Data Driven Leadership

Empowering Nonprofits with Data: United Way’s Innovative Approach

Guests: Denise Luster, Chief Strategic Intelligence and Information Officer, United Way | Stephanie Fritz, Senior Director of Strategic Research and Analytics, United Way

Data drives positive outcomes nonprofit organizations just as much as in for-profit enterprises. Nonprofits can leverage data to make a real difference in communities and the lives of individuals. In this episode, we take a deep dive into an innovative project lead by Stephanie Fritz and Denise Luster at the United Way. Specifically, this project harnesses the power of data to improve the lives of people in the community.

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Data drives positive outcomes nonprofit organizations just as much as in for-profit enterprises. Nonprofits can leverage data to make a real difference in communities and the lives of individuals.

In this episode, we take a deep dive into an innovative project lead by Stephanie Fritz and Denise Luster at the United Way. Specifically, this project harnesses the power of data to improve the lives of people in the community. Senior Director of Strategic Research and Analytics Stephanie and Chief Strategic Intelligence and Information Officer Denise have been instrumental in forging a unique partnership with the State of Indiana to better understand the needs and outcomes of individuals who use community organization services.

Stephanie and Denise worked on this groundbreaking project for several years and bring a wealth of experience to the table. In this episode they discuss the intricacies of collaborating with nonprofits to gather valuable data and developing a tool that safeguards client information while complying with strict regulations.

In this episode you’ll learn:

  • How to uncover the benefits of utilizing data-driven methods within the nonprofit sector
  • The need for data literacy among organizations supporting disadvantaged communities
  • About the obstacles faced when gathering and consolidating data from various origins

In this podcast:

  • [05:11-09:36] How United Way collects data to measure outcomes
  • [09:36-16:18] How connecting data improves community outcomes
  • [16:18-24:48] Stephanie and Denise’s journey to understanding data importance
  • [24:48-33:12] Stephanie and Denise’s passion for helping others through data analysis
  • [33:12-41:45] Why data is important for community change
  • [41:45-43:57] How high-quality data is leveraged to help people

Our Guests

Denise Luster

Denise Luster

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Denise Luster is the Chief Intelligence and Information Officer at United Way of Central Indiana. Denise has over 20 years of experience in the design and execution of evaluation strategies, data analytics, social research, and program evaluation including outcomes measurement.

As Chief Intelligence Officer, Denise provides executive leadership, strategy development, planning, execution, and accountability for creating real business value through data analytics. She determines the essential projects that informs community impact and fundraising data strategies.

In her career Denise has conducted data-driven analyses to inform the development and implementation of strategic and tactical plans to accomplish the mission and financial goals of the organization. In her roles, Denise is required to employ a variety of analytical research methodologies to gather and analyze data to inform strategic decision making which has produced transformational results in a variety of areas that include, early childhood education, post-secondary education, workforce development, financial stability, basic needs, and human services.

Denise Luster earned a Bachelor’s degree in Public Affairs with a concentration in Management. She holds an MBA in Finance from Indiana University Kelley School of Business.

Stephanie Fritz

Stephanie Fritz

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Stephanie Fritz serves as the Senior Director of Strategic Research and Analytics Director for United Way of Central Indiana. Stephanie guides the reporting and analytics process for United Way’s impact strategy, community data strategies, and oversees the community partner accreditation process. Across these strategies, Stephanie leads a research team that focus on how community data can inform and support the human services sector. Her priorities include developing reporting and analytic tools with community-based organizations in mind.

Prior to her time at UWCI, Stephanie was an admissions and retention analyst for graduate and non-traditional programming at for the University of Indianapolis. Stephanie completed a master’s and bachelor’s degree in sociology at the University of Indianapolis.


Jess Carter: The power of data is undeniable and unharnessed, it's nothing but chaos.

Speaker 2: The amount of data, it was crazy.

Speaker 3: Can I trust it?

Speaker 4: You will waste money.

Speaker 5: Altogether with duct tape.

Speaker 6: Doomed to failure.

Jess Carter: 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, Jess here. You are about to hear from Stephanie Fritz and Denise Luster from the United Way of Central Indiana. And I really enjoy this episode. They do a phenomenal job unpacking a really complex data project they're taking on. And it's a nonprofit, right? They're looking at how all of these nonprofits in central Indiana can better leverage their data and the state's data to understand what programs they're providing to what types of personas and leverage state data to understand what are the outcomes.

So can we actually evaluate their program's efficacy against general outcomes? Like, did you get a new job? Did you skill up? Are you on unemployment still? Or could you get off of that? So they'll unpack that story in more detail. But one of the things I want you to listen to is Denise and Stephanie have been working on this project for multiple years and they've been in the nonprofit world for six years and 25 years. What you hear isn't just a great data project. It's two people who stay under the pressure, even in the middle of COVID, because when things got hard, they remembered their why and they remembered their unique place in the larger why and why their role was so important. I think it's super inspirational. I think it's really encouraging. And they are just a class act on how to get a really complex project with like a hundred different stakeholders aligned, activated and making progress. I hope you guys enjoy.

