In this episode, Paul Kresser, Deputy Chief Information Officer and Former Chief Data Officer of the City and County of Denver, discusses how he uses data to run Denver. He dives into how municipal governments handle shifting to the cloud, how data leads to better managed cities, and so much more.
In this episode, Paul Kresser, Deputy Chief Information Officer and Former Chief Data Officer of the City and County of Denver, discusses how he uses data to run Denver. He dives into how municipal governments handle shifting to the cloud, how data leads to better managed cities, and so much more.
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Steve Hamm: [00:00:00] Paul, it's great to have you on the podcast today.
Paul Kresser: Steve. It's really my pleasure to be here. Excited for our chat today.
Steve Hamm: Yeah. Now tell us about the government in Denver. I understand you have the city and the county government, and they're kind of combined there. And also beyond that, what are the major governmental initiatives that are underway and how is data supporting them?
Paul Kresser: Sure. Absolutely. So city and county of Denver has kind of a unique organizational structure where we are both serve the municipal function as the city, but we also serve as the administrative arm of the state. So the county function as well. So in our form of government, those two are unified.
So it's called a unified go. City and county, uh, together as one. And what that really means practically is that we deliver all the services. One would come to expect from a city, uh, such as, you know, we have our public works department. We, we call it Dotty department of transportation infrastructure. We have, you know, our [00:01:00] plane development departments, um, all the public safety functions as well, but then we also have those county.
Uh, level functions that we provide or services that we provide as well, such as the public health authority, uh, human services department, and of course our Sheriff's department. So it's really what it means is we have a large breadth, um, of services that we're responsible for providing and from an it perspective, it means a whole, uh, host of agencies that.
Responsible ensuring, uh, that they're empowered and enabled to deliver those services. So, yeah. So as an organization, um, city county of Denvers, we have about a 2.6 billion operating budget across all of our appropriate funds. And that is, uh, supported by roughly 13,000 full-time employees.
Steve Hamm: Mm-hmm
Paul Kresser: When we talk about the major government initiatives underway, actually, our mayor just gave his final [00:02:00] state of the city address not too long ago ago.
He's actually in the final year of his final term in office where he laid out, um, our priorities for, for this remaining year. And there sort of bucketed into a few categories, um, kind of chief amongst them is ensuring both housing and economic justice, uh, in our community. Um, real emphasis on addressing, uh, the impact of climate change, um, investing resources around better policing, uh, reducing gun violence and fighting, uh, fennel that sadly exists in our community.
And then finally investing in, um, The children in Denver. So collectively there's a lot of work that data is supporting directly supporting in those, um, initiatives. I, I can speak quickly to one in the, uh, better policing, uh, and fine fennel area. Um, we're really, we've, [00:03:00] we've pulled teams of data analysts together, um, across multiple agencies, whether they're in the public, uh, public safety agencies, um, folks on the GIS teams that my directors lead here in our central it department technology services.
Folks over at health and human services and elsewhere, uh, in the city to kind of form a task force that is pulling all these data sources together to identify where both public safety hotspots and public health hotspots exist. And they're looking at dozens of different variables to identify those areas so we can concentrate our resources, um, in, uh, at, at those identified hotspots.
Steve Hamm: Oh, well, that sounds really cool. You're taking on so very complex issues, these social issues like homelessness, like, you know, climate justice, these other things really, uh, very difficult to, to figure out exactly what's happening and [00:04:00] then figure out what the right response is. So I think it's great that you guys are using data to, uh, to help you go at that.
Paul Kresser: Absolutely. We're proud of efforts.
Steve Hamm: Yeah. Now I understand that you were you're behind Denver city and county's data strategy. So what's the strategy. And what challenges and opportunities are you seeking to deal using data?
Paul Kresser: Sure. So our data strategy is actually directly supports, um, the mission of the department in which I work technology services. And that department's mission is really, it's quite simple. It's to improve city performance and we've. Identified the four pillars by which we organize, um, the, our tactics around, uh, improving city performance.
