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
Data Before Decision: How AI Enhances Dealer Operations
What happens when you combine 40 years of dealership experience with cutting-edge artificial intelligence? Troy Ottmer returns to share how he's becoming "an augmented individual with an expanded toolbox," using AI to amplify his industry knowledge rather than replace it.
Troy reveals his methodical approach to consulting—always examining the data before jumping to conclusions or AI-generated solutions. This process allows him to quickly understand client businesses by analyzing everything from employee satisfaction metrics to customer reviews, creating a comprehensive view that would take weeks using traditional methods. The result? Faster, more accurate insights that help dealers identify their blind spots and growth opportunities.
The conversation tackles a painful truth for equipment dealers: those not adopting AI technologies will soon be left behind. But Troy emphasizes that implementation must be thoughtful, with proper training and leadership. "We manage processes, we lead people," he reminds us, highlighting that technology alone can't fix cultural issues like poor customer service or departmental silos that plague many dealerships.
Most fascinating is Troy's discussion of missed opportunities in maintenance services. With dealers capturing less than 5% of maintenance hours—despite this being among the most profitable service categories—AI analysis helps identify these revenue gaps and create strategies to recapture this business. Troy shares practical examples of using data to identify customers with competitive filters or changing purchase patterns, enabling proactive outreach that demonstrates care and expertise.
As dealership consolidation continues across North America—with major brands reducing dealer counts dramatically—the strategic use of analytics becomes essential for survival. Troy's message is clear: AI isn't about replacing humans but augmenting them, giving team members better tools to serve customers and anticipate needs before they become problems. The future belongs to dealers who embrace this augmented approach, combining the irreplaceable human element with powerful analytical capabilities.
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 continuing our artificial intelligence discussions again today with Troy Otware. We did one with Troy a couple of three weeks ago where he gave us his background, starting as a mechanic in trucking and moving into dealerships, et cetera now in consulting, and one of the things that he pointed out when we last talked was how he went to data before he went to the market, and I'd like to use that as a starting point on how he operates now in the consulting world, how he helps people. So with that, troy, as a pretty weak entry, but giving you all kinds of landscape to play in, let's go.
Speaker 2:Well, ron, thanks for having me back again Always a pleasure and, as we were saying prior to recording the recent podcast you've had on the various angles that people are approaching from AI, I'm excited to talk about that today and I think for me, being a conventional dealer operations guy coming out of the 90s and managing my way up to this point, you know what you just said in the opening statement was I never did anything without reviewing the data and obviously AI was not an applicable item for any of us in the 90s, 2000s and so on up until recently. But I'm still approaching it in the same method. I'm not just going straight to AI and saying, ok, ai, here's my problem, give me the answer, and then I run with that answer and say, hey, ai, here's my problem. Give me the answer, and then I run with that answer and say, hey, dealer, principal, here's what we have, let's go, here's the solution to all your problems. There's still a validation process that we must go through and one of the common phrases we're all using data is noisy and I've had a number of conversations in the last 10 business days with people from within the sector. We're talking about the dealer world and outside, and everyone uses data, and they use data in such a way that they don't even realize they're using data. Every decision is database. Now, there's a lot of emotion that goes into decision making a lot of times too, and you know you got to try to remove that.
Speaker 2:And my approach from being a conventional dealer operations guy to becoming a consultant is how do I want to make a difference in the world around me?
Speaker 2:And, as I find myself saying this a lot, I want to leave my clients better than I found them and what value do I bring to them. Obviously, as a consultant, you do freak people out a little Like oh that consultant people is expensive, yes, but probably no in a lot of cases. And if you can get through that discovery phase, what I call it, when I do a dealer review or I'm having a conversation about being hired, I want to understand what your pain points are. And the first place I'm going to go is, well, after the conversation is let's look at your data and if it's in one department or all the departments, let's do that review. And, as you know from doing this for a number of years, managing data, even in the old school ways and even with AI is still not an easy task, so we want to work smarter, not harder, and I know I probably said that the last couple of podcasts- it goes almost today without saying One of the interesting things.
Speaker 1:Looking from my perspective, companies and people that do not supplement their knowledge and skills with artificial intelligence are going to be left behind. Oh, absolutely yes, and so package that up a little bit. Why is it that you think that AI enhances your skills, knowledge and ability in what you do?
