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
If Best Doesn’t Mean What You Think, What Does It Mean
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
What if your dealership stopped reacting to problems and started predicting opportunity? We sat down with Mets and Nick, the team behind a from-scratch dealer management platform, to trace how a human-centered CRM evolved into a scalable DMS and where AI now multiplies the impact. The throughline is simple and bold: technology should fit the business, not the other way around—and clean signals beat crowded screens.
We walk through the early missteps and course corrections that every tech leader will recognize: rebuilding the stack to something future-proof and hireable, resisting feature bloat, and prioritizing role-specific views so parts, service, and sales see only what they need. From there the conversation shifts to the power of triggers. Think: the buyer who always orders every two weeks but has gone silent, the fleet that hits a three-year mark, the prospect who clicks a high-value email at 10 p.m. With disciplined data capture—site behavior, email engagement, telematics, service milestones—AI can surface these moments automatically and route them to the right person at the right time.
We also tackle the cultural roadblocks. Dealers will approve a multimillion-dollar machine in a heartbeat but hesitate to invest five figures in software that guarantees faster quotes and same-day invoicing. Yet this is where ROI hides: shaving clicks off the parts counter, auto-alerting sales to strong intent, turning completed jobs into instant, accurate bills. As sensor data grows, AI helps redefine what “best operator” means by weighing idle time, safety, maintenance, weather, and job complexity, not just output. Roles evolve too—analysts curate data quality and validate model insights while frontline teams act on event-driven queues instead of chasing stale lists.
If you’ve wondered how to go from dashboards to decisions, this conversation lays out a practical path: start with foundations, capture the right signals with consent, let AI find patterns, and make it effortless to act. Your brand and territory are strengths; pairing them with proactive, data-led workflows is the competitive edge. Enjoy the episode, then subscribe, share with a colleague who still lives in spreadsheets, and leave a review telling us the first workflow you’d automate.
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 going international today, so we have a gentleman from India and a gentleman from Canada, actually from what am I gonna say Holland or the Netherlands?
SPEAKER_02:Well, technically it's the Netherlands, but it is uh euphemistically known as Holland.
SPEAKER_01:Yes, that's right. Nick and Matt are joining me today. We're gonna talk about artificial intelligence and the dealership world just floating around. I don't think anybody's got a real clear definitive answer as to what this is, but that's where I'm I'm gonna start. Um, and if you wouldn't mind, I'd like Mets to give everybody a short introduction to yourself and what you do, and then after that, Nick, if you could do the same thing, that'd be great. Mets?
SPEAKER_03:Thanks, Ron. Uh I am Ron's best friend, and um I'm one who encourages his hobbies. Um aside from that, uh I got to know Ron by uh realizing I needed to learn more about our industry, and so I forced myself uh on him by coming to visit him at his home and asking for three days of one-on-one training, and that's how we uh we got to know each other.
SPEAKER_01:That is how we started, isn't it? I didn't even know. That is how we started. I didn't even think about it. Aside from the dinner that I flew out to have with you in Chicago, yeah, right. Which I also forced on you. Nick, you've been much kinder to me, sir.
SPEAKER_03:So aside from that, aside of leading leaving the dealership world, uh, and in the sense of like working directly at a dealership, um, I now uh run visibility DMS. Uh and that is a from the ground up new dealer management software platform uh that we've been building for the last uh I think this May is five years, Nate, Nick. Yeah, and and Nick's CTO.
SPEAKER_01:Yeah. Wow. So you started with COVID. You're the guy that's responsible for that.
SPEAKER_03:For for starting the company during COVID, yes.
SPEAKER_02:Wish I could take credit for COVID.
SPEAKER_00:Where are the interding in all of this? I I I know Mets since like last six years, I guess. And we started working on the DMS since day one. And right before COVID. Yeah, we started with very little, with the uh the code is everywhere, we had a very little vision, and now it's it's a humongous monstrous platform that does everything for the dealership. It has every single nuances, every single thing. So we did lots of things in six years. Uh looking back at it, it's pretty amazing. And uh Mets and I live like a 20 minutes away. We are become a very good friend in the last six years. So and Ron, I hear about you here and there. So yeah. It's uh it's uh nice to yeah, nice to nice to connect with you. Yeah, totally. And uh I'm from the from the technical side, I'm from the IT industry. I consider myself as a learner. I'm still learning about the new stuff, and uh it's a it's a good time in the industry. There are lots of things happening as everyone knows, and and lots of things are gonna change very quickly and very fast.
SPEAKER_01:So let me let me challenge the term, first of all. Let's just not call it artificial intelligence anymore in this discussion. You guys created a system, a business using intelligence to evolve it for about five or six years. So, Nick, I'm gonna assume you're more technical than Mets is. What's the first step? How do you start?
SPEAKER_00:I think the first step was no go ahead, Nick. No, no, no. First first step is always understanding what you want to do, right? Where you want to start, what is the business. Um you don't want to drive yourself ahead of the business. Like, if if I'm looking for a pen, I'm not gonna go up and buy the entire steppers, you know. Like, I just gonna understand what we're looking for, and then depending on that, we're gonna use the technology to achieve this in a very efficient and better way. That's what it is for me. That's what the starting point is, understanding what we need.
