Data-driven and data-sharing systems still have a long way to go in convincing farmers to embrace them.
Until farmers can see the benefits of various platforms and feel comfortable choosing between them, they are likely to remain cautious, the Kansas City Federal Reserve Bank’s agricultural symposium heard.
“Should all farmers adopt all technologies?” posed Kansas State University economist Terry Nelson.
“I think the answer there quite clearly is ‘no.’ ”
Gregory Graff, an economist with Colorado State University, said most economic models focus on technology’s impact upon profitability, and extrapolate from there, but in reality, cultural and psychological factors also play a role in uptake.
“Conditioning variables” can propel or retard expected technology incorporation.
Deanna Kovar, John Deere vice-president of precision agriculture, said farmers are willing to embrace technologies that they can see working. They are reluctant about technology they can’t be sure about.
“Certainty” about positive results will drive adoption “more than anything else,” Kovar said.
That’s led to autosteer systems being eagerly incorporated but slower acceptance of variable rate technologies.
Nelson, who specializes in surveying and studying farmers’ attitudes and production results from new technology, said “network externality” factors make acceptance of the new big-data platforms a challenge.
That concept means data-sharing platforms can offer access to great comparative information, but only if many others in a similar situation share their data with it. A farmer gets little if there aren’t many others sharing their data.
Nelson said that farm production data will probably end up creating a monopoly platform at some point because farmers don’t want to have to use multiple platforms and want to connect data from various systems.
“That’s why there’s a winner-takes-all model for data platforms,” Nelson said.
Graff said he sees the same striving of data platform companies to provide a comprehensive system.
“It really seems like a scramble for becoming one of the potential natural oligopoly,” said Graff.
Farmers are already good at using “small data” from their own farm production. Being able to measure their performance compared to peers is the promise the big-data platforms hold.
“It’s on the big-data side of things that we think, we hope, that there are still some significant gains to be made.”
Nelson said farmers aren’t being irrational when they are cautious about data-sharing platforms. Without proof the technology is helping them achieve better results, and that they’re getting something for sharing, and that they’re using a platform that’s going to be the best one, they’re likely to hold back. Sometimes waiting is the optimal decision.
“Some time in the future I expect the number of data platforms to substantially decrease, such that the farmer would have a better chance of choosing a successful data platform,” said Nelson.
Kovar said aggregate numbers of farmers incorporating new technology platforms doesn’t necessarily represent the true uptake by commercial agriculture in the United States.
“What percentage of acres are leveraging the technology? Acres, not farms and farmers,” said Kovar.
“Adoption of precision agriculture technology should be measured at the acre level to truly understand the impact these technologies are having on our industry.”