Learning Without Scars
As a third-generation educator, it is easy to say that teaching and training are in the blood for Ron Slee. From his beginnings as a coach, through his time at McGill University, Ron developed a foundation for the work he does today. From working within dealerships, to operating a consulting company, creating a training business and running twenty groups, Ron has been directly involved in this Industry since 1969. Ron has been known as the industry expert for years, and has brought this expertise to bear through his training programs. Today, Ron provides specialized, job function based internet based subject specific classes, job function skills assessments, as well virtual seminars and webinars. These courses are designed for manufacturers and their dealers, as well as independent businesses in the construction equipment, light industrial, on-highway, engine, and agricultural industries through Learning Without Scars (www.LearningWithoutScars.com). This platform is a continuation of the work begun by Quest, Learning Centers which was established in 1996. This training is aimed at improving dealer parts and service operations through qualified people that are knowledgeable in using operational metrics and current market and operational best practice methods.
Learning Without Scars
Why UCC Filings Mislead Equipment Sellers
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If you’ve ever planned territory coverage or “market share” off UCC filings and still felt confused, you’re not alone, and you might not be the problem. We sit down with Nick Mavrick of Built Data to question a 60-year industry habit: treating UCC filings as the source of truth for construction equipment demand. Nick explains how UCC data can overweight the smallest firms and create a distorted view of fleet ownership, buyer strength, and real opportunity for equipment dealers, OEMs, and rental companies.
We walk through what a corrected market view looks like when you model companies instead of just transactions and validate the curve with multiple data sources. That means bringing in firm revenue and employee size, credit and capacity signals, and the broader context that better reflects how construction equipment markets actually behave. The result is a clearer picture of concentration: the small set of large contractors and fleet owners that drive a big share of equipment value, plus the long tail of smaller businesses that come and go.
From there, we get practical about execution. We talk market share by brand and territory, share of wallet, and how you can overlay buyer intelligence with CRM systems like Salesforce to create a closed-loop sales funnel. Measure each stage, spot gaps early, and course-correct fast instead of waiting for a market share report after the fact. If you care about capital allocation, sales coverage, and raising margins in a volatile industry, this conversation gives you a sharper map. Subscribe, share this with a teammate, and leave a review with the biggest myth you want the industry to drop.
Visit us at LearningWithoutScars.org for more training solutions for Equipment Dealerships - Construction, Mining, Agriculture, Cranes, Trucks and Trailers.
We provide comprehensive online learning programs for employees starting with an individualized skills assessment to a personalized employee development program designed for their skill level.
Aloha and welcome to another candid conversation. We're joined today by Nick Maverick, who his last name kind of indicates the kind of individual is it's a bit of a maverick turning over stones that other people have have left sitting. And Nick operates a business called Built Data. And if you've listened to these podcasts, he's a very interesting man who's got a fair amount of horsepower and walking down new roads to help us all. So with that as the introduction, I wan I want to get Nick to explain to us the industry has used UCC filings for about 60 years as a tool to determine market opportunities. And that's all I'm gonna say. And Nick, I'm gonna say we've we've had many, many things where the status quo has been protected for a long time, but very few that have lasted 60 years. What are you doing to replace our traditional view of UCC filing so that we have a better read on what happens in our markets? There's an open question for you.
SPEAKER_02Yeah, well, first of all, Ron, thank you for uh being a blessing and um for uh quite some time now. And the names of folks that you associate with are world-class, whether it's Jay Lucas or Steve Clegg um and others, you know, dot dot dot. So thank you. Regarding UCC filings, um in my career, I probably have, under decisions that I've made, um, have probably bought a million dollars worth of that data. I would say it's a fair sum, in different corporate roles, whether it was Volvo or other companies. And for many years, I looked at that data as if it was um the source of truth. And in much of my um career, I looked at it as a representation of the market. And late in my career, I realized that it was very, very distorted. And uh, you know, if we define UCC finance, these are liens, it's free public information that can be um accessed uh virtually in every state in the United States. It's free public information.
SPEAKER_00Basically, it's every machine that was financed, correct?
Why UCC Filings Distort Reality
SPEAKER_02Well, good question. Not necessarily. And when you when you peel into it, and I can show you a graph momentarily, it really is the um it generally is a lender seeking to secure a public filing with a very small borrower. And and the data shows that. So if you look at the population of companies, about 62% of the dollar value of all UCC filings congregate with the smallest companies in the United States. So it congregates with companies less than a million dollars in revenue and less than 10 employees. Okay, so hold on a second.
SPEAKER_00So what you're implying there is 60 plus percent of the people that file UCC are small business, under a million bucks and under 10 employees. Is that what you said? No, the value of equipment.
SPEAKER_02So 62 with UCC filings report. And what I can show you on the screen.
SPEAKER_00Yeah, no, no. I'm just trying to so 60 percent, 62 percent of the value of the machines that are financed. Correct. Are with small businesses that have revenue a million dollars or less and 10 employees or less. Now riddle me this.
SPEAKER_02That population of companies with less than 10 employees and less than a million in revenue, they only employ 23 percent of the contractor base. Okay, essentially as a proxy of assets. It should be uh 23 percent. And so the it it's as a representative data set, it's the majority of UCC filings congregate with with small companies, and it vastly overrepresents that population.
SPEAKER_00So so let me let me interrupt. That means that data is not as valuable to us as what we once thought. Correct.
SPEAKER_02It's and it's uh I'm gonna say um it is very, very good at the smallest part of the market that uh doesn't matter. And if somebody doesn't know that, it's very dangerous.
SPEAKER_00And the and the the reason I bring that up is because almost uh there were people that extracted and and reported out UCC filings for years, more than one of them. And the dealers, it was almost like they had to check off a box for their companies that they evaluated the market and used UCC filings as one of the tools.
