Using Big Data and Applied Microeconometrics to Improve Policy: Trees and Sidewalks Program

The NYC Department of Parks & Recreation’s (DPR) Trees & Sidewalks (T&S) program repairs tree-related sidewalk damage to reduce risks posed by street trees in the city. The Capstone team was asked to evaluate how this program could achieve its objectives more efficiently and proactively, given its limited budget.

After an assessment of the T&S program protocols and available data, it became apparent that the quality of data could not support the quantitative analysis necessary to respond to DPR’s initial questions. Instead, the project was recalibrated to address the program’s data management process, the protocol for assigning sidewalk repairs, and the backlog of repairs that was growing systematically. The team identified a number of key issues, such as non-standardized data input, poor management of successive requests for repair, inspector scoring bias, and discretionary prioritization of repair work. Additional interviews further revealed that DPR does not have complete information on which sites have been repaired to date, which is crucial for improving budget allocation and efficiency going forward.

Based on the analysis of the T&S program, the team came up with a number of recommendations that focus mostly on improving data management, revising specific protocols, and increasing transparency. A key recommendation of the team centers on which factors should be included in determining the assignment of repairs among the many sites with damaged sidewalks. The team also recommended establishing a monitoring system to enable the central office to supervise the processes that take place at the borough and community district level.

With the implementation of the recommendations, DPR will be able to improve their data management practices and with that be able to use their process’s information to constantly improve their service delivery and ensure that budgets and resources are utilized in the most efficient, value-maximizing way.