If you were in Las Vegas, in January 2023, sitting in the audience of the opening keynote
of CES—perhaps the most influential tech conference in the world—you likely had one
question on your mind: “Why is John Deere here?” After all, they’re the tractor company,
right? They make machines that push and pull and move and dig, that’s their thing,
right? Well, not according to their CEO, John May. “We’ve quickly become one of the world’s leading
robotics and AI companies. Our solutions leverage technology like computer vision,
advanced sensing and compute, machine learning, and data analytics.”
There’s one key word there: solutions. That’s a word that gets thrown around a lot by companies
like Apple “…solution…” “…solution…” “… solution…”; Microsoft “…we provide an
end-to-end tooling solution…” “…deceptively simple solution…” “…the best end to end solution…”;
Google “…bespoke AI solutions…” “open sourcing solutions…” “…a great solution…”.
This linguistic mimicry, their mere attendance at an event like CES, it’s all… peculiar for a
tractor company. Unless, does John Deere think it’s a tech company? Well… yes,
they do. At least according to themselves, in this LinkedIn post, sharing an article entitled
“John Deere: ‘We’re a Technology Company.’” And that assertion appears increasingly less
absurd. While the company lays off hundreds in its manufacturing plants, it’s simultaneously
staffing up its tech divisions. Of fifteen current US job listings, twelve are in software, data, or
robotics—just three in manufacturing. The company has been going through a metamorphosis from one
that makes machines to one that makes solutions. Apple, for instance, does not merely make
computers or phones or tablets. They make integrated technology solutions,
blending software, hardware, and services into an ecosystem that envelops ones digital experience.
Correspondingly, John Deere no longer merely makes tractors or combines or loaders, but
rather integrated production solutions—blending software, hardware, and services into an ecosystem
that envelops a farmer’s day-to-day experience. At the extremes, the company appears entirely
disconnected from its original form as a small Illinois storefront selling shovels and
pitchforks. Never could John Deere himself have imagined that his company would eventually go on
to operate, for instance, a satellite network. But waxing nostalgic about humble beginnings
would mask what the company now truly is: it’s not an endearing family business, it’s not a scrappy
underdog, it’s a market-domineering behemoth. It has the business of agriculture, especially in
America, in a stranglehold. And so might Apple, with consumer electronics, but farming is not
something you pick up or put on. It’s not one’s digital experience, it’s one's entire experience:
it’s your job, it’s where you live, it’s what your family does, it’s what your neighbors do,
it’s what your descendants do, it is an all encompassing way of life whose future is now being
dictated by one tractor company that’s decided it’s big tech. But John Deere’s power, their
influence, their ability to change the course of history has been centuries in the making.
It started with this—the self-scouring steel plow. Plows had existed in some form
for millennia—so many millennia, in fact, that we can’t even say how old they are—but by the 1800s,
they’d been refined and refined into this: a single-piece cast-iron plow. These could be
pulled by an animal, and would efficiently loosen the soil to bring nutrients to the surface before
planting a fresh crop. And these worked great, for the time, except for here—the American midwest.
The soil of Illinois and its neighbors was thick, moist, and rooty, in a fashion that would lead
it to clump on the plow, forcing farmers to stop every once in a while to clean it off.
But John Deere had an idea: he would manufacture the same plow,
but of polished steel. This cut straight through the midwestern ground with far greater ease, and
the soil would shed right off rather than clump. While he was not the first to invent this concept,
he was the first to start manufacturing a steel plow en masse, and his production
steadily grew into the hundreds per month, and a later thousands. This innovation played
an instrumental part in spreading agriculture across the region, and transformed John Deere
from a mere shop into a growing manufacturer. By the turn of the century, after the company
had passed through the generations of the family, Deere had become a leading agricultural implements
manufacturer, but the industry landscape was changing beneath them. Like the plow, tractors
as a concept, had long existed. Through the 19th century it was typically animals like horse or
oxen that pulled plows and other implements, yet around the world, across industries, animal
power was being replaced by steam power. Whereas horse-drawn stagecoaches dominated the past, steam
trains were now the dominant form of long-distance transport, so the logic carried that steam-powered
tractors could replace animal-power on farms. And they certainly could, the technology existed,
but steam-powered tractors never became ubiquitous due to their high up-front and operating cost.