SPEAKER_01:Okay, so back to you then, Matt. So for me, it was what need or want statement did you give to Nick? What did you tell him you wanted to do?
SPEAKER_03:Um what I wanted to do is approach it from a more um human perspective. And so, you know, what what we've tried to do is look at it from a natural object point of view instead of a transactional system. In the end, we had to build the transactional system, but we wanted to model it and represent it to people in a in a human way, not that they were learning how to run transactions or run a you know feeded accounting system. We were we started with a CRM. And so we were dealing with really much more natural objects. And and then we wanted to make that something that was more intuitive, you know, the to get away from um a transactional systems type interface and be able to do it in technology that would allow us to eventually let people engage with it in a much more natural way.
SPEAKER_01:So, with that starting point, Nick, how much backtracking did you have to do from where you wanted to go at the beginning? What did you find you doing you had to go back and do over?
SPEAKER_00:It's an agile approach. You go step at a time, you do small things, um, you work with Mets and maybe the client, and let's see what they are looking for. Are they happy? And then you just simply build on top of it. You don't think at the end line, finish line, you do slowly, steady step at a time, and building on each other. Like let's say I'll give you an example, you do three things, and uh your mind, the third item is the best thing that you did, but the client might not like it. When Matt's gonna try it, he might think that you know what, the second thing is the best. So you just have to go with what will be the useful and what would be the best feature for the client and how they can interact with that and how useful it will be, rather than what you think will be the best, and you just have to build on top of it.
SPEAKER_01:So, knowing what you know now, is there anything you do differently? No, I wouldn't do it. No, I'm kidding.
SPEAKER_03:Um I I think one of the things that was really fun about um one we we did backtrack a little when I first met Nick. The CRM application that we had was built in a a little more obscure technology, uh, just slightly. It was harder to work with. And so before we started the full DMS project with a couple of partner dealers, uh, we rebuilt the main application uh into a tech a technology stack that we knew would be very common and that we'd have no problem hiring future developers to understand. Um so that was our little backtrack. And and then Nick's right, you know, like um agile software is about taking what's next and evolving with the people that are using it in order to put in place the next piece. And I think you know, what what helped me do that uh is one Nick understood the requirements as far as uh structurally to think you know ahead and not limit them limit ourselves structurally. Uh, but also from my perspective, then it was like, okay, well, if someone asks for you know a little feature that does this, I know it's gonna morph. I know it's gonna become the next thing because I've seen it in operation in uh you know half dozen places. And so I can sort of predict where people will want to go. And so we only build it in a way that it will be conducive for doing future iterations of that.
SPEAKER_00:Oh, and just add to what Matt said, uh just to just add to quickly what Matt said, the foundation is very important, right? So uh what you want to build, you want to make sure your the choice of technology, the choice of platform, the the foundation has to be solid, then the requirement will change. You you you will grow, the software will grow, grow. But as long as the foundation is better, that they're not gonna cause you the financially and the mentally and the time-wise is not gonna give you the hard time down the chain. So that's what we learn on, and that's what we as mentioned. We corrected. As soon as we realize this this framework and the technology we're using, it's not gonna be scalable. It might be good for now, but once we're gonna have that many user-based and the clients and the dealers might be problematic. We we realize that and feature on right away.
SPEAKER_01:How important is it? This is to Nick. How important is it that you understand the business that you're designing a system for?
SPEAKER_00:That's a very, very important. Like uh it's just give you the like in some scenarios when you have to make a decision, what would be the right, what would be the best or what is important and what is not important. Where you know the business, then you can kind of like a little predict about it, and most of the time knowing the domain knowledge and the business knowledge will help you to to make that decision right and better. And sometimes you might think, oh, you know, this is not a big deal, but uh but sometimes if you know about the industry and the domain, and as a technical person, this might not be a big deal, but for the user who's doing this um a thousand times a day, for them, it's a very annoying thing, right? So understanding about the business and how they work their day-to-day life cycle, that would help that way we can see the world in a different way. We can see oh, this might not be a small little thing, this would be an annoying thing for them, and then we can approach it better.
SPEAKER_01:So, let me let me break the the the systems world into three pieces, and I'm gonna call the designer an analyst, the programmer a coder, and the installer an installer. And I'm gonna start with the premise that from a business system perspective, whether it's Microsoft Dynamics or Zap or Infor or Constellation or Vital Technologies or anybody, less than 50% of the available tools are used. Why is that?
SPEAKER_02:Why why are less than 50% of the tools that are built used?
SPEAKER_04:Yeah.
