These Standardized Metrics Will Help Cities Measure Their Post-Pandemic Recovery

Nextcity.org
April 1, 2020
Gregory Scruggs

When Ontario Premier Doug Ford included construction sites on the list of non-essential workplaces he closed last week as part of the province’s effort to stem the coronavirus pandemic, he singled out Mackenzie Vaughan Hospital as one ongoing project that should nevertheless remain an active job site.

The state-of-the-art medical facility slated to come online later this year in Vaughan, a city of 335,000 just north of Toronto, couldn’t be ready a moment too soon as the greater Toronto area braces for a surge in patients. But the hospital project is no Chinese-style rapid response to the coronavirus, like the Wuhan emergency hospital built in 10 days. Rather, Mackenzie Vaughan owes its existence in part to a wonky but vital dataset: the ISO 37120 standard for city indicators.

In January 2015, University of Toronto professor Patricia McCarney met Vaughan Mayor Maurizio Bevilacqua for coffee at City Hall. The Ontario city is one of the “boomburbs” perched just north of Canada’s largest city that has quickly gone from rural outpost to suburban enclave to small city in its own right.

McCarney directs the university’s Global Cities Institute and runs the World Council on City Data, a non-profit on a mission to convince cities that they should standardize their data collection. Vaughan’s rapid evolution into full-fledged city -- it incorporated only in 1991 -- made Bevilacqua eager to participate in ISO 37120, the council’s flagship initiative.

The International Standards Organization, or ISO, sets global standards on thousands of industrial goods like lightbulbs, tractor parts, and elevators. A certain wattage lightbulb made in Mexico should meet the same standards as a similar lightbulb made in Morocco. Under ISO 37120, participating cities agree to standardized definitions and data-collection methods for 104 different urban indicators, from how much solid waste is recycled to the number of women who serve in city government.

At their coffee date five years ago, McCarney ran through the numbers in the council’s Open Data Portal with Bevilacqua. As she recalls, the mayor nodded approvingly at strong marks for foreign-born population, degree of higher education, and high school completion rates. But he stopped in his tracks at the health care indicators. For the number of hospital beds per 100,000 residents, Vaughan came in dead last among 100 cities in 39 countries.

“You reported zero,” McCarney recalls telling the mayor. The number was true, because the young but fast-growing city relied on a hospital in a neighboring city. What’s more, even for similarly sized cities, Vaughan was a laggard for not having any hospital beds.

Vaughan had broken ground on the 350-bed hospital in July 2014, but fundraising was far from complete. The sense that Vaughan lagged behind its peer cities -- not just in Canada but even in sub-Saharan Africa -- has galvanized CAD$162 million in donations thus far.

“Cities brag about their best data points, but if there’s a gap, they can also use them to leverage funding,” McCarney says.

This kind of data-driven success story is vindication for McCarney, who has been making the case that cities need reliable, easy-to-compare data for more than three decades. As a PhD student at MIT in the late 1980s, she recalls cobbling together over a dozen footnotes to prepare a single table comparing water, housing, and sanitation data for four African cities. That same haphazard data collection plagued her time at the World Bank’s Africa Technical Infrastructure Division in the early 1990s. While national-level data offered reliable measures of GDP, for example, cities simply had no key performance indicators or management data.

“It felt very normal and nobody was really surprised,” she says. “It was just accepted as fact that there was very little data and it certainly wasn’t comparable.”

But such resignation was problematic as the multilateral bank wrote checks for major infrastructure projects. “At that time, the bank was spending a lot of money but it wasn’t guided by data that was high caliber or comparable across cities even in the same country,” she says.

McCarney continued to dwell on this problem after she left the bank in 1993 and began teaching at the University of Toronto. In 2008, the World Bank funded McCarney and fellow Canadian urban data specialist Helen Ng to recruit nine cities around the world and inventory all of the different metrics that they tracked: Belo Horizonte, Bogotá, Cali, King County (metropolitan Seattle), Montréal, Porto Alegre, Toronto, and Vancouver.

The nine cities collected 1,100 indicators between them. Only two were comparable across all nine. Homicides, for example. “There’s not a lot of gray area there,” McCarney says.

