Industry 4.0 Moves to the Great Outdoors

Speaker A: For the first time, the kinds of automation technologies that we're used to thinking about in really controlled industrial environments, or maybe the kind of offices that we're in and office work, those things are coming outdoors into the farms and forests and fields that matter so much for the food and fiber, that kind of power, uh, our society. And, uh, for me, from what I'm seeing, it's happening just in time.

Speaker B: Welcome to the so what from bcg, the podcast that explores the big ideas shaping business, the economy and society. I'm Georgie Frost. First came steam, then electricity, followed by computers and automation. Industry 4.0 is what comes next. The digital connection of everything. And now that's coming for the outdoors and outdoor industries. So what does Industry 4.0, uh, actually look like when it leaves the controlled environment of the factory and heads out into the field? And what can leaders in other industries learn from agriculture's experience? Well, joining me today is David Potear, senior tech leader in industrials and climate at BCG. Industry 4.0, uh, from your standpoint with outdoor industries such as forestry, agribusiness, oil, mining, just explain to us what it is.

Speaker A: Well, I think you did a great job on sort of reminding folks about what the 4.0 is. Right? You know, essentially steam, electricity and then the IT revolution. And then some Germans about 15 years ago decided we needed a new word for what was going on in factories. Something emergent was happening. We would have said machine learning around the time that this concept came out. And now we probably would say frontier, uh, models and genai and then robotics, like being able to do something about it. It's not a dashboard. It's not an insight for someone to look at. It's taking action in the M moment in the work. So we're starting to get digital twins of the outdoor environment of farms and forests and mines and so on. What happens in an emergent kind of way when those systems start to get wired like the factories that we think of?

Speaker B: Well, let's use one of those as actually a really illustrative example. And that is, of course, farming.

Speaker A: I think what I've noticed in particularly the last five years or so is we're starting to really see concrete examples of these 4.0 systems in action. I'll give you just one example. It made a big splash at the big Consumer Electronics Show a few years ago. The show invited John Deere, which is not sort of the company you would imagine, to come to the biggest consumer electronics show in the world. And I think the system see and spray ends up being a bit of a poster child for what this looks like. This is a spraying machine that's putting herbicide crop protection down. It has cameras adjacent to every spray nozzle. It has vision. So it's not a blind piece of equipment. It has cognition. It has some of those same, uh, GPUs that we expect to make AI models work onboard, hardened and cooled on the machine. And then it's got robotic actuation, it's got nozzles that can adjust their spray volume and height, um, very precisely in the moment. Um, and that whole system is talking like crazy back to home base, to the machine and to the operator. And the result is, um, there's a recent study from the University of Arkansas that those machines can put down 50% less herbicide and have the same amount of weed free impact in the field. Georgie, you know, like we talked about, this isn't only about farming. Uh, let's take for example, forestry. It is remarkable what's happening around instrumenting our forests. There's a startup here in Boston called Cloris Geospatial that's working with a whole constellation of satellites and spaceborne lasers to essentially build a map of all the carbon that's locked up in all the forests, the world and the accuracy of these systems, these new. And it's sort of like factory Earth is manufacturing wood. And now we've got cameras overhead like we were inside of a factory building. And just by having those cameras overhead, we're able to get a much better sense of the carbon footprint of forestry activities and start to create incentives that are more aligned with what's needed, uh, around changing our carbon footprint.

Speaker B: A factory is a controlled environment. The field is anything but. Just what are the biggest challenges of taking this sort of technology outdoors?

Speaker A: Um, we've got a smart doorbell system, we've got some DIY security cameras in the house. And you think, how hard could it be? Right? And uh, there's some good reasons why it's taking until 2025, 2023 to see these kind of systems come online. It's hard. And you mentioned the big one with no roof. Uh, the challenge with that factory, imagine we're in some manufacturing environment and at random intervals the utility turns the lights on and off. That's weather. They turn off water and turn on too much water. You're flooded or you're drought, um, uh, and the temperature is all over the place. And so that's one of the big challenges is the unpredictability of the supply chain in the factory environment. The other Big one you mentioned is these sensors and systems. They don't like to work in these tough environments. It's dusty, it's hot. I can remember spending, uh, time at a, uh, startup that I sold my startup to, Indigo Ag, um, and one of the first pilots in the field, we thought it would be cool to have iPads out there in the Midwest. And you know What, Georgie? At 118 degrees, iPads stop working. And, you know, farmers will chuckle. And there's a lot of stories about Silicon Valley tech folks coming, getting their boots dirty for the first time and having these, aha, uh, moments about, I don't have Internet connectivity, my equipment doesn't work. And so that hardening is part of the reason why this sector is one of the last ones to really feel this wave of Industry 4.0 happen.

Speaker B: What would a, uh, farm that can actually sense and respond to its environment look like in practice? And how close are we to the sort of ideal?