Speaker 2:Well, it takes 40 years of tribal knowledge. Okay, and tribal knowledge, some, you know, some people don't like that word, but it's perfect, it is a market word, it's, it's right. It's not meant any form of disrespect or anybody being overly sensitive. Think about it, though Every group, every business, every community, there's tribal knowledge that gets accumulated, but it doesn't always get access or it's not accessible, probably is the better way to say that. So, for me, my why as to who I am today and how I go to market, is how do I take 40 years of knowledge? Gut instinct, intuition, you know, learning before learning without scars was a thing. You know all those scars that came from learning the hard way, the school of hard knocks. You know the, the, the, the mistakes, the failures. All those things have quantitative value, and there's that value word again that we're going to talk about, and for me, it allows me to navigate the various different entities or markets that I go into, which isn't just the dealer world. I cross over into several other industries just simply due to my background, and now I'm taking that knowledge base and I'm using AI to look at the problem, using my tribal knowledge, and then I go in and I use agentic AI or write an agent for me to go focus on this particular problem. And had I not, if I just had the AI side of the conversation, only that knowledge base, I wouldn't be near as effective. So what I'm describing, what I'm bundling up here for you, is Troy Otmer is now an augmented individual with an expanded toolbox. I started my career as a technician still have a lot of those same tools, a couple of same toolboxes that I'm in around. So you know, 40 years ago. Now, fast forward to today, I still have those toolboxes. Don't use them like I used to use them at all. However, my new toolboxes include all the data process management that I learned along the way. Now AI is taking that and I'm coming full circle. To put the cherry on the top, which is I come fully dressed, ready to work, ready to attack any problem and look at it objectively. And yes, an AI again, you put data in.
Speaker 2:That doesn't make sense. You're asked a silly question, you get a silly answer, but if you structure your experiences around the task at hand, you can generally come out with a very strong product. And, of course, you still proof it out, you still validate it. You don't just roll with it. But you know that's how I would bundle myself.
Speaker 2:And, as a matter of fact, in a recent conversation yesterday, you know, I was asked a very similar question. Well, how do you see AI helping this client? And I said I see AI as me understanding your business in a very expeditious manner, very quickly. However, it also allows me to pull in your HR data and understand your surveys and your employee experiences. Oh, and now I can pull in your customer data, your Google reviews, and then I can compare all that and I can build a platform, or, with partners, I build a platform. I'm not building all these things myself, but, in a very basic sense, I can now give you a better idea of what a 360 synopsis of your dealership or your business looks like. So that's how I would bundle what I'm doing as an augmented version of my past self so I'm, I'm going to translate that into funny words um, you have to understand.
Speaker 1:And that comes from the tribal knowledge, and I don't think there's anything wrong with that terminology, because everything that we have done and learned started thousands and thousands of years ago in tribes, correct, and we throw out things that aren't applicable anymore. And there's a lot of that. And you know my metaphor the electric engine replacing the steam engine and how long it takes people to adapt. But before we can do anything, we have to understand what the heck it is we're trying to do and what they're trying to do and all the rest. And I I translate that and say we have to understand before we can be understood, correct? So if I'm going to communicate with somebody, as you do, going to the data and as an augmented person, you're filtering that data to the point that you can communicate to that customer with better knowledge and, in many cases, more knowledge of their business than they have.
Speaker 2:Yes, fair comment. Fair comment. Spot on yes.
Speaker 1:And the dilemma that we have is with using artificial intelligence. We need a new skill set Asking questions. How do I know what I need to know? I have to ask a question. Now. I can ask AI, copilot, gemini, a whole bunch of different tools Right, and they can give me answers. Well, gee, that wasn't the right question, so we have two paths coming down here.
Speaker 1:Most social media deals with algorithms. The algorithms are made by people. Some of them are biased, some of them aren't. It's hard like hell to know the difference, but you can't take what you see as fact without verification anymore. There's so much, like you said, noise out there. So when you're looking at a company back in 80, when I started, I used to say to people when I called up look, I know your business better than you do, and to prove it you're going to pay me and, and that that's kind of a screwed up way to it worked at the time because it was kind of cute. But that doesn't work anymore. And if you're talking to a company and you know their business better than they do, first of all, that bothers them. It does, yes, so let me go into a different direction.
Speaker 1:Business systems at use in the capital, goods industries, dealers and others distributors and others are used probably 40 percent of the capability of the system, and the employee is the one that's making that decision, not the company, because they find what they need and we're all guilty of this what they need to do their job and that's as far as they go. If I'm working the counter selling parts, I know how to find the price, I know how to find the availability. That's about all I need to know. The customer calls me up, I ask who they are. Maybe I have help on the phone because I can see who the phone number is, but there's privacy things to get in the way, so I have to ask who you are. That's a wonderful way to start a relationship with somebody who wants to buy something from who the hell are you?
Speaker 1:Yeah, and then the next question is what do you want? And then they start quantity, part number, quantity part number. And I just start typing. And we've been doing that for 100 years. Yes, sir, and I classify. I call that paper to glass. We took a manual system. We just put it on a screen and instead of writing it, we typed it. So now I got fat fingers and guys that we didn't have typing on when we were in school. And how do I break through to the customer, the person you're talking with, that you understand their business and you looked at different aspects the customers, the employees, the payables, the processes and what's their pain point, what keeps them up at night. And you start talking about how that can be solved. And how do they respond to that? With fear, with resistance, with excitement. How do they respond to that? You mean the customer, yeah, your customer, that you're talking to.
