Audio Transcript:

James Mintert: Thanks for the introduction. Appreciate the opportunity to visit with you today. I’m Jim Mintert, former director of the Center for Commercial Agriculture. I’m now an emeritus professor, uh, at Purdue University in the Department of Agricultural Economics. I’m pleased to be here and visit with you a little bit if you haven’t had a chance to take the survey. Uh, go ahead and shoot that, uh, code with your phone. And I think we’ve got maybe a half a dozen questions or so. We’re gonna use responses to the survey during the course of the presentation, so we’ll be showing those results live as we work through the presentation, as we talk about, um, what we’re gonna, uh, discuss with respect to, uh, precision agriculture and technology. So, with that, I wanna start off a little bit though, talk a little bit of background.

[00:00:50] Ag Economy Barometer Insights
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James Mintert: Uh, about 10 years ago, my colleague, Dr. Langemeier and I started a project, uh, jointly with the CME Group called the Ag Economy Barometer, where we survey farmers across the nation every month, uh, to learn more about their perspectives on the ag economy and on the what’s taken place on their own farming operation with respect to profitability and, and just get an idea as to what people are thinking. That survey’s done every month, and we release the results on the first Tuesday of every month, and it’s so happened that that worked out, that we’re actually in the process of releasing those results live on the internet as we speak. So I’m gonna show you some of those results going back to 2015. And show you this month’s results as well.

So here’s the overall sentiment index and that sentiment index is based on five questions that we ask. It’s really mirrors what the University of Michigan has been doing for decades with respect to consumers, except we just talked to farmers and we’ve adapted their methodology to the farm audience. So there’s the sentiment index going back to 2015. The current reading this month, 1 52, that’s up 11 points in February and up 64 points since September. So in the aggregate corn, soybean, wheat, cotton farmers, people that raise beef cattle, people that raise, uh, hogs and people have a dairy operation have become markedly more optimistic about what’s going on in the ag economy in the U.S. And what’s going on in their own farms than what they were telling us last August and September. So a big turnaround in improvement in sentiment. A lot of that, most of that occurred after the November election, so people have become much more optimistic since the November election. We saw this back in 2016 and early 2017 as well, is when people became much more optimistic, expecting things to get better.

We decomposed those results into a Current Condition Index and an Index of Future Expectations. And until this month, the big improvement in sentiment was really about people thinking it was gonna get better in the future. That’s the green line on that chart, that Index of Future Expectations, and it really took off. It started to take off in October, which our survey was done just a couple of weeks before the election in October, and then continued in November, December, and carried over here into the early part of 2025. This month, the Index of Current Conditions really took off jumping 28 points in February, and that’s up 61 points since September.

And before we started here today, we were talking about what’s happened with respect to corn and soybean prices and wheat prices these last few weeks. Our survey in February was done the week of February 10 to February 14. The grain markets did look better than than they do today, so the results for March are probably gonna be different. We’re gonna be doing the March survey next week. I’m thinking things could look a little different, but people became quite a bit more optimistic about that current situation as well as the future expectations.

Then one of the questions we ask is about investments on their farming operation, and that really ties into what we want to talk about here today. That investment index has been kind of sideways for much of the last, uh, couple of years. But really started to improve again last fall and this month in February was up 11 points. That’s a big move for that index, and it’s up 24 points since September. That Farm Capital Investment Index is based on a question that says, do you think now is a good time or a bad time to make large investments in your farming operation? And a reading of 59 is clearly not as good as we got back in say, 2021, when that index topped out over 90 when people were pretty optimistic about investments in agriculture and in their farming operation. But a reading of 59 is, as you look at that chart, it’s one of the most optimistic readings we’ve had, uh, over the last three years. And so that was a little bit of a surprise to us, but it told us that people were ready to make some investments. If they thought the returns are gonna be there. And of course that picture might change a little bit when we do the March survey, but that’s what people were telling us just a few weeks ago.

Michael, one, one caveat on that chart, Jim, is, is the index is below 100, meaning there’s more people think it’s a bad time than a good time, but there, but certainly it has improved, uh, recently.

[00:05:01] The 5 Managerial Levers
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Michael Langemeier: Um, now let’s talk a little bit about where technology fits. There’s essentially five managerial levers a farmer can pull. Uh, two of these related to gross revenue out, uh, obviously output price. Uh, you know, changing your marketing strategy a little bit or working, you know, trying to get, trying to get an optimal marketing strategy. There’s also yields, of course, that’s very important. Technology can impact those, of course. Uh, also costs, uh, manage how much it costs you to produce. And again, technology can fit into that piece. Uh, and then I wanna go to the far right here. Or MyFi far right. Anyway, uh, manage the people that help you with the four levers above. And so certainly, uh, certainly the labor situation on your farm, um, you know, having someone responsible for hr, if you have, uh, several people on the farm making sure that things run smoothly.

The, the bucket that we’re gonna be talking about today is the asset side. Uh, and so technology can have a large impact on what your balance sheet looks like. Uh, but, but it also, uh, can impact these, these other levers in particular yield and costs. And we’ll talk more about that here in a little bit.

[00:06:04] Precision Ag Adoption
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James Mintert: So we’ve done several research projects over recent years to learn more about why people adopt technology and what impact it has on their farming operation. And so the results I’m gonna show you here in the next few minutes are based on some survey work we did several years ago with a couple of my colleagues at Purdue, um, looking at precision ag technologies. And we sorted people that responded to our surveys into some buckets. And I’m showing you the first two buckets on the slide there, the non adopters of technology. And what we call passive adopters and a non adopter is pretty self-explanatory. A passive adopter is someone who has adopted a technology just because it was embedded in a piece of equipment that they already acqui acquired.

So the classic case there is maybe you weren’t really using a yield monitor before. But you picked up either a new combine or in a case of this operation or in that size category, maybe a used, uh, combine that already had a yield monitor in it. And so it’s got a yield monitor. You want to, you wind up collecting the data, you wind up looking at the data and maybe using it a little bit.

