Building Trust with Data: Inside Indiana DWD’s Governance Journey

Transcript

This has been generated by AI and optimized by a human.

Show ID [00:00:04]:

The power of data is undeniable. And unharnessed, it's nothing but chaos.
The amount of data was crazy.
Can I trust it?
You will waste money.
Held together with duct tape.
Doomed to failure.

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.

Jess Carter [00:00:34]:

Welcome back to Data-Driven Leadership. I'm your host, Jess Carter. Today's conversation is all about data governance, something we have touched on quite a bit before. But this time we're diving in head first with real world, actionable insights that any business owner can apply no matter where you are on your data journey.

Jess Carter [00:00:51]:

This episode gives you a rare look behind the curtain at how public sector operates when it comes to managing your data. As citizens, we often wonder how government agencies juggle vast amounts of information. How do they protect it? How do they protect us? How do they make sure it works for them? Today, we're getting answers, and you might be surprised by how much of what's happening in the public sector can apply to the private sector as well. I'm joined by two experts from Indiana Department of Workforce Development, Diana Barrett, their data and privacy officer, and Stephanie Semaan, their data governance manager. They're shaping data governance practices that not only ensure data protection, but also drive real outcomes for workforce development programs. Through their experience, they'll show us how to put data governance into practice, whether you're just starting out or refining your existing strategy. In today's episode, you'll hear about the day-to-day of data governance, the challenges that come with it, and how organizations can ensure data works for them rather than the other way around. Plus, we'll touch on how lessons learned from the public sector can inform the private sector. Let's get into it.

Jess Carter [00:01:59]:

Welcome back to Data-Driven Leadership. I'm your host, Jess Carter. Today, from the Indiana Department of Workforce Development, we have with us Diana Barrett, data and privacy officer, and Stephanie Semaan, the data governance manager. Let's get into it. Welcome, you guys.

Diana Barrett [00:02:16]:

Thank you.

Stephanie Semaan [00:02:17]:

Thank you.

Jess Carter [00:02:18]:

Yeah, we're so glad that you're here. So people know that I've worked, I've served, had the pleasure of serving, Department of Workforce Development in Indiana and a couple other states. So I'm so excited to have you guys here and get to hear more about what you've been up to because you've, you're certainly you've been there more recently than me, so I'm familiar, and for people who aren't, we've talked a little bit in previous episodes about the concept of an unemployment insurance program. There are federally mandated programs, but there's also some state programs for the unique differences each state has. And then there's this re-employment component as a, you know, a separate part of the program. But there's also, like, things we haven't talked about. Like, we call it R&A, research and analysis.

Jess Carter [00:02:54]:

There's how states look at, like, what's their supply look like, what's their demand look like? And that looks like jobs. And, you know, hot jobs list is an analysis that they provide. And so my first question for you guys is understanding, you know, you're here to talk about data governance. What is the scope of that? What does that look like in your roles at Department of Workforce Development, are you looking at data governance across all of those programs? Are you focusing more on some versus others? What does it look like?

Diana Barrett [00:03:21]:

Yeah, I can kick us off with that one. So we are taking data governance pretty seriously and we are hoping to apply it to the entire DWD.

Jess Carter [00:03:32]:

Okay.

Diana Barrett [00:03:32]:

What we are not doing is going all in, all at once, at the same time. So we really have this phased approach because when we started building out the data governance program and it really started out of a pure need, we need to tie some loose ends. We need to create some processes or even just document some processes that are already there. But we decided to go pretty slow because we understood data governance. Although we might have been doing data management, data governance was another level of that. And we realized that we really need to give people the time to adjust to that change and to actually adopt it and then implement it. So we did not apply the flip-the-switch approach where we are like, hey, we have a data governance office and we're going all in. But yes, we are kind of identifying where there is a greatest need, whether that's within the UI system or whether that's in the workforce side or any other programs or initiatives that we have.

