Using Data Analytics to Fight Homelessness in New York City
The power of estimation makes life a little simpler. Think about it: Your car provides a rough estimate of how much fuel is left in the tank so you don’t find yourself stranded in the middle of rush-hour traffic. On the golf course, you’ll regularly estimate the distance to the hole, allowing you to grab the right club from your bag.
While estimation can make road trips and a day on the green more enjoyable, it’s not necessarily the best fit for data analytics. Case in point: ZDNet recently highlighted New York City officials’ struggle to curb a growing homeless population. As the issue continues to intensify, New York City has come to come face-to-face with the very real limits of estimation.
Data Analytics for Enhanced Accuracy
ZDNet reports that best guesses have put the figure of homeless persons in New York City at around 62,000. Unfortunately, that’s about as useful as the data gets. The city has been relying on manual data collection within very siloed structures. The resulting data set ends up being inaccurate and isolated.
For example, a homeless person could be counted or surveyed in one part of the city on Monday, then counted again by a different official in another part of the city on Friday. Without a central data analytics platform, the two officials have no way of knowing they encountered the same homeless person — who is probably slightly annoyed with city officials continuing to ask them the same questions.
To solve this dilemma, Mayor Bill de Blasio and his team have deployed a more modern data analytics strategy. By using StreetSmart, a customer relationship management system for the homeless, city officials will be able to more efficiently collect and track accurate details surrounding the city’s homeless population. Better yet, thanks to its centralized nature, StreetSmart will seamlessly coordinate data from multiple agencies leading to a more accurate understanding of the problem.
The mayor hopes that this understanding will open new opportunities to reveal the answers the city seeks. If nothing else, cleaner data should lay a solid foundation for allocating current resources to the areas of the city — and the people — that need them most.