Govlaunch Podcast

Data Insights Part 1 of 3: Miami partners with mySidewalk for data storytelling to improve citywide performance

Episode Summary

In this episode, Mike Sarasti, Director of Innovation & Technology & CIO at City of Miami, and Stephen Hardy from mySidewalk, share the work they are doing to build a strong data culture and push Miami forward.

Episode Notes

Govlaunch is the wiki for local government innovation and on this short series, we’re talking all about data driven insights. I’ll be highlighting some of the innovators in local government leveraging available tools to better use various data sources, to make sense of their data in-house, and ultimately lead more efficient and resilient organizations.

Our goal is to expose local governments of all sizes to the tools available and to provide useful information about some of the leading products out there - so that you can spend less time researching products and asking the hard questions and hopefully get to make smarter, more data-driven decisions much faster.

More info: 

Featured government:  City of Miami
Government Guest:  Mike Sarasti, Director of Innovation & Technology & CIO

Featured Maker: mySidewalk
Maker Guest: Stephen Hardy

Visit govlaunch.com for more stories and examples of local government innovation.

Episode Transcription

Lindsay: (00:05)

Welcome to the Govlaunch podcast. Govlaunch is the Wiki for local government innovation and on this short series, we're talking all about data-driven insights. I'll be highlighting some of the innovators in local government leveraging available tools to better use various data sources to make sense of their data in house and ultimately lead more efficient and resilient organizations. Our goal is to expose more local governments of all sizes to the tools available and to provide useful information about some of the leading products out there. Hopefully you can spend a little bit less time researching products and asking the hard questions and get to making smarter, more data-driven decisions, much faster. I'm Lindsay Pica-Alfano, co-founder of Govlaunch and your host.

Lindsay: (00:48)

Today, I have the pleasure of chatting with Mike Sarasti, director of innovation and technology and the CIO at the city of Miami to learn about the work they're doing to build a strong data culture. Stephen Hardy from mySidewalk joins us as well and together we'll learn about what made Miami choose them to help with data analytics and reporting and what you should know as well in your search for an appropriate vendor.

Lindsay: (01:16)

Thank you both for joining me today. Can you each quickly introduce yourselves and share a bit about your roles, Mike, I'll start with you.

Mike: (01:24)

My name is Mike Sarasti. I am the director of innovation and technology CIO at the city of Miami. I've been in this role started as innovation officer five years ago. Uh, I've been in this role as a proper CIO now for three years. Um, 15 years in government before this, I was over in Miami-Dade County doing a number of things around, uh, data, digital services, um, software development, and now kind of the full range of proper CIO activities, uh, as well as supporting our mayor's Miami tech push to bring a number of companies to the region and, uh, supporting our local civic tech space.

Stephen: (02:07)

Hi everybody. My name is Stephen Hardy. I'm the CEO of mySidewalk. I'm a city planner, turned technologist, and I have the honor of leading the team at mySidewalk.

Lindsay: (02:18)

Great. And Mike, to begin, I want to start with a little background on Miami. Can you share with us when this shift to being more data-driven really began and how Miami was using data, both in-house and by leveraging open source data historically prior to working with mySidewalk?

Mike: (02:36)

Yeah, I'll be honest. It's probably one of the first things that I wanted to do coming into the city. I got hired, uh, I'm not sure they knew why they were hiring me. I think my, my previous boss, the one that brought me to the city said, uh, I'm really looking for a process Ninja. And I was like, I'm not sure a title, sir. We should think about something a little bit more official and then ended up in the chief innovation officer role. But the idea was that it would have this process improvement lens. So even though it was innovation, it was really looking at it as a proxy for process improvement. And, you know, data would be at the core of that. In my previous life at the County that a lot of advocacy for open data and I'd seen the light and I wanted to put that into practice.

