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Podcast

The Difference Between Preventative and Predictive Maintenance with Intangles

Predictive Maintenance Solutions Help You to Avoid Downtime

Episode 323:  In this episode we discuss the need to change with the times in order to avoid being left behind. Things are certainly changing fast with technology in the trucking and parts industry and there are certain things that just don’t work anymore. There are also ways of doing things that are better than before and that can save time and money.

For example, with new and exciting AI solutions, fleets are now able to shift from being reactive about their maintenance, to being very proactive. Our guest this week is Alan McMillan, President of Intangles. Intangles uses physics-based AI to create a virtual twin of your commercial vehicle. This allows them to predict when each specific truck will break down so that it can proactively be repaired and avoid down time.

Predictive Maintenance Solutions that Help You to Avoid DownTime

Links

Sponsors of this Episode

Heavy Duty Consulting Corporation: Find out how many “fault codes” your heavy-duty parts business has. Meet with us today. Visit HeavyDutyConsulting.com

Hengst Filtration: There’s a new premium filter option for fleets. If you’re responsible for a fleet, you won’t believe how much using Hengst filters will save you. But you’ve got to go to HeavyDutyPartsReport.com/Hengst to find out how much.

Diesel Laptops: Diesel Laptops is so much more than just a provider of diagnostic tools. They’re your shop efficiency solution company. Learn more about everything Diesel Laptops can do for you today by visiting DieselLaptops.com today.

HDA Truck Pride: They’re the heart of the independent parts and service channel. They have 750 parts stores and 450 service centers conveniently located across the US and Canada. Visit HeavyDutyPartsReport.com/HDATruckPride today to find a location near you.

Disclaimer: This content and description may contain affiliate links, which means that if you click on one of the product links, The Heavy Duty Parts Report may receive a commission. 

Transcript of Episode

Jamie Irvine:

You are listening to The Heavy Duty Parts Report. I’m your host, Jamie Irvine, and this is the place where we have conversations that empower heavy-duty people.

Alan McMillan:

With today’s technology, there’s no reason to be broken down on the side of a road because of an engine problem.

Jamie Irvine:

That’s a bold statement at the top of the show from our featured guest. In this episode, we are going to talk about predictive maintenance for heavy duty parts businesses.

We’re going to talk about the difference between predictive and preventative maintenance inside of a fleet on commercial equipment, and we are going to talk about why the statement, this is how we have always done things is such a dangerous mindset in heavy-duty parts and service. Let’s get started.

When you are repairing commercial equipment, every truck, every trailer, is unique because once it goes into service, it encounters specific unique environments and conditions and driving habits that then start to change the way that the truck operates.

And over time, things start to wear at different rates. And so really when you think about it, each truck and trailer in heavy-duty is a unique piece of equipment.

It’s very much the same way with heavy-duty parts businesses. The business itself, although it might be a parts business or a parts and service business, and it may share many common characteristics with all the other parts and service businesses in the industry. Each business is unique because it has a different owner, it has different people working for it, and there are unique things about that business.

That being said, there are some things that you can do as a business owner to actively do preventative maintenance on your heavy-duty parts and service business because statistically speaking, if you do or don’t do certain things, you are going to get a specific result and it may not be the result you’re looking for.

But that doesn’t mean that you can just have a blanket one size fits all solution for your heavy-duty parts business any more than you can apply a one size fit all solution to every problem on a commercial vehicle.

It’s just not realistic because of the uniqueness of each business, it is important that you approach each problem in your business in a specific way, and we have found at the Heavy Duty Consulting Corporation that if you apply a disciplined, methodical way of going about looking for root causes of problems in your business, you can then develop a strategy that has all the best practices inside of it, but also allows for the uniqueness of each business.

And that’s something I think at my company, at the Heavy Duty Consulting Corporation we’ve actually gotten really good at.

We have been treating heavy-duty parts and service businesses the same way that you treat a commercial vehicle. We do a pre-scan to identify fault codes or problems in the business just like a diagnostic technician does with a commercial truck or trailer.