Welcome back to Data Driven Leadership. I'm your host Jess Carter. On today's episode, we're talking to Denise Luster, Chief Strategic Intelligence and Information Officer, and Stephanie Fritz, Senior Director of Strategic Research and analytics at the United Way of Central Indiana. Stephanie, Denise, welcome to Data Driven Leadership.

Denise Luster: Hello, excited to be here today.

Stephanie Fritz: Hi, thank you so much for having us. Yeah, we're excited.

Jess Carter: So I'm really excited about talking to you guys today, mostly because we've had a lot of private sector conversations on this podcast so far, but there's this huge element of how can nonprofits better leverage data for meaningful outcomes? And I feel like you guys live in that space. Is that right? Can you both kind of, maybe Denise, you go first, but take turns unpacking what is your role and how does data play a role in what you do all day at United Way?

Denise Luster: So yes, we do live in this role. I appreciate you having us on today. We take our role here very seriously because when we talk about data, I always try to say we're talking about people. And when you're talking about people, especially human services, you're talking about having such an impact on our lives, especially people, you have people who are vulnerable situations, people have been marginalized, things of that nature. We take that role seriously when we're talking about data.

So I am the Chief Intelligence and Information Officer here at United Way. I'm responsible for all of our data strategy here at United Way, Central Indiana, in terms of community data, all of our data in terms of showing the impact that we are having on our investments in the community, and also seeing our fundraising analytics data.

Jess Carter: Awesome. Stephanie, what about you?

Stephanie Fritz: Yeah, so I'm the Senior Director of Research and Analytics. And so where Denise helps lead the vision, I help with the execution. So I lead the team. Well, I have a senior manager and a director who just received a promotion to come up under me and then a team of research analysts. And so it's our job to take that vision and then execute it. So we focused specifically on evaluating the impact. So taking the data from our nonprofits and mapping that to be able to see the outcomes. Then we also have a sector that works on helping identify community data. And then we also have a sector where we just support nonprofits and their data collection. So I have those kind of three strategies underneath me that I help on the day-to-day and executing the strategy.

Jess Carter: That's awesome. So first intrigue I have, because my first job out of college was actually nonprofit work. So one of the first questions I have is, I don't know that I've ever met somebody who was in a nonprofit that had this much effort and energy around their data. Is this a new trend? Are you guys like ahead of the curve? I mean, I'm not asking you to brag. I realize we're nonprofits, we're not always so great about that. But I'm seriously curious, is this starting to happen more often where there's more teams and research teams dedicated to the strategy and the execution and the programs and leveraging data to do so? I always like to think that we're trying to be ahead of the curve and trying to be innovative and looking for solutions to help people, right?

Denise Luster: I'll start with United Way Network. So in terms of United Way Network, we are probably the largest or one of the largest data teams in the entire 1800 United Way Network. We discovered here at United Way that as we were starting to look at data, and we get a lot of money from donors and from nonprofit, other federal, national, state, nonprofit organizations and local funders. And we take those investments seriously.

So some of the questions we were getting is, hey, we're investing a lot into United Way so they can invest in partner organizations. What is happening? How are we moving the needle? Some of the areas that weren't necessarily seeing the needle move. And so we have to start to reassess how are we collecting data? How are we thinking about data? How are we measuring outcomes? How are we asking for some of that data back from the organizations that we invest in? So we can have the proper strategies, make other decisions.

So I've discovered over, I've been here almost 25 years, from the time I first got here at United Way to now, there's been a significant change in how we think about data, collect data, report on data, and invest in data. And I think that's important for the human service sector. We think about it in terms of sometimes universities or corporate or things like that, but it's very important for this particular population to understand the needs. And if you don't understand the needs, how can you really come alongside communities and to provide some type of assistance or help or be a partner. So I think that's why you see a movement, especially in nonprofit organizations, to partner, to invest in big data strategies, because you have to use data as a driver for proper decision-making.

Jess Carter: So we're starting to see that. I see that more and more over the 20 something years I've been in the human service sector. Okay, so it is starting to be a movement, but you guys certainly are standing out, especially in the United Way’s Network. I think that's so cool. And it sounds like from what you just said, funders play a role in that. Like if they're asking for feedback and they want to know how, if they're moving the needle, to use your example, are we just funding a program in an ongoing way? And maybe that's meaningful, but you tell me if it is. And then do we need a new program and what should that look like? So it sounds like funders are actually helping us move towards a program efficacy approach to our data. Is that fair?

Denise Luster: Absolutely. I think that's right. I think funders, I think investors, I think clients of those community organizations that we invest in are saying the same thing. So I think we're being responsive to that, or trying to be responsive to that in innovative ways.