So those are folks that are passive adopters, they’re really not adopting technology because they’re seeking new technology, ’cause they’re seeking new information, they’re seeking new ways to, to monitor and, and manage their operation. They’re just doing it because, well, it’s there. Okay.

So if you look at the next couple of buckets, Those are folks that are more aggressively interested in managing their operation in a way that they weren’t doing it before. These are folks that are actively seeking some new technology to make their farms more productive and to try and improve their productivity. So you can see how we sorted the buckets there on the data user side, yield monitors, GPS yield maps, GPS guidance. Maybe starting to do some analysis of, uh, the data that they’ve collected on their own computer, uh, either either at home or with, with someone else.

And then the information seekers are the folks who I maybe would characterize as folks who are. Uh, early adopters, uh, first movers is a, a terminology that gets used a lot when a new technology becomes available they want to jump on it and try it as soon as they can get their hands on it and try and use that, uh, going forward. One of the things that we observed, particularly in those last two categories, but especially those information seekers, one of the ways that they were gathering information and improving productivity was their willingness not only to analyze data on a computer, and in most cases, that probably was somebody on the farm. But also the ability and willingness to share data with someone else. And one of the keys that we observed in our surveys was that people who were willing to share data, um, and manage data more aggressively, spend more time managing that data, extracting information to try and improve their operation, were gaining more, uh, from the technology.

And so thinking about it going forward, one of the things you want to think about is your willingness to share data, um, with other people, whether it be a service provider, whether it be a peer group. The idea that you can just use data from your own farm to make your dec improve decision making, uh, from our perspective is probably a mistake. You probably need to be thinking more broadly than that to gather information from other farms and use that as well as information gathered on your own farm.

So looking more at some of the research we’ve done, uh, I wanna explain this chart first and then I’ll show you where, where folks kind of wind up on it. So, the charts suggest that the green line would indicate for a given level of inputs if you’re on the green line, you’re getting the most out of those inputs. Right. So at any given level of inputs, if you’re on the green line, you’ve really maxed out what is possible or what’s attainable, uh, with respect to the efficient usage of those inputs. And we’ve got output on bushels per acre as an example on that vertical axis. So if you look at the next one, how do you characterize the efficiency of those people in those different groups? The non adopters are clearly not capitalizing on the possibles, uh, possible efficiency gains associated with using precision technology. They’re the least efficient. Passive adopters are a little more efficient than the non-ad adopters, but not much. And then when you look at the data users and the information seekers, they’re pretty close.

So who could gain the most from adopting new technology, new precision ag technology? Well, clearly it’s the folks that haven’t adopted anything. And secondly, the folks that have maybe done some passive adopt adoption, but really haven’t taken advantage of everything that’s out there. So that’s who could gain the most. And Chad’s got some other research he’s gonna share with you later that kind of supports that idea.

And then the second point is, do you need to be that first mover? Do you need to be that person? That’s the first one to adopt a new technology. And our research would suggest that maybe you don’t. Maybe you can wait a little while, but not too long. But wait a little while to de to, uh, make sure that other people have confirmed that this technology does have some benefits, not just a one-off kind of a situation. ’cause if you look at our research, the gain of being that first mover was pretty darn small. And in fact, you’ve taken on more risk by doing that. And if you think about it, you know, think back to an old farm management axiom, which is, um, neither be, uh, the, the first to try the new nor the last to cast aside the old.

That’s kind of the idea here, right? You want to monitor what’s going on. You want to pay attention. You want to be aware of the new technologies, but you don’t have to be the very first, but you want to be following along pretty closely. If something looks like it’s gonna work.

Michael Langemeier: The, the caveat to that, Jim, and I’m not disagreeing here, but it’s the information seekers that, that make that curve move up over time. And so that’s early adopters that, that push that curve up over time. And so that’s why they’re doing it, is they’re hoping there’s enough gain to push that frontier up. But you, you’re all right, there is risk associated with being that early adopter.

Chad Fiechter: Alright, so we’re gonna jump to the results, uh, that you guys said.

All right, so this is, this is the question about do you use data to make decisions?

So, um, I farmed with my family for a while and so this, this puzzle over technology adoption is, uh, something that maybe, maybe I was the one who said maybe we should talk about this as a group. But, uh, ultimately kind of grew up in the age of when, uh, precision ag technologies was really taking off. And I actually was an undergrad in sort of some of the, the early classes around it.

Um, and so this, this idea that we’re moving towards using data to make decisions, obviously this group is really heavy into, uh, using the data that you collect to make decisions for your farm.

So this one I think is a really interesting question because I love that there is certainty in this room that. Uh, you believe that yes, you are, you are using technology to make your farms more profitable. This was an open question for me, and I think probably what is, so maybe I’m the only one interested in this topic, but, uh, one of the things that really drove, um, my concern over technology adoption was, I, I was really struggling to identify what things, uh, made me more profitable. So I love the fact that we, we do have a few people in here who are probably more in my camp that I’m not really sure how technology benefits me. Uh, but, but I love the fact that we have got a lot of certainty, uh, here.

So let me jump back to these slides.

[00:13:24] Identify the Right Technologies
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Michael Langemeier: This is a very important slide. I’d like to tell my students that. And so, um, unfortunately we’re not gonna have a quiz at the end of it. If we did this, this slide would be on there. And so, when you think about technologies, I’m not gonna pretend that this is really simple. Um, and, and, and you need to ask a series of questions here.

Do you resist technology adoption? Uh, do you wait a long time before you adopt technologies? That’s the thing you have to talk about. Are you leaving some money on the, on the ground or, or on the table? By doing that? Uh, does your farm community love or resist technology adoption? Maybe this is your, your, the, the family situation. Uh, does the rest, your family members, uh, not like to pay a lot for this new technology? Uh, who are you talking to about farm technology? Are the, are they the right people? Obviously you’re probably talking about, uh, input providers, but you are talking about others in your community that have adopted similar technology. Has it worked for them? Uh, could technology allow us to farm more acres with the current machinery? This is something we’ve been doing for a long time, for decades. Uh, you buying larger machinery, uh, and saving on labor. And that leads me to the next point. Uh, does technology lower our labor efficiency and productivity?