So those are organized around reliability, uh, which for us means technology works as expected innovation, uh, which we translate as technology improves operational performance access, uh, which is technology connects [00:05:00] customers to information and services and finally partnership, which is forward thinking collaboration with our customers.
So. We obviously recognize data, our data, uh, well, our data, the city and county of Denver's data and information assets are really the key to helping those departments deliver exceptional city services to our residents and constituents. So we really wanna empower them and enable them, uh, to take advantage of these incredible data assets that we own.
So our data strategy. It very much mirrors the department's mission. We're really focused on trying to provide, not just technology. That that's actually the simple part. We wanna really provide the access to the data, the frameworks, the strong governance, all the tools and expertise that comes with it.
And it's required, uh, for those city agencies to be able to fully leverage their data, uh, to deliver those exceptional city services we're seeking for our and residents.
Steve Hamm: Yeah. Yeah. Now [00:06:00] you worked for the city government of Boston for eight years. And now at Denver, what's the status of cloud and data analytics adoption in municipal governments overall kind of, and, and in Denver, in particular,
Paul Kresser: Yeah, Steve it's, it's a really exciting time to be in this space specifically, uh, working, um, in city government. So I'm proud to say that Denver's pioneering spirit is showing through here. We are a very early adopter, I would say, relative to some of our peers in this space in really, uh, leveraging those cloud and data.
Analytic solutions. Um, you know, we are not afraid to take some chances here. Uh, wouldn't say we're risk takers, but we make informed decisions. Um, and, and to which allows us to, you know, take some chances and if we're gonna fail, we're gonna. Fail fast and we're gonna move on. And we're fortunate to have the full support of our CIO and administration [00:07:00] who really isn't encouraging us to be an innovation leader in this space because they recognize we're always gonna have challenges around resources, whether that's human capital.
Um, so our staff, or whether it's financial resources. So. You have to work smarter, not harder, um, in that capacity. So these types of cloud and data analytic solutions allow us to do that. Um, and we're excited to be recognized as a national leader in this space when it comes to our adoption of these types of tools.
Steve Hamm: Yeah. Yeah. Now, now I know that you have, you you've rolled out an enterprise data hub. Tell us about that.
Paul Kresser: Absolutely. Yeah, we're really proud of this achievement. So it's been roughly a three year journey for us, um, from when we identified our or our enterprise data hub platform and the architecture that was gonna support that. And for the past three years, not only have we been. Rolling out the [00:08:00] technology associated with an ingesting more and more data sets, but we've been building the team's capacity, uh, to support it because that that's the key.
The technology's actually the, the easy part here. It's having the skill set, the, the correct members on your team, the institutional support, and, and most importantly, the culture that's needed to take advantage of a solution like this.
Steve Hamm: Yeah. Now I would imagine that recruiting talent and organizing data teams is a big challenge for cities. I mean, you don't have, you don't have the big box that the tech industry has to pay people. So how do you go about recruiting and retaining and, and just really getting the teamwork right.
Paul Kresser: You you're absolutely right. It, it is a perpetual challenge for us. Um, but for that matter, it's, it's a challenge for anyone that's in this space, these data, um, professionals really, you know, All organizations, hopefully [00:09:00] by now have recognized the value and the importance that analytics, um, in really being able to leverage their, you know, data has, um, has done for their organization.
So we're all in the market looking for more talent to support those efforts. We've taken a little bit unique approach here. Denver, um, relative to kind of the traditional data team model that may exist in other cities, we're very much focused on the data team in our central it department. Technology services is really focused on providing the platforms.
Building out the governance structures, the frameworks providing the, um, the educational material, the resources to enable the data analysts that exist in the department. And as I mentioned before, there's over 200 of those in our departments. We believe they will always understand their data better than we will in the central department, in the central it department.
We wanna enable them to help [00:10:00] unlock, um, their data for them. We do that by trying to break down the barriers to the data, primarily around access. And that's where tools like our data or platforms like our data hub are so important. So we've consolidated all of our data engineering, the data architecture.