Speaker 2:Sometimes well, I think I've experienced all of those situations and sometimes at the same time it's by the look on their face and it goes back to part of the problem has nothing to do with AI the way the dealers have ran. One of the problems is we've gotten away from value-added selling. We've stopped teaching the front counter people to ask those important questions. I walked into a dealership the other day for a meeting and nobody knew why I was there or who I was. No one asked to help me. How may I help you? Who are you here to see? You know you're here to look at something. No one asked me a word. I sent a text message. I'm here. Somebody came to get me and I'm like okay, I learned a whole lot about that business right there, where there's a big old fancy service counter and a big old fancy car counter, and I could have been some bum off the street right and or I could have been the most important client they'll have all year. I'd like to think, if I do get to work with this particular group, that maybe I'd help them fix that particular problem. But that's not uncommon to all the dealers and I've had the good fortune in the last five to 10 years to not only work for dealers but also be on the customer side and walk into dealers, and everything you're saying right now is exactly the problem. I'd walk in and the customer experience was horrible Employees or they didn't care. Maybe they're bad employees, maybe they work for bad bosses, I don't know but you know how do we handle that. So part of this problem is training related. It's a culture problem and we're at definitely, dealerships I was going to say they're at an inflection point. No, they've been at an inflection point for a long time for a lot of reasons. At an inflection point for a long time for a lot of reasons, and AI is not their savior simply by saying, hey, we have AI now. Now you can work smarter, not harder. There has to be some collective training and processing and, yes, it can do simplified tasks, but how do we implement that? So when I go to talk to a dealer, I'm not leading with hey, ai is going to save you and Troy and AI plus, you know, together combined, that's not the answers.
Speaker 2:I will use AI. I make no secret of that. I use it to give you answers in real time, so I don't have to wait until a quarterly report comes out, so I don't have to wait till an orderly report comes out. I can tell you at maybe same day. Some business systems can allow that processing to happen, but by the next morning I can pretty much have you an answer of what happened in the previous three to five days and how the month is going to look. I know you and I talked about before and what's your projections for next year, right? Well, I can't tell you yet. I don have my my reports. Well, that's unacceptable. I should. I, fortunately, was raised in a world that you can have predictive analytics, even in a world without ai and no question, and and and.
Speaker 1:the problem that you're exposing, troy, I think, relates in a different way. Every 20 years, the number of dealers that we're competing with in the marketplace and I don't care if it's equipment, forestry, mining, marine, whatever it is is reduced by half. And you want to talk about a failure of leadership. Hello, so you know. Translate that and this is 2025. In 1985, we start with 100 customers. 2005, we got 50. Now, 2025, we got 25. And leadership looks at the revenue line. Yeah, revenue is going up. I'm okay. Well, it better go up. You're only dealing with a quarter of the people you're competing with anymore. So there's an interesting statement, and the one that becomes more.
Speaker 1:I think telling your job now involves a lot of learning. It involves a lot of time in your head, thinking the operating leadership of a dealership doesn't have time to do nothing, baby. No, they're putting out fires all day long. The phone rings, let's get out of here. And we've been. That's why I think we've been reducing the number of dealerships so much. We've been putting profits ahead of people, cutting back on the number of people. Everybody says customer loyalty is gone. Well, we haven't treated customers very well to make them be loyal, true? So all of that combined. And here comes ai, and and I'm going to use it, as I think you do, as an excuse we could have done all of this stuff manually, there's no question about it. We didn't know what we needed to do. And today, I think, the business of equipment dealers whether it's on highway trucks, whether it's tractors, whether it's lawnmowers, whether it's air conditioners in your house, the dealers it's now business to business, it's not person to person, and they haven't figured out how to work that yet.
Speaker 2:Well, it's a dynamic that I think. Ai is certainly applicable to all these conversations we're having and part of it. If you look at Learning Without Scars business model of the training platforms you guys have developed over the last handful of years, you're really taking this to a whole new level and the type of education you can provide now to dealers and've always I'm a product of some of your early education programs and you've always provided good information. But the tools today are even better, more robust, and you can certainly take a counter person, um and or a service person and you can move them through the training curriculum relatively quickly or self-paced, but still very fast. And, and you know, dealers should invest and I well, that's a plug for your program it's dealers aren't investing with anybody to a high degree. Their training is limited to oem type training or vendor specific training. Well, that's all self-serving for the OEM and vendor. Yes, you need to know some of those nuances, but that's really not the training I'm talking about. True, you know, down in the trenches, get your fingers dirty, type. Okay, how do you teach these people to sell better when a customer walks into the dealership? Welcome to ronsley dealership, right? How may I help you oh, can you need parts here? Let me walk you over to the parts department and so on. Um, you know it's.
