Data Analytics and the Fight against Housing Blight

A Guide for Local Leaders

April 3, 2017

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Authors: Bradley Pough and Qian Wan

As cities across the country struggle through tumultuous economic and demographic changes, many find themselves asking the same hard question: How do we prevent our housing stock from falling into further disrepair? This question cuts to the very core of what it means to be a city, as housing blight depresses much of our communities’ financial, demographic, and economic fortunes. Fortunately, several cities like New Orleans and Detroit have developed a set of answers to this vexing question as they have turned to digital technology and the promise of big data to offer potential solutions to the challenges of housing blight. Now, other cities are looking to replicate their success, hoping to find in their own data the answers to their housing woes.

This paper will serve as a guide for cities interested in employing data analytics as a way to combat housing blight. Relying on multiple case studies as well as interviews with experts in the field, this report provides local decisionmakers with a set of recommendations for how they can develop a data solution tailored to their local needs. Part I introduces the reader to the issue of blight and discusses why it has proven so vexing for so many cities. Part II describes the role data can play in helping to target housing blight, and introduces the various case studies from which this paper pulls its recommendations. Part III closes with a set of five action steps that cities interested in developing a blight-targeting data solution can follow to get their project off the ground.

This is a working paper of the Responsive Communities project produced by Harvard Law Student Bradley Pough and Harvard School of Engineering and Applied Sciences Student Qian Wan. This paper is a product of the students' work in the HLS Responsive Communities Lab course, co-led by Susan Crawford and Waide Warner.

Last updated

August 25, 2017