Bayer Announces Data Science Driven Pricing Structure

10:17AM Aug 08, 2019
Aerial application
Fungicide Application
( Lindsey Benne )

Imagine taking the risk out of buying inputs—especially risk associated with trying an unfamiliar product. Would it make you more willing to try products or practices in which you’re not familiar?

Bayer’s banking on it. Company executives recently explained Bayer will change the way it markets products to farmers in an attempt to better share risk.

“[With our data science] we can make specific recommendations to the grower and give them outcome-based pricing,” says Liam Condon, president of Bayer Crop Science. “If you don’t achieve the outcome we predict you, don’t have to pay for that outcome. If you achieve more, we share in that incremental value.”

For example, if Bayer’s models tell you to apply fungicide at VT for a 3 bu. per acre gain, and you only gain 2 bu. per acre, you get a refund on some of what you paid for the fungicide. Alternatively, if you gain 6 bu. per acre, you’d pay some of that value to the company after the fact. Note, anything above a 10 bu. per acre gain above expectation would be “all yours.”

“It’s not just for seeds, it’s for fertility, fungicide/crop protection prescriptions as well,” says Mike Stern, Bayer’s head of Climate Corporation. “Even though we might have to refund some, the grower is most likely in a good spot and we’re still selling fungicide. All recommendations are based on the fact that we can bring data profiles in.”

The new system will be based on information gathered in Climate Corporation technology such as FieldView. The information users enter in will inform recommendations and anticipated outcomes.

Last year Bayer took its first step toward this new pricing model by releasing Seed Advisor, which uses information farmers enter into the system to give seed recommendations, including multi-hybrid options.

The company doesn’t have a launch date for the new pricing system and certain agronomic recommendations as there are several complex variables yet to be finalized.