Imagine a machine that flips a coin. If you guess correctly, you win a prize. Without any extra information, you might simply pick heads every time and win about half the time.
But what if you had details about the machine, the coin’s balance, the surface it lands on? With enough of the right information, your predictions would improve. And if you had perfect access to every relevant factor, you could predict perfectly and win every time.
This example shows a simple truth: Information, and our ability to access and use it, determines how well we can predict the future and make the best decisions.
While prediction is valuable in any field, agriculture is uniquely dependent on it. Our industry is shaped by long production cycles where decisions made today may not show results for weeks, months or even years. Layer on the variability of nature and markets, and the need for accurate, timely data becomes clear.
In swine production especially, advances in data generation, sharing and analysis have the potential to transform how we work. We are still early in this transformation, which makes this the right time to address critical questions:
• Who owns the data generated on a farm?
• How can farm data remain private and secure, yet still accessible when needed?
• What standards will structure and organize data?
• How can different technologies be integrated to generate additional data?
• As agri-tech grows, how will government policy adapt, and who will guide that conversation?
The answers will shape the future of swine production for decades.
Fortunately, our industry has a long history of developing proactive governance in other areas. Programs such as the U.S. Swine Health Improvement Plan (US SHIP) and Secure Pork Supply (SPS) have set nationwide standards for disease prevention, biosecurity and movement controls well before crises occur. These models show the power of coordinated, voluntary adoption backed by strong science and clear incentives.
We can also learn from other industries. History shows that organizations that address privacy, infrastructure, ownership and regulatory challenges early thrive, while those that delay often lose their competitive edge and even face restrictive rules imposed after problems emerge. When we apply this lesson to agricultural data, the benefits are clear: improving profitability, ensuring fair use and enabling innovation without sacrificing producer rights.
If the swine industry takes a proactive path, avoiding the pitfalls others have faced, we can set the gold standard for data-driven precision production worldwide and reap the rewards that come with it.
