Professor Steve Goldsmith and co-author Kate Markin Coleman discuss their newest book, Collaborative Cities: Mapping Solutions to Wicked Problems.
In this episode Senior Editor Betsy Gardner interviews Professor Steve Goldsmith and Kate Markin Coleman about their newest book, Collaborative Cities: Mapping Solutions to Wicked Problems. They discuss how their respective backgrounds in local government and nonprofits inform their ideas about collaboration and how important it is to work across sectors in order to improve services for residents. Coleman and Goldsmith outline how mapping and visualizing data is crucial to these collaborations, particularly around issues of public safety, homelessness, and sustainability.
Music credit: Summer-Man by Ketsa
About Data-Smart City Solutions
Data-Smart City Solutions, housed at the Bloomberg Center for Cities at Harvard University, is working to catalyze the adoption of data projects on the local government level by serving as a central resource for cities interested in this emerging field. We highlight best practices, top innovators, and promising case studies while also connecting leading industry, academic, and government officials. Our research focus is the intersection of government and data, ranging from open data and predictive analytics to civic engagement technology. We seek to promote the combination of integrated, cross-agency data with community data to better discover and preemptively address civic problems. To learn more visit us online and follow us on Twitter.
Betsy Gardner: Hi, this is Betsy Gardner, Senior Editor at the Harvard Kennedy School and Producer of the Data-Smart City Pod. Since we started this podcast, we've had great support from our listeners. And to make sure that you don't miss an episode, please find us under the new Data-Smart City Pod channel wherever you listen. Make sure to subscribe so you get each episode and thanks for listening.
Welcome back to the podcast. I'm Betsy Gardner, Senior Editor at the Harvard Kennedy School and Producer of the Data-Smart City Pod. We have a great episode for you today. I'm going to interview Professor Steve Goldsmith, who usually hosts, and his partner and co-author, Kate Markin Coleman, about their recent book, Collaborative Cities: Mapping Solutions to Wicked Problems, which is out now. So tell us a little bit about this book. You both come to this topic from rather different backgrounds. So how did that inform the writing?
Kate Markin Coleman: So why don't I begin? So when you are married to someone who's a professor, if you don't get your answers in really quickly, cut out of all of the conversation. So both of us, in different ways, I come from the social sector, Steve, obviously from public sector in academia. Both of us in our work have been concerned with what I would call wicked problems or grand challenges. Complex problems, multi-scaler, all sorts of factors play into them. And both of us had come to realize that no one agency, no one organization could address those problems effectively alone in that they required cross sector work to address.
The problem is that cross sector collaboration is very difficult. And so we talked about this a lot. How do you overcome the barriers that make it difficult to collaborate across organizational boundaries? And we began to think about location intelligence, called that data visualization using a geographic platform. And for a variety of reasons, because so many of the problems are place-based, that's how we came to the notion of location intelligence. And so really, it was through discussion that we came to mapping as a tool to facilitate the formation and operation, and ultimately, adaptation of collaborations designed to address wicked problems.
Betsy Gardner: Steve, do you have anything you want to add?
Steve Goldsmith: Well first, I'd like to add, it's very confusing. I've lost control of my podcast. You're asking the questions and my spouse is answering, and I feel like there's been an abrupt diminution of my role in this podcast. So that aside, no, I don't. I would only add the following. Kate was an ALI fellow at Harvard when we first began to think about this. And I look at problems from the government side. Kate's got a long history as a senior executive at one of the largest, if not the largest, nonprofit in the country. And she looks at things differently.
So to me though, increasingly, there were limitations of what government could do. Kate was paying attention to wicked problems. And the more difficult the problem, the more limited the ability of government to resolve it. Not the more need for government to play a part, but the more limited its ability to resolve it. And the other issue, and Kate pointed this out earlier to me, was I generally think about problems from the bottom up. I find an anecdote and I generalize it. Kate thinks a little bit from the top down, from the system side. So if you do that, then you come together on the location issue. Because top down or bottom up, your problems organize themselves around people and places. So that's a little bit about how we came to the notion of the book.
Betsy Gardner: So it sounds like that vocational data, using it in a really collaborative way, was really the cornerstone for decision making throughout your careers. Can you give us an example where mapping or vocational intelligence drove policy, or it drove funding decisions, maybe in an unexpected way?
Steve Goldsmith: Well, let me start with an answer that may not be unexpected. When I was mayor of Indianapolis, I was trying to figure out what to do in the communities that had been most neglected for the longest period of time. And I wanted to identify the communities, and then I wanted to identify the assets in the communities. So I started with the GIS guy. I said, "If I wanted to say, I wanted to pick eight neighborhoods, communities of 8,000 to 20,000 people each that had been most neglected, where would they be?" So then there was a discussion about what would the factors be, and then that person tried to map them. The next question would be, what are the assets in those communities? The nonprofit, the church, the small business, the fill in the blank.
