Report

Piloting the London Office of Data Analytics

29 Mar 2018
Description

What would happen if London could source, analyse and act upon its public sector data at a city scale?

This question formed the basis of a year long pilot of a London Office of Data Analytics (LODA), a collaboration between the GLA, Nesta, twelve London boroughs and ASI, a data science firm. In this report, we outline the pilot’s origins, methods and what we have learned to date.

The impetus for piloting LODA began with a recognition that on many issues, London’s public sector data is like a jigsaw that has never been put together. Every team has their little piece of the puzzle, but no one has the ability to put those pieces together, take a step back and see the big picture. Given the current pressure on public services, that fragmentation is a serious problem as it hinders many of the tried and tested ways of delivering more and better with less. How can boroughs intelligently design shared services if they don’t have data on the scale of the problem, demand or opportunity beyond their boundaries? How can they coordinate the actions of different teams if those teams don’t have data on what each other is doing? How can they target resources at areas of greatest need if they lack the data on where that need lies? And how can they predict and prevent problems from occurring if they don’t have the data that could collectively point to cases of highest risk?

Taking inspiration from the Mayor’s Office of Data Analytics (MODA) in New York City, the aim of LODA has been to overcome precisely these challenges by putting in place the technical, data and organisational resources to apply data science at a cross-borough level. To test the concept and see how it might work in the very different political and administrative setting of London, the pilot focused on identifying unlicensed HMOs – houses in multiple occupation. There are estimated to be up to 15,000 HMOs in some London boroughs1, yet only 10-20% are believed to be correctly licensed. Could data help local authority building inspectors find more of these properties?

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2018
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