Predictive Analytics and What it Means for Agriculture

Predictive analytics is a type of data analysis that uses algorithms and machine learning to predict future outcomes accurately. In agriculture, we apply it to tasks like crop yield estimation, pest and disease management, and water management plans. 

Mainstream adoption of predictive analytics in the agriculture industry results from the agtech boom agricultural data revolution. Farmers can make informed decisions about their crops and harvests with predictive analytics, resulting in better yields and profit.

History of Predictive Analytics in Agriculture

Predictive analytics in agriculture can be traced back to the 1800s when farmers started creating records of their yields and weather patterns. In the 1930s, statistical analysis became more standard, and more advanced predictive analytics soon followed. With technological advancements, farmers can collect and analyze data more efficiently, improving agricultural practices.

Predictive Analytics in Agriculture Today

Today, predictive analytics in agriculture is more accessible than ever before. Farmers leverage  agtech tools to make informed decisions about their operations. These tools include sensors, drones, and machine-learning algorithms that help farmers collect and analyze data efficiently. Predictive analytics supports precision agriculture applications and allows farmers to make better decisions. 

The benefits of predictive analytics in agriculture are vast. Farmers use it to optimize crop yield and minimize damage from pests and diseases. It helps farmers make informed irrigation decisions, reducing water waste and higher crop yields. Farmers can save costs on resources, such as fertilizers, by accurately predicting outcomes and increasing their profits.

Predictive analytics also helps farmers stay ahead of the curve. With predictions of weather patterns and the commodity market, farmers can plan their crops accordingly and make appropriate decisions to minimize the risk of crop loss or loss of margin. They are saving time and resources and improving their overall efficiency.

Predictive analytics is a powerful tool for shaping farming practices and disrupting established procedures and protocols. And yet, it’s not a new tool – the history of predictive analytics in agriculture goes back decades. It’s just that today we have more data, better data, and better technology to analyze the data. The benefits of predictive analytics are enormous. Change can happen faster than it has in decades past. Predictive analytics is shaping to become a vital tool for farmers worldwide. 

At Bankbarn we use predictive analytics to help make quick, frictionless, and intuitive experiences for our borrowers. We start with data-driven decisions and AI-powered credit risk models to quickly and accurately measure borrower risk. That means farmers can get back to doing what they do best – farming. And farming with the financing they need to grow their dreams.