SPEAKER_01Yeah.
SPEAKER_00And I was one of those people, and I didn't realize that it had such a thin option, a thin view of what the market opportunity was. Because I was using that for mark for sales coverage, for correct for salesmen, et cetera.
SPEAKER_02People have often looked at it as a proxy of um the market and as a proxy of market share. And why not show you?
SPEAKER_00Yeah, I just I just opened it up.
The Charts That Flip The Market
SPEAKER_02Okay. Because when you see it, it's gonna it it jumps off the page at you. And let me just make this um full screen. So we're looking at some charts. This these are earth-moving assets principally. Here we're looking at the dollar value of firms. So on the left-hand side, status quo is what we call UCC data. It's what people have used for years. And if you notice, uh 91.7 percent of the assets in UCC filings are companies less than$1 million employees. Now, riddle me this. That population of businesses is about 83% of the businesses in construction are less than a million dollars, and they employ 23% of the workforce. Okay. Now, using employees as a proxy of assets, right? And employee, I hate to put in those terms, but you're good. As a proxy of assets or as and as a proxy of revenue, it is vastly overstating this segment. Now you have to say, why is that? So before you even ask the question, why is that? You can say, look at this chart on the left. There's no way that's representative of the market, right? There's no way that 92% of all value of all equipment is purchased by less than by companies with less than a million dollars in revenue. And if you peel off to the right, you'll notice these numbers are pretty tiny: 0.3, 0.2, 0.4, 0.2, 0.1, 4.7, 0.1, 2.4. By no means is that representative of the market. In fact, it's essentially opposite of the market.
SPEAKER_00On the right hand side, well, before leave before leaving that, what that is showing to me is that we're looking at a reporting vehicle that needed to be using Poisson because that's a pure match of Poisson. Yep. Where ninety-95% of the volume is with five to ten percent of the companies. So our our market coverage, you know, a bit, you know, Steve Day at Tractor and Equipment used to say, I'm only interested in the top ten percent of my customers, the the big guys, because that represents such a big deal. And my argument with Steve was always, well, you're letting 80% of your customers in. No, you won't touch them, you don't call on them, so you're you're like leaving that to the competition. He said, Yeah, but it it really doesn't matter. I said, not individually, but in the aggregate, it does. And and that was a miss. This is that graph should not be that presented this way, it should be presented from the the eight one billion plus down, not from the zero to a hundred five hundred thousand or whatever.
SPEAKER_02Yeah, and and if you if you look at the right hand side, please know the left hand side and the right hand scale a little bit different. But what when we've modeled um our data scientists model the distribution and look at assets and verify it with a bunch of data.
SPEAKER_00Let me let me interrupt you again. I hope everybody heard the term. When we have our data scientists, this is more than data analytics. These are people that are specifically trained in statistics and science on looking at historical transactions, market segments, etc.
SPEAKER_02Yeah.
SPEAKER_00And and we haven't, I I don't know very many people that have used those in in my 60 odd years.
SPEAKER_02And people don't want to believe the the how skewed the left hand side is. I can assure you that the right hand side is correct. And so what I want to point you towards is just the right hand side. And and some of this will be very intuitive to you personally. Let's look at the 54.8 percent for companies over a billion dollars.
SPEAKER_00Yeah, and that's that's exactly that's exactly what sticks out.
SPEAKER_02Right. And we know from the ER top 400, the ENR engineering and news records, top 400 companies, they account for 25 percent of all U.S. construction spending. 100% the 400 companies, 25% of all U.S. construction companies. So you could say, well, Nick, well, what about 25 and 54.8? Well, clearly there's more than 400 top companies, right? You can go to five, six, seven, eight hundred, and you'll be at fifty-four point eight percent of the fleet.
SPEAKER_00So go go go a little further. Take go down to fifty million.
SPEAKER_02Yep.
SPEAKER_00Seven, twelve, twenty, you're at 80 percent.
Common Sense At Scale For Fleets
SPEAKER_02That's four categories. That's right. And these are companies in I call this common sense at scale. Um, and I call the left. Um, you know, it's sort of hate to say it, it's um the left-hand side has caused companies to probably uh not only waste a lot of time, but companies that I've done business with have wasted millions, tens of millions, hundreds of millions, if not billions of dollars, um, off of a data set. If you just look at the left, it doesn't, it's so misrepresented. And you look at the right, which is a correction of that curve, um you you almost have to say, why, you know, why is that? Um you know, you could say, is it uh well, uh I'll just kind of stop there.
SPEAKER_00So well, okay, so let me let me let me bring it back and and commercialize this for a second. So you've got all this data. Yep, you suck it from federal records, and what I used to do with the reports that I looked at is I did it by county. And I could go back 20 or 30 years looking for trends, looking for changes, looking for areas that had limited competition, et cetera, et cetera. Do you sell that data today? We do. How do you sell it? What's the vehicle you use? You have to call people? You what do you do?
SPEAKER_02Well, we don't, it's an interesting distinction. We consider ourselves a predictive buyer intelligence firms. We are not data brokers. There are data brokers who are on the left-hand side who will say sell um UCC data.
SPEAKER_01Yep.
SPEAKER_02We process uh data from multiple sources, um, government sources being one of them, multiple private sources. And we look at a bunch of things. Like we look at credit scores, we look at available credit, we look at capex, we look at maintenance capex, we look at sort of a bad reputation index. Um we look at employment, we look at velocity, we look at the underlying market conditions, and we are giving an opinion on the data, which is the right. So we we're we're not a data broker. We do make that available, data available to our clients via our tools.