Once we’ve figured out what those fault codes are, we have to do that root cause analysis to help the business owner figure out if there’s upstream or downstream issues that are contributing to this symptom that we’ve identified.

Once you’ve done that and you’ve taken that disciplined approach, then you can look at the unique situation, what makes the company unique, what makes this problem or this situation unique just like you would with a commercial vehicle. Maybe this vehicle is used in a very specific vocation with an environment that is unique and so you have to adjust for that.

Well, when you’re working on a heavy-duty parts and service business, you have to take that same approach. What uniqueness about the business owner or the employees or the market that they serve or the economic conditions in the region that they’re operating in? And you have to factor for those things.

When you do this, what you end up with is you end up with a customized strategy that has all the best practices built into it that is statistically going to solve the problem, but has allowed for the uniqueness of the situation.

And it’s not just about identifying the problems and then fixing them. It’s also about getting the business into a position where if these things are done on a regular basis, if there’s preventative things done on a regular basis, you can avoid a major breakdown, if you will of the business.

And this is very similar in the way that you think about fixing a commercial truck. You can apply that same thought process to how you work with heavy duty businesses. And again, I think at our consulting company, the Heavy Duty Consulting Corporation, we’ve gotten really good at doing this.

So if you operate a heavy-duty parts and service business and if you’re encountering problems or if you would like to have that pre-scan done to try to get ahead of some of these problems and put some preventative maintenance in place to make sure that you don’t have a catastrophic failure, then by all means please reach out to us.

Head over to heavydutypartsreport.com. There’s a new Consulting tab in the top menu and just click that. It’ll take you right through to our consulting website where then you can book a meeting with us. We look forward to talking to you.

I thought that this was such a good way to start our conversation today because our featured guest is going to go deep on the difference between predictive and preventative maintenance when you are a fleet and you are responsible for repairing commercial vehicles. So we’re going to take a quick break.

When we get back from our break, I’m going to introduce you to our featured guest and we’re going to talk about that.

Are you deferring maintenance because of filter cost or availability or worse yet, are you trading down to no name filters to try to save a few bucks? Either way, you are rolling the dice.

The good news, there’s a new premium filter option for fleets Hengst Filtration. If you’re responsible for a fleet, you won’t believe how much using Hengst Filters will save you, but you’ve got to go to heavydutypartsreport.com/hengst to find out more. That’s heavydutypartsreport.com/hengst. Head there now.

At Diesel Laptops, they go way beyond diagnostic tools. They are your complete shop efficiency partner from diesel technician training to complete repair information, parts lookup tools and robust technical support. They are there to support you every step of the way. Learn more and download your free starter pack today by visiting diesellaptops.com. That’s diesellaptops.com.

We’re back from our break. Before I introduce my featured guests, I just wanted to remind you that we are looking for parts distributors that would like to join a special beta program exclusively for the listeners of The Heavy Duty Parts Report through partners of ours.

We are developing parts visibility solutions for distributors that really are going to empower them to make the parts that they sell visible to the customers that are buying them throughout the entire supply chain at all times.

And in addition to that, we’re going to provide them with some additional resources that are going to lower the number of phone calls the parts counter has to take each and every day. If you’re interested in this, head over to heavydutypartsreport.com/jamie and book a meeting with me to discuss the details.

We would love to have you join the program. In this episode’s featured guest interview, we are going to talk to a company that is pioneering the next evolution of predictive maintenance using something called physics-based AI.

This is a fascinating conversation that really is going to highlight where this next generation of AI is going to take us and he does a really good job of explaining the difference between predictive and preventative maintenance and how this technology is empowering predictive maintenance at a new level.

I hope you enjoy the conversation. My guest today is Alan McMillan, president at Intangles Americas. Alan McMillan is a technology executive with over 25 years of industry experience.

He knows the transportation industry. He studied automotive power technology at St. Clair College in Windsor, Canada and recently served as the CEO of Auto Serve One, a digital inspection platform for the automotive aftermarket. Alan, welcome to The Heavy Duty Parts Report. So glad to have you here.