Diana Barrett [00:04:33]:

And we basically, as I described it before, many times, Stephanie and I carry light and we enlight the dark corners and figure out what's not there, should be there. And once we do that, we gather a team and start creating things.

Jess Carter [00:04:49]:

That is so cool. Well, and you said something I already want to ask about. So you kind of said, hey, we were sort of doing data management, but then we had to move on. For people who have no idea what that means, what do you mean by that? When you say we started with this data management thing and then we kind of moved on to data governance.

Diana Barrett [00:05:05]:

Yeah, well, if you just Google, you will see that data management and data governance, there's always a question which came first. What we think is, we did have some data management. So we have a lot of different programs, a lot of different databases that support those programs. So data is collected not in one place, but it's really everywhere. So different teams have a different way of working with that data and managing it. So we did have data management, but there wasn't data governance, like an overarching approach that is going to be kind of like DWD stamp. Like, this is how we do things, this is what we do at data collection. This is how we go about sharing, and this is how we go about organizing the data through our databases.

Diana Barrett [00:05:53]:

So that's the difference between data management and governance. Because honestly, if we did not adopt data governance back in 2021, things would have still continued. We would have still been able to serve the population, we would have still be able to give our data to the researchers. But it might have taken more time, more effort, more people to untangle all these processes.

Jess Carter [00:06:17]:

Sure. Well, and while I have you, Diana, one of the questions I was going to ask is, you play a key role in shaping what data governance looks like at DWD. Can you break that down for us, like in a, like a day in a life? Like, what does that really look like? And help us understand why is it so important?

Diana Barrett [00:06:34]:

Absolutely. It is very dynamic. So honestly, day-to-day looks pretty proactive. There is this flashlight that we carry. We really try to figure out, like, okay, where is this thing that should be here? Does it exist somewhere else? Let's place it in the right spot, though. It is kind of proactive, but in reality, how we started is somewhat reactive and that is really not in a bad sense. So we started out of the need to create clear processes in managing our data. Again, not that we didn't have processes, but they were not documented.

Diana Barrett [00:07:11]:

If they were documented, sometimes they were not easy to find. And at that time, we started talking about putting those clear processes together, documented, working with people to adopt these small, incremental changes. Once we created those processes, like, it wasn't, hey, everybody, now we have it, you better get on board. But we did a slow, and we continue to do, kind of this slow rollout and incremental approach to adopting it, then implementing it, evaluating it, refining the process, and then applying this refined process all over again. So day-to-day is a wonderful combination of strategy, collaboration with everybody, and a lot of busy work to actually get things done. So to your question, why it's critical to have effective data governance, because that will translate into effective programs. So it's not a short path, it's not linear. But these two things, effective governance and effective programs, they exist in the same orbit.

Jess Carter [00:08:20]:

I appreciate that. I think it makes a lot of sense. And Stephanie, for you, one of the things I was wondering, you know, when it comes to implementing a best practices, what are some of the biggest challenges that workforce organizations face or anyone trying to implement something like this? Where, where do you feel like you look back and think, man, we really struggled through some of this?

Stephanie Semaan [00:08:39]:

I mean, I could think of a few challenges, but I will name a couple that I think went hand in hand and helped each other. The first one would be getting the stakeholders buy-in. You know, while they do understand the importance of data governance, the importance of adopting a best practice, they have their own thing going on, they have their own priority, they have their own workloads. So getting on their priority list and getting them to really translate that agreement into action and taking steps into implementing some best practices took time or took a little bit, it was a bit challenging. But we did eventually get to do it with the second challenge that was de-siloing, you know, in large organizations specifically, you can have siloed teams, you can have siloed systems, siloed data. So working through these barriers, trying to break through these barriers so that you can increase some of the awareness and bridge some of the gaps and maybe oftentimes help combine some of the efforts. Because when you're working in silos, you may be duplicating efforts. So combining some of those efforts and freeing up some time and resources to really focus on the implementation, then that helped with implementing and getting that buy-in and getting some of the best practices translated into, really, action steps.

