Weather Analytics Creates A Global Database For Predictive Modeling

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By : admin |March 05, 2014 |news |0 Comment

By John Farrell, Forbes

September 6, 2013 – Bill Pardue has worn many hats in his career–but he’s more excited about his current business than any that’s come before.

I spoke recently with the former newspaper reporter-turned-data-dealer about the history behind his new venture, Weather Analytics, and what it offers to clients.

“A third of U.S. commerce is sensitive to the weather,” he said. “With modeling based on truly global data, companies are in a position to make better decisions for business.”

And no one, he added, is doing what Weather Analytics is doing.

The Short History

After ten years as a reporter and editor for the Denver Post and Associated Press, Pardue went to Harvard Law school in the 1980s and began working in Washington, D.C. on Federal regulations for emerging technologies and how they would affect companies’ operating environments.

This led to a major role as a divisional CEO and Chief Global Product Officer for LexisNexis, where he first got interested in big data and how it can be used to provide risk assessment to clients in the private sector as well as the U.S. Government.

Shortly after, Pardue founded his own company, QBase LLC in 2005, to provide data analytics to intelligence and military agencies, and it was during this time he realized that there was no truly global database with a consistent means of organizing weather data.

This later led him by chance–or luck–to the doorstep of climatologist John Keller, a Senior Research Meteorologist at MIT Lincoln Laboratory and at AIR Worldwide in Boston. At the time, Keller was working with co-founder Chuck Khuen, to put together a business model, but they needed someone with knowledge of the database market.

Keller, like Pardue, had seen the need for a comprehensive database of weather information, and he began archiving and cleansing climate data from organizations and agencies around the world, backing it up to a server in his basement office.

“The idea of a weather and climate database came to me way back in 1983,” Keller told me in an email. “I tried to interest LexisNexis in the idea, but I guess it was ahead of the times, and they passed on funding a project.”

But the idea stayed in his head for another 20 years.

“Then about ten years ago, I realized that computer technology and the development of the Internet had gotten to the point where it made it possible for me to demonstrate the concept on my own.”

Meanwhile, Pardue and his colleague Beverly Parker had spent months quantifying and qualifying the data they’d reviewed from dozens and dozens of companies.

“When we started out,” said Pardue, “we talked to a lot of outfits that claimed to have global weather data–and none of them did.”

So he and Parker sat down with Keller and Khuen to start from scratch: build their own database business on Keller’s archive.

Build it and they will come…

Weather Analytics is not even a year old, but they haven’t had to look hard for clients.

John Crowley, VP of Financial Institutions at the company, discussed some of the weather related problems that businesses are having. For example: the lack of real weather data outside of North America and Western Europe.

“I had a meeting with a global private equity firm with major U.S. retail investments”, Crowley told me, “and one of the variables that they couldn’t predict was the cotton crop in Africa, which affects the ultimate return on this portfolio company. The solution would be to utilize Weather Analytic’s global micro-climate model to ascertain ground moisture and seasonal weather variables going forward.”

Without hard data, he said, they can only guess how the climate will affect their projections for cotton supply over the next 12, 24, or 36 months.

“And that’s become a recurring theme for everything from construction insurance to infrastructure financing,” Crowley added. “The need for forecasting and predictive modeling. Many projects are underwritten with insufficient data that makes it very difficult to adequately or appropriately price a risk.”

Another example: a global insurer and a major international investment bank are looking to expand a port in the British Virgin Islands. Given the 24-month construction schedule they currently have on the boards, said Crowley, weather predictive modeling around the period will help them assess potential delays to completion and revenue risk on ongoing operations.

So, Weather Analytics is off and running. The company’s database is also appealing to other big data analytics firms. Recently, the company announced a partnership with Cambridge-based Via Science, which I wrote about earlier this summer.

And while it’s early days for both companies–Via Science launched in March, one month after Weather Analytics–they’ve seen traction, and are talking jointly with clients.

SOURCE: Forbes