Transformed, not invented
Smart cities built from nothing rarely become great. The greatest cities transform themselves.
“What I learned over years of traveling and studying smart cities is that the ones built from scratch fail to become a megapolis. The best cities transform themselves from existing cities.”
History bears this out. None of these cities started over. They decided, again and again, to become better versions of themselves.
- CopenhagenAn industrial harbour too dirty to touchHarbour baths where people swim in the city centre
- PittsburghSmoke so thick streetlights burned at noonA city rebuilt around universities and medicine
- WarsawAn Old Town left in ruins by warRebuilt stone by stone, now a World Heritage Site
- HamburgWorn-out port land on the ElbeHafenCity, a new district on the water
The Premise
Every transformation is a decision. A city is the accumulated result of millions of them, and their consequences compound for centuries.
Haussmann’s boulevards still carry Paris. Penn’s squares still shade Philadelphia. A ring road built in one decade can divide neighbourhoods for fifty years. In the end the quality of a city is the quality of its decisions, and most cities have no system for making them well.
- EvidenceWhat the city knows, and how well it knows it.
- DecisionWhat it chooses to do, and on what assumptions.
- CommitmentBudgets, laws, contracts and bonds.
- ConstructionStreets, pipes, rails and buildings.
- Daily lifeHow people live, move and meet.
- ValueProsperity, health, trust and the cost of capital.
- LearningWhat the next decision should know.
The Intelligent City
Fourteen domains of a great city
Our Intelligent City work mapped the city as fourteen domains. They still hold. Great cities are strong in several at once, and each domain is shaped by decisions that cross into the others.
The counts show how many of the cities we evaluate have a major drawback in each domain.
The Cities
The cities that could be the world’s greatest
These are the cities people most want to visit, live in, raise children in and build a business in, held back by serious drawbacks: crime, street disorder, cost of living against after-tax income, taxes, schools, business burdens, getting around, healthcare, unemployment, harsh weather, natural disasters and a hard path to citizenship. They are listed by metro population, largest first, not ranked.
People already want to be there. The work is making them stay.
How to read the scores
Demand scores how much people want each city, from 1 to 5, on four things: whether they want to visit, live there, raise children there and build a business there. The total is out of 20.
Drawbacks score how severe each problem is, from 1 (minor) to 5 (severe). The total is out of 60. A city's focus areas are its drawbacks rated 4 or 5.
All scores are IntelCity estimates based on our reading of public evidence. They are a starting hypothesis to be replaced with sourced data, not a published index.
What these cities have in common
The same problems, everywhere
Counted from the list above.
A signature idea
Civic Decision Debt
Decision Debt is the accumulated future cost of decisions a city deferred, never owned, or never revisited. Like financial debt it compounds quietly. Shocks rarely create weakness in a city. They expose the Decision Debt that was already there.
What residents see
- Rents rising faster than wages
- Commutes that get a little longer every year
- A flood that nobody saw coming
- A bridge closed for emergency repairs
The decisions underneath
- Zoning left unchanged for decades while jobs grew
- A freeway built in the 1960s and never reconsidered
- Drainage sized for a climate that no longer exists
- Maintenance deferred across five budget cycles
The starting question
What do we actually know?
Every serious city decision mixes certainty with assumption. Naming which is which is where good decisions begin. Take one common question: should the city build a new rail line?
| Level | For the new rail line |
|---|---|
| Known | Today’s travel times, ridership on parallel bus routes and the land the line would cross. |
| Probable | Population and job growth along the corridor over the next twenty years. |
| Assumed | That zoning near stations will allow enough homes and offices to fill the trains. |
| Unknown | How remote work and automated vehicles will change travel demand. |
| Unknowable | The next pandemic, war or shock the line will have to live through. |
The goal is not certainty. It is calibrated judgment under uncertainty, with assumptions written down, owners named and triggers set for when to look again.
About IntelCity
IntelCity applies Decision Architecture to the city.
IntelCity is founded by Andrew V. Vasserman, author of The Decision Before the Decision and founder of Logyc. His work asks how organizations turn what they know into consequential commitments, and what those commitments go on to create or cost. Cities are the largest and longest-lived commitments people make.
IntelCity began more than a decade ago as Intelligent City, which first mapped the fourteen domains above. Years later the domains still hold. What has changed is our conviction that the hard part is not the data in each domain. It is the decision that connects them.