Speaker 2:It comes back to you know one of the notes I put down for conventional dealer operations. You know the strengths. You know that dealers have is. You know they have processes, they have OEM support and, in theory, they have experienced staff. Well, a lot of the experienced staff is retiring. They're older, they're not coming back. And how are we training the newer generation to come into the dealer world, not only the technicians, but everybody else that plays a critical role.
Speaker 2:You know things in the old days were reactive. You know silos between departments, silos, silos are more prevalent today due to the noise that comes from all the data within each silo. It's maddening in my mind, right. And you know tribal knowledge versus scalable systems. You know I think you need both. You can't. Tribal knowledge should never be discarded and in scalable systems or AI and other type of systems should not be ignored either. You need to bring these together, not one versus the other. You know, and you know limited forecasting or predictive ability. You know we're living in an age where predictive maintenance is something we can really do. Very well, we've been able to do it very well for a long time. I think we can do it even better now.
Speaker 1:And what's remarkable by picking on maintenance for a moment, is survey data for the last 40 years that I've seen and associated equipment distributors that surveys every five years for the longest time Maintenance the dealer gets less than 5% of the maintenance hours. Yep, and the primary reason that is given by the customers in those surveys is well, they charge the same thing for a journeyman mechanic as they do for a maintenance mechanic. And so we go to the dealers and say, well, why the heck do you do that? Well, I get more money if I do repairs. The customer repaired the machines down. That's more important than doing an oil change, really no. So you know again the models that we're working with.
Speaker 1:I used to do the same thing any time I was at a dealer consulting job. I'd make a point at 8 o'clock, 9 o'clock in the morning, sometimes 6. I'd go to the competing dealers. I'd sit in the counter and have a cup of coffee with them and just shoot the breeze. Know me from Adam and you find out more in 30 minutes talking to people and walking around through their shop. They used to kick me off the property after a while because it became clear who are you? What are you doing back here.
Speaker 1:Well, I'm just, you know, having a look at what you got available, how many of these fields. I mean, you got a lot of field trucks here. It's eight o'clock in the morning. How come they're not out working Getting organized? Oh, are they on a customer job already? Oh yeah. Oh, so you're charging them while you're sitting here getting ready, oh yeah, and they don't recognize the idiocy that we're exposing. You know a standard thing that used to drive me crazy the OEM sets the benchmarks of performance for your dealership. Right. If you want to continue to be a dealer, here's the things you have to do, and one of them is you have to hold, let's say, 80% parts availability. The only part that's important to the customer is the one you don't have.
Speaker 2:That's right, and nobody pays attention to how long it takes to get the back order here. Well, and that's where the advanced analytics that we have capability to do today really can play a big role in improving the customer experience. But at the end of the day, if we don't have customers, we don't have a business right, we don't need employees. And I'm not saying that you have to just bend over backwards and everything the customer demands they get. They're not always right, even though they are the customer, but you have to articulate how you say no, when you say no, and the why behind saying no and what that means. Right, and I really like engaging with customers. So it's not just me over here armchair quarterbacking. You know this is me speaking from. You know, real time activities. And then our last conversation I think it was that one I mentioned I'd spend one day a week, the entire day, on the road either making sales calls by myself or with the sales person or persons or different ones, you know and I would want to go see customers that recently had purchases large purchases, medium, small and or angry upset customers. I want to do a follow-up and a lot of times I'd walk in and they were chewing on me as I entered the building and, as you know, we were leaving the building, they were shaking my hand, saying thank you, Appreciate the time. You know, and we'll see you next time at the dealership. And you know that. You know, and they weren't all that easy, but a lot of them were, and it's just really being willing to ask the questions. And when I had people that I rode with, I would, I would talk to them about, hey, get to know your customer. And where I'm going with this little rant is using AI and a system that has good alignment. It has limited noise, where the CRM is not noisy, where your DMS and your business system and the CRM are aligned.
Speaker 2:Before you go see that customer, look up and see what did they recently buy from you? Did they buy a truck? Did they buy a tractor? Did they buy parts? Did they have a big service job? You know, hey, their customer satisfaction index score for you is listed here. Why did we get a bad rating? Why did we get a good rating? You know all those things.
Speaker 2:Go out there with that knowledge and today you can in every dealer. You should be able to get that in real time and you know, within, let's say, within a week of it happening. So real time, five days, you should be able to go out and see the customer and you should embrace that, and I think that's one thing. That and the dealers they're still not teaching their leaders. They fast track people into positions that are beyond their skillset to lead. Next thing, you know, you end up and I'm not opposed to young people or anybody getting promoted.