Jess Carter [00:09:56]:

That makes sense. Well, for the people who've never worked in state government, which isn't the three of us, but you know, I've always heard there's people who have tin hats and there's people who, who are worried about what we're doing with their data and then they hear governance and it's like, okay, so now you're tracking, are you tracking me from one place to another? I always try to explain to people, actually DWD is a great example. Some of this data is federal data. You don't even own it, right? You're helping administrate a program with unemployment data that is a federal program and it's really federal data. Is that right?

Diana Barrett [00:10:28]:

That is correct. Yep.

Jess Carter [00:10:29]:

So then how you protect it, share it…governance is actually a conduit to protecting their data because you appreciate what it is, what its source is, where it came from, where it's going. I think, you know, a lot of times there's these other narratives people will make up about, you know, that we're creating governance or we're tracking. And it's like, hold on. Actually, this is a really important component of privacy security protection. Do you feel like there's misnomers, like where people perceive that we're doing far, far more than we ought to be with data and you have to explain that that's not the case?

Stephanie Semaan [00:11:02]:

Yes, you know, data is very important. Everybody wants data and they want to use data for research. But there are some stringent requirements around what we can do with the data and who can use the data for what purpose. So this is where data governance can help clarify those requirements, can help identify who can do what, why, and how. And we collaborate closely with our legal team, too, to identify those legal requirements and regulatory requirements to make sure that we are compliant with our federal mandates. We often have those conversations. And again, when you have data in different systems and siloed, sometimes you want to be able to share those data for the same purpose, but you have to figure out the mechanism to do that and make sure that you are following regulations and being compliant, doing it under the law, like we like to say.

Jess Carter [00:11:52]:

Yes, well, and one of the things I wanted to ask you guys because when I was there, we didn't quite have like, an enterprise data warehouse yet that sort of brought in unemployment and re employment data. Do you guys have that today?

Diana Barrett [00:12:04]:

We are building it up.

Jess Carter [00:12:05]:

You are?

Diana Barrett [00:12:06]:

Yes, we are. We have started on it. It is a long process just because of the sheer, well, the amount of data and the different databases that the data currently live in. But yes, we are, we are on that way.

Jess Carter [00:12:18]:

Because I think a lot of people, we talked to Florida at one point ten years ago and they had just built theirs. And you know, it seems so simple when you explain to a normal citizen, like, if you're seeking unemployment services, your hope is to also be in our re-employment system because you're looking for jobs and you get re employed. And so being able to track: Jess was on unemployment for how long? Did she have to exhaust the program or did our re-employment programs actually help her reduce the duration which she was on unemployment and maybe wage up, we call it, or skill up? Maybe she has higher wages than when she first went on unemployment like some of those things are ways we've talked in the past about what good government looks like is how do you hold government accountable not just for honoring federal programs, but actually making a difference innovatively with strategies and understanding what, specifically, Indiana needs? And it's really hard to do that if you don't have an enterprise data warehouse. Because to your point, you might have governance, but it's so tricky because you're looking at one source system for Jess unemployment and then a different one for Jess re-employment, and you're trying to connect the dots and it's just complicated. So I was gonna say, if you weren't even down that journey, governance is still so important, but it is such a bear. Have you found as you've started that process, that it's yielding kind of faster momentum for the governance initiatives?

Diana Barrett [00:13:43]:

Well, we actually work in lockstep with a lot of our teams. That includes security, that includes our data engineers. And like you said, I don't think we even realized when we embarked on that journey how big of an animal that will be. But I think really, and this is not probably something that the public wants to hear, but we are taking a slower approach because in some instances it's fine, we are okay taking a risk, but in other instances, it's like if we take this risk now, it's going to cost us more time and money to fix it later on. So we are still a little bit away from having all our data in the cloud environment where, you know, we can all access it internally without having to go through several people. It is 2025. We probably should have been a little further down the line with that. But it's just the reality we live in.