Speaker A: I suppose a great farmer needs to run a machine shop, trade commodities on a future market, understand genetics and biology and chemistry at a really deep level. Agronomy. And then, uh, you know, they need to run a business and typically with a decent amount of labor. Um, and they will have systems for all those things, like we might in our house. I mean, one of the expressions in the industry is every plant is a sensor. And if you just think about that for a minute, that leaf canopy is telling me a lot in a corn plant early stage, or that apple orchard, that apple tree is telling me a lot about what my yield is going to be like this season in the blossom of the flower. So being able to read those sensors. And there's literally startups today, Georgie, that are bioengineering plants to communicate messages with us in the colors of their flowers and leaves. Which is wild to me. But even if you don't do that, a leaf has something to say. Every gardener knows that. And so watching the plants and having eyes on the canopy, not only from the machines that are working in the fields, but from space overhead. So using our public space assets, Landsat, the European Space Agency Sentinel, to watch these fields every day and compare these fields to all the other fields that benchmarking potential to understand where do I stand right now in the season compared to the last season, compared to my neighbors, and make smarter decisions. And then the second big piece is that robotic revolution, that farm implement. We think about a tractor, by the way, all kinds of crazy new forms coming. Ah, John Deere just acquired a company called Gus G U S S. And if you saw one of those tractors, Georgie, they don't look like a tractor. First of all, there's no cab. Uh, it's all electric, and it's essentially a roving tank for delivering the kinds of crop protection systems and chemicals that an orchard needs. Um, and instead of being super gigantic, it's actually fairly reasonably sized and you just have a lot of them.

Speaker B: I just want to return back to something that you spoke about at the start of your answer. Very, very human aspect of this conversation, and that is that farmers are under enormous pressure. We know that unpredictable weather, volatile markets and emissions mandate. Then you throw in the fact that there is a very real skills gap. You know, a farmer that's worked the same land for 30 years, how do you actually get them to know and understand and use this sort of technology and equipment? Is Industry 4.0 the answer to those pressures or just another thing for them to have to manage and worry about?

Speaker A: Yeah, I think it's definitely some of the big forces. Right. If you think about climate change. So remember, that factory has no roof and those input streams are doing things today. The number of farmers you meet who say, this is a season like I've never seen before, it's just remarkable how many folks are having those seasons. And these are folks that have had 20 and 30 seasons of experience, Georgie. That's a major force to deal with, um, and the change in those inputs. The second big one is, um, big changes around what it is to farm in relation to the climate system. So, you know, agriculture is 25% of global emissions. So any scenario where we get to a better place, farming will change. Farmers care about stewarding the land, they want to do right by the land, but the recipe is changing probably faster than in a lot of farmers lifetimes. And then the third big one that we're all living through is just global geopolitical uncertainty. So farmers these days in the United States, for example, having a hard time marketing their grain on global markets, um, relationships that took 30 years to build, and then having a hard time buying the inputs. Just at the moment in the US where farmers need nitrogen to make corn do what it's supposed to do, we have the war go down. And so I think, um, for sure, it's a tough time to be farming. And, you know, I'm an AI optimist, Georgie, and I, I think that this isn't a fourth thing that's something to worry. It certainly is something to worry about, and farmers are thinking a lot about it. But I would like to make the case with you on our. So what, that it's AI to the rescue and we could talk maybe a little bit more about that? Um, I don't mean that in a naive way to say that it's going to be smooth or easy, but. But it does feel a little bit like a just in time moment to me.

Speaker B: Is there a concern, and I think this is a cross industry issue of the adoption gap. Now, I was quite surprised. 15% of farmers already strong AI users, but that rate doubles for large farms. So does this technology help everyone or just make the big players even bigger?

Speaker A: Yeah, that statistic you mentioned came from Bushel, one of the startups in the space. They've been doing a survey for several years now on tech adoption and for the first time they put Genai tools on the list. Georgian. Right off the bat, 14, 15%. Um, which could sound small or large to you. To me it sounds large and encouraging. Um, and it's actually larger than the average when you talk about average industry penetration in the United States. What I can tell anecdotally from things like that survey is that even with the stereotypes of, for example, US Farmers aging as a demographic, those are true statements. You know, that the age of the American farmer is, um, older than ever. Um, these are practical business people. And when there's a technology that can make a difference for the bottom line, they're all over it. And, um, one story I heard, Georgie, that I think has really stuck with me is there's a sense, and this is, I'm, um, crediting Nick Horeb, who was the founder of Harvest Profit, um, and a tech entrepreneur. His perspective is, you know, there was a period of time where farmers didn't weld. And it's actually not that long ago, Georgie, that we had horses doing most of the work. Um, you know, only a little over 100 years ago that was happening. And, uh, the transition to tractor, which people were pretty skeptical around, you know, the horse is pretty convenient. It also fertilizes the field. Um, and so at some point when that transition was well underway, farmers realized they can't bring a giant piece of industrial machinery into town for a repair. I'm going to have to learn how to weld. Nick's perspective is that's probably what AI is. I can't tell you how many farmers that we go and have an interview, um, to talk with them about AI and tools, and they're cutting us off and saying, yeah, but have you tried this? And have you seen that? And we're learning Things from the growers that we're meeting. Um, and what I think is so encouraging about that is when we talk about that future farm with satellites in the sky and tractors that are automated on the ground, uh, there's still very much an important human element there and there's so much volatility and change. Uh, these human orchestrators are more important than ever. And I think these genai tools, this new welding skill is just going to be so important and it's scratching an itch that we've seen for a long time that each one of us, I'm guilty as a tech entrepreneur too, Georgie. We invent a new system, a new tool. We're so excited to get that new iPad dashboard system forecast into the hand of the farmer. And you go and sit down at the kitchen table with them. Um, and they need two monitors now and they have 19 logins and they're just like, not another software subscription please. And I think, I think for those of us that I'm sure you're playing with them too, these tools, um, do just such a good job of taking in all that context for us, making connections. And most of the important problems on the farm are multidisciplinary problems that involve the weather and the futures market and machines. And so I see farmers starting to realize I might have a real coach here that can help me get my hand around this, uh, almost like a new member of the staff.