If we’re spending a lot of money on technology and our machinery investment per acre is really high, do we have relatively, uh, are we relatively efficient on labor and vice versa? I. Uh, if we’re using older technology, it, uh, is, uh, if we’re using older technology, uh, is, is that helping us on labor? Those usually go in the opposite direction. Uh, so looking at labor efficiency and productivity and looking at machinery investment per acre, uh, is really important.

Uh, another thing to think about, uh, when we’re thinking about strategy, we’re either thinking about low cost producer or, uh, different, uh, product differentiation, producing higher value crops. Uh, does technology allow us to grow higher value crops? Is the information we’re collecting there valuable, uh, to producing some higher value crops? And that could be as simple as popcorn or waxy corn, something like that. Uh, could net technology change our crop rotations and mixes? Uh, can we use technology to to, to, uh, think about our crop rotation? Uh, and then I think Jim added this one here ’cause he’s, uh, uh, semi-retired here. Could technology get us to Florida sooner after harvest, uh, to spend more time at the lake? I think especially, I think for Jim, it’d be golfing,

James Mintert: especially Florida.

Chad Fiechter: Yeah. Okay. So we put in that last bullet point, uh, kind of facetiously, uh, but. Uh, ul Ultimately, one of the things that has become really apparent, especially in this, uh, we’re, we’re living it right now with the, the corn and soybean prices, but, uh, is ultimately all those decisions about what technologies we adopt and how much we’re willing to spend rolls up into a bushel of corn, a bushel of soybeans or bushel of wheat.

And so as we’re thinking about how do we adopt those technologies, I’ve got some students, uh, sitting up here that were in my class, a lot of times what we do as. Uh, ag economist is, is trained people how to do these partial budgeting exercises where we identify what are the costs and what are the benefits of everything. So kind of as we’ve talked through this, this presentation, we said, well, what are the simple questions, right, that we could ask around, uh, what technology is doing for us? Or what are these specific technologies doing?

So the first one we put is, will the technology increase the bushels? Right? And this is a simple yes no. And, and how many more? Um, and I’ll get to. A a point on how many more in a little bit. But, uh, the second one being, will technology decrease my cost of production? Um, and so if it does, if it if overlap right? The, the key or, or at least the, the poster child here is, uh, guidance and helping us with overlap, right? If we save that time, uh, it’s gonna decrease our cost. Uh, will the technology allow me to manage my operation better? So one of the things that came out that Jim, you didn’t talk about was this, uh, perception of convenience. Do you wanna say anything about that?

James Mintert: Yeah, so one of the things that did come out in our surveys, uh, of producers with respect to technology adoption is people, one of the reasons people adopt some technologies is just because it’s more convenient, right?

And a classic case. And if you visit with some of the, uh, companies that provide this technology, one of the classic cases was guidance. Um.The initial thought process with respect to guidance was it was gonna be all about efficiency. And you’ve probably all seen discussions and maybe thought about some of this with respect to more efficient uses of inputs, whether it be seed, uh, or spraying. But a big reason why people adopted it was because it just made life easier. It just made life simpler, right? And so, one less thing to worry about, maybe that allows you to be a little more productive in terms of spending more hours in the field. Uh, but still largely about making life a little simpler, a little easier, and that’s a factor.

Chad Fiechter: There’s sort of an indirect benefit, right? If the convenience allows us to be better managers and we could potentially get a higher price output, price, lower our cost of production, or just do uh, things a little bit better, uh, that could also indirectly impact, sort of how we assess the technology. And then the, the last point, and, and this is a point where, you know, I’ll, I’ll be transparent, like, I liked technology, right? Like I got, I got some joy out of kind of knowing what was new and trying new things. Uh, and so there’s a, there’s a component too where we can say, well, I actually want to do this right? This makes my life a little bit better. I enjoy it.

Um, but this last point, this question four of, but how far can we go, uh, in pursuit of this better life if our ultimate goal is to make our living producing commodities? And so in, in this case, um, what I have there is if yes, how much are you willing to pay for a better life, right? These are all, these are applicable reasons why you could choose to add, uh, adopt technologies. Uh, so we’ve kinda at the bottom here, uh, if you add up the yes amounts and subtract the costs and it’s positive, go for it. Right? If, if there’s, if this thing leans in, in the positive direction, let’s go ahead and adopt

Michael Langemeier: Chad, many, many times it’s harder to measure the benefits than the cost. And so when we talk about this in class, what I tell students to do, I talk a lot about risk in class. When I, when I talk about this in class, do what if analysis, how many bushels, uh, would I, would I need to save in order to pay for the technology? How much lower would my cost of production need to be in order to adopt this technology? And so I think that’s how we can approach, uh, thinking about the benefits.

Chad Fiechter: So I made this really cool slide. Um, basically just says everything that I just said on the last slide, but trying to highlight this fact that we, we. If we’re looking at evaluating technologies, we’re, we’re gonna have to look for, you know, what, where are we gonna get more money outta this technology, right? And so I put down there more bushels or lower costs being these direct effects, but then if it potentially makes us a better manager, it gives us more time. And that leads us to higher prices. That could be a great indirect effect. Right? And ultimately we gotta get to how do we quantify these numbers?

So I put on, uh, the, the last point here is this better life component. And I, I think, um, a, as economists, that’s a, that’s a perfectly viable thing. If you can put a, a, a number two, what’s the sort of enjoyment that I get out of these technologies? Uh, that’s a great way to, to think about it.