But with the turn of the century came gas-powered tractors: cheaper to buy,
cheaper to operate. Popularity exploded, and while Deere was originally reluctant to stray beyond
their agricultural-implement core, they eventually realized they had no choice if they wanted to
stay relevant. They tried to design their own, and it was plenty capable, but it was just not
competitive. At about twice the price of that of equivalent machines, their tractor never had any
shot of commercial success, and then its designer died from pneumonia following a week of testing in
the wet and cold, so John Deere rather elected to just simply buy their top competitor. With that,
the Waterloo Gasoline Engine Company was folded into John Deere, and over the following years,
their tractor, the Waterloo Boy, enjoyed wild success. Once again, like with the self-scouring
steel plow, Deere didn’t invent the technology, but they popularized it—they identified the
opportunity, scaled up manufacturing, marketed successfully, and helped transform the tractor
from a niche, novel technology into the solution for moving power on the farm.
Over the decades that followed, the company transformed again from primarily an implement
company into a machine company—offering combines and balers and planters and sprayers:
essentially anything you needed to turn a field into a farm. Through much of the 1900s they were
always a significant, but underdog player in the industry until the 60s and 70s when their primary
competitor, International Harvester, began to falter. And with its collapse in the 80s,
John Deere took a firm lead in the industry—becoming the go-to,
ubiquitous source of agricultural equipment in the United States. But then, another monumental shift
in the field. Like the tractor introduced the mechanical era of farming, information
technology introduced farming to the digital age. And again, John Deere had to adjust on the fly.
This started on June 23, 1995 when Rockwell International Corporation, traditionally a US
defense manufacturer, unveiled its proprietary Vision System—effectively firing the first shot
of the digital farming revolution. It seems so simple now, but Rockwell’s Vision System
was poised to usher in a new age of efficiency by using defense satellites to pinpoint and track a
tractor from above, which, in turn, would allow a farmer to better monitor their field’s yield,
or when it came time to plant, better disperse seeds and spray chemicals. Precision farming
had arrived, and while Rockwell was first, competitors such as Case Corporation, and Agco
Corporation were close on the company’s heels. So too was Deere, which took it one step further.
To the late-90s American farmer, GPS and precision agriculture was a handy tool, but still a finicky,
expensive, and difficult-to-use luxury. It helped, but it wasn’t required.
At least, not until Deere made it a practical necessity. As they did when developing their
tractor, Deere looked further afield for help. This started at Stanford,
where the company collaborated with engineers to develop an autonomous GPS-controlled tractor.
While it worked, it didn’t work well enough to take to market. The problem was 1990s GPS
just wasn’t accurate or dependable enough. So, more partnerships. Now Deere, along with
NavCom Technology and NASA’s Jet Propulsion Lab, sought to figure out how to create a more reliable
positioning system to support not just yield maps but autonomous guiding—the former a helpful tool,
the latter a potentially revolutionary product. While autonomous guiding may have seemed a
lofty ambition, its use case was well grounded. Before the rise of precision farming, farming was,
well, remarkably imprecise. Take, for instance, actually planting a field. Now, laying down seed
is actually a rather complicated process with a whole host of decisions to make and factors
to consider from when to seed to how to establish then plant the field’s headlands and borders. But
regardless of such considerations—or what crop one is even planting in the first place—each and every
farmer, since the dawn of the tractor, has dealt with one major inefficiency: overlap. In farming,
overlapping is practically unavoidable—as a tractor operator threads rows back and
forth across their field, it’s nearly impossible for there not to be slivers of field—whether it
be where rows meet headlands, or just between rows themselves—where the farmer doesn’t pass
over a small section twice. And considering the alternative—what farmers call sparing—this makes
sense: if a farmer is to miss a small sliver entirely while drilling, there will, of course
be no crops, if they miss it with pesticides or fertilizer, the section’s yield will drop,
if they miss it during harvesting, well that’d be an expensive and embarrassing mistake, too.