Speaker B: I'm curious though, not to burst your bubble on the excitement here, but regulation and data, there is of course going to be a lot of data. Sensors, machines, platforms, all collecting this really useful data. Who owns it, who controls it? Does the farmer always know what's being taken?

Speaker A: It's certainly the right question. And look, it's not unique to farming, right? I mean if we're driving, you know, a really modern car that has extensive driver assist. I don't know about you, but I haven't looked too closely at my user agreement in terms of what Toyota or Tesla or any of those companies know about me. But uh, what we know is that in the automotive space, our driver behavioral data and the imagery from our camera systems, those are the things that are making self driving car a, uh, reality. I think you're right. It's trickier from a small business perspective for a farmer operator. And a principle that I've seen applied a lot here is that, you know, the farmer and the farmer's data should be used first to make sure that the farmer benefits directly from their own data and systems. And in a Lot of cases, what you're starting to see is farmers able to opt into sharing and benchmarking type systems in a give to get kind of model, which I think feels fair to a lot of growers. Um, but that's not to say you're right, it is a thorny challenge. And it's one of these things that has to get overcome to kind of imagine that future farm that we're talking about.

Speaker B: So beyond farming, what's the lesson then for a leader in any outdoor industry and for all industries?

Speaker A: Maybe we'll start with the outdoor industries. I hope that's a little more obvious from the conversation today. I mean, I think I am just continually surprised and my colleagues in the industrials practices here at BCG at How fast, um, pick your most cutting edge technology from inside a factory, how fast that's moving outdoors. And so for those leaders working with your teams to stretch the imagination around what's possible, doing experiments and tests, um, and doing more of this grafting of what's working in traditional industrial environments into the outdoors. But maybe I'll take a swing at something that I hope people take away regardless. And here I'm going to crib from an industry, uh, 2.0 story. And maybe you've heard this one. It definitely bears telling from what I've seen on farms. And it's this idea that when electrification was first starting here in the Northeast and manufacturing facilities that were designed around a giant prime mover that was powered by steam and then belts. Right, belts that would move drive trains all through the factory to power a sewing machine for, uh, a factory that's doing fabric. What was the first move in electrification? People just put the biggest electric motor they could in place of that steam motor and left everything else in place. And then what happened over a period of 10 to 20 years is the kind of people that designed and operated those factories started to realize that if they broke the pattern entirely, there's no reason to have a gigantic electric motor. I could have a little motor with every sewing machine and then run power to the machines. And you can imagine how that changed the layout and the productivity of that place. And I think we are, I don't know if we need to say 5.0 now, Georgie. I worry if we say 5.0, we're going to run out of numbers at some point. So whatever you want to call this 4.0 outdoors is at that same kind of moment. It probably is that fundamental. And so I think the thing I'd like to leave folks with is we will probably be surprised. And I would be surprised if we're not a little bit embarrassed by answers that people like me give when you ask, imagine what a fully digital future looks like. I'm probably more in the camp of the guy who's putting the giant electric motor in place of the steam machine.

Speaker B: Well, we've covered the so, uh, what finally, it's the now what? What are the next steps to take to truly benefit from Industry 4.0?

Speaker A: Yeah, well, I mentioned a couple things. You know, one is, um, I can't resist jumping on a soapbox, Georgie, around how easy it is to build software. I'm not it's that easy to build great, important software of record, but to build functional prototypes right now, it's never been easier. And so I hope one thing folks will think about from a so from a uh, what's next? Is pushing your product teams to accelerate testing and learning out in the real world with your customers. And I'd say that's the second thing on a what's next is have a review, have a think about your business, sit down with your leadership team and ask yourself, what about our business depends on strategic advantage that we have that comes from knowledge and data and insights that only we have. And then just imagine that that's going to go away. The way the food system works is going to get rewired and the way that these industrial systems, outdoor industrial systems work is going to get rewired. And so being able to look around the corner with your teams by pushing on some of these bedrock assumptions, I think is a really valuable exercise.

Speaker B: David, thank you so much and thank you for joining us. You can find links to more of David's research in the show notes.

Speaker A: Georgie, thanks a lot for that. That was a lot of fun.