Diana Barrett [00:14:40]:

And for some things, we were more prepared and some things we were continuing to prepare our staff and our systems.

Jess Carter [00:14:47]:

Absolutely. I mean, and I don't think that you're. I don't think you're behind when it comes to the state agencies. I think that you guys have. I mean, I don't think other people appreciate how much you hear these topics like fraud during COVID and what a big deal that was. I mean, I remember one of the stats that stuck with me because I did some work in Nevada was that they had more unemployment claims than they had citizens. There were plenty of reasons why the agency's been a little distracted the last half-decade. And I don't think you're alone in that.

Jess Carter [00:15:16]:

But I think people don't appreciate even this. Data governance, when set up correctly, can literally be one of the vehicles that helps combat fraud, right? You can use your governance strategy and your management strategy to actually support all of these initiatives and enhance. Like—I know auto-adjudication is something that we talk about—all of these things. We can evaluate them and their efficacy and improve those programs and policies. But I really appreciate, Diana, that you guys are. And I think everyone should hear this.

Jess Carter [00:15:47]:

There's this tension between program efficacy and outcomes and privacy and security. And you guys are talking about that like it's a foregone conclusion. And I don't think everyone else appreciates how important it is to say, like, this is PII. In some cases, it's federal data. You do not want to cross the line. So to your point, we're really glad you're moving slowly and accurately.

Diana Barrett [00:16:11]:

Our data is really attractive. We understand how attractive administrative records are to everybody. So whether you're a nonprofit and you want to see how your participants did in this program, and if they have wage gains or they found another really cool job, we really understand that. But the function of our governance isn't only to fix our internal processes. So you are aware, as a member of the public, what the process is, how long it takes. It's going to take. We also tied loose ends around internal ownership. Who is the person that is going to say ultimately yes or no to a data share? But also on the other side, there are so many regulations and laws, especially with the prevalence of privacy laws in the last few years, that we really have to.

Diana Barrett [00:17:00]:

We operate under a very strict federal law, but there's also all those privacy laws that. That touch on the data that we hold, and we really have to be aware of that. But our function is also to help the data recipient understand, like, if you are going to be a custodian of the data we give you, these are some of the things that you need to be aware of. And this is really not to be mean or to be a sheriff and go after them if they do something wrong, but it's really protecting us as an entity that provides this data, but it's also protecting the recipient. So they are really good custodians, and they're aware of. Of what they're getting themselves into by receiving this data, especially if it contains PII.

Jess Carter [00:17:45]:

That's right.

Stephanie Semaan [00:17:46]:

I like to use the word “responsibly.” I think our approach is more of a responsible approach than rushing into it or moving slowly. It's just making sure that we're taking the responsible steps. So we're taking, you know, the right steps to get where we want to be.

Jess Carter [00:17:59]:

I think that's right. Well, we were talking before we hit record, right, about like you were putting together some data sharing agreements, right, Stephanie? So I don't know that everyone on earth knows what those are. I know what a data sharing agreement is because I've worked at several state agencies. But can you kind of, could you educate a little bit on. Hey, when we say that, here's what we mean?

Stephanie Semaan [00:18:17]:

So a data sharing agreement basically is just a contract that outlines the requirements, the confidentiality requirements. If you're a data recipient, if you come to DWD and request to receive data for a research that you’re conducting, if you're a public institution that you want to conduct educational research, you know, connect some educational records with some wage records and you're recipient of DWD data. Well, one, we have to do the legality check, make sure that this is the purpose, meets the requirement, the legal requirements, you are an eligible recipient of the data. And then once we do that, we have to contemplate all of that into a data sharing agreement, into the contract. And in that contract we make sure that we outline all the confidentiality requirements, all the security requirements to make sure we're compliant again with the law and to hold people accountable with how they're using the data and making sure that they're only using it for the purpose for which they're getting it. So that's basically in lame terms, this is what the agreement is about.