Jess Carter: That's awesome. You're seeing like actual clients come in and say like, how effective is this program?

Denise Luster: So we invest in, we don't do direct programming here at United Way. We distribute, that's part of the thing that I think we do very well. We bring organizations together in terms of partnership and investing in those organizations. And they are the ones who see direct clients, but we invest in those organizations.

Jess Carter: Cool. Stephanie, you're gonna say something?

Stephanie Fritz: Yeah, so I would kind of like add into that space. So I'm glad that Denise made that point because when we are working, we have 88 accredited partners that we support through United Way of Central Indiana. We also support a huge sector of grassroots and smaller budgeted organizations as well. I'll say within that, I have seen a trend. So I've been at United Way for six years in the fall. And when I came on board to where organizations are now, I think to Denise's point, I'm seeing nonprofits move in this direction. There is more community data available. I think board members on nonprofits are asking for more data-driven programming to make sure that what we say in this space is, how are you assessing the needs of your community? And then how are you collecting data to say that your programming is meeting the needs of the organization and the community that you're serving.

So there's this growing need to have very localized data, have a very localized understanding through data available, and then collecting the data and assessing that in a way that's not just qualitative, but also quantitative. You have to have both. And I see nonprofits growing in that space and they've grown tremendously over the course of even the six years that I've been here. And one, it's community data, but I also think in the government sector, you see the same thing. The federal government's asking for more information. That's driving state and local governments. And the funding that's being pushed out from there is driving nonprofits to meet those goals. So it's one internally within the organization to be curious and to collect more information and to report out all information.

Jess Carter: So it's not just funders, it's also within the state and then also the, just the organizations themselves. So that's awesome. Very cool. I'm excited to hear that. Well, so I don't know, do you guys have a theoretical project you could tell me about that exemplifies how you're using data to evaluate program efficacy?

Denise Luster: I can talk about we have our I don't even know if you want to call it a project. I think it's the core of what we're trying to do here at United Way, where those organizations that we're making an investment in, we're asking them to report back on, okay, in terms of who are you serving in terms of demographics, across race and ethnicity, geography, etc.

For the last several years, I've been working on a project with the state of Indiana, particularly the management and performance hub and partnership with the consultant as well, Department of Workforce Development and Department of Education, as well as the Commission for Higher Education. Where we wanted to, in response of, trying to be responsive to the questions we were getting from donors, funders in the community and ourselves internally as a staff, right? You have to assess your own programs and what you're doing as well in initiatives to say, okay, in terms of the dollars and the clients and things that we're trying to connect, where are the outcomes? Where are we showing progress at? Where are the improvements being made? Where are the gaps? So there is a limitation to some of that data that we're getting back from the organizations and we wanted to understand their income or educational outcomes and higher ed outcomes. In order to do that you have to connect that data to something.

So we started having conversations with the state of Indiana, the Management and Performance Hub. I'll start saying MPH for the purposes of this conversation. MPH to say, okay, how do we connect the data? And one of the things we ran into is they had never done a project like that with an organization outside of the state of Indiana, outside of the state agency, where they probably shared aggregate data, but we wanted to share client role level data, match that up with state level data, so we could see in terms of who's unemployed, what's their incomes, who's graduating, who's passing ISTEP, those types of things.

And so we worked on that for several years, which measures a lot of legalities and things like that in partnership with Resultant, develop a tool to make sure that client data is protected. That was a big issue, making sure that client data is protected and no personally identifiable information is shared. At the end of the day, we want to make sure that we were adhering to protect those clients' information and adhering to federal, state, whatever regulations in terms of doing that. So we worked on that for several years where we can match that up. And we finally got an agreement last year to do that. We're very excited about that, building out our own data warehouse to bring that data into. So we can not just inform United Way. This is to help to inform the sector in terms of, we have these hundreds of thousands of clients, right? And also the form of the state of Indiana. Hey, the state of Indiana knows a certain thing about certain clients if they're getting unemployment or if they're in pre-K through 12, they know a certain thing about clients. But in terms of what is happening with those individuals when they're going to community organizations to receive services, that's a part of the, that's a gap, right? So we wanna bring them along with us to understand what's happening with clients in our community holistically. So that is a big project we've worked on for several years.

Jess Carter: Very exciting, very innovative, but at the end of the day, we want it to inform. Yeah. We want to inform. Well, and for those people who don't know, we take a pass at this and you guys can correct me. So not every state, right? If you're listening from another state has an MPH. So one of the unique things in Indiana is that we have this agency that is absolutely focused on data initiatives at the state, largely focusing on state program efficacy, federal program efficacy. How can we help all of our agencies sort of be a data center that helps them raise a tide that raises all boats, right? And so that's primarily how it's kind of been rolled out in the last, I don't know, almost decade now, I think it's been in existence. But you're right, they also have this sort of statement in the creation of this agency that they are to provide data beyond the state walls to help all citizens. And so you guys are a first major lift. So I think this is pretty neat that you guys are finding ways to get row level data where you can really understand on an individual level what the outcomes are, what your program was, or what the program was that interacted with them, what the outcomes were.

