Latest / The Pivot Podcast with Fexingo: How Businesses Change Direction and Survive Disruption / How a Farm Equipment Maker Pivoted to Precision Agriculture
Transcript
- Lucas: When you think of a company that pivoted from hardware to software, you probably think of Adobe or maybe Microsoft. But there's a 180-year-old company that made that shift without most people even noticing. Luna: Let me guess — Deere and Company. The tractor maker. Lucas: Exactly. John Deere. And the pivot didn't start recently. It started in the late 1990s when they first put GPS receivers on combines. The insight was simple: if you know where you are in the field, you can plant seeds more precisely, apply fertilizer only where needed, and track yield by the square foot. Luna: But that was just a feature on a machine. When did it become a real platform play? Lucas: That happened around 2013, when Deere acquired a company called Blue River Technology for something like $300 million. Blue River made computer vision systems that could identify individual weeds and spray them with herbicide — not the whole field. Luna: So they went from selling iron to selling intelligence. Lucas: Right. But the bigger pivot came in 2020, when they launched the Operations Center — a cloud-based platform where farmers can store all their field data, get weather forecasts, and even share data with agronomists. It's basically a CRM for a cornfield. Luna: And they charge a subscription for it. Lucas: They do. The base tier is free, but premium tiers cost hundreds of dollars per year per field. By 2025, Deere was generating about $6 billion in annual revenue from precision agriculture — that's roughly 15 percent of their total revenue. Luna: That's significant for a company that's been making tractors since 1837. Lucas: And it required a massive cultural shift. For most of its history, Deere was an engineering company that built machines that lasted 20 years. Software requires continuous updates, bug fixes, and a very different relationship with the customer. Luna: It's like the difference between selling a refrigerator and selling a streaming service. Lucas: Exactly. And the hardware guys at Deere were not thrilled at first. There were internal battles over whether to give away software to sell more tractors or charge for it as a standalone product. They eventually landed on a hybrid model. Luna: What did that look like? Lucas: The GPS guidance system is still a one-time purchase on the tractor. But the analytics platform — the Operations Center, weather data, field health maps — that's a subscription. And they also offer a pay per acre model for some services, which aligns their incentives with the farmer's. Luna: So the farmer pays less if the crop fails? Lucas: In a sense. If the season is bad, they use fewer data-intensive services. It's a variable cost, not a fixed one. That's a big deal for farmers with tight margins. Luna: And I imagine the data itself becomes more valuable over time. Lucas: That's the real moat. Deere now has petabytes of field data spanning years. They can train algorithms to predict pest outbreaks, optimize planting dates, and even recommend which seed variety to use based on historical performance in that specific field. Luna: Which makes it very hard for a startup to compete. Lucas: Exactly. The network effects are real. The more farmers share data, the better the models become, which attracts more farmers. That's the classic platform flywheel. Luna: But there's a tension here, right? Farmers are famously independent. Are they comfortable handing over all their data to a single company? Lucas: That's the billion-dollar question. Deere has had to be very careful about data privacy. They promise that individual field data is never sold to third parties. They aggregate and anonymize it for the models. But trust is fragile. Luna: And they've faced criticism from farmers who say they're locked into Deere's ecosystem — that they can't repair their own tractors or use third-party software. Lucas: Right. The right-to-repair movement has been a real pressure point. Some farmers feel that Deere is using software to create a monopoly on repairs and add-ons. Deere has pushed back, but they've also started making some diagnostic tools available. Luna: It's a balancing act. You want the platform to be sticky, but not so sticky that customers resent you. Lucas: Yeah. And that's the challenge for any legacy company pivoting to a software model. You have to bring your customers along with you, not force them. Luna: Speaking of bringing people along — if these conversations have moved your work forward in some small way, we'd love your support. It's what keeps the show ad-free and independent. Lucas: Yeah, you can find us at buy me a coffee dot com slash fexingo. No pressure, just if you find value in what we do. Luna: Okay, back to Deere. So they've made this huge pivot, but what about the traditional tractor business? Is it still growing? Lucas: It is, but more slowly. The equipment business is cyclical — it booms and busts with commodity prices. The software revenue is more stable and higher margin. That's the real reason for the pivot: Deere wants to smooth out those cycles. Luna: So the hardware becomes a vehicle for the software, literally. Lucas: Exactly. And that's a pattern we see in other industries too. Think about how Tesla sells cars but also sells software upgrades for things like acceleration boost or full self-driving. Luna: Or how Peloton sells the bike but makes recurring revenue from the subscription. Lucas: Right. But Deere's advantage is that their customers are businesses, not consumers. A farmer is much more likely to pay for a service that demonstrably increases yield per acre than a consumer is to pay for a faster acceleration. Luna: And the data proves it works. I've seen studies that precision agriculture can boost yields by 10 to 15 percent while reducing input costs. Lucas: That's the kind of ROI that justifies the subscription. And it's why Deere's pivot has been so successful. They didn't just slap a screen on a tractor and call it innovation. They built an entire ecosystem around data. Luna: But it took a long time. They started in the late 90s and it's now 2026. That's almost 30 years. Lucas: That's the lesson for any legacy company considering a pivot. You can't do it overnight. It requires sustained investment, a willingness to cannibalize your own products, and a lot of patience. Deere spent over a decade just building the data infrastructure before they could monetize it. Luna: And they had to change their talent mix. I read that by 2025, about 15 percent of their R&D budget went to software. Lucas: That's up from virtually zero in 2000. They had to hire data scientists, UX designers, cloud engineers — people who wouldn't normally think of a tractor company as a tech employer. Luna: And they set up a separate innovation office in Silicon Valley to attract that talent. Lucas: Exactly. They realized they couldn't build the future from Moline, Illinois alone. They needed to be where the software talent was. Luna: So what's the next frontier for them? Lucas: Autonomy. Deere has been testing fully autonomous tractors since 2022. They already have a driverless tractor for tilling that you can control from a smartphone. The next step is autonomous planting and harvesting. Luna: That would be a game-changer for labor shortages in agriculture. Lucas: Huge. The U.S. has a chronic shortage of farm workers. If Deere can offer a subscription that includes both the autonomous machine and the software, they could completely reshape the economics of farming. Luna: And that's the ultimate pivot: from selling a product to selling an outcome. Lucas: Yeah. Pay for the harvested crop, not the tractor. That's where they're headed. Luna: It's a far cry from the green tractors your grandfather drove. Lucas: Totally. But the company that made those tractors is still there. They just learned how to pivot.