Why My Cost-Adjusted Livability Index for Cities Is Wrong

By Professor Pinch  MAR 20, 2012 9:05 AM

There are plenty of things my index doesn't take into account when you think about what makes a good city.


My last article was a take on the Economist Intelligence Unit's Livability Index, which ranked 140 cities across a variety of dimensions to see which city ranks as the best city to live in. The EIU ranked Melbourne, Australia, as the most livable city, while I came up with a different ranking that had Atlanta at the top (See Can an Index Determine the Factors That Make a City 'Livable'?).

But even I said I thought the result was wrong and I was going to talk about why I thought so. It's not that I thought I did a bad job putting my index together, but there are plenty of things my index doesn't take into account when you think about what makes a good city. It's not just one set of factors, or two. Livability is determined by combining as many dimensions as possible to reach that conclusion.

What am I talking about? Well, take a look at some of the other entrants into the Best City Contest put on by BuzzData and the EIU. Since the EIU's original ranking had a number of English-speaking cities at the top of the list, some of the entrants developed applications where you could select the best city based on language. After all, what's the point in moving to Vancouver or Atlanta or Sydney if the only thing you speak is Swahili? Others looked at a variety of factors like physical distance between cities and interactions of various languages and cultures.

And yet, there are some data sets none of them incorporated into their livability benchmarks that would have been great to use. Personally, I think data about tax rates and municipal expenditures would've been a great addition. But some of the cities may not have had that kind of information, which brings up bigger questions about their governance and the accountability of municipal governments in those countries.

Another facet of city living that didn't get a lot of attention was the study of commuting patterns and traffic flows between a city's suburbs. Consider this snippet about Atlanta traffic from the US Census:

From 1970-2000, one of the biggest changes in the worker flow patterns in Atlanta has been the huge increase in the number and percent of workers commuting between suburban residence and suburban place of work. More than half of the commuting flows are from the suburbs to the suburbs.

This flow issue shouldn't be underestimated. Since most public transit systems were designed to facilitate commutes from the suburbs into downtown districts, the suburb-to-suburb flow was completely overlooked. Suburbs built bigger and bigger highways to deal with the flow in the forms of interstate beltways, intercounty connectors, and toll roads. In short, they were built around connecting cars, not people. And then came the look-alike shopping centers and chain restaurants, blended and laid out in one long, never-ending stretch of banality. It's not a commute. It's surviving a gauntlet of drabness.

But let's get back to the creation of livability benchmarks for a second. If you sit and think about it, the number of data points you could incorporate into a livability index are endless. And those endless possibilities are both a blessing and a curse. A blessing because you can build an index to fit almost any purpose you can think of (relocation, business climate, etc.). A curse because as the number of benchmarks proliferate, each one will lose meaning. Making sense of four benchmarks is a lot easier than reaching some sort of conclusion after reviewing 45.

What's needed is a new way to deal with the deluge of data. A way to allow people in disparate locations to analyze, visualize, and collaborate on data sets. And sites like BuzzData could be the future of data analysis because what BuzzData lets you do is exactly what I described. It's a place where you can upload data for others to see, along with visualizations and other analysis. It's crowdsourcing with big data. And if you're an organization with a distributed work force spread between dense urban areas, suburbs, and ex-urbs but have lots of data to work with, working in a cloud-based platform can help you gain productivity you would sacrifice by having your employees commute.

That's the beauty of this whole new data-centric economy and cloud-based production and consumption. It solves a lot of problems from our legacy of bloated organizations, bloated commutes, and bloated economy with something simple, low-cost, and distributed. In short, it's the way of the future. And a little contest to redesign a livability index may have just given us a peek at it.

Twitter: @japhychron
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