That was more complicated, because nobody had really thought about the assets in those communities, they just thought about the problems in those communities. It was actually easier to map the problems than it was the assets. So that led us to a very substantial half billion dollar infrastructure program in those communities that was both personal infrastructure and physical infrastructure. But it also led us to the conversation that we're now having with Kate and the book, which is, what are the nonprofits, who are the individuals? How do you partner with them? What are those issues? How does that affect your budget and your contracting? So that was an early example that became more mature when Kate started to relay to me some of her experiences with the YMCA.
Kate Markin Coleman: So in the book, there's a particularly concrete example of how working, using maps literally changed the funding. There's an organization in Miami, Florida, called the Children's Trust. And it was started, I think you call it an ad valorem tax. So property taxes go to fund programs for children in the Miami Dade County. And so historically, the Children's Trust, among other things, funded quality improvement, sort of processing stuff, for early childhood providers. Their board, at some point a few years ago, challenged them and said, "How do we know our investments are actually producing the results for kids that they need to?"
And so they did an exercise where they created maps. They layered poverty levels of the kids on census data. And then they plotted, because this is a really a sophisticated organization. They plotted all of the childcare providers and ranked with a quality assessment. And here's what they found. They found in certain areas, while there might be a plethora of providers, there were deserts in terms of the quality of providers. And so they went back and they thought about, "Well, how could we change our funding to improve access to high quality childcare for people in these areas that were really poorly served?" And they decided to, instead of doing process payments, they added direct payments.
So they fund centers directly with salary subsidies to help supplement the salaries of the providers. Because they're so often underpaid, they provide direct funding for education, for continuing education for the childcare providers in the sites. And then really interestingly, they provided subsidies to pay parents who were earning too much to qualify for childcare subsidies, and therefore couldn't afford the high quality sites. And if you listen to what they say, they absolutely could not have done that if they had not seen, with their own eyes, the concentration of providers, and yet, the paucity of high quality providers.
Betsy Gardner: That's a great example, because it doesn't sound like they necessarily changed the amount of money that they were working with, but it was just that they could direct it to so much more efficient use. So I think that's a great example. So it sounds like in some ways, this data was there in these examples, or at least the potential for mapping this information was there, but it wasn't really driving these improvements or driving these effective funding decisions. So do you think that literally mapping it either helps humanize the data or it just helps direct attention to where it's needed most because it is visual?
Steve Goldsmith: Well, there are two components, I think, of an answer. And I'm going to suggest that Kate provide one and I'll provide the other. One is how the visualization of the mapping data creates a narrative that brings people together. And I'm going to defer to Kate on that. The second though, is that this conversation about mapping is more than a map. And the map in the book, and the map in our conversation, serves as a platform for multi-layered data. And it is the layering of the data. I mean, take Kate's last example about Miami. It's not just the access to childcare. It's the quality of the childcare mapped against it. It's the location of the childcare. It's other things as well. So I'm going to get back to the layer data, but I think Kate explaining how the mapping narrative brings people together for collaboration, the formation of the collaboration is a particularly important point of the book.
Kate Markin Coleman: Yes. So one of the things that we found when we were doing the research is this very human tendency to center oneself geographically. You tend to put yourself in place, and then you look and you put yourself in place relative to the people that are around. You just think about all the apps that you have on your phone that are premised on this one. Once you have me on the map and you see where others are, it can become we. And then we signals interdependence.
And that's a really important part of organizations coming together, seeing that everybody has a stake in solving the problem. One really cute example, in the book, we talk about some work that was done in Indianapolis and the organization was mapping need in a particular area. And they put on the map, just one map, the addresses of the people who were part of the collaboration, who were actually part of a church group, who were doing the. And all of a sudden, those individuals saw that right where they lived, someone near them was experiencing, whether it was poverty or housing challenges. So that me became we.
Betsy Gardner: Almost sounds like there's two types of collaborations, because one is myself as an individual, seeing myself as part of this larger group, like when I can see who is in my neighborhood, experiencing these different things that are being mapped. And then there's the collaboration across systems or institutions at another level. So what would you recommend for city leaders? They might have some data. They might have some maps. They might have some people who are understanding their individual place within this data. But they don't already have like that network approach that you're talking about. They don't have that collaboration at an institutional level. What do you recommend? How can they break down those silos? Especially because you've broken down silos from two different sides. So how can city leaders start to do that?
Steve Goldsmith: Kate and I have discussed this. I think that what one would do is say, "What is the problem we're trying to solve?" Not "What's the data we're trying to map?" But what is the problem? And the more complex the problem, the more it needs a system response. And the more it needs a system response, the more it needs this larger framework. And so once you say, "We're trying to solve homelessness." OR "We're trying to address the issues of COVID. And which schools are open, and which restaurants are open, and under which conditions are they open?" Then you say, "Okay, what data do we need?"
Steve Goldsmith: And often, the city has a more advanced GIS system in the nonprofit. And Kate work for the largest nonprofit in the country and she'll tell you about that, where their mapping is when she was last there. But so then if you say, "Well," and we said this in the book, "Somebody needs to be the platform organizer whose data creates the narrative that brings people together." And then you have these issues of operation and iteration as well. So just going back to your question, what's the problem? Who are the stakeholders? What data do the stakeholders have? And how should that be mapped?