Speaker 2:What I'm simply saying is don't put people in positions where they struggle too much and fail and because when they're failing and struggling, they're not taking care of the rest of the team because they're trying to survive. And while this podcast is centered around AI and things like that, I still in my consulting and my conversations. The human element is critically important and I'm not a fan of the thought process that AI is gonna replace everybody on the planet and we're all out of a job. Yes, some jobs will be displaced, but new jobs will come in support of all these other things. So it's going to come down to a matter of either you learn new skills or you will get left behind. So that statement I do agree with, but I don't think it's all doom and gloom.
Speaker 2:So, somebody used the term the other day. Yeah, it's just going to be like the Terminator, I think the original one with Arnold right, and I'm like, well, I don't think so. Well, robots are a thing, but I don't see it going that direction either.
Speaker 1:It's the whole nature of business and development and technology. At one point in time, an automotive production line needed 20 years of use before it broke even. Yeah, imagine. So here we've got. A couple of weeks ago I was kind of intrigued NVIDIA announced a new robotic chip and it's $2,900. But if you buy more than $100, it's 2,900 bucks. But if you buy more than a hundred, it's 1,900 bucks. And that got my little head going. Well, darn it. Every joint on a robot has to have a chip Correct. So you probably got a hundred 200 chips in a robot.
Speaker 1:Now we're back to the production line of 20 years before it breaks even. How much is that robot got to be displacing replacing in order to pay for itself? But everything you're doing and everything that we're kind of blaming or using AI as the stick, it's about building relationships. It's about getting the customer to trust you, because they don't know what the heck's going on either. They look at you as a savior. How are you going to do that? You know it's sitting talking to those people. Somebody comes in the front door within 10 seconds. You better acknowledge them. Just stick your hand up if you're 10 seconds. You better acknowledge them. Just stick your hand up if you're on the phone and wave at them, it doesn't matter, it's being people first.
Speaker 2:Well it's going down to. One of my notes is I wrote AI as the game changer. Right, it's an operational process. Right, we still have to interact with people. Right, and you can go to market with all the different things predicted maintenance, telematics, ai parts stocking and dynamic pricing. Some of those things have been already out there for a handful of years to some degree. Smart technician scheduling, capacity planning, all those things you can give. Everything I just mentioned leads to improved market intelligence and lead scoring. So now, when you understand your market and you're scoring all the leads, you know which, the probability of success, all these different things based on all these different factors, now you're moving your operation at the same pace as as well faster, but with the people along for the ride. They're not just on the sideline watching it all go by and then you, then you bring it forward. Where you use the buzzword today is agentic AI. So that's just a fancy way of saying hey, that's you know, you building these little agents to work together. So that's Troy Otmer, again being augmented by three or four different agents running.
Speaker 2:In our last podcast, our reference I was actually in the middle. It was running while you and I were talking. It was distilling data based on a very complex, prompt structure that I wrote, that went out there and gathered all this data. And now this data is part of a presentation for a project I've been working on, and you know. And of course, there's validation processes. But guess what? You write these agent AI platforms to help you validate. Because you read it I read a lot too, man. I have thousands, maybe millions of words, but you know it's really good.
Speaker 2:So what does this do for the humans? Well, it enables the leaders, the managers, the technicians, the part sales, new sales teams. They can upskill and increase their throughput because, ron, if you want more output, you need better throughput capabilities. Right, you know, and we can go down the rabbit hole of Six Sigma lean process management, all that rabbit hole of Six Sigma lean process management, all that you know. But at the end of the day, you want more output. You got to have improved throughput and you got to quiet the noise, and you know. And you want your employees to engage your customers better and you got to give them the better tools to do that and you got to train them, you got to lead them. And you have a saying John Dowling mentioned it the other day when he was presenting. He said you know, ron says we manage processes, we lead people, and I wholeheartedly support that and you know. So he was out there quoting you, by the way.
Speaker 1:I pay him a lot of money for that.
Speaker 2:I know that's a good point.
Speaker 1:No, but the thing that you're exposing again it goes back and I mentioned it. We've got to know to deliver to you information not data, information Correct that you could translate into action. Yes, and training is important and something that we have been terrible at in the 90s is when it really became prominent. In the 90s, almost everybody AED Caterpillar. Everybody stopped training because it was too expensive and that's when we started it. I sat in front of the computer and I talked for the summer and created eight textbooks, 250 pages each, and in those days I could talk for 30 minutes and I'd leave the computer and it would take them an hour and a half to catch up with me with voice recognition stuff. Today it's instantaneous. I pick up another piece of software a couple of three years ago that it was limited to 5000 words in a product. It was an audio track type of product that created subtitles. At the same time, last week it became 20,000 words. Well, all of a sudden you can be talking about books.
Speaker 2:Yeah.
Speaker 1:So I can have, I can turn around and I can take an audio book and I can run that through the computer with voice recognition and turn it into my own document that I can then put through Copilot and make it more casual or make it more formal or make it sexier or whatever. It's all kinds of different things, right? The problem that I see with artificial intelligence which, by the way, was first introduced to the world in 1950, is that and I mentioned it earlier we have to learn how to ask questions and as you're evolving, you're finding better ways to ask those questions to get the answer you're looking for. And you do it by making mistakes. Yep, yeah, I have to go. Oh, that's no good.
