Managing your farm data for profit

Shay

Foulk: Welcome back everyone to another episode of the Ag View Pitch. Today you have Shay Foulk and Lewis Stearns. Lewis, how are you today?

Lewis

Stearns: Doing great.

Shay

Foulk: And if you would tell the listeners where you're located and what you do and what your role is.

Lewis

Stearns: Yep. My name's Lewis Stearns, founder, lead agronomist for Progressive Crop Solutions. We are based in Ohio, but we've expanded out and we're doing a good bit of work across the country now. We provide business and agronomic advice or consultation to growers, and we specialize in taking in spatial data, business data, whatever data we can get, and we normalize that information, clean that information, and then we spit out some tables and some charts and show you some trends that are happening in your data, and then look at, you know, what are some management changes you can implement, uh, maybe to become more profitable, more efficient.

Shay

Foulk: So you just said a whole lot of things— data solutions, data management, stuff like that, uh, that I know a ton of producers have issues with. And obviously you identified that that was a need. How long have you been doing this? Why did you get into that space? And what specific needs did you see growers were not having met that you thought, hey, I can step into that space and provide value?

Lewis

Stearns: Yeah, so I started this in 2015, um, through college and outta college. I wanted to be on the hardware side. Uh, I did a little work with Ag Leader, a little work with John Deere, and after a few years of doing that, I realized there's all this information being collected, you know, there's all this hardware out there, but no one was doing anything with it. Mm-hmm. And I just kind of started as a sideline. I had no, no intention of having a business at the scale we're at today. I was just working out of the back of the family farm's, uh, shop, just wanting to help some neighbors. Mm-hmm. Um, and just realized, you know, how powerful this information is if we can do it right. And, uh, we've just slowly organically grown by listening to growers and, uh, giving growers that information they need. You know, what we do isn't shiny. We don't have a lot of fancy websites right now.

Uh, a lot of the work we do is in Excel and things like that, but, uh, The insights that we were able to glean out of that kind of speak for themselves if you talk to a lot of our clients, and that's what's driven our growth and kind of our North Star.

Shay

Foulk: Are you working with any specific data platforms or, you know, any particular systems, or are you kind of open to helping people wherever they're at?

Lewis

Stearns: Yeah, so we— that's one big thing we focus on. I mean, we're building internal tools, so we are building that not fancy platform, but, you know, we need to, we need to be able to handle the scale we're at right now. We're piecing together 6 systems to give the outputs that we want, but we don't go into a grower's place with any preconceived notions. We come onto your farm and, uh, we want to hear what you're doing now and make little tweaks. We don't want to come in and tell you, you need to do X, Y, and Z because of this. You know, if I'm coming to your place in Illinois, and I'm from Ohio, you know, I don't know exactly about your region, so I'm not trying to be an expert. Let me look at what you're doing now. Let me look at your data and then let me tell you kind of what the data is saying. And hey, can we make some small tweaks for some, maybe some big gains in the future?

Shay

Foulk: So, you know, myself being in the consulting space, with what Chris and I do, you know, I was at a meeting here the other day and a grower, or not a grower, excuse me, a farm operation family, they said, we want you to tell us what you think. You know, tell us what we should do. And I agree with you that sometimes the process is helping them find that solution internally with what they're already doing. But there, I mean, there are situations where it's like, hey, these are good practices, these are things that you should consider. And, and your clients and your customers say, hey, you're the guy, you know, you're the person in the field, you know what you're doing here. So do you feel comfortable going in and saying, hey, here are some recommendations on just what you know of from data collection that here's some best practices that you should maybe be doing differently.

Is that fair?

Lewis

Stearns: Yeah, yeah. Because I mean, I hate to say it, but we come across operations all the time. They're like, oh yeah, we've been collecting yield data since 2005. And I say, that's great. You know, that's going to give us a great background. Let's, let me have that. And let's get started. And they say, oh, yeah, I don't remember where those last 10 years are, or we bring it in and half of it's missing. Or, you know what I'm, it's just, You never know what you're gonna get. And, um, as these solutions that we provide and other companies are providing become better, um, the loss in potential revenue or the, the value of that data just is becoming greater and greater. And you may not realize it now, but that, that stuff does have a value to your operation. Maybe not to someone else, but to your operation.