Alan McMillan:

Thank you for having me. Appreciate it. Nice to meet you and your audience.

Jamie Irvine:

Yeah, Alan, it was great to talk to you when you were doing a press release at one of the conferences we were at, and I got to learn a little bit about all the things that you’re doing. So today we’re going to talk about predictive maintenance. And before we really get into that, why do you think the trucking industry is important to everyday people?

Alan McMillan:

I think during Covid it really showed how much we rely on it. I don’t think people appreciated the implications the trucking industry had until they started seeing supply chains being affected. Everybody appreciated, of course, became a critical industry and designated as such, rightfully so. I work from my home.

I mean, I get the truck, Amazon or whoever’s pulling up every day, I get my groceries delivered. It’s not just long hauls. That’s important. Now the last mile’s becoming much more important in the last couple years is more and more people are working from home. I think it’s indisputable how important the trucking industry is to us.

Jamie Irvine:

I agree with you completely. And I live in oil country and we’re surrounded by mines and oil fields and logging and all of this vocational applications of this heavy equipment. And you just think for a moment, right, how important it is for things like energy and heat and cooling in the summertime and all of the things we rely on.

Okay, so you understand the importance of our industry now predictive maintenance has been something that is really needed in the trucking industry. Back in the old mechanical days, it was very difficult to predict anything and you basically were always reactive. So tell me a little bit more about why the predictive part of maintaining commercial equipment is actually so important for us to move forward.

Alan McMillan:

Well, you can imagine nobody likes to be broken down by the side of the road, and given that the industry is becoming much, much more sophisticated from a data point of view, why not use newer technologies like AI in order to predict if an engine’s having an issue? Of course, it has all sorts of locations from a better uptime lowering your cost of operating.

Really it’s the change in the data that’s being generated from the engines that we can access. It’s the enhanced technologies that we have like AI and also the right to repair act, which meant we are able to access that data that in the past only OEMs could access.

Jamie Irvine:

And when I think about the older days of mechanical, as I just mentioned, you had to be so reactive, getting in front of these issues to prevent roadside breakdown events and things of that nature.

It can go a long way to really lowering the total cost of operation, which as a fleet is something that you’re very concerned with. So talk to me a little bit about the economic impact of being able to get out in front of some of these issues in a predictive maintenance kind of perspective.

Alan McMillan:

Sure. Well, let’s first define, there’s preventative maintenance which people sometimes conflate with predictive maintenance and preventative maintenance is something that the OEM tells you every 10,000 miles do this or every 50,000 miles do that.

With predictive maintenance, we’re trying to predict and optimize when you should do A, B, C before, of course a catastrophic failure happens or before it’s really needed, but also while you are trying to optimize your vehicle from a fuel point of view, you want to be able to change, for instance, your oil or your filter when it starts costing you money.

When that vehicle’s running down the highway and it’s not optimized, wouldn’t it be great to be able to predict, hey, you should change this or do this and therefore I’m going to get much better fuel mileage. By having that predictions of what is needed, it’s not just preventative prediction to allow you to optimize the states of when you should change or change your configurations within your engine.

Jamie Irvine:

Well, and I really appreciate you making that distinction between preventative and predictive because I agree with you. I think one of the problems with the preventative approach is you might be changing things too quickly. You might be changing them too late, too late is obvious, it really hurts. But too early is also a problem because you’re artificially increasing the cost before it needs to be.

Alan McMillan:

That’s right. I mean it filling up for landfill with things that don’t need to be filled up. It has a cost to it, it’s downtime. Your turnaround time. A lot of fleets keep a certain percentage, 10-20% of their fleet is kept in reserve because they have to bring it in for maintenance, for scheduled maintenance, for an unscheduled maintenance downtime.

So that has a huge cost operationally. But if you can optimize when you bring your vehicle down, your actual assets are more on the road, you have a more efficient running fleet.