Speaker 1:So just imagine that I can take the dollar value of a transaction and the time between the transactions, so I can say transactions once a week, once every two weeks, once a month, once a quarter, and dollar values of 50 bucks, 500 bucks, 5,000 bucks, and I can build a grid for every customer, for every dealership, right? And if that buying pattern changes, I want the customer names delivered to the person the next morning. So the day it changes within 24 hours. You missed a day, you missed a dollar value. I'm going to go hey, troy, what's going on Right? And you're going to say well, what do you mean? Well, I'm just noticing a little bit of a difference on your account. Is something going on in the company at the moment? And what I'm trying to convey to the customer and how I communicate, that is I care, I'm here to help you. What do you need from me right now? Is something going on I can help you with, and it's a completely different sales gig, isn't it?
Speaker 2:Oh yeah, well, Ron, it comes down to dealers oftentimes that they they come up with the answer from the service side. We got to sell labor. Yes, that is that's what you do, but that that's actually inaccurate. Yes, your job is to take care of your customer, your installed base, the people you're selling product to, newport, et cetera. And yes, you have to run your business in a profitable manner.
Speaker 2:Enough on reducing their downtime and or, and like we said earlier, customers don't use the dealer maintenance services because they're sending out a level five tech at the highest rate when you should be using a level one or two or journeyman or what have you, at a different rate. You know, I, you know, I had that philosophy when you and I first met many years ago and I followed that same thought process by adapting, you know, to those market needs from a maintenance side. And look, I made more money at the end of the day for the dealer groups I've represented by focusing on driving high levels of maintenance and having technicians working, and occasionally you would have a high-end tech on a project, for whatever reason it happens, but the goal was never to have those people on changing oil and filters or basic maintenance right, and you know, and I put them out in the field, I don't want to see them in the shop, let's go to the customer. So you know. Field service. You know, and I put them out in the field, I don't want to see them in the shop, let's go to the customer. So you know, field service. You know, I don't want my trucks coming into the shop every morning at 8 o'clock to be dispatched. No, they're mobile, they can dispatch from home and they go straight and we'll run parts to them. You know, and all those different things. So I mean dealers shouldn't just focus on hey, we need to sell labor or we need to sell parts. No, you need to reduce your customer downtime. You need to improve that experience. You need to improve your first time fixed rate. Uh, you know, so it's now. You don't have to go out three times to fix a problem. You do it the first time, you know. And then you know, target targeted sales wins every time. You know, have a plan, execute your plan Right, you know.
Speaker 2:And then, with, with AI and you can, you can validate the ROI, like you were mentioning. Hey, within within a day's notice, or within that same day, from the morning to the evening you can say hey, what happened to your business today? You're trending down and you see that in real time. So, and look, if you get that answer in one to two hours, that's real time, right, you know, versus, I'll get an update on Monday morning and it's Tuesday now, but next Monday morning I'll have an update. You can't run your business effectively Tuesday now, but next Monday morning I'll have an update.
Speaker 2:You can't run your business effectively and that's why, you know, we had to be creative by and creating queries to mimic what AI can do for us very easily today, and there's a lot of hard efforts behind the scenes. But you know, to me, this AI adoption is a leadership opportunity. And I say leadership I'm not just talking about your general manager, parts and service managers, et cetera. I'm talking about dealer principals or ownership groups, private equity included, and I know PE and others like them. They have a different mode of operation and profit before people does happen and while they're not publicly traded, they're very similar into, you know, focusing on shareholder value, and it's easy to keep the shareholder in front of the customer because, remember, shareholders, you have no value if you have no customers.
Speaker 1:I used to have fun using, you know, customer retention as a tool. Harvard, in the 80s, made the comment that customer retention was the single most important thing to drive profit. So then you know, in your thinking and mine relative to maintenance, I'd sit down with a group of people at the dealership and say you know how many hours does it take? I got 2000 hours on my machine every year. How many hours should I be spending on maintenance? And we'd look at it in those days 250, 500, 1500, blah, blah, blah. And we come back with a number that was 40 to 50. To make this arithmetic easy, let's use 50.
Speaker 2:Right.
Speaker 1:And then I'd say to them well, what, what's your working machine population out there? What do you think it is? They don't know, which is a big problem, but well, 5,000 machines. Okay, how many people does that mean there's doing maintenance out there? 50 into 5,000, thousand? Well, that's a hundred people. How many have you got seven? Who do you think the other 83 are working with? Or 93 are working with? Oh well, wait a second. How much do we make in income on maintenance? Your hourly rate's 100 bucks. So I charge 50 for maintenance, 50 hours times 50, that's 2,500 bucks. And that much parts through another, that's $100, so I charge $50 for maintenance, 50 hours times 50, that's $2,500. And that much parts, that's $5,000. So $5,000 per machine for maintenance, and instead of $93, let's just say it's $100. How much business have you lost.