SPEAKER_03:Because they don't fit everyone's business model or they don't fit everyone's business focus. When when I um when I set up the central contract management department for Tormont um and built uh contract management software there first, which is where I learned how to do this, um, you know, I started speaking at CAT conferences about the whole project. We did some write-ups, people got interested, people came and looked at what how we were doing it. And the first thing that happened was they all thought it was great. And the next statement was like, well, we see it this way, and I see it that way, and this area is a focus for us, and it wasn't for another dealer. And so, you know, in in the end, tools represent all the available functions that different users might need, and some won't. Uh and I think that's sort of a a modern way to handle it is to recognize that um you don't want to show everything to everyone, that it's important to have functionality that hides or turns off, uh, and that isn't constantly facing every user. So, like you click on a menu, you get 27 options, and they may only ever use three. So, but you keep showing 27 options to someone.
SPEAKER_01:Okay, so let me let me take that as a starting point. And I'm gonna say, Nick, I've got uh 10 stores, I've got four people on the parts counter in each store, so I've got 40 people selling parts. Why can't I have the individual parts salesperson select from the options that Nets just explained and build his own?
SPEAKER_04:Assemble.
SPEAKER_01:Like we build a house, we got studs, we got panels, we got insulation, we got plumbing, we got electrical, etc. And we and we frame it. Can we do the same thing with software?
SPEAKER_00:Um it's a very it's getting very expensive. You know, software is people just understand software is oh, I can just build it. They don't they don't understand the nuances that comes with it. Like once you build it, then you have to host somewhere because software needs a computer to run on, and that computer cannot be your laptop. It needs the secure place, it it's like you have to either put it on a cloud or you have to buy the service, and you have to regularly maintain it. Now, the business who specialize in selling the parts, um that's not their that that's not their domain of business. And they might be able to do it, but for them, they don't have expertise. They might be able to build it themselves as well, but then they'll have to figure out or they'll have to hire someone or they have to learn oh, where are I gonna host this? Okay, now this technology is now redundant. Now I need to upgrade the technology, like what it will take to upgrade. So there are, and then there is a constant security threat. Okay, the what happened if you're where you hosted your application, that server burnt down, or there is some flooding in that area. Uh, like your entire thing will go down, and if your software is go down, there are 40 people, how are they gonna sell their parts, right? So most of the company, what I realize is they their business is not writing a software, their business is selling the parts, right? So they either partner with someone who are best at writing the software and understand the business as well, that how best way they can sell the parts, uh, like the DMS, and they can partner with the visibility DMS or any other DMS or any other providers, and then their job is to sell the parts. Other providers' job is to make a software that will enable them to sell more and more parts in a very fast and effective way. So there are very clear lines, and if you're gonna do everything together, you're gonna fail on both sides. So that's why I have seen that most of the company is just like do what they are best at and then seek other self who they are best at.
SPEAKER_01:I agree with that. So why why should I even have anybody on staff that does systems? Why don't I contract for that completely? It's not my expertise, it's not my business. I'll buy somebody's services.
SPEAKER_00:Like so, what I so when I say technology, technology is not just uh the writing of software. Like technology comes with you enter the door, you have the fingerprint. Like that's also a technology, you know. Like you enter the door, then you punch your card, you open your computer, your computer goes back. Like, you know, so technology is everywhere. So when we I think this term gets misused that IT, it is not IT, it is IT software development is different than the regular uh information and technology. IT, IT is different than the software developer. Software development is the own dedicated branch inside the IT, right? So now the company needs the IT people, they don't necessarily need the software developer or the or the designer or something. They need the IT people for their day-to-day businesses, like um the like the the their punch card, their timeshift, their laptop management, their inventory management, their email management. Uh so you can get those kind of expertise, and those are the very easy expertise. Um then the software development. So I think most of the companies now have a small set of those IT staff uh to do those and manage that.
SPEAKER_01:Okay, so let's let's then leap forward to artificial intelligence.
SPEAKER_03:Can I add something to that first?
SPEAKER_01:Oh, yeah, go ahead, Matt. Sorry.
SPEAKER_03:Because Nick touched on a couple of things there. Um, and we have a lot of experience dealing with different companies of different sizes. There's a lot of value in having people on your team that understand technology, uh, but that are also focused on um the implementation of that technology. We come across a lot of people who want systems, who love shopping for software, and who want to be more advanced, uh, but it's always like someone's sidebar. Right? And to have someone on the team that is focused on that uh prevents people from doing like shadow IT, you know, because you sort of alluded for a moment there to you know the idea of something like uh what Microsoft put out, like Power Apps, where pretty much anyone who had some little bit of Excel skills could build software. Like, do you do you really want your parts person who isn't really good at it and isn't trained on it spending hours building it? Uh it happens in every dealer. Ask someone for their fanciest spreadsheets, and someone has got a thousand or two thousand hours into designing and maintaining a spreadsheet. You know, and I think if you want to really apply technology, it it's definitely beneficial to have um someone who understands it and someone who's focused and can take a project and keep it going. Because you know, dealership businesses are very reactive. Um, and it's pretty easy to get distracted by day-to-day. And projects just sit around and no one picks them up, or just six months later they're like, Oh, yeah, I was trying to implement a CRM. You know, and uh I think there's a lot of value in people who who are focused on it if it's something that you want to add to your business.