SPEAKER_00Um okay, so you if if I want, yeah, I can buy data from you by itself. If I want, I can get your opinions on stuff.
SPEAKER_02Well, the data already the when we present the data like the right-hand side of the screen, we are giving an opinion on the data.
SPEAKER_00Um so that's not but if I understand it right, that is a a pure report of what the data says. That's not an opinion, that's a fact. That is a fact. That's that's well said. Yeah. Okay. So you'll present that fact. You can do it by state, you can do it by county, you can do it by year. Can you do it by brand? Yes. Yeah.
unknownOkay.
SPEAKER_02And we go ahead. And we allow our clients to to download that data via our tool. And what it means is functionally speaking, behaviorally, we're allowing them to uh align the data set with what they're trying to accomplish as a business. Big difference. The left-hand side kind of throws up data at you and says, here's everything, it's representative of the market, go get them, right? Yep. And people generally are frustrated by UCC data. Um, they don't can't paint exactly why. There's a lot of sort of uh fishtails around it that say, well, it's a lot of people pay cash or um that's that's been an excuse forever. Yeah, it is. And I don't know about you, but most businesses love zero percent interest, right? Um and if their cost of if their weighted average cost of capital, um if they can borrow money less than their weighted average cost of capital, they'll borrow money, right?
Built Data And Buyer Intelligence
SPEAKER_00Yeah, but the other the other side of that, Nick, is it's it's a bit of a fool's game because the manufacturers have used deferred payment terms and low interest money terms to keep production plants busy. And all it does is, and because the dealers, the people that buy the equipment, don't necessarily look at forward cash flow. It's a year out. Oh, yeah. And and they get they get caught. Shouldn't, but they do. And a lot of businesses have gone out of business because they took a divert order because they thought it was such a good deal and they weren't able to sell it because everybody had product.
SPEAKER_02That's correct. And you know, if we if we come out the data a little bit different way, the right, if you look at the right-hand side of the screen, the right-handed side of the screen are generally companies. Just look at the 10 million plus companies or even 5 million. These are companies with operating histories, been around a while, they have operating assets, they're going concerns over many, many, many years. They are pillar clients for OEMs, dealers, and rental companies to have. The left-hand side of the curve, all these left-hand side charts, are very, very small businesses, and they come and go. And they're extremely uh expensive to target and they're not reliable. Um, some of those companies, yes, do evolve and slowly make their way to the right, um, but there's certainly a fraction of them.
SPEAKER_00Okay, so let me let me come back at it a different way. We can do this by state geography, we can do this by industry, we can do this by brand. Can I do it by industry like mining? Only mining, only forestry, only construction.
SPEAKER_02Yes. We construction and forestry and ag, yes. We personally don't specialize in mining.
SPEAKER_00Um can I do can I do governmental as well? Oh yeah, yeah. And I can do it by county, by state, by city? Correct. Yeah. Okay, so this is this is valuable. Okay, so and and you let people download your data. So you go out, you you harvest data across whatever range of databases you have to go to. You reformat in a manner that uses your data that your data scientists use, and you'll sell that raw data to uh a dealer.
SPEAKER_02And over I want to just explain one thing. There's a um we consider ourselves predictive buyer intelligence. So, generally speaking, we don't oversell people. They come here for specific outcomes. They're trying to increase their market share, they're trying to increase the participation rate, they're trying to increase the market share in a specific place. They're looking to, if they're an OEM, they're looking to allocate capital better, plan their products better. They're looking to align with their distribution better on the most important outcomes, not spray and pray, not everything. So clients come for a solution and we fit the data for them for their needs.
SPEAKER_00Um so you you do not have a standard database that you've extracted from public and private data sources that are available for somebody to create their algorithms and evaluations. You do it for them.
SPEAKER_02Well, we we will offer the folks our data set. Where I was going with that is there's a sort of a legal standard about whether somebody's a data broker and whether somebody's predictive on buyer intelligence. The left hand side of the front of the page here, they are true data brokers. The right hand side of the front the page is predictive buyer intelligence.
SPEAKER_00See, I I don't buy that.
SPEAKER_02Okay.
SPEAKER_00And the reason I don't buy it is because you're going out, that's data, and we already established that's facts.
SPEAKER_02Yep.
SPEAKER_00That's not predictive or anything, that's just pure facts. It's historical.
SPEAKER_02Correct? Well, we do we do look at the past and we are forecasting the future.
SPEAKER_00Um how can you forecast the future when you're looking at it here as a one-year picture? Well, the left-hand side you're a point-of-time report right there.
SPEAKER_02Left-hand side of the page is status quo, it's UCC, it's what happened yesterday and in the past.
SPEAKER_00It's history.
Data Versus Prediction Debate
SPEAKER_02The right hand side of the page, we're looking at the the capacity of firms today. And we do, you're not seeing it in this view. We do forecast what happens to those firms in the future.
SPEAKER_00But that's that's that's all I'm saying. What I'm looking at here, the right hand side and the left hand side, they're both data files.
SPEAKER_02That's correct. They're both static.
SPEAKER_00Yeah, that's exactly right. And it's it's extracted from the same data sources, from the same public and private data files, and it's put into a report and a database that you guys designed. Yep. It's the same database, in fact, for both of these.
SPEAKER_02Well, uh, I mean, we're we don't rely on UCC information.
SPEAKER_00We find it extremely understand, but the data that you use for the left is the same as the data you use on the right. None, I don't know if I follow you. I'm sorry. The the data on the left is UCC filings, it's credit scores, it's no left-hand side is is UCC filings.
SPEAKER_02With um we've identified those firms and we've established their revenue and their employment, and we've looked at their credit stores. So we have studied those companies.
