Here’s what London can learn from New York’s data-driven approach to smart cities

FDNY firefighters extinguish a fire after an explosion caused a building in Harlem to collapse in March 2014. Image: Getty.

How should London go about becoming a smart city? As the capital seeks to meet record demand on its infrastructure and public services, it’s a question that has been occupying the minds of City Hall, policymakers, academics and industry alike.

Some believe London should emulate the technology-led approach of cities like Rio de Janeiro, with its network of urban sensors and NASA-style operations centre. Today, in a report for the Capital City Foundation, I argue a better starting point would be to learn from the comparatively low-tech, but data-driven, methods of New York City.

The Mayor’s Office of Data Analytics

Michael Bloomberg made his fortune providing data analytics for the financial sector. So when he became New York mayor, he wanted to prove that data could benefit cities, too. To that end, he created the Mayor’s Office of Data Analytics (MODA), a small team of data analysts who can combine, interrogate and seek insights from data sourced from public sector organisations across the entire city.

MODA has applied its data expertise to improve the efficiency of public services, predict problems and prevent them from arising, target the city’s resources more effectively, boost economic growth and support tax enforcement.

To illustrate the benefits of such an approach, consider how it worked with the New York Fire Department. Every year, FDNY inspects more than 25,000 buildings it believes may be at risk of future fires. It used to prioritise buildings for inspection based on a list of criteria created by fire fighters themselves. As MODA’s first director, Mike Flowers, has put it:

“Veteran fire fighters know what dangerous buildings look like. They know how important it is for a building to have an operable sprinkler system, the impact that the improved building and fire codes have had over centuries of construction, and what type of business activity is most frequently correlated with dangerous fires.”

MODA worked with FDNY to see if data could be used to strengthen fire fighters’ natural intuition. By analysing data from past fires, they were able to create a much more accurate prediction model.

The results are highlighted below. On the left is a map showing the results of the original fire prediction model. The map in the centre shows the predicted location of fires according to MODA’s analysis. On the far right is where past fires had actually occurred. The contrast is striking. Whereas the old model failed to identify high-risk zones in areas such as Harlem, Downtown Manhattan and the Rockaways, the new model very closely reflected reality.

Location of fires as predicted before and after the use of MODA’s model. Source: NYC Mayor’s Office of Data Analytics, Annual Report, 2013

Prior to applying MODA’s analysis, the first 25 per cent of FDNY inspections typically resulted in 21 per cent of the most dangerous buildings being discovered. Using their prediction algorithm, the first 25 per cent of inspections now result in more than 70 per cent being discovered. The use of data has dramatically reduced the number of days that New Yorkers are at serious risk.

A MODA for London?

Like New York, London has numerous public sector organisations operating across the capital, not to mention the 32 boroughs and the City of London. Each is guardian of its own data: in very few cases is this information joined up and acted upon. Remarkably, even City Hall does not systematically collect data from London boroughs, except for that required for statutory purposes, such as population and school place statistics.

If London is to meet the needs of its 8.6m residents, London cannot continue to act as 33 separate islands. Instead, the city needs its own MODA team, led by a chief analytics officer reporting directly to the mayor.

Today’s report outlines how, by combining and analysing data from different public sector organisations (and indeed private sector firms such as mobile phone operators), a London MODA could tackle diverse problems. Dealing with “beds in sheds” (that is, illegally converted outbuildings); improving food safety inspections; identifying empty homes; helping new businesses decide where to set up shop, and fighting tax and benefits fraud. The list of potential applications is essentially limitless.

The fact is that all cities are flooded with data – but by itself, data is of little value. To have an impact, it needs to be joined up. It requires people with the time, skills and resources to interpret it and act upon it.

Currently, few of those things are in place in the capital. If London is serious about becoming a smart city, before it rushes to add new technology that would give it even more data, it must first make sure it has the ability to use what it already has.

Eddie Copeland is the head of technology policy at Policy Exchange. He tweets as @EddieACopeland.

His full report, “Big Data in the Big Apple”, is available here.

 
 
 
 

Urgently needed: Timely, more detailed standardized data on US evictions

Graffiti asking for rent forgiveness is seen on a wall on La Brea Ave amid the Covid-19 pandemic in Los Angeles, California. (Valerie Macon/AFP via Getty Images)

Last week the Eviction Lab, a team of eviction and housing policy researchers at Princeton University, released a new dashboard that provides timely, city-level US eviction data for use in monitoring eviction spikes and other trends as Covid restrictions ease. 

In 2018, Eviction Lab released the first national database of evictions in the US. The nationwide data are granular, going down to the level of a few city blocks in some places, but lagged by several years, so their use is more geared toward understanding the scope of the problem across the US, rather than making timely decisions to help city residents now. 

Eviction Lab’s new Eviction Tracking System, however, provides weekly updates on evictions by city and compares them to baseline data from past years. The researchers hope that the timeliness of this new data will allow for quicker action in the event that the US begins to see a wave of evictions once Covid eviction moratoriums are phased out.

But, due to a lack of standardization in eviction filings across the US, the Eviction Tracking System is currently available for only 11 cities, leaving many more places facing a high risk of eviction spikes out of the loop.