SPEAKER_01:It's we we we start getting into interesting or weird, let me use that word, areas customer relationship management by the combination of the three words, either one of you picked this up. How do people that use CRM software, customer relationship management software, manage the relationship? They manage the relationship.
SPEAKER_03:A relationship is about information. You have talked about this before. Like you're a you're a terrible husband if you forget your wife's birthday, you know, and that's one person or your anniversary for that matter. Um relationship management is about having information, and and having a CRM at a dealership is about making sure that people who are out on the road aren't constantly calling back to the office to ask questions or to have to get approval through a slow process.
SPEAKER_01:Nick, do you want to modify that or expand on that? Or you got a different view?
SPEAKER_00:No, I think Matt's on right on point.
SPEAKER_01:Um Okay, so customer relationship management to me says you're giving me the information that tells me that Nick, who normally buys every two and a half weeks, hasn't bought anything for four weeks. Go find out what's going on.
SPEAKER_03:Yeah, your wife hasn't invited you. Your wife hasn't invited you out to the movies for two weeks because you forgot her birthday. Precisely. Yeah, like and and that's the driver. I'll go back to our conversation many times of that's like metrics and triggers, right? And it's like there are two things you can, or a couple things you can do with CRM, but the most valuable thing is to have the computer do what it does, and this will be a nice segue for Nick. Um, to do what it does, which is understand information and turn that into triggers. Hey, so and so hasn't bought in four weeks, and they've always bought every two weeks. You know, probably requires a phone call. Um, you know, these customers bought machines three years ago this week, and they haven't, we haven't seen from them. Probably time to go ask how old that machine is and if they're keeping it or if it's still there or if they need a replacement. That's that's you know, data mining. And I think where one of the things that Nick's been working on is exactly that idea of like, how do you mine data in a non uh linear way in a sense without having to think about every variation of it um and come up with every trigger by yourself.
SPEAKER_01:Nick, do you want to expand on that? He gave you an opening.
SPEAKER_00:Yeah that's just like that's just like AI how you're gonna now we're gonna go into this AI and all this modeling terminology. AI is nothing but gonna help you or excel your task or achieve your goal in a in a very effective and a faster way.
SPEAKER_01:And it's interesting we call it artificial when it really isn't artificial at all. It's real.
SPEAKER_03:Neither is it intelligence. That's rather recognition which is exactly what you're asking it to do.
SPEAKER_00:Yeah so in a legacy CRM system sets the criteria so no one no one really set the criteria in a legacy CRM system so legacy I I mean it's not even a legacy because MI is still evolving. So in a current and old CRM system where the person who operating the CRM who deciding that you know what like uh I haven't talked to Mets for uh a month it's time to give him a call or oh why this guy is not purchasing for the last six months let me let me just send him an email so the guy who operating who making a decision who should go after and who should ignore now there are human minds tend to make a mistake or we try to lose focus when there are too much information given to us right so um the growing company where there are so many variations where you're gonna miss something you might gonna reach out to 10 different people but then you're gonna miss all the hundred people which you haven't thought about or you completely lose track of right while the AI and and those modern modeling software where you're given your data um and you have to give it in a meaningful way that it can understand your data and then it acts like a human but like a thousand times more powerful than human in terms of that thinking process. So uh we might be able to miss some of the dimension but it's never gonna miss it going to figure it out okay Nick purchased the groceries at this store um 10 times in a like a 10 time in a every week but then he's not doing it for last three weeks. Okay Nick I'm putting him in a grocery bucket then he's gonna he's gonna create all those bucketing segmentization then he can target all those different variations just by your instruction. So you don't have to do much so that's the real power of the AI understanding your data and kind of like increase your sales.
SPEAKER_01:So let me let me frame it a different way I've got a large dealership and we've got 60 field service trucks ideal in an environment that has four seasons in the wintertime the technician's gonna leave the truck running while he does the repair so he can get back in the truck and it's warm. I want to turn the truck off after 15 minutes. Good idea or bad idea?
SPEAKER_03:I like this one the answer is how much time do you want your tech how much time do you want your technician spending to try and bypass that system you put on his truck I'll I'll lock it up in such a way that if he does I fire him I'm serious. I agree what what we tend to do is like we you you know we talked about this system has 27 features that you know that every dealer uses three but not all 27 you know and yet there are continuously new things that people want that don't exist and we're always limited by the way that we have um not just programmed the system but also enabled the system to do things I have reports that do these things and answer these questions but I don't have the other ones. Okay I don't have functions that do certain things like let's let's stop there though.