I imagine that there are trends like who was the person running the program? Maybe there's efficacy where like Denise and Stephanie running a program is gonna have really high fidelity, but Jess just started running the program and it might not have as high. She might need more training or something. So there's all these different ways. I'm sure that those outcomes can help you guys help all the entities around you say, Hey, how do we sharpen our programming? How do we understand which ones are best, the best investments for these kinds of individuals? So and again, are you—ignorant question here—are you guys done?

Stephanie Fritz: We found a way forward and now we're building out the EDW to start to pull the data in. Is that what you said? So I think it's interesting that you talked about the EDW because I think another like great to answer another question first before are we done? No, we're not done. This is a long-term longitudinal study, but something that also was unique that's great about MPH is other states, the data is very siloed. In the different state governments and offices are not necessarily connected. And the MPH has allowed us, they had the key data sets that we needed. This is through our family opportunity strategy, and that strategy is providing two-gen services, and two-gen means basically providing integrated, holistic supports for both parent, caregivers, and youth in the same family. So the idea is that you're supporting the children and the parents at the same time in an integrated manner, with the focus of moving the, with the emphasis for United Way, financial stability and educational success. Because we are really focused on economic mobility for whole families in Central Indiana.

And in that space, the data, our MPH, had workforce development data, education data from our Department of Education, and then Commission on Higher Education data all in there, what you called is the EDW. And we could work in a partnership with MPH to access, and then also through that, the entities, they help facilitate that conversation with those states all at 1 time. And it really allowed us to work in a streamlined manner for something that would take a much longer time if we were to have to pursue each entity separately.

So that's what's really amazing about this. And no, we're not done. So we've just had a chance to we've hashed for the first time this year. And I know that's a question later is like, what are surprises like the time really is shocking in any of these projects. These are large scale projects and we consider this a longitudinal study. So no, we're just at the phase where we're now looking at the data for the very first time, which is incredibly exciting, but then creates new questions.

Jess Carter: Well, and the importance, I think, too, a lot of people don't appreciate this but I'm sure it wasn't exciting for every day of the last several years, right? So pace is hard for me personally I like to move at my pace. I never understand why other people can't. And so that's like a life lesson in my, like some of my leadership journey is like, hey, we need to move at the pace everybody else can. And there might be days where I need a new hobby because what I need to do, everybody else is sort of still working on it. And so that's a leadership journey for me.

But I think what's really important is, while it takes a while, if you had just tried to do this quickly or cheaply, you're actually at the point when people actually realize, oh, I'm so thankful I didn't do that. Because now you're seeing the data and you're gonna ask totally different questions of it than you had 3 years ago. And you have the mechanism in place to go get those answers. But if you just gone and asked questions and got results of those questions, you are going to keep repeating this sprint-based, repetitive questions of the data. And now you can actually listen to your data and explore what it's saying. And I think that's such a hard experience for people to understand until they've gone through it. And then it's like, oh, there's like, let me ask questions of my data versus let me get access to it in this robust way where I can really start to unpack what it's saying. And it sounds like you guys are just about there.

Does that resemble your lived experience in any way?

Denise Luster: I think it's, we are big on partnerships. So it's asking questions about our data, trying to listen and trying to learn, but it's also trying to educate. So the listening part is listening internally to what fundraising is hearing from their donors, what the impact team is hearing programmatically or trying to develop. What are the marketing and brand needs, but also listening to the partners that we work alongside, those accredited partners and non-accredited partners that we work alongside and trying to, we are a certain place with data. They are seeing the clients. We have to be able to listen to them and bring them along with us in this whole process to get them to understand why United Way is asking these questions.

Also to hear from them and to learn from them, to learn from them so as we're doing our analysis, we're thinking about those things. We always think about equity, we always think about community, we always think about age, staying in place, the economic mobility, poverty, things like that. What are we hearing from all of this holistically? So when we're doing our analysis, or we're thinking about, hey, how are we gonna report out on this? It's very critical to think of those things so we can be able to replicate or we can be able to lift up outcomes or answer some of those questions or come back and say, we can't answer some of those questions based on the things we're asking and to iterate and to make those changes. It becomes bigger than United Way and it's also healthy. At the end of the day, we want to help inform the sector because I keep going back. I always keep going back to the people at the end of the day. It's not about the technical component of the work. We're doing this for a reason. And at the end of the day, it should be to help people, to help children, to help families. And I always have to keep that in mind when we're thinking of the data.