Jess Carter [00:19:17]:

From your perspective, so you've been working on data sharing agreements for a minute, you're working on the data governance piece and it's changing. I feel like data governance trends are moving kind of quickly. Do you have any sense for what trends in data governance entities should be paying attention to right now?

Stephanie Semaan [00:19:33]:

I think it would be just stating the obvious to say, you know, digital transformation, adopting AI, innovation, automation, those are all the trends and will continue to be an evolving trend and something that data governance professionals should continue to stay current on and be aware of and pay attention to. But there's again this responsibility. Yes, we want to adopt new tools. Yes, we want to be able to share data, but we want to do it responsibly. We want to make sure that while we do that, we're maintaining the integrity, the accuracy, the security, the privacy of the data that we have.

Jess Carter [00:20:08]:

Yeah, I've been around DSAs—data sharing agreements—for a long time and it could be theoretical if you wanted to, but like, have you seen someone not think one of those through and it's a nightmare?

Diana Barrett [00:20:20]:

I will say for myself and I have been working with data sharing agreements probably 50% of my time for about eight years now.

Jess Carter [00:20:29]:

Wow.

Diana Barrett [00:20:30]:

It really is a learning process. Every time you read something, you learn something new. You connect it to another knowledge that you have, and you start to kind of lock in the protections around data. So I would say I'm absolutely not surprised that our data recipients are like, oh, wait, oh, yeah, that's in the data sharing agreement, but we understood it differently. Those data sharing agreements, they're not meant to scare you away. They're really a joint agreement telling both sides, hey, let's not get ourselves in trouble. So these are the things that we need to be aware of, and this is where the data needs to live, and these are the people who can access it.

Diana Barrett [00:21:15]:

Because even if you have a data sharing agreement, doesn't mean that now everybody gets access. It really needs to be on need-to-know basis. And we need to know as custodians of that data, that sometimes it’s federal, sometimes it's state, but we also need to know who is accessing our data for which purposes. So we are also aware that those are very long contracts. But once you understand the basic data protection standards and then you expand that to data protection standards that are particular for the dataset that you're looking at, it really just becomes easier. And I would say it just becomes the way of operating. You don't even think about it. It is a long way.

Diana Barrett [00:21:56]:

And that's one of the reasons why our data governance office is there as well, to help our data recipients really work with that data in a completely fully compliant way.

Jess Carter [00:22:09]:

In my head, there's a correlation to, as you guys roll out data governance and management and your data, your data essentially becomes more valuable because it's better quality, it's a better fidelity. Do more people want data? Are you seeing data sharing agreements increase over the years? And do you think any of that's tied to, it's not just that they want it, it's also because it's a higher fidelity than it used to be?

Diana Barrett [00:22:30]:

I think that's partly the case, but also, Jess, you mentioned earlier, if you want data on a person, you connect it to a different agency's data or different data that's publicly available. And you create this holistic picture. I think where the public's understanding and with the existence of mechanisms to actually have that much data in a faster way than we used to do before, I think that's also opening up the eyes of researchers like, hey, maybe we ask for this data and then you know, these are the questions that we can answer.

Jess Carter [00:23:04]:

Oh, that's cool. As you've been great public servants, if you were to wake up tomorrow and you were in a enterprise wide, you know, very large organization, but in the private sector and you were in charge of governance, what would you pull from what you've done in the public sector that would in every way be applicable, more applicable maybe than ever? How would you think about taking the lessons you've learned in governance in the public sector and apply it to a large company in the private sector?

Diana Barrett [00:23:32]:

I think there is great benefits of having people that have previously worked for the private sector work in the government sector and vice versa. There are a lot of things that we can kind of cross-pollinate. The government is a much more regulated industry, with the exception of some industries that are as regulated. But it has many rules. Things naturally move slower in government because you have multiple layers. In the private sector, things move faster. And sometimes, and I do have the private sector experience, I've also worked in the nonprofit sector. And speaking from just my own experience, it can be that fast pace can be more prone to mistakes. Those mistakes, if caught early on, might not blow up into anything.

