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 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.
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.