State architects, our data, privacy and protection team, the, the BI analyst, those all exist on our central data team in technology services. But the analysts themselves actually are in the agencies. And we really are trying to push self-service model by which they, um, have ease of access. To the data, they need to do the analysis that they're being expected to perform by their leaders.
So we're, we're no longer in the business of trying to create and run reports for agencies it's much better and much more sustainable. Um, for those who understand and work with the data, the most to be doing that, we just need. [00:11:00] Enable them. So, but we get, we have great tools. Um, you know, I, I refer to them as toys when I'm doing interviews with potential candidates that we get to play with.
And that certainly is an attraction. Um, as we try to recruit and retain talent that we get to work with some of the best technology in the market right now.
Steve Hamm: Yeah. Yeah. Yeah. I mean, I remember years ago, I mean, it seemed like city and it, you used to always hear about disasters, expensive disasters, but it seems like in recent years, cities have really gotten much better at managing it. So.
Paul Kresser: I would like to think so. Yes, we've matured. We've matured. A great deal.
Steve Hamm: Yeah. Yeah. Now I was, I was picking at your LinkedIn profile and I saw that you, you said you're focused on data driven decision making.
Uh, and I typically think of municipal government decisions are being primarily driven by politics. So, you know, there's [00:12:00] a little bit of a friction there. How do you deal with it? Are, are politics an issue or are you just kind. Put on the blinder as, as, and go and go straight past him.
Paul Kresser: Sure. I mean, it, it would be naive for me to say that politics are not of a variable at play. Right. But I overwhelmingly will say that I, I do think it's a common misconception that municipal government is strictly or very heavily driven, um, by politics. My experience here in Denver and prior to this in Boston.
Yeah, we're trying to do good work. There are thousands of city employees trying to do the right thing day in and day out. And by and large, they're relying on data, uh, to help drive and inform. Those decisions, you know, I would say actually the, the friction I deal with much more in my capacity is, or former capacity as chief data officer at city and county of [00:13:00] Denver, um, was the friction that exist from people trying or wanting to do good, wanting to help residents or constituents, but us.
Being able to allow them to do that because of certain data regulations or, or restrictions on data use associated with the data that they were trying to use. So for instance, um, trying to take a benefit information that may have been collected for one purpose. And offered for a different purpose. It may not be allowable under, um, the regulations by which it was collected.
So it, those are tough conversations to have to telling somebody, trying, trying to help a constituent
Steve Hamm: So you've been working in governments for quite a while. Now, when you look back at your career, what are the most important lessons that you've learned along the way about managing it in cities? How are you putting the, that knowledge to work in your current role in Denver?
Paul Kresser: Sure. Well, [00:14:00] actually the best advice I ever received, I didn't receive over the course of my co my work career is actually something my dad shared with me at very young age that I I've tried to live by, which is a. It's important to remain rigidly flexible, not flexibly rigid, but rigidly flexible because in, in this in this space, flexibility is key.
The variables change so quickly that if, if you're too tied or, or too dependent or, or, um, too invested in something that you can't adapt to the circumstances. Then you will, it will really be a challenge for anyone trying to make meaningful, uh, change in this, in this environment. So, so I try to maintain flexibility at all time, obviously within reason.
And then it's, it's simple stuff, right? Don't start too big. Don't try to boil that. Start start [00:15:00] small with objectives that are actually achievable and that will demonstrate value amongst, um, your leadership. And it's really, and I can't emphasize this enough. Um, it's really enticing, especially in the data space, right?
We we're, we have vendors approaching us all the times promising the. Big thing, just do this pilot with us, you know, and you won't believe what the return will be and yeah, that, that stuff's important sometimes. And it's great. And yes, you'll probably get, uh, you know, recognized in a, you know, industry publication or something of that nature, but it's, it's totally unsustainable and it's.
Long term, making the meaning meaningful, deep changes at the institutional level that are needed to really support the transformation that you'll want to achieve as an organization. So here in Denver, we're really focused on building that solid sustainable foundation. That's grounded in. Good. Data governance practices.