Shay

Foulk: Do you, I mean, do you think it's to the tune of, uh, tens of thousands of dollars, maybe hundreds of thousands of dollars for some operations?

Lewis

Stearns: Easily.

Shay

Foulk: Yep. And what, in what facet? I'm going to dive into some of your, you know, common data errors here in a little bit. But, you know, what, in what instances would that be that drastic that maybe the listeners are like, okay, yeah, great, Lewis Shea, we've heard, we've heard data, we've heard about data management, but do you have any, you know, stark examples of that, I guess?

Lewis

Stearns: Yeah. So a lot of what we do is we're indexing things to historical production. So we know every year is not the same, but we're, again, we're looking at trends that are similar. So if I'm looking at a field or a zone, and I have 10 years of, of yield information and planting information, and I, the more I know about that field over the past 10 years, the better picture I can get to kind of predict what's gonna happen in the future. You know, when certain things happen, when we get into a drought, when we get into a flood, how is, how is that field gonna react? What management things can we do? You know, what fertility things can we do? And then what kind of, you know, anticipations or predictions can we make to kind of outguess and improve that yield that that field is trending towards?

Shay

Foulk: So I'm going to, I'm going to ask you a little bit of a prodding question here, because I just had a really interesting conversation on this a couple of weeks ago. The gentleman that I was talking to said, do we need to be careful in ag that we're not utilizing some of this historical data as like a self-fulfilling prophecy? Meaning what you said was we have 10 years of data, we kind of know how this field reacts, but, but what if your management practices were off in that 10 years? Are you yield limiting that acre? Are you yield limiting or production limiting, profitability limiting by just taking in the presumption that that 10 years is representative of what that field can do? Or how do you approach that, I guess?

Lewis

Stearns: Yeah, and that's a, that's a great question. We get that all the time. You know, why would I want to use the old information to improve? Well, we have to know how that field has reacted in the past to be able to improve it going forward. And that's where having a lot of information and a lot of metrics really helps because we can pick out, you know, hey, these are the best areas in the field, these are the worst areas in that field. A lot of times the worst areas are the easiest ones to improve with simple things— tile drainage, you know, pH, clearing fence rows, things like that. A lot of what we do isn't— doesn't have to be complicated.

As we get more intense with that and we evaluate those zones, a lot of times we can use topography, we can use climatic conditions, and we can get very technical to kind of say, okay, you know, why is this area the best spot in the field and what is limiting that? So it doesn't become what you're saying, a self-fulfilling prophecy where we're just, we're handcuffing ourselves to what that yield map currently looks like. That's all it's ever going to do, right?

Shay

Foulk: Oh, that's great. I appreciate the feedback on it. And I think it's important for people to maybe differentiate that in their mind that there's a ton of valuable data out there. Don't overlook what you already have to extrapolate to the future. Yep. I'd like to turn a little bit here. So we're at a, you know, we're recording this here, the first part of December of 2023. But more so importantly, we're at the end of one season. There's a bunch of data that people have from the year., and then they're looking into 2024 already, improvements, things like that. Uh, so I had reached out to you and asked, you know, what, what are some things that producers need to be considering, uh, at this time of year? And, and I maybe just have you dive into a couple of the topics and then I'll, uh, bounce some questions off you.

Lewis

Stearns: Yeah. So when I get handed a pile of data, uh, whether that's several years or, or just one year, you know, there's a, there's usually a list of things that I anticipate that are maybe wrong with that information. Number one, just mislabeling of products. A lot of people want to evaluate, you know, varieties and different things like that with their yield data. That's fine. That's easy to do. But when you're changing varieties and you're in a hurry that, that day you're planting because rain's coming and you change the variety in the planter and you make two passes with the old variety mapping and you forget to make that change, that's going to skew that data. So being able to correct that and go back or at least make a note and pass it along and say, hey, listen, you know, I've got 80 feet or I made 2, 3 passes here. We need to correct that.

But that's our number one error is mislabeling of varieties or chemical products or just different things like that.

Shay

Foulk: How do you, how do you fix that if you don't remember what the hell you did when you were planting or combining?