SPEAKER_00:Yeah how do we define decide what data element we want to collect we want to report on we want to store nobody's done a a dump of every single data field that we should be considering in what sense in any sense I don't know what I'm gonna need tomorrow I better collect it today I think probably much of it's there it's just never looked at the with the use of AI you don't need to collect anything it can figure it can strap a data for you you know so every okay so stay there the first time a data element appears in the system AI will create a field such that it can be replicated and reported on later it can do that yeah is that understand your data and it it doesn't capture it it's just understand your data and until you need it then it can do the word is called segmentization then it can do the embedding and segmentization on top on on top of it. Okay so where do we keep the data if we don't store it that's why you see all the memory size and everything is going super up because all this hyperscaler is is is buying all those memory chips to store all our data like so I so I think you're agreeing with me the first time a piece of data is enters into the system it's gonna be stored somewhere and collected it's gonna be stored there and just sitting there it's not gonna and when AI thinks that now this data I need to read it to understand it better then and then it's gonna go and read it. Otherwise if if you're not gonna ask anything to AI to get a good meaning out of the those data then this data is no use of AI and it's just gonna preserve it somewhere I mean as a we as a as a we need to preserve it somewhere so that later on the AI can go in and access those data.
SPEAKER_01:Okay so let me let me go back to a live example and I agree with everything you're saying not to be agreeable but to open the door to a different thing. Almost every dealer now has a website that allows customers to go in at 24 hours a day with security to look at a part inventory to see if the custom the dealer has the part or not how many dealers do we know of or what systems give triggers in the morning to say that George last night looked at this part number I know of almost none in the dealership world.
SPEAKER_03:I agree why is that are because they're not there you have to log it we we've done this project where we have where we cookie and log everything that a visitor is doing everywhere they look in order to generate that data. The data's there now you have to want to put in place teams that will then find those things right like like everyone runs a mail campaign who in real time or at least the next morning after a mail campaign looks at which of their recognized distribute distribution contacts in their audience engaged with something in a significant meaningful way so that they can then call them up and be like George you looked at our D6 email last night at 10 o'clock that's about five hours after it went out so we know you're lying in bed watching it. You want a D6? And that that that means changing your thought pattern.
SPEAKER_01:Okay so stay with stay with that one for a second because there's privacy laws now that say you cannot call unless the customer gives you permission does your system ask the customer if they want to have permission for us to call you tomorrow because you're looking at this page people hide that in terms and conditions or something yeah you've you've got it but you got to have it there. Yeah and I bet you if we got on a plane and went to 100 dealers we'd find 99 of them that didn't know what the heck I'm talking about.
SPEAKER_03:Yeah and they and they also you know are working in a reactionary way. Like all this AI discussion and data collection discussion means that a dealer wants to work in a proactive way not in a reactive way. So if your 95% of your day is about answering the phone and ordering the part or taking an order or dealing with a customer's problem then you're not ever going to use your data because it's irrelevant to the way you want to operate.
SPEAKER_00:Yep yep so Nick about every 20 years 50% of the dealers in a supply chain I don't care about construction equipment it could be anything go out of business every 20 years people that are selling washing machines people that are selling lawnmowers people that are selling boats 50% of them go out of business every 20 years why is that you have to change with the time and you have to you have to understand where the world is moving right so you if if you if as a company being rigid and you might get a success by doing things A right and doesn't mean that you're gonna keep doing things A and you will assume that okay I'm gonna have this success all day long. The technology is moving the world is moving the people's mindset is moving I might like to wear something uh five years ago doesn't mean that I'm gonna like that like that sneakers or I gonna like that you know pants and shirts it's like our mind is changing right so with that every company needs to adopt and the good thing is that sometimes sometimes change is very hard like you know sometimes it's not only adoption is very hard but to see the change is very hard. Yeah to accept that they're happening. Yeah and when we go to the some of the dealership and when we explain that you need this we we got lots of resistance in a very passive way they don't say it but like we have to we have to explain them why this functionality is useful to you why why this is going to enable your salespeople to do even a job in a very efficient way like we got some of the projects where we have to build just the website and something but we'll have to justify or we'll have to say that not only the website you need certain elements that you know who are visiting your website and what they are looking at what they are clicking on. I mean you want to build a website so for you just the website is good enough but sometimes we have to educate them that building a website is a one thing but having those connection points having those data collector is another thing because that's going to make you successful in the future okay so let's go to the service department and I got a repair that I do in my shop and it's ten thousand dollars it was done on a time and material basis so I did not give them a quote customer comes in and picks up the machine and goes away when is the invoice going to be created left no why because that's not the way it works man.
SPEAKER_03:You know that that's that's not the cultural way in our industry is what you meant to say yes there's there is all we are a unique industry in that way go go pick up your car and wait for the email for the invoice to show up two weeks later okay so stop there and and you mentioned the reason I'm picking on this Nick is you mentioned change.
