Using Data to Bring Clean Sweeps Where They're Needed Most.

Use Case: Blight and Neighborhood Improvement Products: BuildingBlocks, Slate, and PubliCity City Size: ~280,000 residents, Western New York

The Challenge

Buffalo's Operation Clean Sweep Initiative has been running since Mayor Byron Brown's first term, bringing together city departments, community organizations, health and human services providers, and volunteers to address blight, code enforcement, and quality of life in neighborhoods across all nine council districts. Over six months each year, on a rotating weekly basis, teams move through targeted neighborhoods boarding up abandoned structures, removing graffiti and debris, enforcing code violations, trimming trees, and going door to door connecting residents with government, employment, and health services.

The program had genuine momentum and broad community support. What it didn't have, for years, was a principled way to decide where to go.

In the early years, Clean Sweep areas were chosen largely based on input from Common Council members, each representing their district's priorities. That approach let elected officials advocate for their communities, but it left the program open to criticism about subjectivity. The city later added demographic and socioeconomic data from the American Community Survey, but those factors tended to point to the same blocks year after year. Poverty rates and vacancy rates change slowly. The on-the-ground conditions that Clean Sweeps are designed to address, blight complaints, crime, code violations, change daily and vary block to block.

Oswaldo Mestre, Executive Director of Citizen Services and Senior Advisor to the Mayor, put it plainly: "We listen to our residents and respond back. We need to have more of a data-driven approach to how we do clean sweeps."

What Buffalo Built

In 2017, Buffalo won funding from the New York State Attorney General's Cities RISE program, which provided $8 million in grants to cities addressing blighted and vacant properties through data-driven approaches. All Cities RISE participants were connected to Tolemi's BuildingBlocks platform, and Buffalo became one of the program's most expansive implementations.

Working with Tolemi, the Citizen Services Department, the Buffalo Urban Renewal Agency, and the Department of Management Information Systems integrated nearly 50 datasets from over 12 city systems into BuildingBlocks: 311 complaints, police and fire calls, tax delinquency, foreclosures, utility payments and shutoffs, building permits, property sales, and more, updated nightly across all 97,265 parcels in the city. BuildingBlocks automatically derived additional insights from that data, including LLC ownership patterns, vacancy indicators, owner occupancy status, and fix-and-flip activity.

From there, the Citizen Services team used BuildingBlocks' Score Manager to build a Clean Sweep score that could drive the annual selection of neighborhoods and determine the specific mix of services each area needed. The score weighed 311 calls, police incidents, code violations, and tax delinquency as indicators of distress, while also incorporating property sales prices, fix-and-flips, and building permits to monitor for signs of neighborhood change that might indicate risk of displacement. Those property-level signals were combined with housing cost burden, poverty levels, and unemployment data from the Census Bureau to produce a final prioritization score.

The result was a process where data, rather than political input alone, drove the selection of where Clean Sweeps went and what resources they brought. As Michael T. A. Smith, Save Our Streets Program Coordinator, described it: "When you're using the data to find out where the needs are most, then you can use that data to tell what services you need to bring into that community. If there's one area with a lot of housing issues, then you're going to make sure you bring those housing partners."

What It's Achieved

The shift to data-driven neighborhood selection changed not just where Clean Sweeps happened but how the city could talk about them. Mestre put it this way: "The data helps us know something's going on. When people say, 'This was the best Clean Sweep ever,' I think, 'Yeah, the data told me to go here.' And then the people in the community said, 'What took you so long?'"

The Bloomberg Harvard City Leadership Initiative, in partnership with Citizen Services, used BuildingBlocks data to study the impact of Clean Sweeps on resident behavior across blocks that had received them from 2009 to 2021. Matching each treated property cluster against comparable untreated clusters, the research found that properties where Clean Sweeps had occurred were more likely to generate reports of drug-related crime and physical environment service needs in subsequent periods, suggesting that residents in those neighborhoods were more willing to engage with city services and report issues rather than simply endure them. It was evidence that the program was building trust, not just cleaning streets.

The operational reach of the engagement extended well beyond clean sweeps. The real estate disposition team built out full property sale workflows in Slate covering multiple program types including yard sales, residential infill, capital assets, and development parcels, replacing a process that had been managed through spreadsheets and manual correspondence. PubliCity gave residents and developers public access to the city's available land inventory for the first time, making it possible to browse and apply for city-owned properties online rather than filing public records requests.

Mayor Brown captured the spirit of the broader work: "Our clean sweeps are another example of the strong partnerships underway in our community, between our city departments, our residents, community-based organizations, non-profits, for-profits organizations, and our partners in other levels of government. All working together to make a difference in our community."

Why Buffalo's Approach Stands Out

Buffalo used data not to replace the human judgment that makes Clean Sweeps effective, but to ground it. The score didn't tell the city which neighborhoods deserved help. It helped the city make the case, defend the selection, measure the results, and direct the right mix of resources to the right places. That's a more honest and more powerful use of data than most cities manage.

The broader platform build, connecting housing conditions, code enforcement, property sales, public health indicators, and real estate disposition into a shared data environment, positions Buffalo to keep asking better questions about where to invest and whether it's working.