So farmers overlap. But they try to do so as little as possible. Experience helps with this, as
hours in the chair, along with a long-established sense of pride in maintaining straight rows,
keeps overlap down. So too do generally normal, rectangular fields, should a farmer have such a
luxury. And then there are tricks: spray foams to mark areas already hit, guideposts along
fences for visual reference, thoughtfully laid out tractor paths calibrated to align with the width
of the farmer’s equipment. But tricks only go so far. One study has put numbers on the overlaps.
Across the study’s 17 locations and four years of planting, the combine driller overlapped at 7.7%,
spin disk fertilizer at 9.5%, while the sprayer overlapped at 15.7%, and the cultivator reached
19%. At every step of the process of growing something, then, the farmer’s overlap is costing
them—8% of their seed is being wasted, 10% of their expensive fertilizer is being overapplied,
nearly 16% in pesticide and herbicide is doing more harm than good, and almost a fifth of their
field is being turned over by the cultivator for no reason. This means more materials. It
also means more fuel, it means more time in the field and in the chair, it means more hours put
on the machines, and therefore more hours in the shop and fewer functional seasons. Such
costs really add up, too, as a bad year will see costs outpace income, while 10 year averages, in
the case of Kansas farms from 2010 to 2019, will only net meager 11.8% profit margins. With such
touchy and tight finances, unnecessarily wasting 8 to 19% of one’s time and money on overlapping
is a massive inefficiency. One that Deere was seeking to address at the dawn of a new century.
The answer was called Starfire which, by correcting notoriously inaccurate GPS data
with ground location data, offered farmers field mapping accurate to within 3 feet or 1 meter,
rather than the 10-to-30 foot or three-to-ten meter accuracy of traditional GPS. With further
work on the product, by 2004, Starfire 2 provided accuracy within 1.5 inches or 4.5 centimeters.
Through the collaboration with Stanford, NASA, and Navcom who they eventually acquired, Starfire
positioned the company again on the cutting edge of the precision farming revolution—not only
did their product provide superior accuracy for yield and seed mapping, it was accurate
enough to address the fundamental inefficiency of overlapping. Simply equip a machine with a
Starfire receiver and a monitor then purchase Deere’s Autotrac program and farmers could now
guide by precise lines laid out on a screen and even let the autonomous feature take the wheel.
Today, through a combination of six uplink sites on three continents, 46 reference sites around
the globe, and leased bandwidth from Inmarsat satellites, the shovel and pitchfork company
is able to provide greater accuracy than the public global positioning alternative, optimizing
every single thread and turn across a farmer’s field. The influence of such guidance can’t be
understated. Only 10% of farmers used any sort of auto steer and guidance system in 2004, but as of
2019, those numbers stood in the mid 50 to 60% range, and on bigger, thousand-acre farms where
the economies of scale blunt the upfront cost and the waste of overlap is only magnified, adoption
rates of such systems have reached over 80%. By applying the same playbook they did with the
plow and the tractor—embracing then perfecting new technology through upfront R&D investment
while also acquiring sector leaders like Navcom—Deere helped push farming into a
new epoch. But that epoch isn’t over, and Deere’s only dug themselves further into the digital turn.
