New York city’s 311 non emergency call system sees an incredible amount of traffic every year. In 2017, the number of 311 contacts set its 4th consecutive annual record with nearly 40 million requests, surpassing 2016 by 11% (nyc.gov). With such a large volume of traffic, it is important for the government to be able to not only address requests efficiently, but allocate appropriate resources as well. With this in mind, we pose the following topic question in analyzing the dataset:
Topic Question: What suggestions can we make to improve the resolution efficiency of 311 service requests in New York?
Improved government services can do a lot for improving the daily life of New Yorkers. In this report we show that the structure of the 311 service complaints/ requests is a criterion develop a unique profile of the local city, thereby serving as an efficient and low-cost decision system for relevant city stakeholders. We will be analyzing two factors in particular to assist 311 service.
- How can we accommodate the needs of people from different zip codes?
- Can we use time series analysis to make predictions on call volume?
By answering these questions, we hope that 311-services can optimize their services to improve the health and welfare of NYC residents.
Github repo: https://github.com/spmuppar/The-Data-Open-Citadel