Skip to main content

Economic Geography of the Cloud

An abundance of digital data predicts where the jobs will be.
  • Author:
  • Updated:
(Photo: Sergey Nivens/Shutterstock)

(Photo: Sergey Nivens/Shutterstock)

If Seattle is the next golden era Detroit, then how is cloud computing the next Model T? As an automobile, the Model T didn't cater to the rich. Isochronic maps ignore class. The time to move from one part of the world to another depends on more than technological innovations in modes of travel. Even today, the ease of one's journey to work depends on household wealth. Henry Ford leveled that playing field. How does the cloud level the playing field?

In and of itself, the cloud doesn't level the playing field. In and of itself, the horseless carriage didn't level the playing field. Ford took a rich plaything, a novelty, and made it accessible to anyone. Rich or poor, no one was stuck on a railroad track. Harbors or river towns mattered less. Likewise, the cloud expands the geographic possibilities.

The analogy of Ford's Model T to Amazon's cloud is incomplete without considering Steve Jobs and the iPhone. Upon second thought, the iPhone is the Model T. The cloud is the pathway without rail. "No matter where you go, there you are."

Where you are is a data point without sound, signal. It's noise. If you fall in the forest, no one will hear you unless you have a smartphone. If you have a smartphone, others will hear you. Without the cloud, no one will listen. You shout into the void via Instagram.

If you fall in a forest without Wi-Fi or cell phone coverage, no one will hear you (let alone listen). You have fallen off of today's isochronic map and you can't get up. Ford's Model T had its geographic limits. So too does the cloud capitulate.

Where the cloud doesn't capitulate, "Moneyball comes to medicine." Major League Baseball is way ahead of health care. For every pitch, terabytes of data are generated. This gives small market teams such as Oakland a chance to compete. The economics of the game are convergent.

What about games where terabytes of data are not generated? Moneyball doesn't work. Algorithms go hungry.

All the advancements of moneyball medicine depend on feeding algorithms. Feeding algorithms depends on good data. Good data depends on smartphones. Good smartphone data depends on the cloud.

Have data. Have smartphone. Have innovation? Not so fast. The trouble with making health care more productive and efficient:

“We don’t know what the data means, because no one has ever measured it before,” Dr. Brett A. Simon, an anesthesiologist who is the director of the surgery center, told me in an interview this month at the new building. Still, he hopes the novel data might eventually be used as a benchmark to help distinguish patients who are recovering on schedule from those who have pain or other symptoms that need to be managed.

Such data collection is like mining a natural resource for which the world has no use yet. Innovation will take two forms, on either side of the new economic equation. Some will generate novel data sets. Others will create clever algorithms that can find the signal in the deluge of information noise.

But humans must first digitize as much of the world as we can before machines can explore it. Behold the driverless car. Google's version works well in two places: Austin, Texas, and San Francisco. Like the Moneyball approach, Google has generated terabytes of data of the roadways in those regions. Meanwhile, Uber is engaged in a similar mapping project wherever the service is located. Thanks to the cloud and smartphones, drivers are poorly paid data entry jockeys. The taxi service is rather beside the point:

Companies that can tap into the data emanating from such smartphone networks have become a valuable resource. Waze, the Israeli traffic app acquired by Google for about $1bn in 2013, collects its information from millions of smartphone users who are signed into the service.

Such data are only as valuable as the applications they can support. Traffic and mapping information is quickly coming to assume a significant place in the automotive world, first to support ride-hailing services like Uber but, more significantly, as a platform for autonomous vehicles.

If the application exists, the company with the best data wins. Thanks to the highly detailed maps it assembles from cars travelling on streets near its headquarters, Google’s driverless vehicles already move confidently around the streets of Silicon Valley, almost as though they were running on invisible tracks. Without that kind of data, it will be hard to be a contender in the driverless future. No wonder a group of German carmakers is prepared to pay $2.8bn for Nokia’s mapping service, Here.

"If the application exists, the company with the best data wins." The places with the best data will also win. Wherever data is lacking will be economically isolated. Health care and education will be poorer, as well as the residents.