SPEAKER_00Okay, so so that then go to the right-hand side, and I submit to you that you've done exactly the same thing on the right-hand side you did on the left-hand side. You're just presenting it differently.
SPEAKER_02Well, except we're not looking at UCCs on the left or on the right hand side. We're looking not at UCCs, we're looking at companies. Left hand side are transactions that we converted to companies.
SPEAKER_00So the right hand side then is not based on purchases. And the left hand side is.
SPEAKER_02The left hand side gives the illusion of that it's based on purchases. And what I would submit is that the Left hand side is highly distorted and misleading.
SPEAKER_00Okay, so there's there's my first comment to you. Yep. For a guy like me, I need more clarity on what the hell those things are made up by. Sure. Because on the surface, to me, it looks like they come from the same damn data source. It's presented differently.
SPEAKER_02Yeah.
SPEAKER_00And that's fine.
SPEAKER_02I'm not uh Yeah, no, I welcome your I respect your the way you think.
Market Share By Brand And Territory
SPEAKER_00Yeah, whether whether I'm you know, I might I might be the only one on the planet that thinks that way, so you have to you you have to filter it and and make it work for you. Because what I'm what I'm trying to get at is like learning without scars, we're we're dealing with employee development, making the employees have more skills and knowledge so that they can better serve customers. And by serving customers better, I believe we create loyalty, and loyalty begets customer attention. And customer attention is the biggest driver driver of profit on any distribution business that you can come up with. But I have a hard time convincing owners that their employees need to be constantly trained and retrained, not just be viewed as tools in a toolbox. And previously today, you and I were talking about it. The employees have created how the job looks in a manner in which it's easy for them. So somebody working a parts counter has figured out how to do the job in a way that makes it easy for the people at the parts counter to do the job. That has not necessarily anything to do with what the job should be. And that's part of my problem in selling it to the marketplace that you need to spend 500 bucks and develop every person that interacts with a customer, for instance. And it's the same thing with you. You've got 80% of the companies that cover 90% of the contracts, 90% of the machines that have been sold or are in the marketplace. And most the one on the left-hand side is the same thing, but it's presenting it in a different way. And that's the way that we have traditionally looked at it. And you're bringing it along in a new manner that people that are used to looking at this kind of stuff say, well, wait a second, I don't understand that. I've been doing this for 30 years. What the hell are you telling me? That's been wrong? And the answer is yes, it's been wrong. It's wrong. Yep. And that's hard for people to accept, my friend.
SPEAKER_02Well, you know, I mean, we're not trying to poke our f look.
SPEAKER_00Oh no, I know that. I know that, but you know what I mean.
SPEAKER_02Yeah. It's uh there's a lot of things uh in the recent times have um institutions that we revere and now look at and say, well, maybe um maybe they were uh should be revered at some point in time, but not no longer. Uh nonetheless, the right hand side is what I was showing you is you asked if we if we license the data set or such, and the answer is yes, we do. Um but we we we want to be uh certainly a company that cares a little bit more. So usually it's solution driven, um where we'll put an OEM is looking for capital allocation or to determine which products it should keep in the market, bring to market, you know, remove from the market. Also, from an OEM's perspective, it always marveled me is that the power of a team working together, right? So OEM's dealers and territory managers offer off operating off of a unified data set, that's correct. It builds trust, is what it does. And so we do license the data set and the tool. Um, and we partner with people on the outcomes. Uh, we are very, very, very accountable for the outcome when we uh partner with folks. And our aim is to, you know, reduce the brain damage from data sets that aren't, you know, if they look at another way, I don't know if I've ever heard anybody say, man, I'm so blown away by uh the return on UCC data. I certainly haven't heard that. What I've heard is what I call confusion. Um we rely on it, but we're not so sure about it. And it's it's all we have, so we're gonna keep using it.
SPEAKER_00And well, you know, you know you know, one of the things that I base almost everything on is return on net assets. And that allows me to look at you know, and in the DePont model, that's the chemical company, it's a pretty standard thing. Or what are the influences of profit? And it comes out that the top 10 are very clear, but the top three are like 90% of the of the whole deal. Sales for employees, one, asset turnovers one, those types of things. But return on net assets basically is turnover and gross margin or net margin, whichever way you want to play it by department. And if I've got that, asset turnover drives my pricing. And and when I bring that subject up in whatever group my whole life, they think I'm out of my mind. And if I can take my turnover of my asset from two to four, I can take my gross profit from 40 to 20, and I end up with the same thing. So I can make my price so competitive at at no loss of net income. And I don't understand yet that they're they're doing this a lot in chip business and a lot of the more recent technology stuff. But our traditional we're we're inventory hogs where turnover, when I started, turnover is one and a half to two times a year, for God's sake. Imagine that means that 50% of your inventory you don't need. And if you're looking at$20 million of inventory, that's$10 million of cash. And in the 60s, that's a hell of a lot of money. So the tools you bring forward, like I can't let anybody take my class onto their system because I'm accredited and somebody has to ensure that I'm in control of my product. I would have thought that that would be the same thing for you. That you'd have let people have access to the database, but they couldn't download your data and put it on their machine without you.
SPEAKER_02Well, we do, it depends on who it is. Um if we we we feel being vulnerable builds trust, right? So if we're dealing, doing business with somebody and they want we want to learn with them. And we we want to be able to learn together. So we do we do allow clients to ingest our data. We don't put restrictions on it. However, um we want to make sure somebody is serious about the outcome. And maybe that's just a principle thing, right? Maybe it's because of um being a you know, call it a founder of this company. Um we want to uh sell something to somebody who can earn a return from it. And we it's a very powerful tool. They have to be serious about it, right? They have to be serious about wanting to allocate. I know these are like not meant to be um sort of uh softball questions, but if the if a company is serious about capital allocation, if they're serious about um providing a data set so they can set up a closed loop with their distribution to see outcomes. If they really want to move market share, um, and again, softball questions, then we love to partner with them on the data set. We do allow them to use the ingest the data, depends on who it is.