Jamie Irvine:

Right and utilization is not just important with the actual vehicles. It’s also important in the shop because you have limited resources when it comes to diagnostic technicians, repair technicians, parts people, and that problem is only getting more complicated as the years go on as people with 30, 40 and 50 years experience leave and there’s a lot less people with that kind of up and coming experience to replace them. So that becomes an issue as well.

So let me talk to you a little bit about the limitations that have existed because you talk about a lot of data and I’ve almost seen a curve where all of a sudden we had all this data available, which was never available before, but then it got to a point where consuming that data in some sort of meaningful way became a problem. So tell me more about that.

Alan McMillan:

So there’s a concept called big data, which is measured by volume of velocity and variety. A truck going down the highway is that is big data encapsulated. So a typical truck can generate gigabytes of data, very high velocity and a lot of variety. What do you do with that data? That’s where AI comes in.

AI can actually provide insights into that data. In other words, we can look at what is going on with that vehicle and we can do predictions upon those insights. But now we’re also doing actions on those insights.

For instance, we just launched a new app where it’s called In Route Connect. We can connect that vehicle to a relevant service center that can take care of that vehicle on the road. So we give you an insight to say, hey, your turbocharger has a boost pressure issue. Maybe you should get it looked at.

You’re planning to spend the night at this center here a few hundred miles away. Why don’t you, while you’re sleeping at it overnight, you can get your vehicle looked at. So that kind of actions on those insights from that data is what’s relevant because of course nobody wants to be able to run with all that data.

Jamie Irvine:

And from a parts perspective, even being able to have that upfront warning and say, hey, I know later tonight I’m going to be pulling into this location, we’re going to get it worked on. You can get ahead of it and say, okay, well it’s a turbo issue, make sure I have the parts available. Confirm that before the truck arrives.

All of those things come together to make the repair event a much shorter time period, which then drops cost, keeps that utilization number high.

Alan McMillan:

That’s right, the turnaround time. The TAT is what a lot of people measure and exactly is that prediction of what is wrong with the vehicle or needs to be tuned that we are sending on ahead to a service center and then they can get ready with the right technicians, the right parts, and that vehicle can get back on the road where it should be.

Jamie Irvine:

So you’re not just on the show because you’re a fellow Canadian. I have had a few people on the show over the last few years talk about their predictive maintenance solutions, but when I heard about the way that you are building yours and the way that you’re deploying it, it really got my attention. It did stand out as different. So could you walk our audience through the way that your system actually works?

Alan McMillan:

The difference is the following. AI has been a, let’s say a catchall term. Most people are doing any type of AI is doing machine learning. In other words, they look at a pattern and they predict from it. It’s similar to if you have a dead body and you ask a coroner to look at that dead body, they can predict what somebody died from. But do you want to ask that coroner to actually tell you how you should have lived a healthy life?

I don’t think anybody’s asking a corner to do that. So in the past, people were using data based upon what something broke from, the trouble codes. They would look at the trouble codes and they would try to predict that vehicle having that same trouble code. That is not the way we do it at all.

Jamie Irvine:

When they were doing that, were they just using a statistical prediction of like, look, we’ve had fault code 1, 2, 3, 4, 5. We know how many times that’s occurred and when these have occurred in the past 86% of the time it was this problem. And so it was really just like an algorithm that was predicting it based off of statistics. And yours is different.

Alan McMillan:

That’s right. The difference is we use physics-based AI. So how an engine operates from a physics point of view is the same. It doesn’t matter if that engine has 10,000 miles or a hundred thousand miles. It doesn’t matter if it’s going up a hill or down a hill. What matters is how much fuel goes in, what the exhaust looks like coming out and what kind of horsepower you getting out of that engine.

That’s the physics that does not change because we understand that we are taking the relevant data from the ECU and we compare that physics that we’re finding in real time. We create a twin model in the cloud. We use a physics-based AI against that twin, the virtual twin of your truck. So every truck has a unique twin. You can have a hundred different Kenworths.