Mike: (03:19)

And the first thing we started with was permitting also personal because I had had to go through the city of Miami permitting process and it was quite painful when I had to go through it as a resident. And I wanted to paint a real picture of what my experience was and that, that, wasn't the kind of, uh, those, weren't the kind of numbers that were being presented at the time. I started to say, Hey, we've got to get a little closer to reality. We gotta be honest with ourselves. We can't be scared about what the real numbers are. One of the first things I did was just like, give me all the raw data. And I went in a corner and brushed up on my Tableau skills, which I didn't really have at the time and kind of fumbled through the software a little bit and, um, and produced, uh, the real number for how long it was taking, uh, to get a permit for a single family home.

Mike: (04:08)

And that number ended up being something like 300 and something days before you even got a permit to build a home. So that, that was shocking for a lot of people because, uh, we had been using numbers like it takes two weeks to get a permit or four weeks, which wasn't untrue, but they were averages that included like 3000 permits that you were able to get in one day. So it was just starting to get more nuanced and I think it made the point, uh, that number ended up becoming this weird, even though it was a really small percentage of the permits became this anchor for driving permitting down and part of the narrative. And I saw the power of the storytelling. this is just one of the numbers, but that number got used over and over and over again to drive change.

Mike: (04:48)

So it made the point on that, like you got a good story on it, it could make an impact. And then, uh, the other piece was, uh, just sort of the advocacy for the nuance and the precision and that like let's step away from the high level stuff and really dig in and not be scared of that. Lining up with Shereen Floyd who, uh, was the strategic planning manager for the city. She was kind of aligning data points from the strategic planning perspective while I was kind of doing the process work and this ended up just becoming a thing and we became the de facto data driven advocates for the city into whatever it is today.

Lindsay: (05:28)

Well, that's great. And I think, yeah, focusing in on how the data is going to point out, maybe some failures in the processes as well. If you just look at those numbers holistically, yeah. Two weeks is the average. And you could have a lot of citizen frustration stemming from something that you don't even know exists. So I think that's a fantastic point.

Mike: (05:47)

And not being scared to look at the pain, right. I mean, that, that was the thing it's like everyone sort of thought that their job was to communicate the best version of the story. And, you know, we were saying, no, it's the opposite. I want to know where all the problems are because that's where we need to dedicate our attention. Um, and I think there were other, there were certainly other people trying to do that. Um, but I was in a position to be a little bit more vocal about it and sort of give permission to it because of my role in the city manager's office. So I really think that's most of what I did that that first bit was just the, the, I kind of had permission to cause a little bit of trouble, uh, out of the city manager's office and let people know that this was okay and give people some space to think about this stuff and not take the hit as a director or take the hit as somebody else. It was like, no, no, this is, this is fine. You can do this. And I think that's really important in data discussions is giving people sort of the space to have these kinds of talks. So they're not on the defensive out of the gate.

Lindsay: (06:44)

Well, Miami is obviously very far down the path in this breaking down data silos and working toward more data-driven decisions. For smaller local governments who are just beginning this process, can you provide another example or perhaps two of the benefits that have been realized from the data work underway in Miami?

Mike: (07:06)

Yeah, I mentioned the permitting piece. That was on building permits. So I'll say that one first, they, they ended up because of having the focus on that number, they took that number down to about a third of what it was then, um, which is, I think it's under 99 days at this point, which would use to be 300 and something. Um, so there was a sort of a simple, kind of a simple win there with the number. Where I think I started getting a little bit more sophisticated now that we've done that. And we've made the point that like metrics are important and they give you visibility over stuff you haven't had before. We can have different kinds of conversations in our business licensing project where we're trying to make it easier for small businesses to get up and running.

Mike: (07:49)

We walked into that project as an innovation project and the conversation was like all over the map because there were three or four departments that had a hand in this. As happens in government, their view was very limited to whatever their direct work was. So I mean, silos and, and all, all the ways that you described them in like textbooks. And no one had a clear view of the entirety of the process, much less like the actual time it was taking across the board for a resident or business owner to be able to complete that process. And they were like, well, why don't you look at the, you know, look at the system and see what the system says, you know, because they hadn't looked at it from the business perspective, they were only tracking kind of these internal metrics.