SPEAKER_00Um so so stay with market share then for a second. And and the market share we're talking about is primary equipment, right?
SPEAKER_01Yeah.
SPEAKER_00So in the construction world, I've got caterpillar, komatsu, John Deere, Volvo, and Hitachi that is probably ninety-seven, ninety-eight percent of the market. And in any particular territory in America, it's different answers in different countries, but in America the top two will be eighty to eighty-five percent of the total market. There's rarely a third one that makes enough money to make money, makes enough sales to make money. So you you end up with the old adage that the more people there are in a supply chain, the less of them that are profitable, because there's not enough net profit money available to keep all of them afloat. And and it shows because there's bankruptcies all over the place. Are are we talking the same language?
SPEAKER_02Yeah, I mean, it it depends on the on the on the product and the I mean, like like everything in life, it depends, but broadly speaking, yes, you are correct.
SPEAKER_00So if I was to look strictly at excavators and strictly across the United States, you'd be able to tell me which states or which territories have the strongest market share brand, second strongest market share brand, third strongest market share brand, true? Yes. Yeah.
SPEAKER_02We can also tell you the share of wallet of the best of the customers, right? Um the customers of the dealer or the the machine owners. We can show you the machine owners um and the number of brands in their wallet and what percent. Correct.
SPEAKER_00Okay. So one of the things that's always bothered me and and maybe you have the answer for this in how you collect and then present the data, is we're subject to the decisions made by the salesman in the field. The salesman in the field is not directed by the organization, he directs the organization as to what he's gonna do. You agree with that? I do. So if if I look at excavators and I look at Michigan, I can find out which brand is number one, two, three. And from that do you get into call reporting, etc., for the salesman covering those clients? We do. Yeah. So you can take something like Salesforce and overlay it on your data. Correct. And now that's two products that you offer to clients. One that is the graphs that we looked at, and the other is the market coverage that begot that market share, right? Correct. Do you sell them separately like that?
SPEAKER_02We we we sell the data with the tool, but we're we're you know, we're look I'd love to show it to you if you don't mind.
Closed Loop Sales Coverage With CRM
SPEAKER_00Um I I think that might get too much into the week. Let's do that in another one. Okay. But that that's probably a subject all by itself. Yeah. You know, what we're what I'm I'm getting at, Nick, with this discussion is the people that are still with us are thoughtful people. There's a lot of people that will start, will have started with this and they've already gone. But the ones that are left are are thinking seriously about what we're talking about and what you're saying about the data that has been used and will be used. And those are the people that, you know, not everybody's gonna walk down the new path. There's a lot of people that'll say, screw it, I'm gonna stay the way I am. I'm comfortable with this, I know what I'm doing. And and those guys have a short life in this world.
SPEAKER_02I would agree. Yeah, lots of volatility. There's no question. They would have um some serious, significant ups and downs. Um we wanted to create a closed loop system um to take the look, the industry as a whole has subpar margins. A lot of it is because of what you referenced, which is extreme volatility. Um as if um that the the best companies have it's sort of avoid the major swings in volatility. And there's lots of ways to smooth it out. Uh if you're if you're experiencing a problem, you can't necessarily fix it immediately overnight. However, you can take incremental steps to get you out of it. So better data to the right target, um, better data coming in at the top of the funnel. We kind of flip the script on participation rate, which is actually impossible to compute. We call it coverage. Um, and better data going in through the top of the funnel and then allowing those lists to be provisioned from the OEM to the dealer and dealer to the territory manager means they're one team. They're allocating their capital to target certain outcomes. Then we can watch it progress through the toll, through the tool in each stage. So when something differs, actual versus goal, they can course correct immediately. They don't have to wait all the way to the outcome, which is what they call market share. If you do those two steps combined, pour better data in through the top of the funnel, not random, pardon my language, horseshit, um, and you watch it statistically go through each stage of the funnel through a dynamic feedback tool that says, I I converted Ron from a contact to an opportunity and from an opportunity to a prequote, pre-quote to a quote, and a quote to negotiating, negotiating to one loss. When I can see it go through that stages, you get like a 5.6x greater outcome than if you didn't do that together, meaning pour random data through the top of the funnel and then don't watch it progress through the stages. So you can course correct, you'll get 5.6x less of an outcome.
SPEAKER_00So the the wild card in all of that is if I've I've got all your data and I'm doing it through the funnel and I've I'm doing those seven steps, I've got 10 salesmen, each of whom has different attributes. And they'll go through those seven steps in a different pattern, each of them. How do I adapt to that?
SPEAKER_02Well, good question. Uh, brilliant question, actually, in my opinion. Those stages can be adjusted to the salesperson. Essentially, what you want to see, though, is you want uh you want a shared goal, of course, with your sales force. What are we trying to accomplish? We're trying to grow with a certain customer base that we believe brings us the gross profit dollars. Yes, they will have different um talents about how they pursue those different stages. Those stages can be highly personalized, but you want to be able to break, you want to be able to do some midstream measurements so you're not surprised, right? And if you said, well, that's maybe too much, right? We really trust this salesperson, then don't do anything, right? Don't give them data, don't put them through a funnel, don't have him self-report his results, speak for himself. I'm all for that, actually.