Lewis

Stearns: Yeah. And there you go. That's bad. You can't, that's bad data. You know, if we're not, We've, we've gone to the point where, um, our clients, we give them a field notebook, the old school. Yeah. You know, everybody remembers the old school Pioneer notebooks. We do something similar to that and, uh, we put it in their cabs and we said, just write down anything and everything as you're going. And that'll help us kind of remember that. Awesome. And everybody makes fun of us cuz they're like, you're a digital company, why are you giving us, you know, paper?

Shay

Foulk: And it is just sometimes tried and true works.

Lewis

Stearns: Exactly. And then we col— we try to collect those when we collect the planning information and that way hopefully fix it ahead of time.

Shay

Foulk: Okay. Yep. So mislabeling of products. Now, one thing I was talking— my brother-in-law's in the, in the agronomy space too, and I was talking with him about, you know, consistency with like large data extrapolation. And I don't know or think maybe that you're doing some of that by hybrid within your company. But, you know, so if you have a certain DeKalb number or certain Pioneer number and you're looking across broad acre spectrum, Well, I might type it in as 1197 and someone else types it in as Pioneer 1197 and someone else says P1197. Do you do any of that at broad scale, I would first say? And then second of all, how do you apply that on a farm level basis?

Lewis

Stearns: Yeah, we do. So we do a lot of aggregation as long as growers, you know, opt in to our aggregation. Okay. We'll provide that information. And we're lucky enough, uh, one of the systems we use is old, but it actually, there's an automation to that, uh, where it, it can kind of guess and then if it thinks that it's off, it'll just flag it and say, hey, um, do you want to correct this to Pioneer 1197 or, you know, 1196, whatever that might be.

Shay

Foulk: So, uh, what system is that if you don't mind sharing?

Lewis

Stearns: Uh, that is called AgStudio.

Shay

Foulk: Oh, okay. Yeah. AgStudio.

Lewis

Stearns: Gotcha. Yeah.

Shay

Foulk: So I've heard that name in a long time.

Lewis

Stearns: Yeah, it's old school, but like I said, a lot of what we do isn't fancy. And, and the, the post fixes are the, are the biggest things like the AMs, the AMXTs, you know, those are a lot of the biggest things that get typed in wrong.

Shay

Foulk: Okay. All right. Onto the next one.

Lewis

Stearns: Yep. Uh, the next one. So this is gonna, uh, go mainly into harvest data, but calibrations. So the first one, um, and I'm gonna talk a little bit, I guess, to corn. As, as we rank things, you know, biggest, the biggest, one of the biggest errors we see is a lot of people are starting corn at 28, 30%, and maybe they're finishing up at 15, 16%. Yep. Right. We know that material flows through that combine differently. And a lot of times, you know, growers think that if my combine's measuring the moisture accurately, it's measuring the yield accurately. And that's not necessarily the case because the way that stuff flows through the combine and hits the impact plate is different and that influences the yield. So that's not necessarily the shrink that needs to be into account. That's more so a flow issue and a measurement issue.

So we like to say for every 5 points in moisture that you change, you need to recalibrate or have some kind of different calibration. This is important not only, you know, as you go through the season,, but also as you change varieties or change fields, you know, you get in that midpoint in the season, you might be going from fields that are 16 to 25. Um, even the automated stuff like the, the Deere, um, Active Yield, it takes a while for it to calibrate in and catch that. So you want to be upfront with that because all that data you're collecting on that wrong calibration. Can be fixed, that it's really hard. And my guys get really angry with me when I hand them that information and, and tell them to fix it. So making sure that we're changing calibrations, uh, when we're changing big moisture, we have big moisture swings.

Shay

Foulk: So only big moisture swings. If I'm going from 18% of one hybrid to 18% of another hybrid, that's not as big of a deal as far as crop flow through that machine. Is that what you're saying?

Lewis

Stearns: But yeah, so that's, as I rank my list, that's number 3. And this is something that growers get frustrated with me on because I'm calling them as they're running if I can see their Climate or their OpCenter. And I'm saying, hey, you're in this field that has a split planter. I need you to take that buggy weight on a couple strips of variety X and a couple strips of variety Y. Because again, that material is going to flow through that combine differently. Yep. And Everybody wants to make their seed decisions on these split planter trials. You know, we've seen as much as 18 to 20 bushel difference or error from what the combine says versus what the scale card's telling us on those strip trials or the split planters.