So I’m gonna shift now, because what we tend to do as economists and what we train students is we do these exercises, right? These partially partial budget exercises. Is anybody looking at this chart overwhelmed?

Thanks. Thanks for a couple chuckles. That helps. I, I would say I, I am right. So we’re gonna quick switch again back to these, uh, menti meter questions. This is a great example of, well, you could, why don’t you give us the history on this.

James Mintert: So this, this was actually a, a spreadsheet prepared by a couple of our former colleagues that, uh, Michael and I, and it’s extremely detailed. It’s extremely accurate. To use it, you would have to fill in every one of those blue boxes. Okay. And if you do and you’ve got a good grip on what all those values are, you’re gonna get some really good information with respect to whether or not you should buy a purchase or purchase a self-propelled sprayer.

We’re not aware of very many people that actually have the level of detail available that allows them to fill in accurately all those blue boxes. So the question is, can you step back from that a little bit and still wind up making good decisions and we contend you can.

Chad Fiechter: Okay, so this, this question was to get it, uh, another point here. So when evaluating a new technology, how confident are you in your ability to estimate the potential benefits? Um, we got a lot of people in this confident and somewhat confident, and then there’s kind of a tapering through the neutral and, uh, the somewhat not confident. So the benefits is, looks like we’re pretty good at this.

The same trend holds here when we’re thinking about costs. So when we get into this, and, and I think this is would be my argument lots of times with farm audiences, is you inherently and intuitively do the process of partial budgeting on a regular basis. This is, this is, you’re very comfortable making these decisions.

Uh, one of the things though that I would challenge is, is here, let’s go back.

If we think about this spreadsheet, oops.

Very few of us are probably comfortable with this level of detail, and so one of the things that I’ve, I’ve wondered about is if you’re feeling. If the reasons that you’re not choosing to do an exercise like this is because you’re not feeling confident in your ability to identify the cost or the benefits, our encouragement to you is.

You’re doing this already, this is something that’s coming really natural as you’re making decisions throughout the time. So maybe the encouragement is to document that or to, to work with someone else to try to verify, are my costs and my benefits, do they seem appropriate? Uh, I remember sitting at the kitchen table with my dad and brother doing this kind of an exercise, and I wish we would’ve went through and kind of, uh, layered things, uh, in the, you know, in, in a more sort of. Formal way, and then I’ll be honest. The other thing is, is we probably overestimated the benefits on a regular basis ’cause we wanted them to look positive. Right, like it was that better life component. We were like, hey, we wanna make sure that we can, I don’t know, get this new tool. The last thing I bought was tracks on a planter and like it was so, it was so much fun having tracks on a planter I don’t know why, I can’t tell you why it was, but it was a great thing. And so I think I remember doing this exercise and I think my thumb was a little on the positive scale as opposed to getting back to it and saying, well, there’s an appropriate amount of money that we could say we just want tracks on a planner. Uh, that’s what something we want to do and not have that exercise be weighted on we, we are a little too aggressive on the potential benefit.

James Mintert: Michael, you were talking earlier this morning when we were discussing this about the idea that you want to approach this from kind of a net present value perspective. You might wanna share a little of that.

Michael Langemeier: Well, ob obviously, when you’re talking about a sprayer, you’re gonna use that sprayer for several years, and those benefits occur over time. And so those benefits in year seven are not the same as the benefits in year one. And, and so you just, just discounting, you know, discounting those future values back to today, uh, is, is very helpful when you’re doing this analysis, uh, particularly with the benefits.

The, the costs, a lot of the costs are, are, uh, there’s some costs that are spread over time, but certainly the cost of the sprayer, those kinds of things, you, you, you know, those, uh, you know, right away. And so those aren’t quite as hard, uh, to think through. And that’s why I was saying, uh, quite often when I, when I talk about these kinds of things, it’s the benefits are harder. It’s harder to estimate those benefits. But, but, but, but my response to that is, is just come up with a first guesstimate, uh, and then do some what ifs. One of my benefits are 10%, uh, you know, not as good as I thought they’re going to be, or 10% better. And, and just see what, see what it looks like.

Chad Fiechter: So with those partial budgeting exercises, there’s these indirect effects that we talked about, about potentially being a better manager. And we’re gonna kind of go through some of these other indirect things, uh, because they become very difficult in trying to assess what are the costs and benefits when there’s things that exist that are, are difficult for us to identify.

So this is a, a research project that I worked on, um, with, with folks down at Kansas State. And, um, we looked at farmers who participate in the Kansas Farm Management Association and looked at their adoption of technology and how it related to their efficiency and generating gross revenue. So instead of looking specifically just at their bushels per acre, we were looking at how can you take your mix of inputs and turn them into gross revenue?

And so the most fascinating thing, and this was a, a series of, um, of farms that responded multiple times to this, this same, uh, data set. And so one of the things that came out of it is the, we, we never saw a negative impact on technology, negative impact on efficiency from adopting technology, right? The technology always paid its way, it always made up for whatever cost they had and some benefit.

And, uh, the places where we did see efficiency gains were when there was multiple precision ag technologies bundled together. So in this case, uh, this is, this is using technologies that existed for, since 2002, right? So we’re talking yield monitors, guidance, uh, grid soil sampling, things like that. When you put those packages together, we were able to see that the farms did advance, sort of in their gross, their ability to make gross revenue with their inputs.

The thing that was the most interesting to us though, and it, and it really ties into Jim’s story in the survey, is that the, the least efficient farms were really the farms that were driving the efficiency gains. So when we took it and we, and we looked at the farms in different buckets, the, the lowest efficiency farms, the farms with the most amount of inputs for their output. Um, when they adopted technology, they saw the biggest gain. So Michael, you’ve, you kind of talked about that a little bit this morning on, on your thoughts on what we, what we think we’re seeing there.

Michael Langemeier: We see the same thing. When we look at productivity differences across countries. It’s, it’s called catching up. Those that are, those that are struggling. Once they adopt that technology, it’s like they leapfrog, uh, that their gap in productivity, uh, increases rather dramatically. I think that’s exactly what we’re seeing with these farm level results.