SPEAKER_00:We often if you try if you go to a car dealer you cannot take your car away unless you pay if you go to a tractor dealer for a repair you can take the tractor away and you can pay me six months later because the invoice isn't even done yet I I might gonna by saying this I might gonna offend some people in some industry but I I've been part of many industries I've been part of the health industry the banking sector the government and also the heavy equipment but so far what I've seen the heavy equipment is the least developed and least educated industry okay so if if you in that regard so I I'm with you if you worked all these industries and this that's don't answer this and I I agree with everything you're saying why is it that we're the least developed in your opinion what do you think is the reason for that I think I would say the the capital comes in um the um the you know the the corporation the capitalistic world I think didn't didn't see or none of the big guys came into it and poured some money in to to just um to just make it the next level and the the person or the companies who are running those businesses who just seeing as okay I just want to if my thing's getting done if my business is going the way I want it to go and not acceptance of the change right you look at like the world of Microsoft you look at the world of like the whole the phone industry where where they started and where they are now and if you look at pick any of the heavy equipment dealership like 50 or 30 years ago where they are started and where they are now you're gonna see that maybe they are like a huge company but you see the huge difference between the Microsoft and them they both might be started at the same time or maybe let's just take not just take the technology company let's take like Facebook um outside of the technology they are in the marketing business right or take some of the banks um the some of the heavy equipment companies and those companies maybe started at the same time from the same same level of starting pace same level of money but now the the distance is very wide because the other guy realized that that putting money to the business is also a a correct thing to do at some point and sometimes what I've seen in the heavy equipment industry um they don't realize or they don't see the real value in the piece of software uh that if if you're gonna say oh I'm building this and I need 100k and everyone's gonna look at you differently where you're gonna go there and you're gonna say oh I need this machine and this machine is going to cost me two million they were like okay I'll give you two million just buy that machine right so where do you see the difference? Because these they see the value of that machine and what they're gonna bring to the table and they are okay to spend two million in just a matter of one second.
SPEAKER_01:But then you're gonna say Matt, do you want to put something in there?
SPEAKER_03:I mean it's it's a consistent experience you know like you you you spend a lot of time in the the large dealership world where there are organizations or departments that have significant budgets and they recognize the value in spending money in the in an information area or in a process tool or software in general. I always say the analogy is like if I can talk to a small dealer owner and I tell them that you know your machine needs a$50,000 engine and transmission and it's like okay go ahead and do it. If I tell them I need$5,000 for software that everyone will get used and make benefit from, they don't understand it. That's a lot of money. Like it's not about a lot of money. Look at look at the sales side look at how much money our dealerships spend on advertising and sales tools they'll they'll pay organizations like$100,000 a year to advertise their equipment but to put a tool in place to make sure that uh you know invoices go out on time or that customers are quoted easily$100,000 for a quoting system to make sure that all of our deal our service departments quote right away and that we're way more likely to get paid that's a lot of money. But I'll spend it on an advertising website who says they're gonna get me higher sales. So it's it's about understanding value, right? Understanding what you're buying.
SPEAKER_01:I'm I'm gonna make it even more critical I like it. I don't think that the people that are running the dealerships know what they're doing. Number one number two they make so much money they don't need to be good.
SPEAKER_03:And number three if they're scared to death to change something because it'll screw it up yeah well guess what the history of every company and every industry is it isn't about those who played it safe it's about the people who come in and they're like you know what we we just did a a project with a small dealer out in California and like you can now go online on their website buy a hundred thousand dollar truck or piece of equipment um it'll generate all the documents send them to you send you the banking information put it into an escrow account and they'll send you the machine they'll drop it off you have an hour or two to look at it and make sure it's all the way you like and if you don't you put it back on the float and send it back and the money comes back out of your escrow. It's like it's a completely different model.
SPEAKER_01:Yeah but why don't why doesn't every single damn dealer do it that way because I think that donuts sell machines true car is ClarMax those people they've been doing that for 10 years.
SPEAKER_03:Yeah they have and and there are people coming into our industry who are starting to do it. We're lucky enough to work with some of them to enable it um but there are people who will figure it out and the buyer remember this is our conversation from many times the buyer is changing. The buyer at Kiwit is a you know 35 year old Gen Z that hates the phone and if he can go and click on something and it shows up and they check it out and then they accept it or send it back they're gonna choose that option. They're just looking for who who has the stuff that they need and enables the way they want to buy.
SPEAKER_01:So Nick go exclusively to artificial intelligence and I'm gonna I'm gonna put two hooks on it I'm gonna say every piece of equipment in every market in the world has global positioning tools on it and is tracked by the minute number one number two I'm gonna say every brand of equipment and every model within every brand has lifecycle management statistics when am I going to start running my business that way I got Nick has to answer this one.
SPEAKER_00:See I I I know exactly what the machine needs I know exactly where the machine is I know exactly how many hours why don't we do that I think it's it's changing I mean the industry is a little slow as compared to the other but it's changing for sure it's just need um it's just need like uh the more companies to build a software or to come as a technology ving in this industry right if you don't have those providers if you don't educate the dealership about that okay we can do this or we have this technology then how would they know about it you know like I could have a car uh just my my car could run like my car car could drive without a battery for 600 kilometers but if no one tells me that or no one's telling me that there is this is the car exists that can you never have to refill or you never have to do the recharge like for 600 kilometers how would I know right so why doesn't need both side of it why doesn't the machine tell you machine doesn't like the manufacture to build the machine they need to partner with the companies who put the sensor in now now that relationship is growing I can see that it's happening but it's just the changes just started so once you're gonna see all the manufacturers going to adopt to this so so they start with you having to have a good enough like a software provider in this industry. Once you have it that create a healthy competition and not only the healthy competition but that just gonna that's gonna educate the entire industry as well. Now there are only I have seen in this industry there are two and three dominant market providers. Now they know that they are only two and three software providers they don't feel an urge of evolve they don't feel the urge of like okay let's do something new you know they are like oh my software is working no one's gonna come up and take our market share so they don't feel the pressure they don't feel the motivation to do anything and that's where I think it got stuck for a lot of 50 years.