Across the dozen American companies Deere has acquired since 2007, only four are traditional
hardware manufacturers, the rest, broadly, are in tech, and increasingly in artificial intelligence,
machine learning, and automation. In 2017, for just north of $300 million, Deere purchased Blue
River Technology, who had recently been testing their new product called See & Spray—what they
called the world’s first smart sprayer, which, by feeding hundreds of thousands of plant images
through deep learning algorithms was capable of identifying crops and weeds before then spraying
herbicide within a quarter-inch accuracy. Not long after, Deere’s See & Spray Select entered
the market. Then, in 2022, See & Spray Ultimate became available for factory installation on 2023
model 410R, 412R, and 612R Sprayers. With a camera positioned along every meter of the carbon-fiber
spray boom, the product would reduce spray volume by two thirds, saving money on herbicides and, by
extending trips between refills, saving time and fuel. The benefits of the next step in precision
agriculture also provided an environmental benefit beyond the farmer too, as this product, the
company projected, would reduce the airborne drift of chemicals by up to 87% and chemical run-off by
up to 93%. In this new era of AI and machine learning precision farming, John Deere was not
the first, as a Dyson subsidiary entered the smart spray space earlier. Nor is it alone, as AgZen,
a commercial outgrowth of MIT research, is pushing into the space, too. Whether John Deere wins out
here, as they have so many times in the past with new technological innovations, remains to be seen,
but given their history, it feels like a safe bet. Regardless of competition, though, this service,
capable of plugging right into the broader John Deere ecosystem, should be a boon for
the American farmer conscious of cost, yield, and overall environmental impact of their work.
Or at least, that’s what it would seem. By standard metrics, farming in the US
has gotten better across the sector’s digital revolution—we’re wasting less,
making better informed decisions, and growing more than ever: just
look at average yields for corn, soy, and cotton. But consider the position of the American farmer.
In the past, being an all green farm—that is running strictly John Deere equipment—was a point
of pride. Today, though, it’s increasingly feeling like an expensive necessity without alternatives.
New-found hyper efficiency comes with a cost, or really, a whole host of costs. Say an Illinois soy
farmer is sizing up purchasing a See & Spray attachment—well, first they’ll need to have a
fairly new sprayer to begin with, which if they don’t have, will be in the ballpark of $50,000.
Then add on another $25,000 for equipment and install, which can only be done at an authorized
dealership. Still, given that soybean pesticides have reached an all-time high this decade coming
in at $77 per acre in 2022, and given that this farmer owns the median sized farm for the
state at 4,500 acres, considering scale, such an upfront investment may well be worth it. Without
See and Spray, pesticides would cost $350,000, with the product, assuming it cuts spraying
down to a third, the farmer would only need about $117,000 in pesticides—so with upfront costs,
savings total about $62,000. But then another cost: See and Spray subscriptions cost $4 per
acre so cut out another $18,000 and the economics become slightly less appealing.
And then there’s the less tangible costs. Fundamentally, precision agriculture is
changing what it means to be a farmer. What was once an occupation defined by individual autonomy,
problem-solving, and improvisation is now increasingly beholden to monitors, screens,
software subscriptions, and the availability of manufacturer-authorized technicians. Undoubtedly,
this is an issue of nostalgia, but it permeates in costly and frustrating ways too.
Consider the solar storms that pushed northern lights as far south as the American midwest. While
it might’ve been a once in a lifetime experience for the farmers who stayed up late to see it,
it caused far more costly problems when the storm knocked out their navigational systems. Just at
the moment farmers needed to be out planting corn their precision navigation systems failed them.
While solar storms are few and far between, issues with software programs and machinery
that’s now more complicated than ever are far too common and far too difficult to get figured out
for your life-long farmer. Rather than hauling a tractor back to the barn to fix a hydraulic
leak and get back out on the field that same day, when new-era hardware fails, there’s a
good chance a farmer will be out of their depth if it’s on the technology-side of the machine,
which as the far more finicky side, it likely is. So rather than fixing it and getting back
out on the field, the farmer’s left waiting for an authorized technician who will be expensive
to pay and costly on time, as it’s unlikely they’ll be available at the drop of a hat.
And all that’s without considering whether the farmer has the tools and information to make the
fix in the first place—which is also a matter of contention. Across the past decade, John Deere has
found itself in the middle of a battle over the right to repair. For those savvy enough or bold
enough to fix their own issues, they often need access to the diagnostic software to begin with,
which is something Deere’s been slow to hand over. Their stated reason to keep software restricted is
a matter of liability and responsibility. If they hand over the keys, they figure,
their machines might get used and altered in ways they shouldn’t. But for an increasingly
boisterous farming community, this withholding of key information is simply another way to make
sure that farmer is also on the hook for costly repair bills that make their way back to Deere,
thus providing the company yet another revenue stream. Regardless as to who is really telling
the truth, what’s undeniable is that the farmer is as financially squeezed as ever,
and with the rise of big tech in farming, they are increasingly being moved out of the driver’s seat.