Mike: (08:30)

The system didn't even include those numbers. So in some cases, we sat the business owner with a spreadsheet and we had them track every transaction that came through the day and created data sets that didn't previously exist, um, which was at first challenging until they had all the data. Now they'd had a month of data and they're like, Oh my God, this, this is totally not what we thought it was. Like, they were blaming like a different department there. They were saying like, Oh, you know, we're, the issues we're having is cause this department keeps sending us bad, uh, applications. And it turned out that that was like 1% of the problem. And we were able to totally change around the nature of the conversation by redirecting it towards, towards the data. So it solves a lot of problems, um, like conversational problems when people are speaking sort of really high level and like throwing all of these reasons why stuff isn't working and, and, and you could be like, that's cool. I understand. That's how you feel. Uh, but here is the, the reality. And all of a sudden it makes every, it just grounds everything in a whole different way when you do it that way.

Lindsay: (09:38)

Right. And not to mention the efficiency pickup, when you start cutting through some of that noise.

Mike: (09:42)

100%.

Lindsay: (09:44)

So you've been working with mySidewalk for almost three years. Can you break down what departments are using this tool and more specifically what you're using them for?

Mike: (09:53)

Yeah. So we've used them for our resident satisfaction survey data. I think we kind of forget exactly where we started because we started some of these things around the same time. Uh, and Stephen and I have known each other for a little bit and kind of connected, I think while I was even at the County around the 311 stuff. But we started, I think with our resident satisfaction survey because we had a, um, we do an annual, sometimes twice a year survey of all our residents, um, to see how they feel about our number of services. And it turns out that mySidewalk was already doing some work in this area. And it was a wonderful way to kind of unlock what was previously in like PDFs or maybe some crude visualizations and make that available in a much more user-friendly way. So we started there and then we started having these conversations about 311 which is, you know, prior to my work at the city, that's sort of my background at the County. The County here in Miami-Dade County is the big 311 player in the city contracts with 311 services. This was an opportunity to the resident satisfaction survey, you know, cuts across all departments, but 311 has some really detailed data about a number of operational departments. Public works, solid waste, uh, code compliance, and a couple other ones here and there.

Mike: (11:10)

A lot of that data gets stuck again in reporting directly to our departments. So they're kind of using it to make sure what's open and overdue from an operational perspective, but it, it was historically very difficult to kind of pull that out and put it out there in a management format that they could see the trending over time. They just weren't doing that kind of work on their own. They weren't doing the geospatial analysis to see like the color coding about where, you know, something was really working well or not working well, or is, is one neighborhood getting better service than the other. I think they all kind of wanted to do that in some cases, maybe they didn't, you know, I think they want it for sure. They wanted there to be, uh, um, a good distribution of services, but maybe not until they had done the analysis. So this was a way to like, get the data out there, get the analysis out there, put it in front of the departments first. So it gave them an opportunity to do all this data cleanup that they'd been postponing for a long time, which I think is like critical because that's half the piece. Everyone's always scared about putting out the data.

Mike: (12:17)

You got to remember that these tools are also tools to put in front of the departments so that they know the data that they need to clean up themselves because once they do that, there's a number of benefits. I mean, what we started doing with mySidewalk has impacted data that we're pushing out on open data, it's impacted data that we might be pulling into our Google environment for something else, for some, you know, mixing and matching in our warehousing environment. So, um, I think all of those things have been, have been super helpful and they've cut across a number of, of departments, mainly our residents, those that are listed on our resident satisfaction survey and those that have a service requests available through 311.

Lindsay: (12:57)

Great. Stephen, I want to take a step back for a minute and perhaps you could just explain for our listeners, what is mySidewalk? What do you all do?

Stephen: (13:07)

Great question, Lindsay. mySidewalk is a data analytics company. We work primarily with local government. Uh, we think it's our job to help unlock insights in community data, all across the country. Mike’s example here is a great one because he was talking about an operational data set in that 311 example, and a resident satisfaction data set, which is both quantitative and qualitative. Uh, and then there's real outcome data as well. And, you know, Mike was, was talking about, are we servicing these different parts of Miami equitably? So to get a full picture like that, you're actually talking about bringing together a survey data set, an operational data set, and then some socioeconomic information all into a data story that makes sense for everyone involved. And that's really, our expertise is in kind of blending those data sets into something that's useful.