Diana Barrett [00:24:21]:

Might take just a little bit of time to correct them. But we, as public servants at the Department of Workforce Development, if we make a mistake, that's at a much higher cost because we are there to serve the public. My briefcase is packed with all these experiences and understanding each other and how we work under different umbrellas. That's probably a very important piece that I would take from one to another.

Jess Carter [00:24:49]:

Yeah. The one thing that you all are, I think helping me appreciate through the whole conversation today is the way you talk about and treat data is, you know, the respect, to use 70s language. There's this concept for responsible, respectful, we're treating data like a, like a valuable product. That is not something that I saw 15 years ago. Private sector was barely doing it, let alone public sector. But I think you guys are seeing and appreciating the value proposition that that data is sometimes on its own. I mean, Bureau of Motor Vehicles sells VIN numbers and that, like, literally generates revenue for them.

Jess Carter [00:25:27]:

Right. Their data is literally a revenue generating product for their department. I think also. But for program effect, efficacy for looking back and understanding what is, you know, if we're going to fund state-specific programs, are they making a substantial difference or do we need to adjust them in some way or another? It's like a science experiment. We can't change 17 variables at once. We got to at least make sure the quality of the data is at the highest fidelity possible, so we can generate all these findings from it. So I hear you and you're saying in the private sector you do the same thing.

Jess Carter [00:25:56]:

You want trustworthy data that's actionable and you can't have that if it's not high fidelity. So I totally get it. Stephanie, what about you?

Stephanie Semaan [00:26:05]:

I agree with both of you on that. And yes, data is an asset. At the end of the day, it is one of the most valuable asset of an organization and we can drive results, we can base decisions on it. So it's important, it's important to be able to use it, but again, use it responsibly and have good quality data. In public service, you have the public trust at the top of your mind. Whatever you do is, you know, you need to maintain that public trust. And even with data, data is identity. Most of the times PII is people's identity.

Stephanie Semaan [00:26:38]:

So just making sure that you're taking care of it and for purpose of maintaining that public trust while improving services, I think that's something that I would take to the private sector as well. You know, yes, improving customer experience, but also maintaining customers’ trust in our products and our services in our company. Because that's reputation, too. That's the reputation of the company in the business. So I think that's the one thing, you know, as you were asking the question, was thinking what I would take is that mindset, just maintaining trust. Everything we do is to also keep that trust and faith in us.

Jess Carter [00:27:13]:

I love that. So you do need a certain level of, like, cultural buy-in when you're trying to implement governance. Because to your point, it is, it's like you're sharing with everyone. You need everyone to care about data quality. Everyone's entering data, everyone's validating data at different systems in different ways at different times. Do you have any advice, any secret sauce on how you guys have done some of that or, hey, if I went anywhere else, I'd make sure I did it. You know, this was one thing we did that really, really helped us when it came to kind of cultural buy-in?

Diana Barrett [00:27:43]:

Yeah, I would say that think about staying ahead in everything you do by fostering a culture of learning and of sharing that learning. So do not concentrate all the knowledge in one team or one person. Continue to support the people to get that deep expertise, but also acknowledge that pure awareness goes a long way. So you don't need everybody to be an expert, but just be aware. In the past few years, privacy rules, laws popping up everywhere. So employees from all our units and from all roles started bringing up an issue to us saying, you know, I don't even know if this is an ethical issue or a privacy issue. Don't have an answer. But something I heard prompted me to bring it to you to look at.

Diana Barrett [00:28:31]:

So that's what we really appreciate and foster that culture of learning. And don't be afraid to seek learning from those who have learned this before you.

Jess Carter [00:28:41]:

That's awesome guys. Thanks for listening. I'm your host, Jess Carter. Don't forget to follow Data-Driven Leadership wherever you get your podcasts and 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. 

Got a question you want me to answer? I'm putting together a special episode where I'll be addressing your questions. Head over to LinkedIn and drop your questions in the comments. The link to the post is in the show notes.