Shay

Foulk: So full agronomist hat on, do you like split planter and the yield data that you get out of that? You know, I— this is a personal preference question, I guess.

Lewis

Stearns: We used to, and then as we've gotten, you know, big into this analysis stuff and the, and the stuff we're doing with the yield data, we think it actually skews or kind of ruins what we're trying to do. And we think it's going to be a problem going forward, honestly.

Shay

Foulk: So what about, you know, a lot of the farm operations around here that do it, they do it as an offense-defense mechanism or high yield, you know, wind protection, whatever it may be. So there may still be value in that, but how are you extrapolating that data? So I guess, is the juice worth the squeeze when it comes to that plan?

Lewis

Stearns: It's a little bit unknown right now because like I said, we're, you know, we're a fairly new company and some of the, the most in-depth analysis stuff that we're doing right now is only a couple years old. We don't know how it's going to affect things, but when we can see strips through the field that are straight lines, usually that's, that's not a good sign for what we're trying to do. So, okay.

Shay

Foulk: And the main reason that I ask is I've, I've not really heard anybody give a clear answer on that, on right, wrong, different seed company, agronomic service. So I just appreciate your input on that, I guess.

Lewis

Stearns: Yep.

Shay

Foulk: Okay. So, uh, calibration on strips throughout the field, make sure that you're getting, you know, weighed. So they're saying, okay, Lewis, I'm supposed to drag around a, uh, seed buggy tender with me and get weights every 2 hours and How in the hell am I supposed to get anything done? Yep. But there's dollars at stake here. And if you want the name.

Lewis

Stearns: Yeah. And it doesn't have to be that in-depth. Well, we—

Shay

Foulk: I know I'm being a little facetious.

Lewis

Stearns: Yeah. Yeah. The big thing is we just wanna know what's the percentage error that that combine is running in variety X is the percentage of error in variety Y. And we'll clean that up on the backside. We're not asking you to, to change the calibration going through the field. We're not asking you to take a million weights. Let's just take a couple measurements and make sure that we know what that spread is in that error so we can make it fair, so you can make a good decision.

Shay

Foulk: Okay, that sounds good. What's next on your list there?

Lewis

Stearns: Um, multi-machines. So having a couple, you know, 2, 3, 4 machines in a field or running in different fields, knowing what those machine errors are, you know, even if they're not running side by side, that can throw off the field the field yields. And again, even with things like Active Yield, we still need to be checking that stuff in, at least once a day we say, especially if you have scales on your cart. And if we're not going to measure every load across some kind of scale, let's just kind of watch that percentage of error because different machines react differently. I don't care how much we like to say the newest technology is so accurate. There, there's error out there. So if you're running multiple machines, track the percentage error in calibrations. And again, we'll fix that stuff. We're willing to fix that, but we need to know what the error is.

Shay

Foulk: So what if, what if everything— and I'm just thinking of Chris's operation— every load goes across the scale, you know, commercial moisture tester, yada yada yada. So by field, by load, by truck, they got all that data. How easy is it to, you know, back— what's the word?

Lewis

Stearns: I'm, I'm Drawing a blank on the word, but back calibrate is kind of the word. Back calibrate. Yeah.

Shay

Foulk: You know, back calibrate on that information. How easy is that and is it, is it as accurate as you would like it to be when compared to the machine data that you're pulling off with your calibrations?

Lewis

Stearns: Yeah. So you're kind of talking two different things. If we're talking, if everything's coming outta one combine, it's fairly simple because we've, we've got kind of one curve of error. But when we're talking two combines, even if we know what came off that field, how do we know that combine 1 is reading 7% high and combine 2 is reading 3% low? You know, we can, we can make some assumptions there and get close, but if we have the exact errors, we can really dial that in and make a really nice clean yield map.

Shay

Foulk: So yeah, so the yield map, that's where it's most important is if you,, you know, what you referred to is you could have a 10% swing there. Yep. And, and maybe not show an accurate picture. Those two combines could be going down the same strip and you got one that looks, you know, green and you got one that looks a little less green because their, their error is just that far off.