They all have their specific twin in the cloud that we are then looking at it from a physics point of view and we can then suggest you to 95 to 99% accuracy what we think is the issue with the vehicle, or possibly you’re going to have an issue a day or two later, later from an alternator point of view, from a turbo charger, from an overheating, from a DPF issue.

We can do the predictions of that because we understand the physics of the engine. We’re comparing against it very unique and nobody else is doing it.

Jamie Irvine:

Right. So the laws of physics stay constant, but the reality is if you had those a hundred Kenworths, they’re all being driven by different people on different roots, experiencing different things.

They’ve had different unique things happen to them through the course of their operation in their life. And so by creating this individual twin for each unit, it allows you to, if I get this right, apply the laws of physics, which don’t deviate, but apply it in a very specific way to that specific unit based on its history. Do I have that right?

Alan McMillan:

A hundred percent. You have it right and in real time. So every hour it’s running algorithms on that vehicle. So as that vehicle goes from 50,000 miles to 51,000 miles to 52,000 miles, it’s continually running those algorithms. See how it’s predicting. So now you go back to the OEM who has their specs that are every 50,000 miles do that.

That’s based upon when the engine was new. They’re trying to estimate in their history what it would look like. But you know what, if you’re driving a truck in a dusty environment or you’re driving it up in a humid environment, et cetera, you’re going to have all different specs of when you should be doing something.

It’s a gross analysis to take a preventative maintenance schedule and try to apply to a vehicle today when you have technologies like physics-based AI to tell you when you should be doing something.

Jamie Irvine:

So when a company deploys this solution into their fleet, how long before the models are created and the data would be usable?

Alan McMillan:

If we have never seen a make and model before, it takes us around 500 miles to start doing predictions. So today we have over 2000 makes and models that we have knowledge on, but past that we also translate all the trouble codes. So an engine’s still going to be putting out trouble codes.

We have put all those into critical, major, minor alerts so that a fleet can look at the comprehensive analysis of what’s going on with their fleet. They can very easily ascertain which one they should work with. From a triage point of view, I should work with this truck, this truck, this truck and this order. So if we’ve never seen that make and model before, three days we’re able to start doing predictions on it.

Jamie Irvine:

So does your solution integrate with existing fleet management systems or are you actually bringing a new fleet management system to the market?

Alan McMillan:

No, we integrate with if somebody’s already running a fleet maintenance software in their shop, they’re running their shop. That’s not our business. We would integrate with the different providers like Asset Works and companies like that. So not a problem to integrate with them.

Where we are living is typically is in the cab of the vehicle. We plug into the CAN bus. We have our own R Flow AI edge device that is operating there. We have our own cell connection back to the cloud, and then the fleet is able to look at their vehicles through the cloud access.

Jamie Irvine:

And does this only deliver the information to the maintenance department or does it also communicate and provide information to the driver so that they can make decisions? How does that integrate?

Alan McMillan:

So more than likely, the fleet doesn’t want the driver to be bothered with this. We’re working with fleets that typically have a command center. So if you think of most fleets of any size, they have operations, they have maintenance, they have safety. Our technology is helping the say stress between operations and maintenance. Maintenance says, hey, it needs maintenance, operations say no, the truck needs to deliver the load.

And then there’s a question around, okay, is that going to break down or what’s it cost me? I’m running inefficiently, is it going to cost me? How much is it going to cost me? So that’s where our insights are helping those two groups out. And we’re about to launch safety related products like camera and ELD shortly.

So all three of those groups within a fleet will have a single screen where they can manage the applications as you’d expect. But also any brand, any OEM, whether it’s Peterbilt, Freightliner, you mentioned Kenworth already, and I’m sure I’m forgetting some other brands, but all the brands in a typical fleet will be in a single screen where they can then manage their maintenance and operations.

Jamie Irvine:

How does it get the data to where it needs to go? Is it connected through a cloud-based? Does it need an internet connection? What happens if they’re in a, let’s say they’re traveling through the Rocky Mountains and they’re out of an internet cell area. How does that all work?