Lindsay: (14:00)

And for those local governments that don't have a data scientist on staff, can you just break down for me, uh, in a really simple way of explaining how do you present this data? 

Stephen: (14:07)

Everyone needs to be investing more in data and data infrastructure. That doesn't mean that you can't make progress if you don't have a chief data officer on staff, uh, quite the opposite, you know, you were asking Mike about bigger cities. Yes. But more data, more problems too. So I would say that the big thing is just to get started, uh, pick a project. Mike mentioned the permitting one, you, there are thousands of different projects and, and we know local government stands to gain about $2 trillion globally from data analytics. So there is a lot of low-hanging fruit here. So pick, pick a good place to start and just start and just go at it from there. Everybody thinks data analytics is about data science, uh, kind of, it's a lot more about what Mike was talking about in data storytelling and visualizations here. Uh, and frankly, most of the easy things to learn here, aren't complicated data problems. They're just about showing patterns and teaching people the value of, of having good data that you can trust. So I would say, uh, you know, making sure that you think about data science as a team sport, and 90% of that team is actually folks who already have on staff communications department is part of that, um, is really the right way to be thinking about using data in a local government.

Mike: (15:27)

Okay. Yeah. I'm going to say a couple quick things about what Stephen just said, first of all, yes. Just do the thing. Everyone gets hung up. Like, what are we going to do? And where are we going to start? Just do the thing. It doesn't matter what the thing is, do the thing. Um, and then second, like we didn't have a data scientist when we started, but we have one now. So this is also part of making a case to leadership. This is valuable. Once you have something that's clear and visual and has a strong storytelling component, it helps you make the case because you create an appetite. Well, I want a little bit more of that. Well, if you want more of that and we want that to be more sophisticated and answer that question that you now have, because now you're slowly making people more sophisticated and hopefully asking better questions, then you're like, well, if you really want the answer to that question, now we need to make an investment in, in this role. So we do have a senior data scientist now, Jen Hernandez, who's amazing. That started as a senior data fellow with us as a temp shortly after we started the work, um, with, uh, with mySidewalk. So there's a, there's a trajectory there too, and it all starts with just do the thing, start doing the thing.

Stephen: (16:37)

You mentioned this Mike, and it's something that I think, you know, you're looking for silver linings out of the pandemic. One of those is I think, uh, all across the country, we're realizing there are good data analysts and public health departments, and that those analysts have a role to play in improving community health, which by the way, it goes a long way in community development. Right. Uh, and so that relationship between, uh, data analysts and health departments and the way we run our communities, I think is stronger now and coming out of the pandemic, there's a real opportunity to continue to build on that progress.

Lindsay: (17:12)

Yeah, that's a great point. So Stephen is, mySidewalk is aggregating data from over 40 different open sources. Can you provide a few examples of these sources you're pulling from, to give an idea of the types of data you're working with?

Stephen: (17:25)

Sure. So short, yes, we are aggregating data comes from places like the burface state health data, it comes from national sources like Bureau of labor statistics, or CDC or HUD. We're also building our own datasets. We have a rich population projection data set that we make available to our customers. We're always building better ways to take high level, less granular data and make it more applicable to smaller places. So we're applying our own data science to the underlying data and making that available. So yes, we're aggregating. Yes. We're creating our own data sets. I think the real magic is frankly in the enrichment that we do with data. Every data set that we ingest, we enrich with time, place and purpose as the way that we describe it. Uh, and that means that every data set that we have can be provided and looked at and compared with every other dataset, uh, we suggest best practices with those. And we make it possible to answer questions like the one Mike described are we providing services equitably?

Lindsay: (18:29)

And the data sources you mentioned are all US-based. So Govlaunch is a global platform. So I just want to confirm for our listeners, at least for now your target customer is in the US correct.

Mike: (18:40)

At least for now, we're only in the United States.