Jess Carter: That's amazing. And I loved hearing you say, cause this is another kind of lived experience. Okay, I have all this stuff. I've got the data. I'm looking at it. Wait, we didn't collect the right information for me to answer a question. We have, we may have to change our intake form. We might have to change our midway through a program assessment. And so some of like, you understanding how the outcome data can actually help us sharpen our programs and help us partner with those. I think it's really exciting to me to understand some of that. So I think the position and the situation you're in, while it's been a long haul, is exciting. You guys are at a good place.

Stephanie Fritz: Yeah, it's never lost on us whenever we make changes to metrics or demographics, the impact that has on our partners, the partnering nonprofits who are funded through our initiatives. And we are really cognizant of, and we were like from the onset of this. So that's what's interesting is like, this project, even though we're talking about a small component of it, it has been a multi-year project that resulted in us expanding partnerships, developing new technology within our team and skilling up ourselves.

But at the beginning, you know, we listened and pulled together focus groups when we determined the metrics to make sure that they aligned with the content area and the area of expertise that these organizations are doing. So we had our workforce and education partners that are doing that work come together. And again, that was something that was also helpful because we were partnering with Resultant at that time to help do that type of work well, to say like, okay, these are outcomes that match not just with the government sector of the work that we see that makes sense, but also makes sense to the CBOs that they are tracking, as well as, and for things that they're not, like, how can we provide supports to get them there? And so I think that's something that's never lost on us. Like when you mentioned the changing of the intake form, that work, like it impacts them directly. So we have to be cognizant of that. And we are so yeah, for sure.

Jess Carter: Well, so yeah, I do want to ask you a few fun questions. So one is, what did surprise you about the project?

Denise Luster: Oh, there were many surprises. To narrow that down, I think the biggest surprise, I knew there would be a large legal component to the work for this particular project. When we were dealing with client information, personally identifiable information, PII, we knew there was over the years, we were very protective of that as well. In terms of the federal regulation, then you have state regulations, you have community-based organizations. So if you hear us say CBOs, it's our community partners, you have their regulations. There was, I don't have a law background, I have an MBA in finance. But man, you felt like you were getting a law degree really quickly, right? And all those things. That was probably the biggest surprise in terms of the length of time it takes to get there, to overcome those obstacles.

For me, it was, you had checkpoints to be like, is this the right way? It really, you reach points, but at the end of the day, it was worth it. So I think that was probably the biggest surprise of it all. I have to say, I know you're asking for one thing, but also understanding state data and try to understand what they have available and their staffing and their procedures and things for accessing that, right? So those were surprises trying to think about how they share data and learning some of the nuances of that, I would say those are the two bigger surprises.

Jess Carter: Okay, Stephanie, what about you?

Stephanie Fritz: I think I echo that. I think I walked away from this process in the sense of, especially working with state partnerships, I have a lot of respect for how much you care and they really protect. They have high regulations around protecting that data. And as a citizen, I like that. So I do understand that. And we take that very seriously as well as here too.

I think the another surprise that I had was for us actually in this was we also had the challenges of COVID that happened as we were doing these like initial agreements and we were like working through this and the state had to pivot and focus on the COVID response and so that really positive so that was something that was I think really unique to this project and just showed that like different priorities. But what was a surprise in that is like, we were still able to accomplish this, like, yes, and it ended up being stretched out and took longer. But it was still doable as long as you have a good partnership, and you keep the communication and you're able to keep being a little bit of a squeaky wheel to keep like, oh yes, we know, we're appreciative, we'll work with you, we can take a backseat right now, but then just keep the ball rolling and momentum on the project. So that's something that was, we were appreciative, we understood, completely understood, because we had our own COVID response happening as well, the entire world did. But that was something that was unique.

Jess Carter: Out of curiosity, if I can push on both of those for a minute, while everything sounds like it was breezy and went so quick and perfectly, there were some hiccups. How did both of you as key leaders in an organization that's highly connected to a bunch of other organizations, you kind of in the spider web of like, critical people in this organization, what were things that you did to make sure like personally that you were checking on yourself on days where it got really hard or days where it got really overwhelming and you were like, should we keep doing this? I bet you had that question. I mean, how did you guys stay the path? You're both still here and you've been on this path for several years. What advice would you give somebody?

Denise Luster: I try to rely on my own personal background. As a person who grew up in poverty, but then realized they were growing up in poverty, I try to think of it from that. And also for a person who still engages and works in the community, and you see people from all different backgrounds and all different economic situations, I try to think of what is the end game here? And it's to help people like me as a kid who were receiving, at the time I didn't know where they were United Way Services, right? To help me as a kid, help the youth that I see through my own church ministry or volunteer with or the seniors that I engage with. You have to keep, what are you trying to accomplish? Who are you trying to help? I have a passion for this, clearly. I keep that at the forefront. Tough days. Data is never easy to work with. You're trying to convince people to use this data that you've worked on for months. And you realize it's not our job to get people to love data, to get them to understand why it's important. And keeping that end game in mind, who you're trying to help, we should all have that in whatever industry, especially human services industry, right? It's not about us. It's not about United Way. It's not about any of the partners who you're trying to help. If you keep that end game in mind, you can overcome those obstacles.