Alan McMillan:

Okay, so when it’s in cell network, our device is capturing the data 10 times a second. It’s listening to the CAN bus for some different data, far more than other telematics type of devices. We’re then sending that back to cloud, a couple hundred megabytes a month, not a problem.

But if it does go out of cell network, we have what we call store and forward. So all of that data, the GPS location, all the engine data is still kept on our device. It could be a few days worth of information. When it comes back into cell connection, it’ll rebuild up all that information and then they’re good to go again. Now you asked about the driver. Does the driver have access to this information?

We put the notifications how they want to be notified. So maybe the fleet manager wants to see it, maybe the person running in hub wants to see it. If they want the driver to be notified for some type of major alert, for instance, we can do that. But they said more than likely they’re back in a central location and then they call the driver and say, hey, why don’t you get this done tonight?

Jamie Irvine:

Fantastic. So whenever I’m presenting something to a client or I’m working with one of my clients to sell something, I always encourage people to talk about the problem, talk about the economic impact, and then how that solution solves that. And then that creates a story of the experience that customers who are ideal for this solution, what they get to experience.

I love being able to recount those stories. So can you tell me a story of one of your ideal customers who started to use your solution? What was their situation? How did it change their operation? What was the economic impact? Just tell us that story.

Alan McMillan:

Sure. So one fleet of garbage trucks, 50 garbage trucks. They used to keep 10 in reserve because obviously a garbage truck breaks down, nobody’s happy, right? It’s on a city street, you can’t even get by the garbage truck. If they had to tow it in, it was about $400 to $500 to tow it and to get it fixed. So that has a cost.

When we actually installed, they figured in the first few months of working, we saved them three blown engines by predictions on the heating that they didn’t have before. And this fleet was CNG. Also, we have a lot of knowledge around CNG.

They estimated from an ROI point of view, we’re saving ’em $500 a month across their fleet from a maintenance point of view, a lack of towing and things like that. But also because we’re helping them run their fleet more optimized. Like we have idling reports. We know when they’re excess of idling and things. So $500 a truck, times of 50 trucks.

But also they felt they could sell off three of their five trucks, which garbage trucks are expensive. That’s like a million dollars because they only needed to keep two in reserve because of their confidence of their uptime of their vehicles now previously.

Jamie Irvine:

Right and from a business management perspective, asset allocation and the capital that is needed to maintain those assets, that’s all a factor in the overall performance of the company financially. So a big impact at every level of the business. That’s fantastic. So let me ask you something. We’ve talked a lot about this.

We’ve talked about the difference between preventative and predictive maintenance. We’ve talked about physics and AI. We’ve covered a lot of subjects. Give us one thing we need to know that you want people who are listening today to absolutely remember from today’s conversation.

Alan McMillan:

With today’s technology, there’s no reason to be broken down on side of road because of an engine problem. If you are fire your maintenance head, there’s no reason to have a broken, I can’t fix broken tires or car accidents, but there’s no reason to have a truck break down mechanically anymore.

Jamie Irvine:

It is a different world that we live in. You’ve been listening to The Heavy Duty Parts Report. I’m your host, Jamie Irvine, and we’ve been speaking with Alan McMillan, President at Intangles to learn more about Intangles visit intangles.ai links are in the show notes. Alan, thank you so much for being on The Heavy Duty Parts Report. I really appreciate it.

Alan McMillan:

Thank you, Jamie. Love your show. Keep it up. Thank you.

Jamie Irvine:

I hope you enjoyed this episode’s featured guest interview. I don’t know about you, but I am really, really excited to see where the upper limits are of the application of AI technology inside the trucking industry. Physics-based AI.

Not something that was on my radar a couple years ago, but it was really good to learn a little bit more about what is coming, how it is going to impact our ability to get ahead of problems with commercial equipment. Fascinating stuff. So stay tuned for more updates on that as we get them.