Lewis

Stearns: Yep, exactly. And all our yield data or all our clients' data, if they have some kind of correction, we're gonna go back and correct it no matter what it is. 'Cause we see the importance of it. So, If we get scale tickets or we get, you know, cart weights, whatever we get, it's gonna get corrected automatically across their whole operation. It's just these little tweaks field by field that are really important. Not necessarily to the maps. The maps, yeah, it is frustrating cuz you see some strips, but when we give guys their, our kind of scorecard with these trends and stuff I talked about, that influences those numbers tremendously and can affect those trends. You know, in ways that, that you wouldn't believe until you actually seen it yourself.

Shay

Foulk: Okay, our multi-machines, need to make sure that you have those synced accordingly and that you're getting the calibrations done so that you have accurate YieldMap information.

Lewis

Stearns: Yep.

Shay

Foulk: All right, what do you got next?

Lewis

Stearns: Um, well, the last one is just improper storage of historical information. The cloud has been fantastic, but those of us that have been using it for a while know that every now and again, usually, you know, once or twice per season, something doesn't make it to the cloud, no matter how new your machine is. So catching that and knowing that there was an error, getting that information into that cloud, but then also backing up hard copies with these corrections that we're talking about., you know, on a thumb drive, old school with a notebook or something like that, uh, in that thumb drive, throw it in the safe and just have it because we've seen some crazy cases where, you know, things happen in a digital world. Um, and you don't want that information gone. So, so have a secondary backup.

Shay

Foulk: Talk through what that would look like. I mean, how often are you wanting to pull data off the monitor? You know, are you doing it multiple times throughout the season at the end of the season?

Lewis

Stearns: Just depends on the size of the operation and what the grower is comfortable with. A lot of times we'll say, you know, after you finish beans, pull the information off. After you finish corn, pull the information off.

Shay

Foulk: Okay.

Lewis

Stearns: Pull that machine information off, put it on a thumb drive, you know, put a document in there on that thumb drive with some notes and some corrections, throw it in the safe. You never know what you might use it for in the future. But different platforms, I guess what I'm trying to say is different platforms require different information. Some still require raw information from the combine. So even if you are gonna pull it down from the cloud, a lot of times you're not getting the raw information. You're getting some kind of shapefile or something that some platforms don't like.

Shay

Foulk: Okay. I'm gonna ask you some personal preference questions here on, on kind of the last half of this. So if I had to, if I had to press you a little bit, what systems, or, or either through data collection or just, you know, equipment systems. What do you like working with the most? What do you think has some of the best data out there? If there's growers that are saying, hey, I like green or red or yellow or blue or whatever, but what I really care about is the best data that I have moving forward.

Lewis

Stearns: Uh, so I guess I'm just gonna be honest with you and we'll see what kind of hate mail we get. You know, the, the, the red stuff tends to be the most difficult to work with and has the, the highest loss rate. There's several times through the year, um, that we'll go pull a card out of a Pro 700 and there's nothing there. And there's no worse, worse feeling for me and no worse feeling for the grower than knowing we put all that time and effort into that and that card wasn't logging for that season.

Shay

Foulk: Why does that happen?

Lewis

Stearns: We honestly, we haven't been able to figure out a great, um, trend or anything that's causing it really. A lot of times you don't even know it. Um, there's some best practices that we put in place with growers is, you know, make sure you're using the factory thumb drive, make sure you're cleaning that thumb drive and, and have it ready to go. But we've had some guys that have been set up perfectly and you go to pull that and half the data's gone.

Shay

Foulk: Case doesn't have an answer for it.

Lewis

Stearns: Not a great one. Okay. And maybe the new guys are listening to the podcast.

Shay

Foulk: There was a little smile there and I'll, I'll save him some of the hate mail here. So we, we were on Red Equipment. Pro 700, in my opinion, is like the worst thing that's ever existed. You know, you just— I put it up on Twitter here a while ago. You know, no one says anything. Absolutely no one, not a soul. And then the Pro 700 says, Your task file is full. We've created a new task. And then you're like, you're like 37 acres into a field and you're like, what the hell is happening? Why is this, you know, all your data? I mean, it's there, but it's, ah man, it's just so inconvenient. So, yeah.

