Syracuse, New York, USA
In Syracuse, Data Delivers Efficient, Effective and Equitable Services.
Project Type:
Equity, Finance, High-Performing Government, Housing, Infrastructure
2023 Gold Certification
Several years ago the City of Syracuse teamed up with the Syracuse Metropolitan Transportation Council (SMTC) to create a data-driven prioritization for road reconstruction. This year, the City and SMTC introduced an equity component to the priority scoring process to ensure that the City does not overlook roads in historically underserved neighborhoods. Inspired by equity score systems in other cities, the City created a metric to measure the amount of historically underserved residents in an area. The new model considers the equity score as well as road conditions when recommending reconstruction projects for the year. In this way, the City avoided completely reinventing the reconstruction priority process while introducing equity as an additional factor.
2021 Silver Certification
Compiled data from GPS units in each snowplow, allowing the city to create and publish an interactive map for residents to determine if a street was already plowed and allowing city staff to quickly identify any streets a snowplow may have missed on its run.
Created a database mapping sidewalks and walkways in 164 parks in order to improve its approach to snow removal, empowering the city to lower the average time to clear paths of snow from 3 days to 6 hours.
Gave city departments centralized access to budgeted and actual financial data, allowing staff to better predict funding needs and allocate resources. Analysis from this data saved the city an estimated $800,000 on salt used for de-icing.
Determined locations for new affordable housing construction by gathering and analyzing quantitative data on the locations of vacant properties and qualitative data from 800 resident interviews.
The Snowiest City
Syracuse, New York is seriously snowy. Averaging more than 120 inches of snowfall each year, it’s officially the country’s snowiest city. Throughout each long winter, staff in the Department of Public Works (DPW) work to keep roads and sidewalks clear and safe so residents can keep moving. Until a few years ago, Syracuse’s snow removal services were challenged, resources were limited, and many residents weren’t happy.
“I used to want to avoid Facebook every time we had a storm,” says Corey Dunham, the City’s chief operating officer. “There were just too many friends and family complaining about the snow on their streets!”
When Mayor Ben Walsh took office in 2018, he was determined to take a new data-driven approach to tackle persistent problems facing Syracuse residents. Whatever the problem in Syracuse today, a first step toward designing a solution is to dig into data. “You can’t fix what you don’t fully understand,” Mayor Walsh said in his 2019 State of the City address. Data helps the City understand the causes of problems and address them, he added.
With clear support from the Mayor’s Office, city staff have worked in recent years to build foundational data practices including general management, performance & analytics, and open data to improve the delivery of city services like snow removal. The aim is to deliver efficient, effective, and equitable services — a goal that has become core to Walsh’s administration.
“We’re not data-driven for the sake of being data-driven. Data empowers us to know if we’re being effective or not, and then pivot when we need to change.”
Deputy Mayor Sharon Owens admits she was once a “data nonbeliever.” Now she has the passion of a convert. “Being able to use data to hone in on quality-of-life issues is crucial,” Owens says. “We spend too much time sending out a wide net when we should be honing in. Residents are impacted by our ability to take data and use it to solve the problems they care about.”
Plowing Through Data
The Parks Department and DPW’s effort to overhaul how they prioritize clearing snow from roads and sidewalks shows how data can translate into better and more transparent city services.
During snow events, the DPW snow plows move into action. The department follows a system of prioritizing city streets for snow removal: the first priority is always emergency routes, followed by hills around the city and roads with significantly higher levels of traffic. Flatter city streets generally found in residential neighborhoods come next.
The City compiled data from GPS units in each snowplow to create and publish an interactive map on the City website, enabling residents and property owners to track the path of snowplows during storms to determine if a street was already plowed. The map includes timestamps of a plow’s most recent pass of a street. The data also equipped the DPW staff to more quickly and accurately identify any streets a snowplow may have missed on its run.
To improve sidewalk snow clearance, the City took a similar approach. Working with the Syracuse Metropolitan Transportation Council, a team of DPW staff members and transportation planners first mapped foot traffic, building a dataset detailing which sidewalks are used most frequently and which are adjacent to the most dangerous streets. Again, data analysis showed the obvious snow removal strategy.
“We determined the most dangerous streets for pedestrians and cleared sidewalks in those areas first. Using data, we were able to make and defend decisions about why we chose to clear certain streets and sidewalks over others.”
The Department of Parks, Recreation and Youth Programs also dug into data to improve its approach to snow removal. The first step was mapping all the sidewalks and walkways in Syracuse’s 164 parks it is responsible for — 13 miles total, the department learned. Previously it would take three days after a major snow event to clear all sidewalks and walkways. After creating a color-coded map making priority routes clear — and buying two Bobcat L28 machines enabling a sidewalk to be cleared in just one pass — the department now clears them in just six hours.
Syracuse officials have also used more data-driven budgeting practices to save money on road de-icing materials. Previously, each department across the city was managing its own financials and budgeting from budget-to-budget, instead of actuals-to-budget. By centralizing the budget planning process and providing actuals to departments, Syracuse was able to make better spending decisions. This approach allowed DPW to analyze data for how much salt it purchased each year for de-icing and how much salt it actually used. The ultimate outcome: officials were able to better predict how much salt they needed to buy. Last year, the data-driven effort helped the city save an estimated $800,000 on salt purchases.
More Results to Come
Syracuse’s efforts to strengthen its data culture and practices have yielded benefits beyond snow removal. The City has also used data-driven problem-solving skills to address more complex challenges, such as poverty, inequities highlighted by the COVID-19 pandemic, and neighborhood revitalization efforts.
Looking ahead, exciting things are in the works — all fueled by the data capacity Syracuse has built. Later this month, the City plans on unveiling a brand-new resident information system revamping its city service request system into a more comprehensive and user-friendly portal.
And by the end of the year, Syracuse will build the first 25 of 200 one- and two-family housing units through the new Resurgent Neighborhood Initiative (RNI). The program supports city neighborhood planning and revitalization at the block level. Affordable housing construction locations were chosen by analyzing quantitative data detailing the locations of vacant and unused properties, and gathering qualitative data through 800 resident interviews conducted over eight months. This stakeholder engagement helps ensure equity, so the City can better deliver on the promise of affordable housing.
“Whether the challenge is housing, a pandemic, or snow removal, being a data-driven city means efficiently, effectively, and equitably delivering services that taxpayers pay for,” Mayor Walsh says. “This is the nuts and bolts of local government.”