Lindsay: (18:43)

Okay, great. Thanks for clarifying. And the use cases I imagine are quite broad with all these various datasets. Can you share an example or two of some other use cases in action with other local governments, perhaps some smaller than the city of Miami?

Stephen: (18:57)

Sure, of course, Lindsay, uh, one of my favorite stories comes from a fire department customer of ours in Glendale, California. Chief Silvio Lanza's has been working with us for a couple of years now. And, you know, they were collecting all of their incident data in Excel spreadsheets, and that's not unusual. You can look at any local government and find Excel spreadsheets full of good data. Through just kind of understanding what their goals were and building out, uh, best practices, uh, fire performance experience with them, they were able to, to start looking at the data that was most important, responding to a fire incidents, you know, what a fire, uh, doubles in size, every 30 seconds, a residential fire. So it's a place where time really matters a great deal. And to Mike's point earlier, you can't get better if you aren't willing to say here's a place where we can improve. And, uh, that there's a goal for that.

Stephen: (19:56)

And so in working with Glendale, uh, they were able to reduce their own turnout times by 30 seconds, and that's a big deal, uh, that saves lives. So that's a direct real community benefit from paying attention to data and to, um, making data-driven improvements. Williamsburg, Virginia is a customer of ours, uh, Mark Barham and Andrew trivet there have launched, uh, a city performance management experience that we think is best in class. It's a much smaller community. You were asking about smaller communities and they're using this to make sure that every department understands what's most important to each other department. They're using it to break down data silos. They're using it to communicate with their board. They run every, uh, board meeting through their dashboard and then they also make it available to the public. So the public at all times has a sense of what the city's goals are and how they're tracking against those goals.

Lindsay: (20:52)

Yeah, that's great. Mark was actually on the podcast a few weeks ago. They're doing some cool stuff, citizen engagement as well. So do not dismiss the smaller local governments. I think Williamsburg, their population is right around 5,000. So it's impressive that they're working with so many cutting edge technology leaders. Mike, I know there are some products out there, a lot of them that help better visualize these open data sources and make sense of data. How'd you all discover mySidewalk and why did you decide to go with them versus a competitor?

Mike: (21:27)

I actually don't remember how Stephen and I originally met because we've crossed paths a number of ways over the years, but I think what stood out is, um, a few things, one very well recommended from people that I trust. First person that comes to mind is Julie Steenson, uh, over in Kansas City who is one of my favorite humans, but also just one of my favorite government people in general. She gave us the good word about the work that was happening there. Uh, it was clear that mySidewalk had this kind of turnkey approach or were offering us something turnkey, but they were also had a team kind of behind the scenes that were really invested in our data. We get offered turnkey stuff all the time and I'm like, yeah, this isn't going to be turnkey for you once you get in there, like, sounds all good.

Mike: (22:21)

A lot of vendors like biting off a little more than they can actually chew. And I think mySidewalk from the get-go demonstrated that they were familiar with the space and understood the nuance of like 311 data and you know, what our challenges might be. Uh, they understood their competitors or like, you know, here's what you would do in that tool versus what you would do in, in what we're doing and how that's something different. So I didn't feel like I had to, you know, kind of put them on pause and I'm like, no, we have something for this. They had all that kind of cooked and thought out before that, which is very helpful because that just helps us get moving, um, at, out of the gate. So it was a turnkey kind of philosophy with an understanding of the nuance and the details of what's happening behind the scenes because then we can get to the real work rather than having that, like those kind of awkward, clunky discussions upfront.

Lindsay: (23:13)

Yeah. That's so important. Finding a partner in the space that understands the challenges. You see so many vendors that have set out to tackle a problem that they have no clue about to even begin with.

Mike: (23:25)

No. And they're discovering it kind of with you and that's a little frustrated because you're like, now you feel like you're catching them up, um, to stuff which, you know, it's great because I want more vendors solving civic problems, but, sometimes it's easier to do that than other times.

Lindsay: (23:41)

Right. Right. And Stephen, what would you say are your differentiators in the market?