Lewis

Stearns: And the new ones are, I think the new ones are, are gonna be better from what I'm hearing, you know, those are starting to, yeah, starting to trickle in. We've seen those in the planning, planning situations and, and they've been pretty good. But a lot of growers that have the, the Case combines are easily retrofitted with some kind of Ag Leader. Okay. And they're still very good for the aftermarket stuff. I mean, they're about as good as it gets.

Shay

Foulk: Okay. So Ag Leader's good in the space. So you went to, you went to worst right away. What's best? What's top of the line that you enjoy working with?

Lewis

Stearns: Yeah. I mean, like I said, Ag Leader is good. Another frustration, and I hate to be negative about all this, but the Deere Active Yield System is great in beans. I mean, we see that thing 1% all day. Yeah. You go to corn and a lot of times it's worse than what the old school monitors were. And we can't predict, you know, what day it's worse on and, and why it's worse because it's constantly changing.

Shay

Foulk: Right. Really?

Lewis

Stearns: Yep. And, and as we talk to growers across the country, work with growers across the country, this is something we're putting together. As the corn dries closer to 15%, yeah, it gets really accurate, but, How many people are harvesting 50% corn nowadays? So that's a frustrating one. You know, I'm still, like I said, I, I like the old school Deere, the old school Ag Leader, and, and the new stuff with Active Yield is fine in beans, but I think we just have some work to do on the corn side.

Shay

Foulk: Okay. Uh, you working with many wheat growers?

Lewis

Stearns: Yeah.

Shay

Foulk: Okay. Uh, anything in wheat in particular, any notes? We, we kind of leave wheat as its own little you know, kids standing off in the corner over there sometimes. So any, any notes or comments there?

Lewis

Stearns: Not really. I mean, wheat's fairly similar to soybeans, I think, in how the yield data is collected. A lot of times there's kind of two different segments of wheat. There's Western wheat that's always has a really low moisture, and then there's Midwest wheat that we might be starting at 25% and finishing at 12%. Same principles apply as corn. We have— we want to be checking that as the yield or moisture comes down. Just for flowability purposes. But other than that, no real differences in wheat data.

Shay

Foulk: Okay, so to wrap up here, if there's listeners that are, you know, either they've been doing some data management things, maybe they're not happy with who they're working with. Maybe they're, maybe they've not done anything. And they're just like, hey, I need to do data management. What, what's the most important— or the key recommendations that you would have going into 2024 of like, hey, here's what you need to do to, to get your house in order, either with data that you currently have, or here's how you need to plan for the year ahead.

Lewis

Stearns: Yep. So just correct or collect accurate information, you know, do go down the list we talked about, follow that list, make sure we're collecting accurate planting data, accurate fertilizing data. And then we're getting accurate harvest data. Once end of year comes around, you need to start thinking about what am I going to measure that data against? And that's where, you know, I talked to you, or we've discussed a little bit about benchmarking it to different attributes. Uh, one big attribute we like to measure against is historical production. Right or wrong, that's what we like to do. We like to say, you know, this zone in this field historically is the best one. And we can say this year we put on this amount of fertilizer, this amount of seed, we got this amount of bushels with this weather. Why did that overperform or underperform?

So we would encourage you to think about it from that standpoint of don't just think about it in the year that you're in, think about it historically.

Shay

Foulk: Okay. One thing, That you said there kind of triggered another question. So from a fertility standpoint, or, you know, custom fungicide application, is there any communication that you as the farmer should have with your retailer on getting as-applied data? You know, what would be some communication recommendations there that you see?

Lewis

Stearns: Yep. So all of our growers across the country we're working with now, we are upfront with them when we give them a fertilizer recommendation. And we say, hey, where would you like these files sent? We're going to— we tell them we're going to ask that retailer for their digital copies of their as-applied maps, no matter how archaic they are or how much they kick and scream about it. We need that information, not because we're questioning the job they're doing. But like I said, we just want to know everything that happened on that field. We want to know the date that it was applied. We wanna know that the rates were accurate. We wanna know that, hey, I had another 500 pounds in the back of the spreader over here and I ran it out in the, in the back corner.

You know, that's information that we would like to know when we're trying to get down to the nitty-gritty of this, of this data.

Shay

Foulk: How's the response on that?