Volatility Renting And The Big Buyers
SPEAKER_00Oh, I know. And and so this brings your rental background and your dealer background together because what a lot of the larger accounts will do to get rid of the volatility is they'll have a core of equipment that looks after their business and they'll handle the bubbles with rentals. And that's how they run their business. Versus the smaller guy, one, two, three, four, five machines, small, medium guys, they don't have enough machines to look after the business properly. They don't have enough money to be able to afford to rent the machine. And if a machine goes down because they've tried to save money by not doing maintenance, they're in trouble. That's right. And the salesman doesn't influence that in any way. He tries to influence the customer in how they run their business, but not how they use their equipment. That's correct. Yeah. And that's a completely different world for anybody that's with, you know, washing machines in your home, lawnmowers in your backyard. All of that's the same principle applies to everything here. It's a hell of a tool, a hell of an opportunity, Nick, that that you're you're creating and providing for people. And it, I believe it's you almost need to have classes to explain to people how the hell to use this stuff.
SPEAKER_02Well, uh, it, you know, you've been a blessing in guiding us in our development. I could just say it it's very interesting. I sent you the Ed Thorpe book, um, I believe. Um, and there's a cluster of uh sort of uh mathematicians, Ed Thorpe being one of them, who um, as you know, went to to Vegas and then he went to the biggest casino on the planet, which is called Wall Street, formed a hedge fund. But he around him was Claude Shannon, who essentially was the inventor of the information age. Around him was Jim Simmons, Renaissance Technologies. And we're we're just inspired by the math behind the business. And we believe the industry can be much more capital efficient. Uh, we believe it can raise its margins to the extent that uh it uses the right data as a source of truth. And you said it prior to us you hitting the record button. It really makes you question when um something so wrong has been so socialized into it is how can it be normalized? Yeah, you you actually opened my eyes and I'm like, holy shit. It you know, it was it intentional? I have no idea.
SPEAKER_00Um, I'm not smart enough for that either. The the the really interesting side of all of this is you know, my line is that a good salesman never sells anything the customers buy from them. And and it's because they have a relationship, and you mentioned it's because they trust each other. And and that salesman is gonna make recommendations to the customer that aren't necessarily products that they sell, but it's the right thing to do, it's the effective answer to the to the problem. And as a result of that, that relationship with that customer, it's gonna take serious, serious flaws for that ever to fall apart. It's gonna be it's like glue, damn it. It's like concrete, you're stuck. But it it's you know, it's you you've you've almost and and you're dealing with a customer whose opinion you need to change. That's hard to do. You know, a guy says the price is too high, and my answer to them is really compared to what? Because I'm not gonna let them get away with the generalization. And I'm not interested in what the football score was last night. Maybe in a bar having a beer I would be, but that's a different deal. So the thoughtful people that are still with us are really interested in this data. Are really interested in how to use the data, and when you mention market share, that's music to my ears. And we don't know how to measure market share in parts and service. We can measure market and share coming out the wazoo on equipment. I don't care what kind of equipment, cars, planes, boats, whatever, how toir balloons. But parts and service, I can't do market share worth a dam. Because I haven't really got market potential. And and so what you're dealing with is the consumer side of the world on a machine. I want to know when that machine's gonna ru be replaced. And I want because I want to get the replacement machine. I sell a machine today, it's bait to me to make money from parts and service, but it also tells me what my sales are gonna be three, four, or five years from now, based on the number of hours the guy puts on his machine, which I control with GPS. I got all the tools today, and hardly anybody knows how to use them. It's scary.
SPEAKER_02Yeah, and I mean, you know, uh if for another time I can show you, we took the same approach to um as I just showed you, it's slightly different to parts and service, which you have a ton of um you and I've discussed it before. The big three rental companies to truly have more Amazon type market power. And the notion of not only what they buy, but what they decide. Exposed. So they've normalized a huge amount of used equipment coming into the market. Um that that naturally has to impact new equipment demand. I'm talking about to the non-rental, non-big three rental company it market. It has dramatically impeded. Yeah. It's wild. And if you said, well, you know, you said it on a prior call. There, you know, you can make an argument there's too many OEMs, right? And especially since you know you have this con intense concentration of three buyers, and it three is massive. Um 30% of all construction equipment demand, you know, arguably could go could be purchased by those small amount of companies.
Focus On The Few Customers That Matter
SPEAKER_00And it's it's it's worse than that. In America, Europe and Asia are different, but because of geography. But in in North America, it's um I'm supposed to have my phone off. Um in in North America, because of distance, I literally have, and let me just use a 80% of the market is controlled by two brands. And it's two out of Caterpillar, Komatsu, John Deere, case, Volvo, maybe Devilon, Hyundai. And the other four or five, they fight for 20% market share. And there's not enough overall profit in that 20 to keep that number of dealers profitable or manufacturers profitable, which means that out of the Volvo case devil on group, one of them's not going to be here in three or four years. Yeah. Yep. And we've we've seen that in mining where there used to be seven or eight, now there's three. Hitachi, caterpillar, komatsu, period. End of story. On the big stuff. And then the the smaller the machine, you get down under 10,000 bucks, you got maybe a hundred suppliers. But out of those hundred, you're probably going to lose six or seven every year to bankruptcy because they can't make enough money. There's too many people competing. So it's an it's a natural life cycle. And when you bring in parts and service, then you come into people's like repair and maintenance in a in a in a machine. Number of people that do the maintenance that's prescribed by the manufacturer for reasons, it's less than 10%. I'll drop flows, change filters, that's enough. I'll grease every now and again, that's okay. That's not good enough. But here, but there is a sort of it's interesting.