Chad Fiechter: Yep.

[00:27:48] Autonomous Technology
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Chad Fiechter: So this next one’s, um, it’s kind of gotten me in a little bit of trouble, but it didn’t mean it to. Um, is, is we, we, we did a project looking at autonomy, right? As we think about what is the future of, of farming row crops and looking at autonomy, um, we built a model of sort of, there’s a long history at Purdue of using, uh, sort of linear programming models to model farm management. And so we, we adapted that model and used, um, autonomous machines instead of people driving the machines. And so there’s, there’s a lot of assumptions baked into this model.

Uh, the, the thing that seems to be driving the autonomous conversation, at least for our group, is around labor challenges. And so what that’s what we’re trying to look at is when does that tipping point happen when the labor costs, uh, become high enough that auto running autonomous machines, uh, would be good? And, and the assumptions behind this is that every operation in corn and soybean, uh, production is autonomous. And, and we’re doing it with this idea of lar large machines instead of sort of, we have colleagues who work with small or medium sized machines and many machines in a swarm.

This was looking at what if we just take all of our operations, uh, with, with large tractors, large combines, and make them autonomous? So a lot of setup there to say, what we found is that right now, at $30 an hour in our model, there’s never a scenario where autonomy is better than having labor do the work.

Now you’re probably, there’s, there’s probably a few of you out here who are saying, we probably hit 30 bucks an hour already on labor with whatever we’re paying and benefits and taxes. Um, and so our hope is to go further and, and try to figure out where that break point is. However, the grad student that I’ve worked with is, he said it’s, we’re not even close yet, right? So what I can tell you is at $30 an hour, it’s, it’s never, it under our assumptions.

The thing that is fairly interesting is though that the autonomy does make it possible to farm more acres with the same machines, right? So you can take, and you can extend the same machinery set and you can do more acres because you’re not the one physically operating the machines.

[00:29:49] Creating a Farm Strategy
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Chad Fiechter: Alright, so, uh, we wanted to ask this question of when we’re thinking about these technologies and how technologies are gonna impact the farming operation, one of the things we wanted to get to is, what’s the farm’s strategy, the long-term strategy of the farm on how you’re gonna be successful.

And so we put in these are, these are my buckets. There’s other buckets and someone brought up another, uh, a good idea here. But you know, are you gonna win in the future because you’re gonna have low input costs, you’re gonna have low overhead costs. Uh, you’re gonna be a diversified farm. Uh, you’re gonna, you, you have a, a really strong land base and that’s gonna support sort of the operations in the future. And then use the best technology. So we, we kind of define these as these potential strategies.

James Mintert: So this is where we, in our discussion said, well, what problem are we trying to solve? What is the farm’s root problem? And what data would you need to make better decisions about that root problem? You know, is the problem, the fact that yields aren’t as good as. Do you think they should be relative to your neighbors? What you’re hearing from, uh, other producers, what you’re looking at with respect to county or state averages? Um, is it the fact that you think your cost per bushel are too high? Uh, is there a problem with respect to harvesting? I. You know, one of the things we talked about was, was a kind of a classic farm management problem where somebody says, well, we, we need more harvest capacity, so we need either a bigger combine or perhaps a second combine.

And as soon as they do that, they realize they just created a new problem, which is we don’t have enough hauling capacity to get the crop away from the combine. And then when they fix that problem, they realize that well, the grain system, the leg isn’t, doesn’t have sufficient capacity to handle all those trucks that are showing up. And when they fix that and get a new leg that has more capacity, they realize the dryer can’t keep up.

So the question is, what is the root problem and what are you trying to solve and what data do you need to do a better job of making that decision? And then from a technology standpoint, as you look at these individual technologies, what problem is that technology designed to solve? And how does that solving that problem actually contribute to your long-term success?

Chad Fiechter: This has, this has been the part that we’ve, we’ve tried to hone in on is how can we marry up these technologies to this, the strategy which we believe is gonna make our farm successful in the future. Uh, one of the things that I, that I felt like I observed growing up in a farm community and and farming is there were times when those, the the technology adoption didn’t really marry up with the, with my perceptions of how these farms were successful in the past. Right?

There was farms that were really successful at being low input cost, uh, farms, and then they were really heavy into technology, and it was always a little bit confusing to me is, is this really the sort of route you want to go or are you changing sort of farm strategies?

And so those, those, the questions around what specific task does this technology simplify and how is it gonna impact either the cost or benefits? I think it’s really important as we think through what is appropriate

Michael Langemeier: Part of the, part of the issue here. Uh, uh, Chad, if I, if I may, it is a moving target. Uh, let’s say we’re focused, focusing really hard on overhead costs and, and you buy technology. Well, that short term that might increase some overhead costs, but, but that tech, that same technology allows you to expand and it puts you in a position to expand, which lowering your overhead costs. And so, and so, this is something we have, we have to look at over time. Uh, you know, just because we’re, we look like we’re in really good shape right now in terms of our strategy. We gotta continually think about, are we doing the right things? Go back to my right technology slide. Are we doing the, are we using the right technologies?

Chad Fiechter: Yeah, that’s a good point, Michael.

James Mintert: So coming back to our survey and actually thinking about some of the research that Chad shared, they actually reached very similar conclusions using completely different approaches.

Ours was based on a survey where we asked producers to self-identify where they were at with respect to technology usage and what gains they were getting from that. And again, the people who would benefit the most are the people who have either not adopted any technology or maybe have adopted just a little bit of technology. Those are the biggest gains in terms of productivity, and that was the same thing you showed on the financial side.

And then related to what Michael was just talking about, if you think about technology adoption, think about what’s taken place in the technology arena over the last roughly decade. Just think for yourself about some of the technologies you’ve heard about. And some of those technologies that have already fallen by the wayside, some of those technologies have already fallen by the wayside, and I would contend that in some cases we were adopting technology for technology’s sake without thinking about how is that technology gonna solve a problem on this farm.