Each city included in the Eviction Tracking System shows rolling weekly and monthly eviction filing counts. A percent change is calculated by comparing current eviction filings to baseline eviction filings for a quick look at whether a city might be experiencing an uptick.

Timely US eviction data for a handful of cities is now available from the Eviction Lab. (Courtesy Eviction Lab)

The tracking system also provides a more detailed report on each city’s Covid eviction moratorium efforts and more granular geographic and demographic information on the city’s evictions.

Click to the above image to see a city-level eviction map, in this case for Pittsburgh. (Courtesy Eviction Lab)

As part of their Covid Resource, the Eviction Lab together with Columbia Law School professor Emily Benfer also compiled a scorecard for each US state that ranks Covid-related tenant protection measures. A total of 15 of the 50 US states plus Washington DC received a score of zero because those states provided little if any protections.

CityMetric talked with Peter Hepburn, an assistant professor at Rutgers who just finished a two-year postdoc at the Eviction Lab, and Jeff Reichman, principal at the data science research firm January Advisors, about the struggles involved in collecting and analysing eviction data across the US.

Perhaps the most notable hurdle both researchers addressed is that there’s no standardized reporting of evictions across jurisdictions. Most evictions are reported to county-level governments, however what “reporting” means differs among and even within each county. 

In Texas, evictions go through the Justice of the Peace Courts. In Virginia they’re processed by General District Courts. Judges in Milwaukee are sealing more eviction case documents that come through their courtroom. In Austin, Pittsburgh and Richmond, eviction addresses aren’t available online but ZIP codes are. In Denver you have to pay about $7 to access a single eviction filing. In Alabama*, it’s $10 per eviction filing. 

Once the filings are acquired, the next barrier is normalizing them. While some jurisdictions share reporting systems, many have different fields and formats. Some are digital, but many are images of text or handwritten documents that require optical character recognition programs and natural language processors in order to translate them into data. That, or the filings would have to be processed by hand. 

“There's not enough interns in the world to do that work,” says Hepburn.


Aggregating data from all of these sources and normalizing them requires knowledge of the nuances in each jurisdiction. “It would be nice if, for every region, we were looking for the exact same things,” says Reichman. “Instead, depending on the vendor that they use, and depending on how the data is made available, it's a puzzle for each one.”

In December of 2019, US Senators Michael Bennet of Colorado and Rob Portman of Ohio introduced a bill that would set up state and local grants aimed at reducing low-income evictions. Included in the bill is a measure to enhance data collection. Hepburn is hopeful that the bill could one day mean an easier job for those trying to analyse eviction data.

That said, Hepburn and Reichman caution against the public release of granular eviction data. 

“In a lot of cases, what this gets used for is for tenant screening services,” says Hepburn. “There are companies that go and collect these data and make them available to landlords to try to check and see if their potential tenants have been previously evicted, or even just filed against for eviction, without any sort of judgement.”

According to research by Eviction Lab principal Matthew Desmond and Tracey Shollenberger, who is now vice president of science at Harvard’s Center for Policing Equity, residents who have been evicted or even just filed against for eviction often have a much harder time finding equal-quality housing in the future. That coupled with evidence that evictions affect minority populations at disproportionate rates can lead to widening racial and economic gaps in neighborhoods.

While opening up raw data on evictions to the public would not be the best option, making timely, granular data available to researchers and government officials can improve the system’s ability to respond to potential eviction crises.

Data on current and historical evictions can help city officials spot trends in who is getting evicted and who is doing the evicting. It can help inform new housing policy and reform old housing policies that may put more vulnerable citizens at undue risk.

Hepburn says that the Eviction Lab is currently working, in part with the ACLU, on research that shows the extent to which Black renters are disproportionately affected by the eviction crisis.

More broadly, says Hepburn, better data can help provide some oversight for a system which is largely unregulated.

“It's the Wild West, right? There's no right to representation. Defendants have no right to counsel. They're on their own here,” says Hepburn. “I mean, this is people losing their homes, and they're being processed in bulk very quickly by the system that has very little oversight, and that we know very little about.”

A 2018 report by the Philadelphia Mayor’s Taskforce on Eviction Prevention and Response found that of Philadelphia’s 22,500 eviction cases in 2016, tenants had legal representation in only 9% of them.

Included in Hepburn’s eviction data wishlist is an additional ask, something that is rarely included in any of the filings that the Eviction Lab and January Advisors have been poring over for years. He wants to know the relationship between money owed and monthly rent.

“At the individual level, if you were found to owe $1,500, was that on an apartment that's $1,500 a month? Or was it an apartment that's $500 a month? Because that makes a big difference in the story you're telling about the nature of the crisis, right? If you're letting somebody get three months behind that's different than evicting them immediately once they fall behind,” Hepburn says.

Now that the Eviction Tracking System has been out for a week, Hepburn says one of the next steps is to start reaching out to state and local governments to see if they can garner interest in the project. While he’s not ready to name any names just yet, he says that they’re already involved in talks with some interested parties.

*Correction: This story initially misidentified a jurisdiction that charges $10 to access an eviction filing. It is the state of Alabama, not the city of Atlanta. Also, at the time of publication, Peter Hepburn was an assistant professor at Rutgers, not an associate professor.

Alexandra Kanik is a data reporter at CityMetric.