SPEAKER_02Like, if I whenever I see a macro number, I get overwhelmed. It's hard to relate to. Let's flip it around and call it the good news. If you want to change your life, you can actually do it today. And the law of small numbers, if you want to change your business and not be, you can look at all those headlines, right? I just said them. Big three rental companies, the Massat Cafex, the MAFSIS disposals. You could say independent dealers are China, and independent rental companies may not have a place because of the big three. Let's flip it on its head, though, though. A salesperson or a rental store or a dealer, um, at least in rental, by example, 3% of the customers could do 62% of the business, 15 people per store. 11 did 83, 50, 60 people per store drive the majority of your revenue and profit. If you want to turn your business around today, you could say it's not clearly you could say 100 clients, right? You could say 200, right? Call it a lot of small numbers. Each sales guy has 50 clients, top clients. It's more about what you don't do than what you do.
SPEAKER_00Oh, exactly. Exactly.
SPEAKER_02You could just say we're happy with these 50. We want to own the most profitable segment of the market where we're actually aligned on the value proposition. TCO and uptime cost money. And we're going to go after those people, we're going to spoil the the heck out of these folks, and we're going to retain it. And here's what we're not going to do. We're not going to change trading bows. We're not going to buy data sets that cause us to misallocate capital. Um we're not going to, frankly, give crap data to a salesperson who turn who you can turn over constantly, and frankly, it breaks families, ruins lives in some capacity. It's irresponsible. So you could just decide what you don't want to do, how you're not going to waste your time and focus there and probably make a pretty good living.
SPEAKER_00And if you remember me talking about Steve Day, who used to run parts for Komatsu, that's exactly what he did. And then he came to an epiphany after doing that for the longest time and discussions, again being open-minded, not closed-minded, being prepared to evaluate or change and do something different. He came to the realization that, yeah, I'm covering the top 20%, but that means I've left 80% of the people out there to my competition only. And over time I'll lose them all, which changes my distribution curve. So and then he came up with a really weird thing. And it, you know, it he added people in the parts department. And he added a person and the sales went up. I said, Oh, that's cool. What are you gonna do? He says, Well, I'm gonna keep I'm gonna follow your thinking. If I if the sales keep going up, I'm gonna keep hiring. I'm gonna stop hiring when the sales stop going up. I said, Cool. So what about having more stores? Because that you know, we've got this quote branch philosophy. I need a a an uh an area where I can have 50 bays or 20 bays or some big number. I don't want any of that. I want a retail outlet, I want a a Napa store. It's it's a it and again, the number of people that are out there that are prepared to think that way are very few and far between. And they're exceptionally look at Hedden Anquist, for goodness sake. He started out as a dealer and decided, well, wait a second, I can make a hell of a lot more money as rental. And that's what he did. He basically took his company into the rental business, went public with it. He's still got a dealership, but it's minor. It's it's a really interesting time, and you're right at the core of it that can have a huge influence on our world. We got to get people to catch up with you, Nick.
SPEAKER_02Well, I don't know about that. I mean, we're here to serve and blessed to be able to learn from you and other people, but it's with a great amount of humility that we look at their people's hard work and we get to count it and report it back to them. And we aim to um tell the truth around data. Um we certainly are inspired by the mathematicians of the world that are the greats when we look at data sets. Um, yeah, you know, we're we're excited about what's to come. Um I can say generally speaking, it's um you've taught me so much about how to approach the market, how to frame it. So I'm gonna say thank you to you for your constant uh guidance, your encouragement, your inspiration as being a man of excellence.
Learning Without Scars And Better Thinking
SPEAKER_00So well, you you it, you know, it's just you we we all have to find the people that we can learn from. And I'm the same as you, you know, I just keep looking around until I find people, and I've been blessed to be able to find them. And I've I've been open-minded enough not to close my mind to what they suggest to me. I think I think I told you I was I was hired to fix a computer problem with a brand new installation at a caterpillar dealer. And the senior partner of Eric Curry, who was the consulting company in Canada, Accenture today, he spent a day a week with me from eight in the morning to five at night, just me, for four months. So basically, I had 16 eight-hour training sessions one-on-one with a guy. And at the end of that, I knew more about inventory management distribution than probably 95% of the people in North America. Because I I had such intense, focused mentoring or training, or coaching, or whatever the hell you want to call it, from a very smart guy. And there's a lot of very smart people out there, but they hide they hide their light in under a bushel. You know, it's it's they're hard to find because they they tend not to want to stick their head up to make it them exposed. Yeah. Which is a shame. You know, one of the things that I ask a lot of people all the time, and is what would you do if you weren't afraid? And fear is a terrible motivator.
SPEAKER_02So who who said that? What would you attempt to do if you knew you could not fail? Um, I have that saying lying around that my father had that. I I have to remember. I don't know if it was just attributed to sort of anonymous proverb, but it probably goes back to the Bible.
SPEAKER_00Yeah. And or whatever you want to call the book that you believe in, because differently they all come to the same place.
SPEAKER_02How would you characterize I'm curious from your perspective? How would you how would you characterize uh a data set that is contrary to what has been uh an established belief for years? Um how how would you characterize it?