So anytime you adopt a new technology or think about it, is the question you want to ask yourself is, how does this new technology address what I perceive to be a problem on my farm? And be honest about that. Right? ‘Cause a lot of us think, well, we’re doing a great job. All right, well you are doing a great job, but is there a way that you could do something better? And would technology help you improve that? But if it doesn’t, maybe that’s not a technology you want to think about. Maybe that’s not what you wanna spend much time on. Right?

So that’s one of the challenges we have in terms of figuring out, because, you know, one of the things we, we thought about before coming to the classic this year was walk in the trade show and thinking about how many technologies you’re being bombarded with. I mean, it’s, it’s amazing, right? And this show has changed over the 10 or so years that we’ve been coming to it. How many more booths there are with new technologies that they want you to adopt, and how do you sort through that?

Well, one way to sort through that is think about what are the issues on my farm that I think need some kind of improvement or could benefit from some kind of improvement that helps you sort through a whole bunch of technologies that you’re gonna be able to push aside and not spend much time thinking about. That’s a way to kind of sort through that and then start asking individually, all right, how would that particular technology really address my problem?

And then thinking about what Michael was talking about. Think about the cost and the benefits, right? And think about, okay, I can’t measure these things perfectly. You can’t measure the cost perfectly. Maybe as Michael says, you could probably do a little better job on cost than the benefits doing the what if analysis, doing the trade offs and saying, well, what if I’m too high on the benefits? What if I’m too low on the benefits? Mm-hmm. How does that sort through? That’s, that’s the approach that I think we would like to encourage. Right?

Chad Fiechter: Yeah. Of course. Uh, I, I also think it from a producer standpoint, um, there was a mountain of data that we collected that we, we didn’t use. And it, we, we dabbled into it and we tried to do things with it, but I felt like that was a good sort of symptom of the underlying problem, right? That we had adopted technologies that was giving us something that we didn’t really know how to engage in a, in a proper way to get value out of it.

Uh, and so I think there’s also a part too where you can think about that. You know, if, if this is, if the product here is collecting a lot of data, what am I gonna do with that data to make a decision that’s gonna impact my cost of production? And, and I think that’s ultimately one of the things that, you know, I’ve been thinking about after not farming for a while, is it all ends up sort of, we’re gonna sell it in a truckload right? Somewhere.

Um, so kind of our, our last point and we we’re gonna have time for questions, which is great. It is just this idea that we, we believe that the technology, and we have touched on basically precision ag technologies. Now, we, as Jim alluded to on the floor, I mean, we, there are so many options out there for new data, uh, data sources that could potentially come in. Uh, farm management softwares, we didn’t even touch that. And so thinking about this is these are clearly gonna be a system together, right? These can’t necessarily just be these standalone pieces.

I think in a sense that maybe in the past we’ve been able to assess sort of like, what’s the benefit of this tractor? It might be the tractor plus the planter, right? Where, where we have to start thinking about it and what about this technology that’s providing us data, and then this technology that’s using that data to make some sort of, uh, decision for our farm.

But that all being said is, that’s only part of sort of your larger farm strategy, right? So that technology is in support of the way that you are gonna be successful in the future as opposed to sort of being like the feature component. Uh, and we did have on there, one of those options was being really good with tech. So I guess technically we can say, we say that, um. But ultimately marrying up those ideas of this is how we have won in the past and this is how we wanna win in the future. And then how do we support that strategy, farm strategy with, with the system of technologies that we’re choosing to work with on our farm.

Other thoughts or should we open up to questions?

James Mintert: So maybe as a wrap up, so whether you look at the research that I was doing with some colleagues, which was survey based and people telling us what they were doing and, and how they perceived the benefits. Or you look at the research Chad was doing, where he was actually looking at financial records coming about of, uh, farms in Kansas and them, uh, um, from with some additional surveys telling about the technologies they were using, reaching very similar conclusions with respect to efficiency gains. And also similar conclusions with respect to the people that benefited the most were people that figured out how to bundle technologies. There were no single silver bullets out there that you could identify that automatically made somebody more productive, made somebody more profitable. It was about bundling.

And then the related point was the people that were particularly in our research, the people that were benefiting the most were people that were sharing data. And so I know there was a big push for a while, a lot of paranoia about the idea of data sharing and being concerns about giving up, uh, access to your own information. It’s pretty clear to us. That there are tremendous benefits to sharing data. And if you’re only using data from your own farm to make decisions, I think you’re really limiting your ability to gain from the technology. So if, if you haven’t made that step, I think you need to think about sharing. And then the next question is, well, who do you share with?

Well, the first step is, you know, you’re gonna share with people you trust, right? That might be a trusted service advisor, uh, in your community. It might be a company. And you know, I not gonna tell you that I would share data with every single company that’s out there, but I’d wanna look at them and think about whether or not that’s somebody I trust. And figure out how to do that in a way that, that you’re comfortable with. And I think you’ll find that to be beneficial. So with that, let’s open up for some questions. Uh, Michael, if

Michael Langemeier: I, if I may, uh, technology certainly can, can, can lead, can be part of a long-term farm strategy and actually can, uh, can, can lead to a better financial performance. But, uh, I want to general, I wanna have, I wanna open this up with a general question.

How do you know if your strategy’s working? I’ll go back to something I’ve been doing for 30 plus years. You benchmark, what’s your profit margin? How does that compare to other farms? What’s your cost per bushel for corn, soybeans, and wheat? How does that compare to other farms? That’s the only way I know of to really figure out whether your strategy is working and uh, uh, and, and as, as we all know up here, there’s a lot of difference in financial performance among farms. Uh, when you talk about profit margin, it’s not that unusual. If you look at, if you look at profit margin over 10 year periods to see a 20% difference between the high and the low. And, and so make sure you’re doing that. Make sure you’re benchmarking and figuring out whether your strategy’s working.