Lewis

Stearns: It's getting better. As retailers upgrade equipment, it's easier for them. They're not having to go out to the TerraGator and pull thumb drives every day. You know, a lot of this stuff has Slingshot or OpsCenter Cloud. It's getting better, but, you know, and I understand on their part, you know, they're trying to be efficient and they have a lot to manage. But if you're upfront with them, usually it's fine. And just make it known, hey, I'm not trying to question the job you're doing. I just need records of this that aren't in a PDF so I can put it into my system and analyze my data against it.

Shay

Foulk: And by the way, if you're a grower, you should not feel bad about that question. Like, this is your farm, this is your data, this is your information. And if your retailer's unwilling to do that, then you should probably be, doing some soul searching, looking around there.

Lewis

Stearns: Yeah. And one note that I did make, Shay, that has been a game changer, and it's something that we just started doing last year, was, uh, looking at soil test information and benchmarking that against yield and historical yield. And that's really opened our eyes to maybe some inaccuracies or some improvements that we can make over some of these university recommendations. You know, the Tri-States, the, the University of Illinois recs.

That stuff's a great starting point, but when I start to break down your field and I'm looking at the yield trends and they're strictly following potash or boron or something like that, and we see as boron increases, yield increases, and we can find a solid trend in that, I can write a nice recommendation to say, all right, we're going to improve zones 5, 6, and 7 because they're low on boron and they're the same as this soil over here, so they should perform the same. Does that make sense?

Shay

Foulk: Yeah, that's awesome. Um, I guess, who is your customer base? Who do you like to work with? Um, you know, if there's someone out there that's like, I, you know, I don't know if I'm a good fit after listening to this conversation, you know, who do you work with? Where are you? You know, how far is your reach? Could you expand on that a little bit?

Lewis

Stearns: So our big thing is we just want growers that want to do better. Uh, we're not big on size. I mean, obviously the farther away you get from our current coverage area, It'd be nice to have a little size, but we're not going to, you know, we're not going to turn you down. We just want people that want to do better. Because if I'm putting all this time and effort into it and you're going to pay me to do it, I don't want to fight you tooth and nail around every corner for every recommendation we're going to make. You don't have to follow it. You don't have to follow it, but at least have the willingness and the open-mindedness to listen to what I'm going to say and want to make improvements. And then let's work together as a team.

Shay

Foulk: I really like what you said there. You know, Chris and I have had this conversation a lot, like with Profit Manager on cost of production analysis. I don't want to sell someone a tool that they're going to use once and then put up on the shelf and look at like a nice shiny tool on the wall in their shop. Like, we want something that you're going to use. And if you're not, you know, if you're not going to be dedicated to using it or whatever, you know, I don't want to sell you something that you don't need. The other thing that I recognize in our space and kind of one of my final questions here, is there's other good cost of production systems out there. It all just boils down to— or I shouldn't say all, but a lot of it boils down to how much you're paying for it. Is it subscription-based versus one-time-based? You know, what are the fees?

Who are you getting when you pick up a phone if you have a problem? You know, user system interface with you as the farm operation. With all that being said, I understand that that's what our space is like. There's other, there's other good people that are doing things in the agronomic world out there. What, what sets what you're doing apart? You know, why would someone want to work with you versus some of the other systems? Just any thoughts on that?

Lewis

Stearns: Yeah, I think it's two things. Like I said, we start out with no preconceived notions of your operation. I'm not going to walk in your door and tell you how to farm and tell you that, you know, you need to do X, Y, and Z because that's what we see in all other farms in Illinois, right? I'm going to cut, I'm going to listen to what you have to say. I'm going to listen to what your data tells me. And then we're going to come up with a plan that makes sense to both of us. And we're going to take baby steps, small improvements to hopefully have big outcomes. The second piece is, honestly, I don't know, we haven't come across very many companies that are, are analyzing and benchmarking data. And giving growers scorecards like we're giving. Like I said, a lot of what we do isn't fancy. I don't have a fancy website. We don't have a fancy interface.

I'm handing growers a lot of paper copies of spreadsheets. But those spreadsheets are powerful, because that is their data on their farm. And we can back up and say, you know, this seed rate is the right seed rate because, or this variety performed this way, because. We're not just guessing or saying, you know, trust me, Shay, you need to do this.