You have to have a lot of patience because you're looking at, hey, at the end of the day, this data is going to be able to help someone move out of poverty. This data is going to be able to help someone get a job. This data is going to be able to help someone be financially stable or have great educational outcomes or graduate high school or read on time. You have to keep all those things in mind because this is a tough sector to be in because you see a lot of, you hear a lot of issues, you read a lot of issues, you see a lot of data and it can be, it can weigh on you. It can weigh on you because of the problems that families are facing. So that was a driver for me. That was always a constant driver for me. And I believe in the power of data to produce outcomes, to move people out of situations that have been created for them, whether they've been marginalized or forgotten about. And I believe in the power of data to make decisions.

Jess Carter: Wow, that's powerful. Okay. Stephanie, what about you? Were you hanging on to your why, too, is what it sounds like?

Stephanie Fritz: Yeah. So it's helpful to have a leader like Denise to be able to help keep shaping that, because I think that was incredibly helpful for the team. For me, I also think about what was going to be given to these organizations in that sense. These datasets, it is not easy to establish a data sharing agreement with state entities. And we talk about the nonprofits that are in the sector. And you asked at the beginning, like, is this growing? Yes, it's growing. But the nonprofits that are in Central Indiana that we support, they are lean in staff and resources. They are mighty, and they are powerful, and they do good work. But if you're asking if they have a full, robust data team to progress and pursue data-sharing agreements with the state, that's just not going to happen. That's not their priorities, because they are focusing on helping the people, and that's what we want them to do.

And so I really kind of focus on like, this is our role, like we can lean into this space, we can be a research team for these organizations, we can pursue these data sharing agreements, get in legal resources and the time and resources to do that. And that's our charge as a United Way, especially the United Way in Central Indiana with the largest research team. If we're not doing this to get it back to the sector to do exactly what Denise said, to access these data resources, then we're not doing our job. And so that's still the end goal and where we want to go in this. But really for me, and I want to say, I don't want to minimize, there are organizations that do have data sharing agreements and there are organizations that absolutely do have a data team, but that's not everybody. And so it's our job to support all of these organizations, especially our accredited partners.

Jess Carter: Man. So yes. Even that is just so insightful because I think your why from Denise, your vision, the outcome you want. Also remembering like there are times where I can empathize with people so much that it's actually, what they call it, it's not productive empathy, it's not cognitive empathy. And so I've had to learn that in some ways, Stephanie, I could see being in your position and empathizing with some of these other entities and being like, yeah, like, this is just like, I don't know if it's ever gonna work, okay? But your ability to recognize we're in a unique role where we have unique resources and skills to bring to this community of entities, of nonprofits, of partners, of CBOs, where we can stand in the gap in some of these ways, is like another way, I think, to tie yourselves back to your purpose and the way that you're serving this greater entity. And I think in dark days, this is pretty, pretty wise advice. You guys are preaching in good ways. So thank you for sharing some of that.

Cause I think a lot of leaders, you probably hear this a lot. They just feel lonely. And I think, especially with data, you can start to have these moments when it's like, doesn't matter, am I making a difference? Or am I just playing? And you need to know that at some point we're working towards the stuff that does. And I think you guys have done that for the long haul in a way that's really impressive.

Okay, another question I have for you. What you did sounds really hard, a little bit intimidating, but also really cool. So if some entity had some resources at their disposal and wanted to do something similar, they want to build a data warehouse or gather data from outside entities about outcomes that would help evaluate their programs or help them understand how their programs are doing and serving their constituents. What advice would you give them on where to start or how to think about creating a similar solution?

Stephanie Fritz: So, oh my gosh, if you ask us like advice of what to do, I'm trying, like we actually have like a list that we were like, before this, I'm like, which do I pick from? Like, we want to hear it. This is great. I know. So the one that I called out, actually, because since I'm kind of like on the stage of like, execution, and I work very closely with and my team works very closely with the nonprofits who are supplying a lot of the data. And then also using this hashing solution to connect their PI data, we had to articulate the why and we had to communicate the long term vision to our various stakeholders, but more importantly to the nonprofits who are supplying this information. We had to train and think about, and that's like the biggest takeaway was like thinking about all of the learning styles. When I felt like I had a handout and that wasn't enough, we had videos, we have manuals, we have quick videos. Our list of resources in order to educate and communicate is just like a growing list of resources. Because when you are working with 88 different organizations, you're working with a multitude of learning styles. And so we really had to be intentional. We had to acknowledge that in order to get the best quality data, it's never a one and done moment. It's a continuous education. And then we really had to think through the process of supporting our partners in collecting that information.