You know, [00:16:00] we want informed by data, our data literacy efforts, and then we wanna give our practitioners in the data space, the opportunity to really gather and share their experiences together, cuz that that's where a lot of the learning takes place.
Steve Hamm: Now you've, you've talked a little bit in the last couple of answers about kind of governance and policy and those kinds of things. And I know that you're a good governance guy from way back. So you have this central it central data. Uh, you know, controls, rules, governance, and then you, you, you provide tools and you try to give the data scientists out on the edge, a lot of freedom.
So, but there's a tension there again too. So how do you, how do you kind of improve data, governments, governance and security, kind of in a centralized way, but also give people the freedom. They, they need to do their jobs.
Paul Kresser: Yeah, it it's a balance for sure, Steve, but I, I would always, err, on the side of more governance is, [00:17:00] is better than less, especially with the. The type of data that municipalities, um, or any, any, you know, government organization for that matter deals with, you know, we, we touch it all, whether it's, you know, criminal justice information, payment card, data, um, HIPAA, uh, even children information FERPA, right?
We deal with highly sensitive, highly protected, highly regulated data sets. So it's really key. It's really important that we have the strong governance practices in place. And going back to the, our data hub. Yo, we, we could have rolled out our data hub much quicker than we have. We've intentionally have gone slow so we can build in those strong data governance processes or practices within the process.
So we will not ingest data into our data hub until we go through a, a very robust checklist, ensuring that we have all the, you know, right. [00:18:00] Um, Stakeholders identified the data stewards identified that they're clear on what their roles or responsibilities are for maintaining, uh, the quality of the data and that they understand what they are and are not allowed to do with that data.
So it it's really key, um, to have those formal governance processes in place to have forms by which you can communicate these, um, And just to ensure from a compliance perspective, um, that we're in here adhering to all the proper rules and regulations.
Steve Hamm:You know, I, I see that Denver has more than 50 departments. How do you manage data across all those agencies?
Paul Kresser:so we, we rely. You know, heavily on our data stewards and our data practitioners in our agencies to, um, to apply our governance, practice, processes and practices.
So we've stood up and we've fostered and nurtured what we call our [00:19:00] Denver data core, which is really kind of our center of excellence center of enablement, whatever term you want to use for those practitioners to come into. Communicate to share and to learn from each other and is opportunity for us, uh, from a central perspective and specifically for our data protection officer here at the city and county of Denver to, uh, keep people informed and abreast, um, of all the rules and regulations from a com compliance perspective.
So. That membership is very stupidly aware of their duties and responsibilities. And then for all the data that we're ingesting within our data hub and making available, um, for consumption across the city, those data stewards have an awesome responsibility to ensure that that data is maintained. Um, that the quality is, uh, maintained it, that they are able to answer any questions.
Any of our other, um, analysts across the city may have around that data. And then finally, we're [00:20:00] fortunate here in Denver to be supported by mayoral executive orders, which actually give us the authority and the power to enforce these governance steps that we're taking.
Steve Hamm: Yeah. Yeah. Now I wanna talk about the cloud for a minute. When and why did you in, in Denver start using modern data cloud technologies like snowflake and how are you using them now?
Paul Kresser: Sure. So our journey be began, um, roughly four years ago and it was born out of the realization that the current technology, our current model was no longer sufficient and was no longer working, uh, to meet the. Demands the analytic demands we were expected to provide, uh, from our agency partners. So they were looking for solutions that could offer near real time.
Um, uh, Capabilities. And we were running reports that would take, you know, batch jobs overnight [00:21:00] and the, the data wasn't handy. It wasn't a, we couldn't make the, couldn't serve them the data, uh, soon enough, right. For them to be able to actually make near real time decisions off of. So we had to explore.
Options and the market at the time had matured to the point where these scalable elastic solutions existed that could offer those near, near real time. Um, Information. So, um, our vision, our initial vision for our data hub was really to create a one stop shop where those 200 plus city analysts could access, analyze and share their data.