SPEAKER_01:Okay so use use software as an example and use systems as an example there used to be 10 caterpillar dealers in Canada today there's two. So people subwriting software they used to provide 10 software systems now they're providing two software systems. John Deere has one dealer Volvo has one dealer Komatsu has one dealer. Even less incentive exactly and and you know I'm I'm I'm the the only thing I'm I'm relating back to is why did the the 10 caterpillar dealers that used to be there. When I started in 69, there were 10 dealers, and every damn one of them was good at what they did. You can't be a caterpillar dealer and not be good without caterpillar telling you, see the there's the road, see it, hit it. They were all good at what they did, yet they're all gone.
SPEAKER_00:Yeah, you you have to invest in the future. You know, there is no simple answer, but you have to see the future, you have to invest in the future, future. Otherwise, if you do what you keep doing now, I think the one have seen the future.
SPEAKER_01:I'm with you, I'm with you 100%. But let's look at the large construction equipment. And Metz is right. There's three or four different layers of business here. Let's in mining, for instance, there's three manufacturers, Itachi, komatsu, and caterpillar, period. End of story, nobody else. When we come to the mid-size, what's going on? How do we how do we deal with this? I I've I've got all the statistics, I've got all the data analytics, I can tell every salesperson for their customers who they should see next week and what they should talk about. But nobody does that.
SPEAKER_02:Maybe it's to no one's benefit.
SPEAKER_01:That's that's a good point. So I pay the salesman only on commission then. Only on commission, or no, let me change that. I'm gonna pay them only on market share.
SPEAKER_03:I'll I'll I'll I'll segue this for a second. We we have um Nick has been working on like what it means to enable a platformed technology with a a true AI or machine learned interface. And it's not so much machine learned because it it is reading what we do. One of the interesting things that happen is as we're like testing this and and trying it out, I find myself very limited by the way I see um the system and what we do. And as Nick is working on it, his wife comes in one night and and he says, Well, try it. And she starts asking completely different kinds of questions of the AI. Um like we have a chat bot that's engaging with the database and the API. And so she starts asking very different questions and also a much more natural way, and it actually starts understanding how to engage with our system in a different way than I. I say stupid things like how many leads did Joe pull up this week, you know, and how many opportunities did he create? So it's a really linear stuff that there's probably a report for, whereas she looks at it and be like, um, what are people buying? And if the AI goes, wait, if I want to know what people are buying, I have to look at like these 12 different endpoints and databases and look at all the data, and then I have to build, you know, a piece of software myself for a moment uh that will analyze that and do a bunch of transactions, and then I can give her the answer. You know, and so part of it is like if we always see our dealership business in the traditional way, we only ask questions the way we've grown up to ask questions or look at it and engage in the way we have, we we don't bring anything new out. And I think the this sort of AI enablement and a way of engaging with information also somewhat requires people to accept that they have to think differently. Right? Like you bring up sensors on machines and what people are doing and what parts in. If you had a true AI questioning or a way to engage with your platform, you would ask a question that you didn't know your system couldn't answer, and then uh trust it to go figure out the information to give you that answer. Like, how do I get all of my sales reps to go and talk to people who are valuable and at the right time? And it will look at things that you didn't think about.
SPEAKER_01:I have a hundred machines, Nick, of the same brand, the same size, doing the same job. I have a hundred operators.
SPEAKER_04:How do I know who's the best operator? You're muted. You're muted.
SPEAKER_00:In the world of AI, like you um if they can know that the AI will know your past history, like the data, collect the data, and what the what the history looks like, what the analytics say, and based on that it will predict you the possible outcomes, and that will help. Like in a if you go to the older way, then you look at you do the same thing, but for you to do the same thing, you have to scrap through or you have to analyze so many details. And we, as I mentioned earlier, we as a human tend to lose focus when we're given too much stuff at once, right? So it's it's first it is boring, and second, there's so much stuff, and we have a finite amount of time, and we have a thousand other things to do. So we try to lose focus while AI can analyze your data faster, we'll help you faster, give you the accurate answer. So so that's where I guess AI can can help you as well, understanding your your past history and the past data.
SPEAKER_01:And then to next question, what motivates anybody to do that?
