there are a ton of people that were part of it, and you constantly mentioned that it's not just Josh Richardson that you had a great IT team, you had great team around you, you had buy-in. It sounds like there was some, to your point, how to galvanize, how to get that buy-in and help people see the vision, and then we can go figure out how to execute it. But sometimes I think the hardest thing is just to get that buy-in.

Josh Richardson [00:35:26]:
Well, absolutely. And I mean, again, you need skeptical people throughout the process. You need people to challenge these things. Certainly even the people who may have not been sure that this could work or that it could launch, they've been really important themselves to making it better. So, yeah, I think I'm really excited about where it's at, and I think there are a lot of people who did really sort of positive things to contribute to it. But I think even a lot of those cases, people with the biggest concerns just about sort of adding another part of the problem is that we have a lot of different tools and resources, and we're saying it's hard for people to navigate them. And so your solution to that is another tool.

Jess Carter [00:36:07]:

Josh Richardson [00:36:08]:
That was a really important point, and I think helped clarify some things about what we didn't want this to look like.

Jess Carter [00:36:14]:

Josh Richardson [00:36:14]:
So even those sorts of things have been really helpful.

Jess Carter [00:36:18]:
Okay. Wrapping up on my questions, but one of them I have to ask, were you ever nervous?

Josh Richardson [00:36:26]:
Yeah, sort of. Maybe every moment.

Jess Carter [00:36:30]:
Do you mean like maybe every moment.

Josh Richardson [00:36:31]:
Nervous that it wouldn't launch? So what I do feel is, like, some of the big things, a data show, and again, we're dealing with really confidential data. One thing I didn't necessarily have to spend a lot of time sort of feeling really nervous about was sort of our privacy. And again, it's because of the structure in Indiana, the advice that we have here, and those different pieces that made it really helpful. Know those nerves to see, like, will people use it or not? Right. I've been telling people for years that, hey, there's this idea that could really be helpful. So I think there may be some nerves there early on.

Jess Carter [00:37:05]:

Josh Richardson [00:37:05]:
But I think now they remain because, like I said, it's really fun to have a tool. And I think that a lot of us, we can sit and we're really happy with sort of the data science work and all these different components that go into it. And so now we're sort of at this point where I guess we can pat ourselves on the back and say, hey, look, we really feel like we know what people ought to be doing, but it really won't matter unless they ultimately do it. Again, it's one of these things about it is that it's going to take significant effort on that worker's part to achieve success. And so our hope is just that we can reduce that effort by that littlest bit or give them greater confidence that it's worth persisting through that training because they know the outcomes better.

Jess Carter [00:37:45]:
That's awesome. I really appreciate the way that from that first day on a napkin, you saw a gap in something and were able to try and come up with some ideas and you had some solutions on how to fill it. And I think I really respect how you hold it loosely. It's not like, well, this has to work now because it's been my idea, and I'm going to shove it through. It's like, well, do people use it? Is there a meaningful outcome? If not, okay, that would stink, but okay. And so I really respect the way I feel like that's tied back to sort of your missional alignment with the agency of, it's got to make a difference. That's why we're here. I think that that's neat.

Josh Richardson [00:38:21]:
Absolutely. Yeah. You can launch tools, but I think the real critical thing here is going to be, does it make a difference? It's the only way that it will stay around. Right. Is obviously if it makes a difference, but it's obviously the only thing that will validate that it was ultimately worth doing.

Jess Carter [00:38:36]:
Yes. What have we not talked about that we should?

Josh Richardson [00:38:39]:
No, I think it's been pretty thorough.

Jess Carter [00:38:42]:
We covered most of it.

Josh Richardson [00:38:44]:
I hope that it's clear. It's been sort of a really fun process, like I said, to move through it. And so, yeah, it was just really good to get to talk with you about it.

Jess Carter [00:38:55]:
Awesome. Thank you for listening. I'm your host, Jess Carter. And don't forget to follow the Data Driven Leadership. Wherever you get your podcasts, rate, and review, letting us know how these data topics are transforming your business. We can't wait for you to join us on the next episode.

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