Rather, "people" — a statistically representative group of avatars will help guide RPA's Fourth Regional Plan.

One of the major challenges in city planning is that the people doing the planning don't always look like the people inhabiting the city. That's especially true in metropolitan New York. Middle-aged white planners living and working in Manhattan with big salaries and short subway commutes experience the city in a way most residents just don't.

Planners often try to bridge this social divide by engaging with as many residents as possible through workshops and focus groups. The Regional Plan Association has done lots of those in recent months, as it begins to develop its fourth once-in-a-generation plan for metro New York, but it's also taking things a step further. RPA has created 10 profiles meant to represent — in a statistically true sense — the people who live in the region. The personas will serve as a sort of fictional oversight panel tasked with holding the plan accountable to its true mission.

"Every idea for the Fourth Regional Plan needs to address — or be highly relevant to — all 10 of them," says Rohit Aggarwala, co-chair of the fourth plan, who presented the profiles with Juliette Michaelson of RPA at an assembly in April. "Or else it's not a plan that serves the whole region."

RPA derived the profiles (or avatars, as they're called in-house) from the latest Census data. Geography was the overarching metric, followed by 13 separate statistics chosen to align the profiles with actual metro area demographics as closely as possible. Since only 8 percent of the region lives in Manhattan, for instance, only one avatar calls it home; and since Manhattan also has one of the area's largest white populations, that avatar also is white. And on down the list.

So from New York City we meet Jim from Manhattan (a white and wealthy tech entrepreneur), Ava from Brooklyn (a teenager whose household earns less than $30,000 a year), John from Queens (a Korean technician whose commute can take an hour), and Xavier in the Bronx (a Puerto Rican immigrant with a median-wage job, a wife, and three kids).

In New Jersey there's Treshia in East Orange (a 21-year-old living with her boyfriend who worries about managing rent in a neighborhood at risk of gentrification), Susan in Ocean County (a 61-year-old with a great job but a 90-minute commute and a bad mortgage), and Bill in Middlesex (a blue-collar retiree who can't afford to live in an assisted home).

There's also Alicia in Long Island (a high school grad who can't afford to move out of her parents' home), Clarissa in Connecticut (a Hispanic immigrant with a middle-income job), and Seth in the Hudson Valley (a black insurance broker who commutes into Manhattan).

Right now, says Michaelson, RPA planners are keeping the avatars in mind as they generate potential ideas. Pairing Treshia's profile with maps RPA is building on employment access, for instance, reveals that her boyfriend can reach very few jobs without a car or a high school education. That helps planners test out ways to address the problem of job access without pushing a solution that might lead to the couple's displacement — say, a better local bus system.

Once the plan is more fleshed out, the avatars could function as a kind of jury to evaluate the strength of a particular plan element. A subway expansion on Manhattan that only helps Jim, for example, might score lower than a tunnel under the Hudson that helps Jim as well as Treshia, Susan, and Bill. In a room full of planners who might best relate to the Jims of the world, that's a healthy check on the plan's vision.

"Planning for Jim is very easy," says Michaelson. "But it's really important to remember that Treshia is also one of 10 people, and she has a very, very different life."

The avatar system isn't a planning magic bullet. The very selection of the profiles, while based on hard data, has an element of artistry to it; the exact same statistics could easily lead to 10 different figures in other hands — most easily by removing geography as the base measure. Ten representatives may also be too few for a metro as immense as New York. There's no Staten Island avatar, for instance, but the borough will certainly have a say in the region's future.

A bigger problem facing RPA is how to reconcile the shifting nature of demographics in a region as dynamic as New York with the static format of a long-term plan. Take the figures on unemployment, which show that 36 percent of people in the region don't have a job, either because they're too old or can't find work. A commuter transport system planned from that data might prove insufficient if the region gets a big economic bump or an influx of young workers.

Shortcomings aside, Michaelson says the profiles have already helped RPA revise some common assumptions about the region. A surprisingly high share of residents live and work in the same county, she says, which suggests that New York might operate as less of a centralized hub-and-spoke commuter network than it's often viewed to be. Helping RPA look beyond conventional wisdom and treat the whole region equally is precisely the point.

"In the 1920s, a bunch of people just got into a room and drew lines on maps, and Robert Moses came around and took the plan and built it," says Michaelson. "That's obviously not the model anymore."

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