SPEAKER_00:I mean, it's AI will not yeah, AI will not like shut down, like AI will change this landscape completely. Like right now, the person's job is to analyze the data. Either that person needs to evolve, or like because this job is changing itself, right? You know, so you might ask that, oh, what's this guy gonna do who used to look at who is the best operator, right? Now, his job how to evolve. His job is gonna evolve of how I gonna feed AI this data, how I gonna, how AI gonna AI gonna give me this 10 recommendations, doesn't mean that the first recommendation is always the best. How I can understand uh the answer that's coming back from the AI, how I gonna, how I gonna feed more information? And so so the job is changing, you know, like everything is changing now.
SPEAKER_01:I I agree with you 100%. And and the only thing I'd like to do, because we're just about out of time, is I don't want anybody doing that. I want the machine doing it to itself. It can do that.
SPEAKER_00:I mean, it can be. Of course it can. Time will come. Time will come like within like it's near, it's sooner than we all we all think, where um every machine will able to analyze and think about themselves. Like you do, you like it will know that okay, now my world changed due, or now my this service is due, and we'll let you know before then even you understand that it's due.
SPEAKER_01:I I agree with what Metz was saying when your wife looked at it, she asked completely different questions. A good friend of mine has Tesla cars for his company, and he brags about the S model because he doesn't have to drive, he just sits there. And he goes two, three, four hours at a time from home to office to airport to whatever. He never drives the car, just gets in, tells it where he wants to go, and the car goes. So I'm an operator of a piece of equipment. Now the manager's job, the leader's job, is to be able to understand what that data that they're looking at means. For instance, out of those hundred guys that are operating machines, 95 of them have more than 20 minutes idle time. The machine is just idling, the engine's just idling. So all of a sudden, I'm gonna have the ability to determine who's a good operator by different metrics, like your wife looking at the questions, because she's looking with fresh eyes. We're all we're all colorblind, or whatever the heck you want to call us. And I think that's I think that's what's confusing a lot of people. A lot of people, I don't understand what is AI? What's it do for me? And I think it's confusing a lot of people.
SPEAKER_03:You have to spend some time to understand it. I think like you asked the question who is my best operator. And again, that's one of those places where it'll be your interpretation in a traditional way to determine what best means. One of the interesting things about an large language model and with all of its knowledge that it has in it, is what does best mean? It'll it'll re-evaluate what best means. Exactly. And and find maybe a different definition of what best of an operator could mean, and therefore start looking at very different metrics or evaluate them differently.
SPEAKER_01:And wouldn't it be nice, Mets, that all of a sudden you and I can be considered the best at something? I mean, I've waited a long time for that, man. It hasn't happened yet.
SPEAKER_03:One day, maybe someone will say it and I'll be happy.
SPEAKER_01:Yeah, that's right. I'll go I'll go for a walk in the woods. Nick, it's a real pleasure. Thank you for your time. And Mets, the same thing. I don't want to go much more than an hour, and we've been already going for an hour, but I hope everybody who's listened to this is thinking a little bit because that's what we try and do, provoke provoke thinking. Nick brings an awful lot of interesting perspectives from a technical perspective uh position. Mets brings different perspectives from a business perspective, starting at a dealership, now running a software company. Um, I won't go into my convoluted background, but uh we've we've got to listen to every voice in the choir in order to make good music. Nick, do you want to want to close that up with anything from your point of view?
SPEAKER_00:I think I'll say don't be afraid of the AI. AI is not here to steal anyone's job, it's gonna axel your job. If you were able to do something in a in a n number of times, now you're able to do it in much lesser time and very very productive and powerful way. So I think we don't have to be afraid, just like you know, we have to be grateful that it's technology is coming and we are in a front face of it.
SPEAKER_01:Yeah, well said, well said, Mets.
SPEAKER_03:You know, I go back to this idea that every once in a while we have to rethink our business. And if we got together on a Saturday and got a bunch of pizzas and sat around and restarted our business, we would say, like, what worked, what part of the business are we good at? And how would we build the exact same business if we weren't tied down with what we currently have in place? And I think uh what we're looking at is like imagine you took uh you know, like an AI system and said, I want to start an equipment dealership. I sell equipment, it has add-ons, it has attachments, I need to I want to sell them digitally because most buyers like that. I need to be able to supply parts and stuff like that. You know, build me a platform that does that. And the AI goes, oh that's you know, that's pretty straightforward building a platform. I'll let me write a bunch of code, but it'll do it in the way that is it's been educated to do, which is you know, 10, like Nick said, 10, 20 years ahead of where we find most of our dealership friends. And I do mean friends. Um and so I think it will either be people who have the advantage already having like great brands, great capital in order to implement it, or it will be, you know, Carvana, who Carvana wasn't an existing, you know, dealership that decided to change his model. It's a company that came in and changed the model of the industry. And and there are people now hunting around our industry doing the same thing. The the probably the best advantage that the incumbents have is that you know, uh an OEM relationship to the product line that customers really want is the one thing blocking someone who's better at running the business from taking on. If you know, if Cat sells a secondary digital dealership into your territory, would you be scared?
SPEAKER_01:Good question, isn't it? Thank you, thank you, Nick. Thank you, Mitch. Thank you, everybody, for listening. I look forward to seeing you at the next candid conversation. Mahalo.
