Latest / The Pivot Podcast with Fexingo: How Businesses Change Direction and Survive Disruption / How John Deere Pivoted From Tractors to Data-Driven Farming
Transcript
- Lucas: So let's start with a number that might surprise you. John Deere's technology and services division — the part of the business that sells software, data analytics, and precision agriculture tools — now generates over a billion dollars in annual revenue. That's not a side hustle; that's a serious business line for a company that was founded in 1837 to make plows. Luna: That's impressive, but I'm guessing it's still a fraction of their total equipment revenue. What percentage are we talking about? Lucas: Great question. Overall, Deere reported about $52 billion in revenue last fiscal year. So the tech services piece is around two percent of the total. But here's the thing: the equipment business is cyclical — when commodity prices fall, farmers stop buying tractors. The tech revenue is more stable, and it's growing at a compound annual growth rate of about fifteen percent over the last five years. Luna: So they're building a recurring revenue stream inside a manufacturing company. That's a big cultural shift. Lucas: Exactly. And it didn't happen overnight. The pivot really started in the early 2000s when Deere began embedding GPS receivers and sensors into its equipment. At first it was a nice to have — helping farmers reduce overlap when planting or spraying. But over time, they realized the data from those sensors was more valuable than the iron. Luna: Right, because if you know exactly when and where to plant, you can reduce input costs — seeds, fertilizer, water. That's a direct savings for the farmer. Lucas: And Deere figured out that if they controlled the software layer, they could lock in the customer. Today, a new Deere combine harvester has over 50 onboard computers, and it can stream about 50 megabytes of data per acre per season. That data flows into Deere's Operations Center — a cloud platform that helps farmers manage everything from yield maps to machine health. Luna: But I remember hearing about some controversy. Farmers started complaining that Deere was restricting their ability to repair their own tractors — that the software was proprietary and only Deere dealerships could fix it. How does that fit into the pivot? Lucas: That's the dark side of the pivot. Deere essentially argued that because the software is integral to the tractor's operation, farmers don't really 'own' the full machine — they own a license to the software. That sparked a huge right-to-repair movement. In fact, in 2023, Deere signed a memorandum of understanding with the American Farm Bureau Federation promising to make diagnostic tools and manuals available. But trust took a hit. Luna: So it's a delicate balance. You want to build a sticky ecosystem, but if you push too hard, you alienate your core customer. Lucas: Precisely. And Deere's competitors noticed. Companies like CNH Industrial and AGCO started investing heavily in their own precision agriculture offerings. Meanwhile, startups like Farmers Edge and aWhere started offering data analytics without the hardware. But Deere had one huge advantage: the installed base. Luna: More than a million connected machines worldwide, right? Lucas: Closer to two million, I think. And those machines are in the field every day, generating unique data. A startup can't replicate that. So Deere's pivot wasn't just about writing software — it was about leveraging a physical network that took over a century to build. Luna: But didn't some farmers start using third-party software? Like, you can buy a Deere tractor but use a different platform to manage the data. Lucas: Yes, and that's the big threat to Deere's strategy. If the data becomes portable — if the farmer can take it to a competing platform — then Deere loses the lock-in. That's why they've been pushing updates that only work with their own cloud services. It's a classic platform battle, but played out on a farm. Luna: So is John Deere now a technology company that also builds tractors, or a tractor company with a tech arm? Lucas: I'd argue it's somewhere in between. CEO John May has said the company's mission is 'to serve those who feed the world,' and increasingly, that means serving them with data. But Wall Street still values them at around thirteen times earnings — which is lower than a pure software company. So the market hasn't fully bought the transformation yet. Luna: What about the economics? How does Deere actually make money from the data? Lucas: A few ways. First, they sell subscriptions to the Operations Center — basic tier is free, but advanced analytics cost several thousand dollars a year per farm. Second, they sell precision upgrades like auto-steer kits for older tractors. Third, they offer a program called 'HarvestLab' that measures grain moisture and protein content on the go, which commands a premium. And fourth, they use the data to offer crop insurance and financing products. Luna: So it's a classic pivot: from one-time product sale to recurring services. You see this in cars, in printers, in coffee machines. But for a 180-year-old company, that's a huge operational shift. Lucas: And it required completely new talent. Deere now hires data scientists, software engineers, even agronomists. Their Silicon Valley innovation center, called the 'Deere Tech Center', has over 500 engineers. That's a lot of people who don't know how to weld a chassis. Luna: Did they face internal resistance? I imagine the old guard would be skeptical. Lucas: Absolutely. In the early 2000s, the company almost killed the precision ag division because traditional managers couldn't see the return. It took a visionary leader — Bob Lane, at the time — to keep funding it. The lesson is: pivots die without a senior champion who can protect the new venture from quarterly earnings pressure. Luna: That's a good point. And it ties into something we've seen on this show before — the importance of having a patient capital structure. Deere is family controlled through the Deere family and the board, so they can think longer term. Lucas: Exactly. Which brings us to the broader lesson: a successful pivot is rarely a single decision. It's a series of incremental bets, some of which fail, but the cumulative effect is a new business model. For Deere, the turn from iron to intelligence is still ongoing — the billion-dollar services business is growing, but it's not yet the main story. Luna: So what's the next frontier? Autonomous tractors? Lucas: Already there. In 2022, Deere unveiled a fully autonomous tractor at CES. It uses six pairs of stereo cameras and a neural network to navigate fields without a driver. That's the logical endpoint: the machine becomes a data-gathering robot, and the farmer becomes a fleet manager. The question is whether farmers will pay a premium for autonomy, or whether it becomes a race to the bottom with Tesla or other entrants. Luna: You know, we talk about these pivots on this show without any ads, and I think that's what makes it different. You get the unfiltered story. If you value that, you can support the show at buy me a coffee dot com slash fexingo. It keeps things ad-free and independent. Lucas: Yeah, I appreciate that. And honestly, if these conversations have given you a new way to think about your own business decisions, that's the whole point. The link is buy me a coffee dot com slash fexingo. No pressure, just a way to keep it going. Luna: Right. So back to John Deere's pivot — do you think other legacy manufacturers can pull off something similar? Lucas: They can, but they need a few things: a durable installed base, a willingness to invest in software talent even when profits are under pressure, and a leadership team that can bridge the old world and the new. Deere had all three. Companies like Caterpillar and Komatsu are trying similar moves. But not everyone will succeed, because once you start selling services, the customer relationship changes. You can't just ship a product and forget it. Luna: That's a good note to end on. The pivot isn't just about technology — it's about committing to a new kind of relationship with the customer. Lucas: Exactly. And that's ultimately what made John Deere's turnaround possible: they understood that the future of farming isn't about bigger tractors — it's about smarter ones.