It’s now time for our concluding segment That’s Not Heavy Duty in this week’s edition of That’s Not Heavy Duty, I want to talk about why people who have the attitude, who basically say, Hey, this is how we always have done it, is such a dangerous attitude and way of thinking. Now I want to tell you a story from 2009.

I had just left the trucking industry. If you remember back then, 2008, 2009, the housing crisis had occurred. I had been working for Traction. They were closing all of their corporate stores in British Columbia, including the store that I worked at.

I had given my resignation a few months before I kind of saw the writing on the wall and I had left. In the interim, I started a company that did commercial building maintenance, and it was very similar in the business model to a mobile repair company.

We had trucks with equipment and technicians, and we sent them out to do the work, but instead of working on commercial equipment like trucks and trailers, we were working on commercial buildings. So you get the idea of the type of business that it was. Now here’s the thing. We had encountered a general manager who was very motivated to help us get our business set up.

We were subcontracting off of him and we were helping him out, and he was trying to help guide us in how we might think about marketing our business. When he started his business back in the early nineties, he used newspaper advertisements to get the word out about his services.

He had been very successful in the nineties doing that in both residential and eventually also on the commercial side of the industry. But this was 2009. Things had really changed. And so when I asked him why he suggested that, he says, well, that’s what we’ve always done, and that’s what worked. And I actually decided to take another direction.

So at that time, Google AdWords Express was a service offered by Google. It was a simplified ad product that businesses like mine could use to regionally get your message out there, get your website found by people who were searching for the services that you offered.

We did very well with Google AdWords Express. We were one of the first companies in our region to use it. When that package got eliminated by Google, we switched to their full AdWords package and we really became students of how to use Google AdWords. And we rapidly scaled our company.

And interestingly enough, the original person who got us into the business ended up buying our business six years later because he couldn’t believe how much we had scaled and grown. We were the third largest in our region. And he realized that we had pioneered a new way to do this and that he was not going to be able to learn it.

So it was easier for him to just buy us and for us to teach him the systems and the things that we had learned. So while it is important to stick to fundamentals and principles in business that stand the test of time, I think it’s really important for us to always be challenging the status quo.

And if you hear somebody in your company say something along the lines of, well, that’s why we’ve always done it, that should be a red flag. That should get your attention, especially if you’re in a leadership position that should make you dig into is this still the best way of doing it? And as the featured guest in this week’s episode kind of points out, things are evolving really rapidly. Technology is changing.

There are new providers of this kind of new technology coming into the marketplace, and there are probably opportunities for your business to make improvements, to increase the amount of output that you have and to scale your results, leveraging some of this technology while hanging on to the best parts of the traditional way of doing things.

So I really think it requires a level of flexibility now that we’ve probably never needed this much flexibility, but it’s something that is a critical skill that I think leadership and management and even frontline employees need to start to develop.

So just by way of conclusion, I want to emphasize this point one more time. We need to adapt and make use of new technology or risk being left behind, and we don’t want that to happen to you. Thank you so much for listening to this week’s episode by way of some announcements. Just wanted to let you know that Google Podcast is shutting down next week.

If you are using that player for this podcast, switch over to YouTube. You have a premium edition. I think you can also access it through YouTube music, or if you’re an Android user and you just want to use a free app for listening to podcasts and you’ve been using Google Podcasts, I personally on my phone have switched to Pocket Cast, and there is a link to Pocket Cast in the show notes of this episode.

Also, if you go to heavydutypartsreport.com and click, you’ll see a banner with all of the different ways to listen to the show.

And there’s a more button, click more, and in the dropdown list, you can find a direct link to Pocket Cast. In any case, regardless of how you’re consuming the show, we appreciate your ongoing support. And if you haven’t already, go to heavy duty parts report.com and subscribe to our weekly email.

You get one email a week so you never miss out on any of our content. And we really encourage you. If you’re listening on your podcast player of choice or on the video version on YouTube, make sure you hit the subscribe button and follow the show for free. Thank you so much for your ongoing support, and as always, I want to encourage you to Be Heavy Duty.

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