Chad Fiechter: Okay. As everybody rushes to the microphones to ask us questions, um, do you wanna, you wanna say a little bit, Michael, about what the Center for Commercial Ag and sort of the other offerings that we have?

Michael Langemeier: Yeah, the Center of Commercial Agriculture, you can check out our website. We have a Commercial AgCast podcast, uh, which, which all of us contribute to. And so I encourage you to check that out. We also have programs. There is the Top Farmer workshop, that’s takes place in early January, in West Lafayette. So that’s just an example. And all of us teach classes and conduct applied research. And so, we’re really focusing on, those that are, trying to make their living from production agriculture. And so we’re trying to provide white papers, podcasts, and in-person programs to help people increase their profitability.

James Mintert: So if you have a question, there’s two mics. One each in each, uh, aisle. And if you would just stand up and walk to the mic. I’m sure there are some good questions out there.

The very bashful audience today.

Chad Fiechter: Well, I threatened the students that we would make them ask a question, but I won’t only put ’em on the spot.

James Mintert: You already gave ’em a semester grade, so you can’t really, you can’t threaten them with any extra points. So, uh, all right.

[00:42:40] Benchmarking Question from Audience
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Audience Member 1: I’ll be the first one because my husband knows that I’m never afraid to ask stupid questions. So you bring up a great point about benchmarking prices and whatnot. I know a lot of farmers and they don’t like to tell the truth or they like to embellish how well they’re doing. What’s a great spot that we can look at benchmarking? Do the, all the universities have, you know, we can go and get, um, you know, price per acre kind, you know, benchmarks from Ohio State University. But what about benchmarking standards per state? Per acre, you know, per commodity?

Michael Langemeier: Well, first of all, most most land grant universities have some, uh, publications on their website related to financial analysis and financial statements. For example, uh, I have like 20 plus publications talking about financial statements. And different financial benchmarks on the, on the Center of Commercial Agriculture. So you can certainly take a look at that. Uh, also, most states have crop budgets. Uh, some states have livestock budgets. You could also take a look at that.

But one of the sources that I look at, well, I look at several sources. Kansas Farm Management Association, farm Business Farm Management, uh, a group over in Illinois, and then University of Minnesota, FIN BIN. I look at all those sources, both for enterprise benchmarks and for whole farm benchmarks.

Chad Fiechter: The, though, I, I think it’s a great question.

I also wondered like thinking about who are the people who would benefit from you, sort of knowing where you stack up. And one of those people in my mind is your lender. And so if there’s potential to interact with a lender and say, is there some sort of group, uh, even like within the bank, if you work in a bank that has other producers to try to get an idea of like, how do I stack up against these people that are, that are close? And then there are sort of formal benchmarking services, uh, facilitated by land grants, but then a lot of private, uh, companies as well.

Michael Langemeier: Uh, and one of the reasons why I focus quite a bit on, on machinery costs investment per acre and, and labor efficiency is of all the, all the costs on the farm, those two costs are extremely variable among farms. And so there’s a lot of difference in what farms are spending in terms of their, uh, investment machinery, uh, and also their labor. And so that tells me you have to get a handle on those two cost centers.

James Mintert: One. One of the things that’s really been surprising for me out over the course of my almost 40 year career, is the fact that we have these huge disparities in cost to production whenever you look at the financial record systems, whether it’s the Kansas Farm Management Association, uh, FBFM from Illinois, the FIN BIN data, there are always these big discrepancies in cost of production. So we have, we have some people who are really low cost producers. And particularly when you think about Kansas Farm Management and FBFM, those are essentially audited, uh, records. So I have a lot of confidence in those records. There’s always these big discrepancies, a cost of production. So if you don’t know where you’re at on that continuum, you really don’t have a good idea of, of what your problems are. And so it could be an eye-opener and. Sometimes it’s, it can make you uncomfortable because you might discover that your cost relative to peers are quite a bit higher than what you perhaps thought before you looked. But you need to know that.

And once you know that, then you can start zoning in on, you know, what aspect of my operation is causing me to perhaps have cost of production that’s not as competitive with my neighbors and, and other people in the industry as I would like to be. But until you know that you, you don’t have that perspective.

And then I, Michael, you might just share a a and well, maybe Chad as well. Uh, you’ve been working on a project that I really thought was fascinating. It’s, I’m not sure exactly how far along that is at the moment, but you’ve been working on a project to make it a little easier to do some fairly simple, uh, financial computations where, you know, we always talk about this, you need to have a beginning, uh, of the year balance sheet and an end of year balance sheet. And an income statement, and if you have those three pieces of information in a reasonably standardized way, you can generate some of the key financial ratios. That would help you do a better job of managing, and you’ve been working on a project to actually facilitate that. It’s not quite ready for prime time, but you might share a little bit of that, uh, what you’re doing there.

Chad Fiechter: The AI craze kind of bit me too. So, uh, I just wanted to understand what generative AI so the ChatGPT of the world, what they could potentially do for farmers. And one of the things that I can’t stand is entering data. So, uh, and as a farmer, it felt like if you wanted to keep good track of something, you had to enter data, right? That you had to, you had to go into a spreadsheet and punch stuff in. So I was just searching for ways that we could simplify not entering data. And so, um, there’s a lot of these AI models that are produced by other people and you can purchase use of those models and, and, um, use them in, in other applications. So I used some undergrads and we build an application to, uh, read, uh, schedule Fs and pull all of the numbers off of a Schedule F and put them into a spreadsheet. And then if you upload simple sort of, uh, you know, current assets, uh, current liabilities, total assets, total liabilities. You can get to sort of computing these ratios.

