Barnard kicked off her remarks by noting her grandfather’s rule of thumb on risk management. In order to lock in some profit, he always sold a third of the crop at planting, a third during the growing season, and a third at harvest.
While this ‘rule of thumb’ strategy has been in the agriculture industry for years, there is a new solution to navigate market uncertainty: machine learning.
Thanks to the increased power and decreased cost of cloud computing, farmers and other participants in the agricultural supply chain have access to more data and resources for analytics now than ever before. Combined with the knowledge and experience that these stakeholders bring to the table, machine learning has the power to completely transform market uncertainty through forecasting and market simulation.
Every single stakeholder in the agricultural supply chain, from farmers to processors and distributors to food retailers, has to face one major problem: market uncertainty. The unpredictability and uncertainty of the marketplace influences all business decisions from the materials used to produce goods to how those goods will need to be priced for retail.
As Barnard noted, those who survive and thrive will be the adopters of next-level tools to navigate markets with agility.