Shay

Foulk: Could you expand just a little bit more on your scorecards? You've said that a couple of times. I want to make sure that we're, you know, hitting on that because it seems important.

Lewis

Stearns: Yeah. So without— it's really hard without showing you an example of it.

Shay

Foulk: What is—

Lewis

Stearns: what a scorecard is, is a summary of a particular attribute and all of the measurements we take against that attribute. Okay, so seed rate is just an easy one. I bring that up. If we make you a VRT seeding script and it goes from, on, on corn, 28,000 to 38,000, just say we're gonna lay out every acre that we planted at 28,000 all the way down to 38,000. And we're gonna show you what was the yield you got in all those 28 zones. What was the yield, or what was our yield goal? What was the percentage of that target that we achieved? And then there's a bunch of other different metrics. So we're gonna break down soil type, we're gonna break down elevation, we're gonna say, Did the low ground, you know, where we planted 28,000 perform better than high ground where we planted 28,000? Seed efficiency.

So I don't know if you've heard of bushels per thousand, you know, in measuring how many bushels we're getting out of 1,000 seeds.

Shay

Foulk: Some people really like that metric.

Lewis

Stearns: Yeah, it's not something I'm completely sold on yet. I get the concept. Yeah, I've stared at it enough to see some errors in it, but That type of stuff is what is included in that scorecard. And really what it does, it's telling us why. And I'll be upfront, you know, it, it's, it's not to prove that we're doing everything right. It's to pick out everything that happened and hopefully have that grower see why that happened. And then we can make that management change or that agronomic change to fix that problem so we don't repeat it.

Shay

Foulk: Okay. So I'll, I'll lean into this a little bit because there's times where I get, uh, you know, soil tests back, or I get tissue tests back— excuse me— you know, I get those tests back and I look at it and I can generally tell, you know, high, good, low, however the test is laid out. But at the end of the day, that can be overwhelming, you know, as a, as a grower to sit there and look at that and say, okay, this is great, I think generally my metrics look good, but what do I need to do? And sometimes that friction point right there is where things get lost in translation, where you're just not having the agronomic input. You know, the retailer doesn't make the time to get with you. And I'm probably guilty of that too, of not just saying, okay, I need to analyze this, we need to discuss it so that I have a point moving forward.

I'm guessing by the look on your face there and you nodding your head that you're taking the time to do that with the growers of just sitting down and saying, hey, I think this is what this means. Here's some things that we should consider.

Lewis

Stearns: Yeah. Yeah. That's— growers want the, you know, the bulleted list, the top 5 things that this information tells me and what can I take away from it and what do I need to do to improve? Explain why, but they don't have— they don't need to understand all 15 pages of the scorecard I'm talking about in every little metric. They need to know what the big things are and what they can take away and what they can change to improve their operation. And that's where us being on the farm and being a small company and careful on our growth, where it's important to us in the delivery of that and the interpretation of that.

Shay

Foulk: That's, that's, I don't think we could end on a better point there. Um, last thing I would have for you, if people are interested in reaching out and, uh, getting ahold of you, how, how's the best way to do that and where can they get your information?

Lewis

Stearns: Yeah, so I'm on LinkedIn, Lewis Stearns, Progressive Crop Solutions, and then our website, progressivecrops.com. We just launched a new website. We've came out of the stone ages. Like I said, we've, we've been lax on marketing and different things like that because we've been blessed with organic growth, but progressivecrops.com. My phone number also, 419-889-2254. Happy to entertain any questions, comments, feedback, anything like that.

Shay

Foulk: And I think as we head into 2024, the key message here is, you know, getting your data in order. Do you have things set up in your operation how you need to? Are you taking advantage of it? And one of the notes that I made here is we have the basics out there. We have fertility and pH and drainage and timeliness. We know how to do those things. And I think, I think growers, farm operations, business managers listening to this need to understand that data is now part of the basics. And we need to have that information moving forward. So Lewis, I appreciate you taking time to extrapolate on that and, uh, look forward to linking in again down the road.

Lewis

Stearns: Yep. Thank you.

Shay

Foulk: And thank you everyone for listening to another episode of the Ag View Pitch, and we will catch you next time.