$1-Billion Opportunity

Field data offers a huge potential revenue stream for farmers, but obstacles remain before growers can market it.

Todd Neeley
By  Todd Neeley , DTN Staff Reporter
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The agriculture industry may be sitting on a $1-billion gold mine with the data it generates, Image by Jim Patrico

In times of lower commodity prices and higher input costs, agriculture data’s potential $1-billion revenue stream for farmers would be a welcome new market. But, this world of ag data collection and sharing has a ways to go to achieve maturity.

The U.S. Senate Committee on Commerce, Science and Transportation recognizes the potential for farmers to sell data to a variety of customers in all segments of agriculture and beyond. Yet, a big stumbling block remains: no standardized way to collect and aggregate that data to make it useful, while still protecting producers’ rights.

Gypsum, Kansas, wheat farmer Justin Knopf, vice president of the Kansas Association of Wheat Growers, told the committee the data he collects on his farm has been valuable in making good decisions.

“Data is all around us, and there is value in it all,” he explains. “While a record of Google searches and websites visited may be useless history to me, analysts and marketers see valuable information that allows them to adjust the content they create. The same, of course, is true in agriculture. While some may see a jargon-filled spreadsheet or just a bunch of various colors on a field map, I see ways to maximize efficiency in my operation.”

The ability to collect data, process it and then use it to make the best decisions has become a core competency for many farmers, Knopf adds.

DATA MARKET. Jason G. Tatge, cofounder, president and CEO of Farmobile, an agriculture technology start-up based in Kansas, explains they turn farmer data into a commodity. They share the revenue reaped from that data with the producers who create it. Tatge notes the movement to monetize farmer data is just beginning to scratch the surface.

“There is a market to put together data to understand best-management practices, for example,” he says. “That is how we can create a revenue stream.”

Tatge says data buyers already include analytics companies, insurance and reinsurance providers, and equipment manufacturers. But, growth in this industry is being slowed for multiple reasons, one being that the vast majority of data generated from farm fields is never even collected.

“Once a person buys data, another wants to buy,” Tatge explains. “The problem is now we don’t have enough data. Eighty percent of data generated in cabs today does not make it out of the cab. The agriculture industry lacks a common interface to be able to get data out of the cab.”

DATA ON THE FARM. Knopf says currently there are three main types of data he uses on his Kansas farm:

1) microdata he collects and produces that is specific to his operation

2) data specific to his farm provided by service partners

3) macrodata the farm provides to others, who in return give the farm information about what is happening in the industry on a larger scale.

“As on many farms, our seeding, spraying and harvesting equipment all have hardware and software that measures and records spatially what is being done or happening in the field,” Knopf says. “Performing on-farm research with sound scientific and statistical principles is one way we use this technology.”

For example, he’s able to quantify how cover crops affect crop yields, which has led to a broader adoption of the practice.

“We utilize satellite imagery as a way to help us identify management zones within a field and predict yield variability,” he adds. “These management zones allow us to modify our seeding rates based on the productivity of the land, which lowers our seed cost on acres that are less productive.”

Knopf uses zone soil sampling to quantify fertility levels in different areas of a field. This allows him to fertilize based on specific soil conditions and nutrient levels.

Data like this will likely have a dollar value associated with it one day. Shannon Ferrell, associate professor in the Oklahoma State University Department of Agricultural Economics, says the application of big data to agricultural production has the potential to improve profitability and manage risks.

“Current technological, economic and legal environments raise issues about how the value of agricultural data will be captured among the agricultural producers generating the data and the agricultural technology providers aggregating it,” he said in written testimony before the Senate committee.

“Producers receiving what they deem to be sufficient value for their data contributions is critical as a potential gateway issue for making those contributions; without large, robust participation in agricultural data systems, such systems will fail to reach their full potential. Thus, addressing the concerns of agricultural producers with respect to their rights in data, the value it creates and their privacy if they choose to share their information is vital to see that the agricultural industry collectively maximizes the value of these data technologies.”

Ferrell says farmers often raise concerns about who owns the data collected. He admits, “There are no clear answers in the current intellectual property framework.

“However, the question of agricultural data ownership may not be as important as ensuring farmers always have access to their data, can receive value from its use and can feel comfortable with the level of privacy--or lack thereof--that can be afforded to those participating in big data platforms,” he says.


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