Um, they were frankly tired of having to wake wait sometimes weeks after they put in a data request, um, for us to grant them access to those data sets. And sometimes Steve, honestly, they didn't even know what data we had available because we had. True inventory or catalog, uh, at the time [00:22:00] of all of our data assets.
So fast forward to today, we've come a long way. Um, we have a much better grasp on our data and we're actually in the process of selecting and soon to be implementing the data catalog solution,that we really think is going to enable those type of selfer self-service analytics.
Um, we wanna promote, uh, across the city.
Steve Hamm: So are you using, um, like a marketplace tech platform for, for the data catalog or how does that kind of work technically, and then also from the, from the user point of view?
Paul Kresser: Yeah. So the, the data catalog solutions we're looking at right now, it's a, you know, they're really a data. It's really a data governance platform. The data catalog is, is a feature of the catalog or of the governance platform. Right. But the, the vision is that those. Uh, a hundred, you know, 200 data analysts across the city [00:23:00] will be able to ACCI, uh, access a portal, the data catalog by which there will be an inventory of all of the data sets that are available to them based on their roles.
So we, from a, from a information security perspective, we apply applied real based access controls, um, across the city. So we've applied those real based access controls to our data sets as well. So based on the. That those analysts are in, they will have all data, um, that they're entitled to by virtue of their permissions.
Steve Hamm: Oh, that's that's cool. So, so when they look at the catalog, they only see data that they have access to.
Paul Kresser: Correct. As yep.
Steve Hamm: That makes total sense. So, you know, you talked about culture a couple times in our conversation today, and I understand that you're using these modern cloud technologies and methodologies to drive cultural changes in your department.
Talk to us about that.[00:24:00]
Paul Kresser: Yeah, absolutely. So these, these technologies, as I, I think mentioned in a prior or answer, um, People want to use them. Right. We use them to attract talent to come work at this sitting county of Denver. Um, So they, and they recognize the power, um, that they offer them ESP, you know, as far as the analytic capabilities.
So we're actually using that in some capacity as leverage, um, with our agency partners to ensure that they are mature enough from a data governance, um, perspective to use these type of technologies. So again, we, before we ingest data or make data available, um, To the analysts. We go, we go through a series of checklists and even ATEST stations on their behalf, ensuring that they, uh, recognize their duties and responsibilities, uh, as relates to the [00:25:00] use of this data, that they will only use it, you know, responsibly and ethically that we have the data governance processes in place to ensure.
Quality. Um, and we've used that to help, to, to frankly help mature the, the data literacy and the data capabilities in our agency, part partners. Um, so they are prepared, able to take advantage of these, the type of, um, functionality that these modern tools offer them.
Steve Hamm: Yeah. Now we've talked in, in the podcast today about a lot of the activities you've done in the last three or four years there in Denver. Let's look to the future. Now, what are the major data management trends that you see emerging over the next year or so?
Paul Kresser: Sure. So Steve, more and more of my time, and I'm sure this is the, the case for others in the public sector right now. We're, we're spending a lot of time talking about that [00:26:00] regulated, protecting otherwise sensitive data, um, that we spoke about earlier. Right? So it is key from a day management perspective to know what you own, where, where it exists and who has access to it.
So, so, so much of our discussions. This again, of course comes back to our data governance. Um, practices are, are centered around identifying what we have, where it resides and who has access to it. So I, I really see those data governance platforms, especially those. Um, with the data discovery and classification feature is being really important in this respect.
So, you know, we have GDPR, um, the European union CCPA in California, Colorado itself recently passed its own privacy act. I think we will see. More and more types of legislation like this, perhaps. And I, I hope even at the national level, some more federal [00:27:00] guidelines as well, so we can all be consistent in adhering to these, um, types of regulations.
Steve Hamm: Yeah, that makes a lot of sense. Now I'm gonna ask you to put your visionary cap on for a minute, looking out five years or more, how do you see data transforming government operations and even society?