But for countless other categories, McCarney describes gray areas galore. When counting firefighters, does that include volunteer or only full-time equivalent on payroll? When measuring emergency response times, does a city track from the moment a 911 call is placed or the time from ambulance dispatch?

McCarney and Ng began working with the cities to harmonize their differing measurements, hashing out how to define a business or a police officer in order to accurately count those categories. The pilot evolved into something called the Global City Indicators Facility, which at its peak collected roughly 100 consistent indicators from 255 cities in 82 countries who voluntarily submitted their data sets. “We built definitions, methodologies, numerators, and denominators,” McCarney says. “These are pretty low-hanging fruit so that Aleppo and Nairobi can measure the same way as Toronto, London, or Chicago.”

Both the World Bank and the Standards Council of Canada encouraged the duo to take their project to the ISO -- it was already a draft global standard by their estimation. So the pair pitched the Geneva-based body in 2012. “They were not that interested,” McCarney recalls. “They had never thought about cities and certainly never thought about standardized city data.”

Ultimately, the ISO is in the business of selling the standards that it approves. “It just didn’t seem like a hot item,” McCarney says. “Cities weren’t on their radar.”

The Toronto city data nerds didn’t lose hope. The ISO had recently branched out from industrial products and approved standards for environmental management systems, so they felt it was only a matter of time. Sure enough, the ISO called back a few months later after a Japanese standards body inquired about standardized urban infrastructure metrics for technical components like pipe sizes and a French standards body sought standardized measurements for tracking business improvement districts. There was, in fact, a market for city data.

That same year, the ISO formally approved a working group for McCarney and Ng to translate their city indicators into standards up to international snuff. Although ISO standards normally take up to seven years, the robustness of the Global City Indicators Facility was sufficient to grant fast-tracked status. The negotiations were at times painstaking -- for example, wrangling for hours with standards experts from a dozen countries over whether PM2.5 or PM10 should be the particulate matter standard for measuring air quality -- but McCarney and Ng shepherded their baby to a July 3, 2014 birthday, when ISO 37120 was born as the first international standard for city data.

McCarney and Ng formed the World Council on City Data that same year as a non-profit to succeed the Global City Indicators Facility and promote the new family of ISO standards, from preparing analytics to running workshops on the nuts and bolts of ISO-approved city data. While the council actively recruits cities to apply for the standard and advises them on what kind of evidence they will need to back up their datasets, a third-party auditor independently vets each city’s data annually to ensure it meets ISO standards. The council invited 20 founding cities at no cost in order to kickstart global adoption of the ISO standard. They include obvious global cities like London, Toronto, and Shanghai, but also more obscure choices like Minna, Nigeria; Haiphong, Vietnam; and Makati, Philippines.

“This has to be something that cities of any size, income, and level of development can do,” says the council’s vice-president, James Patava. “Sure, London, Shanghai, and Los Angeles can do this but what about people with zero data infrastructure? That’s why, say, Minna matters.”

Since the launch of ISO 37120, the international body has approved two more sets of standards: ISO 37122 indicators for smart cities and ISO 37123 indicators for resilient cities.

Together, the family of city data standards could prove invaluable for charting post-pandemic recovery and researching why certain cities fared better or worse. For example, there is already data on number of nurses and hospital beds, as well as life expectancy and age cohorts. Milan, one of the global epicenters of the pandemic, is one of the most aged cities in the world, with 1 in 4 residents over 65.

“That cohort data could be really useful as a framework for better modeling profiles of where the epidemic can spike faster than other places,” McCarney said.

The potential utility goes far beyond health care stats. “Anecdotally, a lot of our cities are expressing significant appreciation that they’ve been collecting this data because it’s going to allow them to understand where things shifted,” Patava says. “For example, having a standardized definition of number of businesses per 100,000 will allow for a really deep understanding of how [a city] can get back to full operation.”

With the Open Data Portal collecting a range of indicators relevant to recovery like number of visitor stays to chart tourism rebounding, graduation rates to see if education services are back to normal, and even debt service ratios and capital spending as measurements of cities’ fiscal health, the cities who already participate now have a valuable baseline of what typical operations look like. Those metrics, in turn, will make them more accountable to residents eager for a return to normal -- or at least an adjustment to a new reality.

“Citizens want understandable answers to how the numbers have changed,” Patava says.