This blog post was initially shared on the NLC website.
While data plays a central role in informing state and local government policies and services, it is often overlooked as a resource. Worse, current data collection and management practices are creating disparities in communities because they often overlook minority groups. In fact, the NLC’s State of the Cities 2021 found that while many mayors and other government leaders are focused on equity, “issues with data create a knowledge gap that perpetuates color-blind policies that do not acknowledge or confront racism, systematic or otherwise.”
I [Heidi Lorenzen] recently moderated a fireside chat during Accela’s annual conference, Accelarate, where I discussed equitable data governance with the following experts:
- Dr. Robert Blaine, senior executive and director of the NLC’s Institute for Youth, Education and Families and former chief administrative officer for the City of Jackson, MS;
- Katya Abazajian, open government advocate and researcher at the Georgetown University Beeck Center for Social Impact + Innovation, which recently released a report on how communities are working together to develop tools to address pressing local challenges in light of the pandemic, and another that outlines a framework for what state chief data officers’ roles should encompass; and
- My colleague Cathy Grossi, vice president of product management at Accela, the global cloud solutions provider powering digital government service delivery to more than 275 million citizens worldwide.
As communities look to improve how they serve their residents, increasing equity is a key priority. Below are highlights from our conversation on community-centered data processes and how they can help governments implement policies that benefit all residents.
Lorenzen: What do you think government employees should know about data equity and why it’s important?
Dr. Robert Blaine: The organization of data is incredibly important. When we start to think about how data is acquired, and how it is focused on various communities, it has huge implications on the factors that drive policy. It’s very easy to have data governance structured in a way that can skew policy decisions. It’s incredibly important to think about how data is organized in order to reach policy decisions that produce more equitable outcomes for communities.
Katya Abazajian: Innovation efforts often happen from the top down, but those projects also have to happen from the bottom up. As anyone working on the ground will know, making connections with community partners and creating opportunities for your community members to provide feedback is an operational shift that has to happen in the day-to-day work of public servants. Everyone across departments and functions needs to understand how to go out into the community to collect feedback about how data should be used, because that’s where you really start to hear what the community needs are.
Cathy Grossi: Agencies are at the intersection of policy and the community, making them uniquely positioned to understand the community and feed that information back to policy. It’s important not only to make sure that data is structured right, but also that the process to collect the data is structured properly. For example, if you only collect data online, you’re not going to be representative of the whole community because not all participants interact online. Sharing data across agencies is also important, since cities and counties sharing data with states, who then share data at the federal level, creates a snowball effect where grassroots data can affect broader policy decisions.
Lorenzen: How do you think governance can work to address data biases and create more inclusive and equitable outcomes?
Dr. Blaine: The repercussions from inequitable practices like redlining still have ramifications today. One of the projects that I worked on took the original 1930s redlining map of Jackson, Mississippi, and then correlated that map to disparities in the community. You could actually see the legacy of those policies and how they’ve affected communities today.
I don’t think that Jackson is unique in that situation. There are many communities that suffer from the legacies of unjust policies. Cities must be able to identify the roots of these problems, then demonstrate through the data their impact on the community, in order to build a discrete set of remedies that can solve some of those challenges.
Grossi: We need to be innovative about data collection through community outreach to verify that the data matches the lived experience of people, because a lot of times it doesn’t. So we need to think about how we can bring a community lens to the data, and then make sure we structure and collect it in an equitable way.
Abazajian: City data can’t be used alone. We have to get out of our comfort zones a little bit and speak to folks who actually understand what the lived experience is. Combining community data with city data is a great way to understand those legacies and the context around how data is collected. I think so many cities fall into the trap of wanting to take a tech product out the door and launch something using this really powerful data, but not realizing that it requires building all these relationships.
Lorenzen: How can governments address problems around data silos?
Abazajian: Most people at the city and federal levels will agree that government needs a culture shift around collaborative data. There are the obvious technical challenges, but there are also a lot of social and political challenges to integrating data comprehensively. A lot of departments are used to working in their own lanes and haven’t mentally transitioned to a digital system of administration. We need to align our values across government departments, agencies and community organizations, because it’s still a challenge of getting everyone to buy into the concept of cooperative data governance.
Dr. Blaine: The ideas of data governance and data sharing agreements can be a real challenge. At the beginning of the pandemic, I was running our COVID-19 response team, and we were trying to create a data-sharing agreement with the state health department so that we could get census data about how infections were moving across the city. It took us four months to get a data-sharing agreement signed, just so that we could start tracking how the pandemic was affecting the community and micro-target how we were providing interventions. Four months in the scope of a pandemic is an incredibly long time.
We need integrated systems, not only between separate entities like local and state governments, but also between agencies and departments within the same local government, so that we can understand what’s happening in various facets of the community in real-time.
Lorenzen: What else do you think communities need to know about data governance?
Grossi: One important data source many agencies are sitting on is production data, the data that already lives in city administration systems. They may not be utilizing it at all, yet it has the potential to contain simple, accessible data points that can lead to immediate, direct action and change. By analyzing production data, even on simple points like permit applications over time or failed inspections in a specific area, agencies can start to get some insights. Then they can layer in other data, like GIS or qualitative data, to develop a broader and deeper analysis.
Dr. Blaine: We don’t need to underestimate our audience. Oftentimes there’s the perception that the community either is not interested in the data or would not be able to understand what the data is telling them. Yet citizens are experts in their lived environment and experience. So when we start to show data that validates their lived experience, and then use that data in transformative ways that include communities in the process, we can build a shared understanding of the importance of data and how it can be used to create solutions.
Abazajian: It’s important to start from the need and work from there. The real impact that data can have on people’s lives comes from what feels like working backwards, by starting with understanding what the needs are, putting in the time early on to do the research, and getting into the community to understand the issue that you’re hoping this data will address from the ground up.