And so that means for us, like when it's time for them to submit data, we don't stop at just like, here's the information we now have. We provide all the information, then we said, oh, well let's do now office hours. So we have quarterly office hours where anybody can log on and get 30 minutes with one member of me or my team. Or the week of submissions, it's all hands on deck because when you have nonprofits who are also dealing with staffing transitions of their own, it's not unreasonable for one of us to make a last minute drive to an organization. And I've done that where the morning of submission, I go on site and I'm helping them actually submit and walk them through that. And that's for our space, we have to be just as committed to supporting them to get the best quality of data as we are asking them to be committed to us.

And so that's like the biggest takeaway. And that is like, you can't as a data team, you cannot just be like, well, why aren't they giving me the best quality data? You can't do that if you are not supporting them in their journey of data literacy.

Jess Carter: That's exactly, you used the right word where like the data literacy piece too. It hadn't struck me yet that all of those entities are in different paths for data literacy, data maturity. And so you're working with whoever, and they're usually in those organizations because they're passionate about the mission and they're really good with people. And so the ability to leverage data doesn't mean that everyone's walking in with a data science degree. So back to Denise, I'm struck back to your comment you said earlier, where it's like, I don't have to make you fall in love with the data. I just want you to understand how you can use it as a tool in your toolbox. That's really powerful and really complex. That's a great point.

Denise Luster: I think the other thing I probably had your question was about if they had all the resources, I would, one, make sure you're trying your best to bring your, that your full leadership team is engaged in this process, your board is engaged in this process, as well as your team. Be realistic about expectations and setbacks in the time to do something like this. It is not easy, but if your desire is to be, whether it's to be data informed or data driven, and if your desire is to do, data is important to communities. I fully believe it's our job to use data to bring about change for communities. If you're in an organization and you have programs and you're seeing people, it's your job to be able to understand what is happening with those people in those programs and to use data and to try to be as innovative as possible to bring about the best outcomes for those particular clients.

I think data is used in a lot of different places and people don't realize that. When you're getting from the federal government, the amount of social services dollars is based on data, census data and things like that. That's coming back in a community. It is our job to do the best we can to leverage that data, analyze that data, report back on that data, to help the people that we say we're trying to help. There's a huge accountability measure there. And if you have the resource to do it, I understand that their first thing is to make sure that they are doing programming for their clients. Data is not always the first thing they wanna do and collect. But it has to be in the plan. Because if you don't do that, then you're not fully doing your due diligence to help that client long-term. And I believe that if you build that in, the qualitative story is important, but so is the quantitative. It is just as important.

Because lifting up the outcomes, telling people what's happening with zip codes, communities, townships, people of color, LGBTQ, telling people what's happening in those communities and the things that are happening that are really good, but the things that are happening to, that are really impacting people in how they live day to day. Using data to do that, I think it's all of our responsibility. And if we're not doing that, then we're not being responsible, really responsible to those dollars and those clients. I believe that with everything that I have in me, and I think that if you have the resources to do it, you should make some level of investment in your data programming, your data initiatives in your organization. And that depends on budget size, right? But you should be lifting, being able to go to your board, be able to say to your clients, these are the outcomes we're having. This is what we're seeing in our programs. This is how we're going to pivot our program based on your feedback, based on who we're serving. I just think that's the right thing to do.

Jess Carter: You structure it so differently in my mind, where I think I've thought in the past that it's this difficult thing where people on the ground really understand what's going on in their community. And you're like, right, but if we get the data from there, we're just giving it back to them in a way that they can better leverage it to make better decisions. For you to phrase it as that's their responsibility. That's a tool that they should be using to help their community, to help the communities around them. It used to be a, when we had it, we'd use it. But the change in, hey, this is stuff that we should have. This is stuff that we should use. It could change an outcome. That's like a life. That's a quality of a life that can change. And I think that’s really empowering.

That's the word that I keep thinking about when we enter into this conversation is just, I think the vantage point you both bring to this whole journey and project is a vantage point of empowering everyone and saying, hey, we're just trying to be somebody who helps everyone along on this road because we want all of your outcomes to be realized because we want your clients’ outcomes to be realized. And I think that's really cool.

Denise Luster: Absolutely. And I love the fact that it's not easy. It is not easy. Organizations don't have data teams. They don't have a certain budget. I fully acknowledge that. But you have to do what's in your structure, your budget, your organization to be done. If you're doing that with a, I'll call it a full heart. If you're doing that and you're really doing that to help your clients, then that's a good thing, right? If we're not doing it, I don't know. How can you really assess equity? How can you really assess who needs help? How can you really assess what's happening on the ground to kids and families? There's levels to this. We're at a different level than some organizations, and that's okay.

