Next-Gen Analytics Helps Spur Business SuccessBy Samuel Greengard Print
Analytics combines data and data sources in new ways to help firms understand relationships that can determine whether they soar or stumble into the digital age.
Turning to Next-Gen Analytics
One organization that is using next-gen analytics successfully is The Flint River Partnership, which helps farmers in the Lower Flint River Basin of Georgia make more informed decisions about irrigation, conservation and crop yields. The basin spans 27 counties and encompasses more than $2 billion in farm revenue annually.
The partnership—which includes the Flint River Soil and Water Conservation District, USDA's Natural Resources Conservation Service, the Nature Conservancy, the University of Georgia and IBM—has turned to IBM's Deep Thunder technology to generate more precise weather forecasts and push them out to mobile devices, including smartphones and tablets. This is significant because the U.S. Department of Agriculture estimates that 90 percent of crop losses are weather-related.
The analytics tool draws on public data from the National Aeronautics and Space Administration (NASA), the United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). It combines this data with historical records from Florida, Georgia and the WeatherBug network, as well as data from agricultural sensors, wind farms and weather sensors.
Deep Thunder provides a 3D telescoping grid to break down data—and, ultimately, forecasts—into smaller grids that can be used on a local basis. The approach has led to predicting snowfall accumulations in New York City and rainfall levels in Rio de Janeiro with upward of 90 percent accuracy.
The analytics tool "provides access to a service previously unavailable to regional producers," says Casey Cox, conservation coordinator for Flint River Soil and Water Conservation District. "Farmers and researchers are currently utilizing Deep Thunder to make decisions in the field that are dependent upon weather variables.
"Irrigation is crucial to production in the Lower Flint River Basin, and having access to a sophisticated, site-specific weather model has provided more certainty in the decision-making process. Farmers are able to optimize water use by evaluating weather patterns and conditions up to 72 hours in advance."
Next-generation analytics ventures beyond understanding events, conditions and factors in a deeper and broader way. It's also about using data more proactively through predictive analytics and other tools.
In the marketing arena, this might translate into harnessing beacons and interactive shelves to understand how shoppers move through a store, provide them with information about products, and generate coupons and promotions dynamically, based on past purchase patterns or data residing in a loyalty program.
In manufacturing or health care, it might translate into understanding market trends in a deeper and broader way and gaining insights into the fast-changing dynamics of a supply chain or patient behavior.
To be sure, there is no shortage of potential uses for analytics 2.0 in business, education and government. Over the next decade, the concept will redefine a wide swath of industries—as well as the way people and companies interact.
"The reality," Capgemini's Schlesinger says, "is that [analytics 2.0] requires a different way of thinking and an ability to combine a growing number of data elements in a way that delivers maximum value. Next-generation analytics is not a new concept. It's simply part of an ongoing evolution of big data and analytics tools."
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