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Orbital Insight was founded in 2013 by James “Jimi” Crawford, an engineer who led a project at Google to convert the world’s books into searchable text. It was around the time of Orbital’s launch that private companies began sending fleets of satellites into orbit, which yielded a glut of cheap, constantly refreshed images of the Earth’s surface. Data was also pouring in from the digitized world in other forms: from the geolocation coordinates tracking our movements to the email receipts tracking our purchases. Many of the companies that produced this raw data, however, lacked the tools to process it, which created an opening for “alternative data” companies. In the past five years, hundreds of them, Orbital included, have cropped up around the world, and they wade through text or pixels in search of trends.
At Orbital, a typical project begins with a broad question that a client is puzzling over: Are chain retailers dying? How is China’s trade shifting? For each of these questions, engineers have to make the abstract concrete. The leap can be an intuitive one — tabulating, for example, the cars in every Macau casino parking lot to predict how well its gambling sector will fare next quarter. When a counting algorithm gets perfected, when the car counter can accurately pick up the cars and leave out the port-a-potties and dumpsters, it can help answer even bigger questions about a given place: the degree of urbanization, the level of gas demand, the fluctuations in population. “You’re building these Lego bricks, and you can put bricks together in new ways,” says Boris Babenko, an engineer who trains Orbital’s software to recognize those cars and planes and ships. Last year, the World Bank approached Orbital to find a way to measure economic inequality. “You could think about it and say, Well, maybe we can look at the number of houses, or the shape of houses, or the presence of pools,” Babenko says. The team ultimately settled on four indicators of poverty using the algorithms it had on hand: the number of cars (more suggests higher incomes), the height of buildings (urban areas have higher buildings, and in the developing world, those areas tend to be wealthier), the construction activity (a proxy for population growth and migration), and the type of vegetation (in rural areas, thick greenery signals poverty; in urban areas, lushness signals wealth).
“Waiting a quarter to see how a company is performing is nonsense.”
Since its founding, Orbital has attracted nearly $79 million in funding (one of its investors is In-Q-Tel, the venture capital arm of the CIA). And the industry at large is doing well: A recent report by J.P. Morgan estimates that investors currently spend $2 billion to $3 billion on big data, a number that’s expected to climb. With alternative data being churned out at such a pace, however, regulation still has to catch up. Mike Gantcher is the head of sales at RS Metrics, which uses planes, drones, and satellites to measure traffic outside retail stores. When clients approach RS Metrics, he says, they often question the legality of using data in this way. “That’s the first thing hedge funds ask, so they don’t go to jail,” Gantcher says. If a person were to make a trade based on nonpublic knowledge — such as a tip from a shipping executive about the contents of a cargo container — he could be accused of insider trading.
The Securities and Exchange Commission has yet to weigh in, so, for now, firms are careful to stick with data that’s publicly available: Twitter feeds, radio broadcasts from cargo ships, photographs from space. Then there’s the issue of privacy. Placed, a company that uses smartphone location data to estimate how online ads impact retail foot traffic, masks any trace of identifying information (Placed was acquired by Snap in June for $200 million). And firms like Orbital rely on lower-resolution images in which people aren’t distinguishable. Besides, a person’s identity is a rare bit of data that to hedge funders isn’t worth a whole lot. “We’re not marketers,” says Zatreanu. “We want to understand not just you but what people like you are doing.”