Betsy Gardner: I want to talk a little bit about the relationship aspect between a nonprofit and a city.
Steve Goldsmith: There are two separate issues here. I'll talk about one, Kate can talk about one. The one issue is national organizations, big deal, nonprofits and federated, or have branch offices, how can they use their mapping skills, such as NAACP did, on census work, where the central office had a set of mapping skills and tried to help the others? The other issue though, is one that deals with how one creates the narrative that brings people together. Cities and states and federal government have money. And they often use that money to contract with nonprofits.
And once one starts to map, you can see that there may be too much of this and too little of that. Do their missions necessarily align in a geographic area? And so there is a little bit of elbowing here in this process where people say, "Yeah, we want to collaborate, but we don't really want to change what we're doing, because that's what our funder gave us to do." So lighting that up on a map and having people understand, "Well, if there's a really important need over here, we need to nudge you over to resolve that need." That's where the tension comes from. But that's also illustration is important to the map.
Kate Markin Coleman: Yeah. And I'm afraid to generalize and say whether nonprofits have more trust. Many of them certainly are on the ground. But to what Steve was saying, there's a really important with nonprofits. And one of them is that because there's such a high degree of fragmentation, they don't have a window into what's happening in the areas where they operate. It's very difficult for them to disseminate practices that work. So there are lots of barriers to efficacy, which this more global view, this aggregate view of needs and response in the community is really important.
So that's where we think that the geospatials, it offers a lot of opportunity to you think about rationalizing the system or even thinking about how to more effectively allocate resources against a problem. The flip side is, because those organizations are really on the ground, you often get a level of creativity and experimentation, which is really important. So finding the balance, we think, has a lot of opportunity to yield very productive results.
Betsy Gardner: Sounds like it's maybe not always the easiest balance to find, but it's an incredibly worthwhile one to really deliver for the community.
Steve Goldsmith: I think that's right.
Betsy Gardner: Do you want to talk just a little bit about where data transparency falls into all of this?
Steve Goldsmith: The more transparency in the data, the more likely the narrative is to bring people to a place they can see. You can more easily argue about an Excel spreadsheet than you can a map. A map is highly visual if it's done right and it brings people together. But there are also situations where particularly the social service where not everything can be transparently provided to everyone else. There's the privacy issues and the like. But the benefit of the mapping is that layers of data can be available publicly. And other layers of data could be available privately. Layers of data could be available to a provider of X services in the community, but not to Y. So I think that coming up with the coding of it and access to it is important. But all in all we advocate, the more transparency, the better.
Kate Markin Coleman: Although in some instances, in the example that I talked about with the Children's Trust, not all of the mapping work could be made public for quite obvious reasons. Another area though, where we've seen the importance of transparency is when decisions are made using that data and those maps to explain to a community why a pipe's being put in here rather than there, why the street's being built here rather than there. So it does serve on some level as a trust enhancing mechanism.
Steve Goldsmith: Maybe as we get to the conclusion, Kate's last answer sets up your work. I can't question you. But if you think about all the work you've done, Betsy, on mapping equity, when you see the inequity of the investment strategy over the last 20 years, it's hard to argue with that. It's hard to say, "Well, no, it's all been fair," because it's not been fair. You can see it's not been fair. And so the visualization of those inequities is the step one of the cure.
Betsy Gardner: That's very true. I think in Oakland, their Great Pave, that was such a good example of literally laying out everything and showing where there'd been disinvestment in pavement and street improvements. And I think that speaks exactly to what you're talking about. Everyone's on the same page. You can't argue with showing the street quality and realizing where has it been disinvested or where it has been ignored. And it was in non-white communities. So do you think that this is the direction that the field is moving in?
Kate Markin Coleman: Do we think that this is the direction that addressing social issues is moving in the future? I would argue that enough things have happened in the larger environment that we would say yes to that. I think number one is since really, maybe the '90s, maybe a little later, we're seeing all sorts of organization forms that are looking at creating social value, even when they're from the private sector, whether it's a B Corp. But the other thing we're seeing is the technology which allows people to come together. And then you add to that the recognition that these are all complex problems that require cooperation to solve it. You sort of set up, and I think in the book, we called it a "Chunian moment," where this approach to addressing issues is becoming more and more standard.
Betsy Gardner: Thank you all so much for being on the podcast today. It's been great to hear about this book, from your different perspectives and experiences, just to highlight the importance of solving these problems collaboratively and really data-driven in a more nuanced way. So I really encourage our listeners to check out Collaborative Cities, which is available through Esri Press or wherever you purchase your books. So thank you both for being on. Thanks for giving up the microphone, Steve.
Steve Goldsmith: Thank you.
Kate Markin Coleman: You're welcome.
Betsy Gardner: If you like this podcast, please visit us at datasmartcities.org or follow up at @DataSmartCities on Twitter. And remember to subscribe at the new Data-Smart City podcast channel on Spotify, Apple podcasts, or wherever you listen. This podcast was produced by me, Betsy Gardner, and hosted by professor Steve Goldsmith. We're proud to be the central resource for cities interested in the intersection of government data and innovation. Thanks for listening.