Paul Kresser: Yeah. So I, I think that transformation's already begun. Um, and, and in earnest for that matter, I mean, we, we can talk about the traditional smart city activities, but I would rather actually go back, um, to what I state earlier about my department's mission, which is to improve city performance and the, the heavy reliance our agencies have.
Or dependencies our agencies have on data to make that happen. So, you know, five years ago, uh, here in Denver, we were looking at permitting licensing data and where bottlenecks may exist in those [00:28:00] processes, um, to improve performance and cut down on turnaround times or review times, um, for how long it took for a permit to get processed.
You know, I, I see that type of analysis being done, you know, exponentially now, uh, across all of our city functions. Right. Really relying on the data we're collecting from our source systems, um, from. You know, our three 11 systems from, you know, uh, all sorts of disparate data sources. And then with these modern data, um, platforms we've been talk de discussing today, really be able to, to do that advanced analytic work and draw insights, um, that may, you know, previously have gone undetected.
And I think the speed at which that can. Um, is only going to increase to the point where we'll be able to use, you know, ML, AI capabilities and technologies to [00:29:00] pretty much, um, Make real time decisions, whether that is, you know, the, the route optimization of a public works vehicle or a snow plow, um, during winter months, uh, if it's, uh, constituent calling into our three one, one call center, being able to instantaneously, uh, you know, Pull up all the interactions we've had, not just from a three 11 perspective on that constituent, but across all the city agencies to have a really informed view, uh, of the customer, right.
And be able to deliver better, quicker, faster services to them. And maybe even to be able preemptively address. What we would expect them to be contacting us on. So I, I really see that's the direction of where this is going. We, we have such a wealth of data and information in, you know, I think collectively most CDOs in my position across the city, we would say we're only just beginning to [00:30:00] scratch the service surface of what's possible with it.
Steve Hamm: Yeah. I, I love that vision there of preemptively figuring out what people are gonna want. I mean, if, if cities can identify needs or gaps before the, the people start squawking about them,
Paul Kresser: Right.
Steve Hamm: you eliminate squawking. that? Wouldn't that be beautiful?
Paul Kresser: Wow. Yeah.
Steve Hamm: right.
Paul Kresser: I think people always love to squawk a little bit about government though.
Steve Hamm: No, I think
Paul Kresser: human nature.
Steve Hamm: I think you're right. So we, we like to end on a lighter, more personal note, and I understand that you love airplanes, airports, and travel. You've got these models of aircraft and photos of airports in your office. What's this all about?
Paul Kresser: Yeah. Great. Great question. Um, so I've, I've lived a very privileged and fortunate life where I've been able to travel quite extensively. So my, my mother was a flight attend for 40 [00:31:00] years, which afforded us the ability to travel. Um, you know, when I was young and with that just comes. The benefits of exposure to so many different cultures, um, different ways of thinking that you might just not normally, you know, most people are not actually fortunate enough to experience.
So I feel, you know, very privileged in that respect and just the freedom that. It comes with, uh, hopping on a plane in traveling. So my office is, as you stated, very well represented where it comes to airline, um, you know, Memor memorbilia I joke, uh, some of it, yeah, even borderline collectible. So maybe it will help fund my children's, uh, college fund
Steve Hamm: Oh, that's funny. That's great. That's great. Well, you know, it's been great talking to you and I really, you know, we don't talk to government people that often it's usually business people, so it's kind of nice and refreshing and different to talk to government people. And I, [00:32:00] and I think. Denver and you, you have this very kind of crisp mission, To use real time data to make just in time decisions that maximize limited resources to deliver better and more consistent services. And I think that is a, is a mission that's great for cities. And that would be great for, for any company. Uh, the way it thinks about its employees, the thinks the way it thinks about its data and the, and the way that it, it thinks about its, its constituents, our customer.
So I really, I really feel like there's been some wonderful lessons in the conversation today. So thank so.
Paul Kresser: Thank you, Steve. I really appreciate the opportunity to talk to today.