Speaker 2:Yeah.
Speaker 1:And so you know one of my favorite little things to do. I always checked it first, but I'd go out into the shop and look at the machines that are in the shop and find how many of them had competitive filters. Oil filters, no others, just the oil filter. And in many cases it's a big number 60, 70, 80% of the machines in the shop have a competitive filter. I said are you going to do anything about that? Well, what do you mean? Well, that guy's got a competitive filter. I said are you going to do anything about that? Well, what do you mean? Well, that guy's got a competitive filter on this machine. Don't you want to get him to use your stuff? Yeah, but our filter is really expensive. I said fine, put it on for nothing. Call him up and say do you mind if I change your engine oil filter? I'm going to put one of mine on instead of yours. I'm not going to charge you for it. Oh, that's okay, why do you want to do that? And then I can start talking about the features and benefits. I can talk about what happens. What is it? You know, particulates. And here we go, and all of a sudden the guy is by the way. Who chooses that filter? The guy that does my maintenance. Do you tell him what filter to use? No, he picks his own.
Speaker 1:Wait a second. This whole thing's upside down, yes, and it's been that way forever. Here comes artificial intelligence, and I'm going to use that as an excuse now, cause I'm going to know I got 5,000 machines out there and they're averaging 2000 hours. That's eight of these filters every machine every year. That's 40,. Eight of these filters every machine every year. That's 40 000 of those filters I should sell. I only sold 372, right, what's going on here? And I can do that for hose, I can do it for batteries, I can do it for undercarriage, I can do tips, I can do it with darn near everything because of ai correct, it was hard before and you and I've done it before manually. It's a bear, it is. But if you want to do the business properly, you got to use it, and that's why I say it's a bit of an, it's an opportunity, it's an excuse. Let's get looking at the business differently.
Speaker 2:Well, it's one thing you said and I know we're getting close to time, I believe but in closing, you know, not understanding what your OEM installed base is in your market is a problem, and the second part of that problem is not understanding what your competition's installed base is in your respective market is also a problem. And, in closing, what I would say to that would be real simple you need to know what the entire machine population looks like. Now you may not be able to go chase all of it because it's OEM specific warranty, blah, blah, blah specific warranty blah blah, blah.
Speaker 2:But make no mistake, a lot of the maintenance that a dealer can do will be on non-oem specific product. And that's how you transition a customer to your oem product at some point down the road by going out and showing them, hey, how well you take if you're a cat dealer, how well you take care of their john deere equipment, and when it's time to trade them out, boom, you trade them out, they roll them into a cat or vice versa. And you know some of the second tier type products that came along, like hyundai, etc. They've made a lot of market share gains against cat john deere, volvo, kamatsu by playing that game and you know saying, hey, we're going to be what's our, we can't go get them head-to-head. So how can we gain market share and or wallet share on them?
Speaker 1:And that's just some of the methods to do that. Yeah, and the interesting thing is there's tools out there Equipment Data Associates, eda any machine that's financed. There's a report. I can buy it, I can do it by county, I can do it by brand, I can do it by dealer. It's been around over 40 years, almost 50. Who uses it? What do they do with it?
Speaker 1:The first thing that comes back at me when I ask that question is well, it's hard because they put the name in differently than we have it in our profile. Uh, okay, so technology has to come into play here. But but there's a whole host of things and it leads the discussion into a different place. Underneath this, I'm asking about AI, and there's lots of iterations, there's lots of things to consider, but it's not really AI at all. It's about doing the business well. Correct. And your comment about selling to john deere replacing a john deere machine and here comes hyundai, and hyundai's done a particularly good job at it, and it's because of their experience in the car business, correct? And who was the first one to do that? Toyota, yep, toyota created Lexus. The top of the Toyota brand line is Camry. The most expensive. Camry is the cheapest Lexus and everywhere we do it's the same thing and they learned that lesson. Well, we didn't learn that.
Speaker 2:Well, funny story on Hyundai. When, as a young tech in the 80s, when Hyundai came to the market, obviously Toyota and Honda, you know, had a good reputation, good quality product, you know, and I was fairly new, so guess, what I got to work on was Hyundai and and I thought that was going to be a curse. Well, I've, really, I've realized very quickly that this is a quality product and it's easier to work on than the American counterpart and I'm like, wow, this is interesting and to see them continue to progress the way they have. They pay attention to what makes their customers happy and their maintenance and support. And then you know the spinoff lines that come from it, their luxury line, you know, hyundai got one of the premier luxury lines. Now, same thing Quality of the product, right.