Stephen: (23:46)

Well, uh, I think Mike said it pretty well. We definitely think of ourselves as partners who understand the problems in local government. I think that the only other thing I'd add is the data asset that we've built is unique and is valuable. We were talking about combining operational data with outcome data and we think that's, that's fundamental to performance management, performance improvement. And so we know that we can bring that right to the conversation. And then the only other thing I'd add is the storytelling part of this, we take really seriously. We're in a space where ADA accessibility matters a great deal where mobile responsive infographics and data visualizations matter a great deal where the story you're telling a story of equitable service delivery or not, uh, matters a lot. And so we bring that perspective and those toolsets to the equation as well.

Lindsay: (24:41)

And Mike, you've a breadth of experience in local government and in the space more generally. And I'm just curious where you see the future of data use in local government going.

Mike: (24:52)

I think the message at this point, all the advocacy has worked. People know data's important and we've got local leaders, you know, all talking about being more data-driven. What I get excited about, it's actually probably a little bit more on the nerdy side. I'm finding more and more people realizing that what really needs to happen is in this cleaning up old clunky datasets to make them useful. It's in that middle piece. That's not that sexy. Because the reality is that some of those like user facing tools have gotten really good and really strong, and people now have an appetite to see more of that. And I'm like, yes, but then when they throw their junkie data in there, then it says all kinds of things that aren't lined up with reality. So I think as business lines start trying to line up what they intuitively and experientially know to be true, you know, is that matching with the story that's being presented on the data?

Mike: (25:51)

I think there was a resistance to data years ago because the data that was showing up on the screen on that kind of simplified chart was not representative of their kind of lived experience. So as things are getting more sophisticated, as Stephen was saying, as the storytelling gets better, I think people want to participate more and more in that storytelling. And they're like, Oh yeah, well, let's dig into the data and figure out what we need to clean up so that way, when we automagically make these charts happen, they're actually representative of what's happening and they become useful for you from a process perspective. So I'm seeing a lot more cities talking about process improvement, doing, thinking about innovation is more than just kind of like a buzz word and really thinking about it more as, you know, systems for process change and data is inevitably like a core piece of that. You have to sort of count your improvements, count your stuff so that you can continue to move the work forward. So I'm certainly seeing lots of my, my peers thinking about it that way  is a little bit different, but some of the core pieces are the same. I'm seeing it continually get more nuanced in that direction, which I love.

Stephen: (26:55)

One idea that I think has some real potential in local government is, and it's rooted in what, what Mike's describing is a lot of the work that needs to happen now is in support of the vision and the insights that come. And that actually is a great economic development and training opportunity in governments across the country, because you actually have staff that can do those things. And also if you're trying to build, uh, capacity, uh, in underserved communities, these as a great way to get started in a high paying profession. So, uh, building talent around data quality and data accuracy is a great first step towards a very lucrative and rewarding career. And so there are opportunities in local government to be thinking about those pipelines in a way that would improve the way that we govern and, uh, be a real economic development tool.

Mike: (27:53)

Yeah. Stephen I made a terrible joke over the years. Well it's not that terrible? I still mean it, but, uh, that, like, I don't even want to talk about big data and AI. And like, I just want people that, like, let's start with spreadsheets. It was a challenge just to get people to start with the spreadsheet. I think people are one using more of the spreadsheet and realizing that like, Oh, this stuff, yes, it is. You do have to have, at some point you introduce all the kind of sophisticated tech, but you can do so much more with a flat file these days. Right. Which is really just a spreadsheet. So people like, Oh, that's it like if I, if I gave you this table in this format, you can kind of ingest that and it becomes part of this storytelling narrative. Like that's the tools that have kind of come around from like the early days where you had to have a, you know, a multi-dimensional data warehouse cube.

Mike: (28:49)

And that was the only way that you could do analytics. And now you've really kind of brought it down to its core, which makes it more accessible, allows you to onboard more people. You can bring in people into the community and think about like data science is a thing that you can learn how to do in a community. So I think that's a great point, Stephen, and it's not just practitioners within government, but it's now a tool that you can kind of loop in what's happening in communities to help people up-skill and find new ways to participate in the knowledge economy.

