Maximizing dairy farm success: How to transform data overload into actionable insights

Ever.Ag’s On-Farm Solutions empower dairy producers to turn complex data streams into profitable decisions in today’s competitive industry

The modern U.S. dairy farm has quickly become one of the most complex businesses to operate. Gone are the days when “Dad” and his kids occasionally sat around the kitchen table or in a meeting with the accountant in town to review production logs, milk tickets, and a stack of expenses to understand how the dairy was doing.

Today, producers must constantly monitor various streams of information, changing market conditions, and evolving regulations. Ignoring or missing critical indicators of problems or opportunities can be the difference between enormous profits or losses.

This brings us to the third trend for dairy farmers, which is to find better ways to aggregate data and disperse it to people who can affect real change on the farm.

Data overload

Dairy operators face the question of how to best manage multiple, often overlapping, data streams. Data flows from almost every aspect of the farm: the milk parlor, the herd management system, feed management software, some financial packages, milk weights and tests, pay statements, labor records, feed purchases, breeding and health records, computer vision, wearables, and much more. Add in a cropping operation, and the quantity of data can quickly double.

Most suppliers provide portals for accessing the information their service has generated. Sifting through vast quantities of this material to uncover critical insights has become a science. Without a data scientist on staff, dairy producers often turn to external providers to help aggregate and interpret their accumulated information.

From numbers to knowledge

The goal of linking multiple data sources to create personalized trends and alerts may seem straightforward, but the practical implementation is far more complex. Defining matched records, bridging different time horizons, and controlling edits and changes require substantial computational power and specialized expertise.

While several companies are crafting standard offerings, and some producers invest at home (often with very complicated Excel models), the industry is undoubtedly moving ahead.

The question, however, remains: what sort of investment are individual operators willing to make in data? If it’s an afterthought, the status quo will win out. Suppose there is a revolution of sorts whereby producers are willing to invest in modern data science tools and platforms. In that case, the dairy industry might be on the cusp of some exciting innovations as companies race to the data gold mine on the farm.