And it is hard. Staffing is hard. Organizations are dealing with mental health of not only their clients, but their own staff. You're dealing with budget cuts. You're dealing with capacity issues. I get it. But data shouldn't be a thing that falls off to the side. Data is people. And if that's falling off to the side, then people are falling away. And that's not a good thing.

Jess Carter: It's good stuff. Okay. So you've done all these amazing things. Color me wildly impressed. I'm so excited for you guys and what comes next. And you sound like very reasonable people. And so I imagine there are gaps. When you look at your project, what gaps still exist? Or what instances of, like, where are you kind of seeing that there are more questions to be answered? Or what questions can't be answered by the data? And what does that mean for you guys or your partners? What's your take on some of those insights you've already shared that you might have?

Stephanie Fritz: Easy question, I know. So now that we're getting the data back and we're looking at the actual data sets from the state, that's where we are now, right? We're now asking, we're just still at that beginning stage, right? It would be interesting to like come back and do this like even a year from now and see where we are. We are now saying, really getting understanding the first time because like we've seen the data dictionary, but it's different than actually seeing the data, right? We know how the data is supposed to look, but then tying it to our program. So we're at the point where now, like, does the data that we have make sense? Are there anomalies in the data that we need to seek clarity? Do we need to increase information and maybe explore other data sets that exist to help us really have the true picture of what's happening with this population and the nonprofits that are serving in this space.

So I think like for me and my team immediately, it's like the gaps that are existing are really more of us right now just looking at the, it feels like we put the puzzle together and we're now looking at the picture of the puzzle and we're saying, oh, I didn't realize like that was actually gonna be a horse or something like that. I'm not very good at analogies, but now we're starting to really like put it together and say, what else do we need? And so that's kind of where there are gaps for me right now, where I'm looking and our team's looking and saying, where else can we go with this? OK, cool.

Denise Luster: I would agree with Stephanie. I think you're always questioning, is this enough? I always say, is this good enough? I'm always assessing, how can we be better? How can we think about this in a different way? I mean, this challenge, you're talking about poverty. You're talking about working class people who are on the verge of poverty, right? From one emergency away from poverty, right? So you see those gaps. You see the gaps in United Way only as might as we are. We raise a certain amount of money that we can distribute out. And so you see gaps, that's why partnerships are important. That's why funders like the Lilly Corporation, Lilly Endowment, who are invested heavily in a lot of our data projects. The gaps are there in terms of food insecurity. The gaps are there in terms of housing. The gap is there in terms of jobs, the gap is there in terms of social issues, health. There are a lot of gaps in terms of, we start to look at the data. There are natural gaps in the data in terms of what the state collects or how we've asked the question, those things like that.

But this is a learning process. This is an ongoing, you ask the question earlier, are we done, are we close to done? I don't think you'll ever be done. In my mind, you'll never be done. If you have no one in poverty, then you're done. Right, until then, you will never be done. So there will always be gaps until that happens. So that's how I think about it.

And it's always challenging yourself. How can we be better? How can we be better? How can we be asking different questions? How can we be making the best investments? As long as people have needs or people are in places where they cannot fully thrive, then we have a job to do here. And we'll continue to do that job and use data to do that to our best of our ability.

Jess Carter: That's awesome. Well, and you guys have, you've mentioned all these things that are so important. You talk about the importance of the data as this responsibility to leverage, but I can also tell that your bar for quality is very high because if that data isn't good quality, you can't use it effectively. And so you guys are looking at that from like an end user perspective to say, is it actionable? Do I have enough for this to actually change some outcome or influence an outcome or provide an insight that could be meaningful at the right time? So you've kind of touched on that. I also think your insights and the analogy was great, Stephanie, because it is like, you know, the horse on the puzzle is that food insecurity data that we don't have yet.

And I love that perspective Denise brings of like, yet, it's not done. We have more we can add to the picture and we've got more nonprofits that might want to participate. And we've got more data sets that we might be able to yield or borrow and pull everybody together to get housing and food insecurity and who knows what else, Medicare, Medicaid. I mean, I don't know what else there is there, but there's so many options to say, how do we round out these personas that we're here for in the first place so that we can help them. So I am just thrilled to have you guys share some of this journey. And that's the highs and the lows.

So thank you for letting me just ride that roller coaster with you. I'm so grateful that you guys are doing this work. And I'm so great to hear that you've been there for six years and 25. I mean, this is amazing. You guys need to do a whole nother, you write a book on grit or fortitude. I'm so impressed with your ability to stay in the hard stuff. And I'm so grateful that you guys were here today. So thanks for sharing.

Denise Luster: Thank you very much for having us. I've always, we're always in a space where we can come and talk about data and show people the power of data and our love and our joy for collecting data and helping people and sharing the story why it's important. So thank you very much.

Jess Carter: It's an important story and you guys have a gift for sure.

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