The other thing is, is that it does it for you. So, uh, one of the things that I thought is as I moved into a world where I’m teaching people how to do things, I would remember everything that I’m teaching. And then I realized that I googled everything that I was doing whenever I was using it for research anyway. So instead of you having to go and look up how do I compute this financial ratio, it tells you which numbers go in that box from what you entered. And, um, what you should interpret this ratio to be. And how you could potentially change it and gives like simple suggestions on it. So ultimately trying to simplify, uh, the, the process of entering data and then using the data to try to get some sort of an insight on where you’re at as a farm.

James Mintert: So fun, fun project. We got a question here. Yeah, go ahead.

[00:48:30] Autonomy Question from the Audience
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Audience Member 2: I have a question about autonomy. I think autonomy scares a lot of people. Um. Um, and you guys said that if you’re paying less than $30 an hour for labor, you’re not gonna make money off autonomy or it’s not profitable. So where do you guys see autonomy being or coming into production ag or where’s the place for that?

Chad Fiechter: Okay, so I, I think I’m the resident expert on that, which is terrifying. Um, but so I worked with this project was with a, a very seasoned, uh, professor who has spent most of his time in the last few years working in not large, broad acre row crop system. So working in the UK and working in, in other spaces in India as well. And where autonomy seems to really be working there is enabling the production of different crops that we can’t do because of labor constraints. And so if, uh, you want to grow organic carrots, and, uh, the big problem is weeding. If you can solve that problem by mechanical weeding or, or with some lasers or whatever, you know, you can, you can make it work.

And so I think there’s a part where, uh, our specific project was on these large scale machines. And again, I, I don’t wanna say that it’s never gonna work. It just in the current environment and what we understand is happening, it seems like it’s, it’s gonna be a struggle in the near term. Maybe long term it will be, but I do wonder a little bit as you think about the crops that you’re growing and, uh, why you’re growing them. A lot of it is we wanted to systematize sort of these, you know, the, the growing of these crops and we’ve got markets. I would think there’s potential that we could move towards sort of a more diverse crop mix. Um, and that you could potentially do now because you’re not having to hire, uh, large.

James Mintert: Chad, when I think about the slide you had on that, you know, to me it’s, it’s the second component of that slide, which is autonomy allows, allows you to farm more acres with your existing size of equipment and your existing labor pool. And you know, if you think about one of the machinery manufacturers here, I think had a video showing a big tractor, pulling a tillage tool without anybody in the cab. Um, in the short run, I think that’s where Midwest agriculture might be headed in terms of its use of autonomy.

How, how beneficial that’s gonna be to people is partly gonna depend on how they price it. Yep. Um, so there is some value there. Uh, the question and the struggle’s gonna be this trade off between who’s gonna benefit. Farmers or the people selling the equipment. Right. And, and there’s obviously cost associated from, from their side. So that’s gonna be one of the challenges going forward. How do you, how much do you charge for that, that kind of technology? Uh, that could limit, uh, its usage. It could encourage it, depending on how it’s priced.

Chad Fiechter: And we didn’t, our, our model was pretty simplistic in the idea that we, we made every operation be autonomous. Whereas maybe there’s complimentary sort of things where you have, you know, the, the classic example is tillage. You have multiple tillage tool tools running. One is autonomous, one is not. We, we didn’t get into the nuance of that, evaluating that specific application.

James Mintert: We’ve got time for another question or perhaps two. Here we go.

[00:51:35] Precision Ag Cost vs. Benefit
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Audience Member 3: On your one chart, uh, that had the green and then the dots. Can you go back to that?

Chad Fiechter: Said the green. Here?

Audience Member 3: There you go. The one thing that I would like to see, and maybe you have it, information seekers, 86% more efficient. What did it cost them to get there? Versus the passive adapters? What did it cost them? And then you, you, on the other side, you have output bushel per acre. We can’t see what that is. Do you have that data? And then we can make the assumption, is it a good thing for my operation or not?

James Mintert: That’s a great question. So this is based on surveyed information. So people were self-identifying the level of productivity associated with the changes in technology that they were using. So we don’t, the output bushels per acre is stylized on that vertical axis with respect to the efficiency gains. So we don’t have a precise number to, to give you there, but it’s a way for you to think about what kind of gains you might be getting from a different, um, adoption of different technologies. Right.

And so the, it’s, it was fairly clear in the surveys that the non-ad adopters and the passive adopters were noticeably different from the people who were in the data users and the information seekers category.

And one of the surprises for us, based on the responses we got. Was the relatively small difference between data users and information seekers. And so the, the question is, you know, where do you fit on that continuum? And it’s, it’s a little fuzzy, right? We did had to, in the terms of the research, we had to do it some, some chopping in terms of putting people into boxes. But there’s really a continuum there. And so the question is, you know, where do you want to be on that and, and what level of detail do you want to go and, and what level of, uh, precision technology, for example, you wanna adopt, but it gives you an idea as to how to evaluate it.

So that’s a great question. But we, yeah, the research wasn’t characterized in a way where we could actually put numbers on that vertical axis, for example.

Michael Langemeier: And just to comment on the non adopters, we don’t know this for sure, but in my experience, the non adopters, what, what happens there is sometimes those are smaller farms and they’re simply gen not generating enough cash once they’ve taken money out for owner withdrawals to have money to buy equipment that has this technology on it. And so those are probably people that are buying older machines, older technology that doesn’t necessarily have that technology on it. And so and so, even though they could gain a lot by, by, uh, by adopting some of this technology, they, they could be, uh, there could be a lot of restrictions there in terms of their cash flow, uh, that, that would enable them to do that.

[00:54:13] Conclusion
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Chad Fiechter: I think we are at time,

James Mintert: Are we done Aissa?

Aissa Good: I think you are at time, but the one thing that I would mention to everybody, I think, uh, all three of you will be around for a little bit this afternoon. Sure. Uh, we do have a booth. Uh, it’s 650 on the trade show floor, so please stop by, uh, and say hello, and if you have follow up questions for the three faculty, they’ll be around round.

James Mintert: Thanks for coming.