SPEAKER_00Um basically I'd say that and and I think this is true, and and you've heard my illustration of the electric engine replacing the steam engine, technology advances since World War II have been so dramatic in so many directions, the mean time between radical transformations has shrunk dramatically. You know, the Murphy's law used to be 18 months, it's now like two or three, where you know the price of software comes down by half, and and and the productive capacity of it doubles. So it's like having you got a car in 1900 and it can go 60 miles an hour and it costs you 100,000 bucks, or you know, say 60,000 bucks it in in 2000, that car is going to cost six bucks and it'll go 600 million miles. It's that order of magnitude difference. And and part of that is why I I give me and you a pass because we can't keep up with how rapidly it's changing. And and you've heard me say this. I I pick software people that are best in class, and I tell them when we contract with them, you got three or five years, because it's going to be impossible for you to keep up. And I'm only interested in people that are in the front of the pack. It it's um it's it's the harsh reality that these people are in anthropoc and anthropoc, again, is now the most important data analytics AI business in the world. Two years ago, because the U.S. said they were spies and didn't want to get them involved with the US military, they dropped in in consequential terms by 80% of the influence in the market. ChatGPT took over. Well, it's the reverse is true. Chat GPT is is sucking wind right now. Oracle, look at what they've done. And Larry Ellison just continues to plod along. Nothing dramatic, but boy, he's got some marvelous stuff. You know, it's amazing what's out there. Look at the data analytics, the logistics management for Amazon, the purchasing management for Walmart, the investment strategy Charlie Munger followed with Warren Buffett, with his lattice work of ideas. I mean, there's there's so many things. So, you know, what would you do if you weren't afraid? That's the kind of stuff I I've been afraid of decisions often. And I have to overcome the fear and say, screw it, let's try it. And that's why I call the company Learning Without Scars, because I've got scars from that trial work, baby. You might have one. Yeah, I've got many, baby. It's you know, but if you're dealing with data, data doesn't change. Facts are awful stubborn things. I love them. And and then mathematical statistics is a passion of mine because of what you can do with it. And normal distribution is the biggest mistake that our industry had for the last 70, 80 years because we figured that there was a median and or a mean and and there was an equal number on both sides of that. It's not true. Poisson is the driving force in almost everything in life. A small number of people, five, ten percent that control 80, 90 percent of the old the overall world. It's true with diseases, it's true, everything. But hardly anybody knows mathematical statistics. And in school today, grade four, grade eight, twelve, thirty percent of the kids in arithmetic are at grade level. That's a horrible indictment of everything we do. So here we got your data, clean sources, identifiable and public sources, and getting market share data by brand, by territory, by salesmen. Holy shit! Who would have thought? And you know, here comes Salesforce 20 years ago, and and they were measuring how many calls the guy made in a day, and then how many sales he made per call, and it has nothing to do with anything. It's a it's an important number, but big deal. Yeah, it's to the right people, yeah. Yeah, to the right people with the right thing at the right time, at the right price.
SPEAKER_02You know, I I was uh super intrigued by the um the Jim and Jim Simmons story at Renaissance Technologies, right? You the notion of the the man who solved the market, right? 100% annualized returns. It sounds made up, right? It sounds like a Ponzi scheme. And it's it's shocking to me um just by inverting a problem, how he he and his team of mathematicians, arguably the some of the best in the world, started out as code breakers, as you know. And some of the best mathematicians on the planet can observe patterns of behavior and extract um 100% annualized returns. By the way, winning at like 51.6% of the time, right? 1.6% better than losing. Shocking. And it's very interesting. Made so much money that became a closed-end fund, as you know. I mean, minted tons of billionaires. And we hope to be a small part of that in the equipment space, which is re-orienting folks. We will not work for competitors, by the way.
Closing Hopes For Higher Industry Margins
SPEAKER_00Um we know too much, and we we want but that's the right answer, Nick. Yeah, you can't, you know, at one point in my life, I I've been in Seattle, Tacoma area, I worked with the Caterpillar, the Kometsu, and the John Deere dealer all at the same time, doing the same thing. And they all were comfortable because they recognized that their markets were different than each other's. Sure. You know, and you remember the movie The Big Short? Oh, yeah. That's one guy. Yep. It's easy. We're gonna have to wrap this up because we just about hit an hour. But you're right. Let's let's think in the next month sometime we get into the next piece, which is you're showing how you're using it and helping influence people in market coverage and market share. Well, we'd be blessed for your feedback. So no, I think I think this has been good. How how what would you say it's a good paragraph to close this with from your perspective?
SPEAKER_02I would say um, I'm gonna go on a different note because you I'm gonna start with Jay Lucas because it brings a smile to my eyes. God has blessed me so much in this business, and that's been the most fun for me. And I when I I know you through no other reason than sort of chance meetings, Jay Lucas, um Steve Clegg, Matt DeLoglos, Mac, Mike Womble, Jeff Bryant, um Terry, I'm not gonna say his last name, you know. There's so many great people in this industry serving. There's so much, so many people who care for one another. I am just blown away by it. The humanity of this industry, I'm sure it exists in other industries, but exists here. What I wish and pray for this industry is it gets out of this brain damage of call it misallocation of capital and it grows its margins to what it should be. There's no reason the industry should work so hard for 2% net income margins if that. And it's it's about time that the industry profitability is reversed. Much of it is self-inflicted. Um it's all it's all self-inflicted.
SPEAKER_00And you know where it came from. You know where it came from? Made so much money in the 50s and 60s, they didn't have to think about making money. When they needed to start thinking about making money in the 80s and 90s, they didn't have the tools in their mind to do it. Yeah, it's it's an interesting trap. I I think, yeah, the the blessings, being able to find the people from whom you can learn is is good. And you got you need to do that inside a company. And we don't communicate well enough, is is my biggest problem as an industry. Within the dealership, within the department, we should have very regular, how are we doing? How do you feel? And and feelings are important. You know, it it's the the first book Patrick Glency only wrote was the three signs of a miserable job. Anonymity, the people didn't know who the employees were, irrelevance, the employee didn't know how their job fit into the overall scheme of things, and immeasurability because they at the end of the day they didn't know whether they did a good job or a bad job. And it it's still true today. Nick, it's been a pleasure. Thank you very much. Of course. And and for all of the people that stuck through this, there's an awful lot of really good information here that I'd really like you to think about, consider, and then act on. And don't be afraid to make mistakes. That's how you learn. Nick, thanks very much. And to the audience, Mahalo, we'll see you at the next candidate conversation.