Speaker 1:What's the luxury line called from Hyundai?
Speaker 2:It is Genesis.
Speaker 1:Yep.
Speaker 2:Yeah.
Speaker 1:I had a Genesis that I bought in California and shipped here and the dealer was going to have to pay for it the next week. So I got a pretty good deal and at that time Genesis had two products. Today they've got six, and the price differential to Lexus, cadillac, all of the premier lines, was $40,000. Yep, and if anybody is going to throw away 40 grand just to have an ornament on your car, then you know I'm Scottish for a reason. But you know this takes us down another path, troy, that I think we need to have another one down the way, but it won't be AI driven anymore, it'll be the analytics, yes, yeah anymore, it'll be the analytics.
Speaker 2:Yes, yeah, and analytics. You know, ron, we're going to have to train people to understand analytics and not over complicate it either. Right, that's part of it.
Speaker 1:I'm almost in a place that we can't train them on analytics. We have to give them the analytics and tell them how to use the tool.
Speaker 2:Well, probably, you know, I don't mean that to be disrespectful, but no well, you're probably right, and maybe I'm being a little optimistic about a handful of folks I'm working with that I think have the capability to learn it. But for the vast majority of people you're probably right, it's a plug and play Plug it in and play.
Speaker 1:Well, yeah, I agree with you 100%. One of the things that's interesting the other day I had a chat with somebody who runs one of the dealer management systems businesses and they're having a hard time getting people, as everybody is. And I said, well, you know every install that you get to. Why don't you make a deal with your customer that you're going to take George and Mary for a year on your payroll and you're going to have them go out and do customer service for you and installs for you and expand their knowledge and understanding of your system? You're going to pay for them and then, when you give them back at the end of the year, they're going to be a hell of a valuable asset for your company asset for your company. And it's kind of putting on the ear like, if I'm if I'm a dealer, maybe I want to provide them. If they've got their own mechanics, maybe I want to give them a mechanic and I'll take one of theirs.
Speaker 1:Yeah, right, ultimately, come back and say, well, why the heck do we want to have that mechanic on your payroll? And if you really want to get nasty, I won't pay an equipment salesman any commission for a sale when he replaces the same brand that I'm representing. I'll pay him a lot of money if he replaces a competitive brand, because if you look at the dealers, they're in their 30% hole and they stay there. You're right, yep, and my goodness, it's so easy. John Deere and Caterpillar have between 70 and 80% of the markets here on equipment. Volvo, camacho and everybody else is fighting for the other 20 or 30. Right, that's. That's like standing at the beginning of a race knowing you're going to lose.
Speaker 2:I've never looked at being a John Deere dealer predominantly the cat dealer always had us 10 to 1 in terms of size in almost every market. But that to me, was not a negative. It was an opportunity to expose their weaknesses. And look, cat dealers are very strong, but every dealer, no matter how good you are, how top tier your OEM is, there are weaknesses that can be exploited. And that's where data analytics will come in to help you open up and kind of peek behind the curtain of what the market truly looks like and where there's opportunity.
Speaker 2:And for a dealer to be successful at any dealer large, small, medium, everything in between they have to be willing to take a look in the mirror and utilize the AI or data analytics dashboards. What have you to? You know, have that bit of reflection. And you know, let's start now or are you going to get left behind, right? You know, let's start now or are you going to get left behind, right? And if you want to grow your business, you know, if it's a multi-generational business, you know they usually when they hit the fourth generation, they're probably on their way out of business or being consolidated. You know, let's change that, let's paradigm shift, let's get busy and, you know, let's change that. That's paradigm shift. Let's get busy and, you know, let's augment our workforce with the best tools we can give them today.
Speaker 1:Let's wrap this this way In Canada, when I started at the dealership, there were 10 dealers. Today there's two. Yep In the United States, when I started with the Caterpillar family, there were 50 dealers. Their goal today is to be under 20. And part of that is because of the cost of the equipment, the money that's required to operate these dealerships. Same thing's true with John Deere. Rush is one of the largest in the country. You know, rdo up north is the same thing, branton, canada, it's the whole country.
Speaker 1:So all of these dynamics have changed and analytics is going to get us there. But it's going back to basics, troy. Yeah, it's very fundamental things. You need a part. I have the part, I don't have the part. Oh, the guy at the counter. How much is that? Filter 15 bucks, boy, that's expensive. Then the guy at the counter doesn't know what to say. Filter 15 bucks, boy, that's expensive. Then the guy at the counter doesn't know what to say. So we have a lot of work ahead of us and you're going to have a lot of fun. You got 20 years on me now, buddy, you better be looking after it properly. So you know, troy, thanks for your time and fellas and people out there listening to us. I hope that our goal with these podcasts is to get you thinking, and I hope we succeeded at doing that and I look forward to having you with us at another podcast, another kind of conversation, in the near future, mahalo.