But Deere is facing their own financial pressure—competition is rising, so they
have to adapt to maintain their relevance. Over the past decade, venture capital money has poured
into startups that insist they can disrupt the world of food production. Whereas in 2013 there
were 42 funds focused on the AgriFood space, today there are almost 300 reaching a peak
of $53 billion of investment in 2021. A simple thesis is presented to potential investors—the
global share of land dedicated to agriculture is peaking as more and more of the world urbanizes,
yet simultaneously, the global population is expected to continue increasing for at least
half a century more. Therefore, it is objectively true that we will have to produce more from less,
and these startups believe the way to do that is through technological innovation.
Different companies have different solutions to this problem—some are focused on “controlled
environment agriculture,” growing indoors to eliminate the threats and resource-losses from the
outdoors; others are leveraging big data analytics and machine learning to remove the inefficiencies
of guesswork; while still others are working to increase outdoor production yields and lower labor
cost through various forms of autonomy. Building on early successes in precision agriculture,
John Deere has committed to developing a fully autonomous production system for corn and soybean
by 2030—that means every step from plowing through planting through harvest without direct
human involvement. And that’s remarkably believable. Corn and soybean are planted
in straight rows with relatively high distance between each plant, meaning there’s already the
predictability and margin for error that makes it easiest for autonomous systems to succeed.
The combination of innovations like precision agriculture, indoor growing,
autonomous production, and more will yield amazing benefits for us all: in sum, they create a food
production system that is less expensive and less resource intensive. But they come at a cost—a very
literal, incredibly significant, upfront cost. The economics of paying an exorbitant amount for
a fully autonomous wheat production system work out first for the absolute largest farms. Just
as with See & Spray, every innovation promises to improve efficiency by a certain, small percent,
so the larger the overall operation, the more valuable that small percent can be,
and therefore the more likely the upfront cost is worth it. So innovations can be worth it,
but only if you grow a ton of food. This has been true for a while—there have been
greater and greater economies of scale in agriculture—which has contributed to
a long-term trend of consolidation. Over the past 25 years, the average size of an American farm has
grown by 7% even as total farmland has declined 8%—as small farms face increasing cost-pressure
by more-efficient big-ag operations, they either shut down or sell their land to big ag.
And as big tech encroaches into farming, innovation is accelerating, which is great
by itself, but this leaves the small family farm behind. A layperson’s perception of farming,
as a mom and pop living in a homestead in Kansas, working the fields around, answering to no boss
but themselves, is becoming a cinematic fiction. Increasingly, those living in regions dominated
by agriculture work not for themselves, but for landowners holding hundreds of thousands
of acres. Often, the owners of this land live time zones away, meaning profits from
production are not spent at the local diner or car dealership, but rather distributed to
a multitude of investors and left to sit in mutual funds. This contributes to a further
gutting of the economy of rural America—one of the rare ways to build a business outside of cities is
becoming an increasing impossibility, and rural resources are being extracted for urban gain.
This is, in many ways, inevitable. Tech innovation, across essentially any industry,
has primarily benefited larger corporations and incentivized consolidation. Farming,
being so far from urban areas and so culturally isolated from Silicon Valley, has long been
shielded from these forces. Yet today, John Deere and others have recognized the upside of bringing
these two worlds together. But this progress will hurt. The death of the family farm is upon us,
and the autonomous tractor sits just beyond the horizon, waiting to unleash its destructive
ability to incrementally optimize yields. The reason why John Deere’s See & Spray
technology is so powerful is that it’s able to interpret visual information and make decisions
on what a given plant needs in an instant, at a huge scale. What makes this possible behind
the scenes is a neural network—the software was fed millions of images and taught to interpret
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