There is a fundamental Catch-22 facing specialty crop agriculture today: growers increasingly need technology to address rising labor and production costs, but those same economic pressures make it harder to justify investing in new technology.
Christina Herrick recently explored this challenge in The Packer, bringing together perspectives from growers, technology companies, researchers and industry organizations on what actually drives AgTech adoption.
For me, one of the most important takeaways is simple: AgTech adoption starts with understanding the numbers.
When I talk with growers about automation, I don’t want to know that hand weeding costs “about $200 per acre” or that labor has generally become more expensive. I want to understand what that operation actually spent last year, the year before and the year before that.
What did weeding cost per acre? What did harvesting cost? How many labor hours were required? How quickly are those costs increasing?
Until we understand the baseline, it is very difficult to determine whether a new technology actually creates value.
That distinction becomes particularly important when comparing operating expenses with capital investments. A grower may look at a $300,000 machine and immediately see a major expense. But if that machine replaces or reduces an operating expense that occurs every year—and that expense continues increasing—the economics begin to look very different.
The article highlights another important point: purchase price isn’t the entire cost of AgTech.
Growers also have to consider transportation, charging, maintenance, monitoring, field logistics, utilization, reliability and the operational changes required to integrate a machine into an existing farming system. A technology can perform its intended task and still fail commercially if those additional requirements make it impractical.
That is why return on investment has to be evaluated at the farm level.
A technology that pencils across thousands of acres may not make sense across hundreds. A machine that works economically in California may require a different business model in another production region. Increasingly, that is pushing AgTech companies toward rental, service and other deployment models that reduce upfront capital requirements and allow growers to validate technology before making a major investment.
But there is also a cost to waiting.
Labor costs continue to increase. Existing equipment continues to age. Perhaps more importantly, growers who begin implementing technology today also begin accumulating something extremely valuable: operational data and experience.
As Agtonomy CEO Tim Bucher put it in the article, “You can buy a machine overnight. You cannot buy three seasons of your own ground truth.”
That may be one of the most important concepts for the next phase of agricultural automation.
We need to move away from describing every new technology as a “game changer.” The real value of AgTech may be less dramatic—and ultimately more important.
Technology can make an operation more consistent, more predictable and more resilient.
For growers operating in an environment of tightening margins, rising labor costs and increasing uncertainty, that consistency matters.
The objective isn’t technology for technology’s sake. It isn’t putting robots in fields because robots are impressive.
It is understanding the economics of an operation well enough to identify where technology can reduce costs, improve consistency and help growers continue farming profitably.
And increasingly, the first step toward automation may not be buying a machine.
It may simply be knowing your numbers.