Stephen: (29:19)

I completely agree. And it's exactly what we mean when we say democratizing data science, right. Because it is to the point where there is no reason for this to exist in, in towers. Uh, this is stuff that everybody can get their hands dirty in and, uh, and we're all gonna be better for it.

Lindsay: (29:39)

Well, a lot of great points, Mike, I want to talk about some takeaways. You'd like another local government to keep in mind when looking at vendors for data analytics and why you'd specifically advocate using mySidewalk.

Mike: (29:53)

Yeah I mean, this is a team that, you know, got in the weeds with us on a number of times, just to make sure that they understood the problem statement. Any one that you're out, you mentioned this earlier, Lindsay like align around a problem statement, don't skip into, you know, technology looking for a problem to solve. I don't know how many vendors a day I see that are just like, here's the tech and like, all right, well, what problem does your tech solve one and two, have you even thought to where it might align with what we're doing in, in the city? So spend plenty of time on that alignment when you're evaluating any technology whatsoever. That process was always easy with mySidewalk. Uh, I didn't have to feel, I had to go too deep to explain some stuff. It just sorta got it. And then it was just a really, it was just an issue of kind of timing and aligning some resources to get our project kicked off.

Lindsay: (30:48)

And Stephen, after working through implementation with over 250 local governments across the US what's some advice you'd share with a local government looking for a solution like mySidewalk?

Stephen: (30:59)

I'm with Mike a hundred percent on this, don't just focus on opening or automating data. Sure. Those things are important, but first get really clear about your end goals, which for our customers like Miami, or about establishing a strong relationship with their residents. One that's based in trust and transparency and top-notch services. And then you need a solution that's easy for your staff and residents to access, engage with, learn from and take actions that will build a stronger community. And that's my advice.

Lindsay: (31:28)

Great. Well, this has been fantastic. I mean, Mike, the fact that you from Miami are bringing up, Hey, let's talk about the boring spreadsheets and let's get away from all this sexy, flashy, cutting edge stuff that local governments presumably are working on. If you read anything in the news. That really helps break down even some barriers between local governments too. Small to medium sized local governments are very dismissive of what large governments are working on and say like, we're never going to be able to do that stuff because we don't have the resources.

Mike: (32:01)

I mean, listen, we love the, the sexy stuff too, but really at the end of the day, it comes down to like the spreadsheet when it comes down. It's not that different. I can sit down and catch up with my colleagues in much smaller cities. And at the end of the day, we're dealing with the same stuff. My organization at the County was 26,000 people. It's the same stuff that you do across the board. So, uh, do the thing, and you'll be fine.

Lindsay: (32:28)

Yeah, it's beautiful. And I love it because that's why we built Govlaunch to bring this community together of every local government out there is really struggling with the same, same thing. So let's stop reinventing the wheel. Stephen, my takeaway, uh, that I think local governments should also keep in mind is that obviously we're talking to Mike from Miami here, but you referenced some clients too that are significantly smaller. So it really demonstrates the breadth of the solutions that your product can deliver. And that this is going to be something that local governments of any size should really look into. And Mike, it sounds like they understand the problems that you're dealing with, which is more than we can say for a lot of vendors out there. So this is again been fantastic. Thank you both for being here and sharing your important work with the wider community of local governments looking to engage more with data and to do so seamlessly. Mike, keep up the exciting work in Miami and best of luck to you Stephen on behalf of mySidewalk.

Mike: (33:23)

Thanks Lindsay.

Stephen: (33:24)

Thanks Lindsay. Take care.

Lindsay: (33:33)

I'm Lindsay Pica-Alfano and this podcast was produced by Govlaunch the Wiki for local government innovation. You can subscribe to hear more stories like this, wherever you get your podcasts. If you're a local government innovator, we hope you'll help us on our mission to build the largest free resource for local governments globally. You can join to search and contribute to the wiki@govlaunch.com. Thanks for tuning in. We hope to see you next time on the Govlaunch podcast.