September 29, 2025 • 55 mins
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.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Aloha and welcome to another candid conversation.
We're continuing our artificialintelligence discussions again
today with Troy Otware.
We did one with Troy a coupleof three weeks ago where he gave
us his background, starting asa mechanic in trucking and
moving into dealerships, etcetera now in consulting, and
(00:24):
one of the things that hepointed out when we last talked
was how he went to data beforehe went to the market, and I'd
like to use that as a startingpoint on how he operates now in
the consulting world, how hehelps people.
So with that, troy, as a prettyweak entry, but giving you all
(00:46):
kinds of landscape to play in,let's go.
Speaker 2 (00:50):
Well, ron, thanks for having me back again Always a
pleasure and, as we were sayingprior to recording the recent
podcast you've had on thevarious angles that people are
approaching from AI, I'm excitedto talk about that today and I
think for me, being aconventional dealer operations
(01:14):
guy coming out of the 90s andmanaging my way up to this point
, you know what you just said inthe opening statement was I
never did anything withoutreviewing the data and obviously
AI was not an applicable itemfor any of us in the 90s, 2000s
and so on up until recently.
(01:35):
But I'm still approaching it inthe same method.
I'm not just going straight toAI 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 myproblem.
Give me the answer, and then Irun with that answer and say,
hey, dealer, principal, here'swhat we have, let's go, here's
(01:56):
the solution to all yourproblems.
There's still a validationprocess that we must go through
and one of the common phraseswe're all using data is noisy
and I've had a number ofconversations in the last 10
business days with people fromwithin the sector.
We're talking about the dealerworld and outside, and everyone
uses data, and they use data insuch a way that they don't even
(02:19):
realize they're using data.
Every decision is database.
Now, there's a lot of emotionthat goes into decision making a
lot of times too, and you knowyou got to try to remove that.
And my approach from being aconventional dealer operations
guy to becoming a consultant ishow do I want to make a
(02:39):
difference in the world aroundme?
And, as I find myself sayingthis a lot, I want to leave my
clients better than I found themand what value do I bring to
them.
Obviously, as a consultant, youdo freak people out a little
Like oh that consultant peopleis expensive, yes, but probably
(03:04):
no in a lot of cases.
And if you can get through thatdiscovery phase, what I call it
, when I do a dealer review orI'm having a conversation about
being hired, I want tounderstand what your pain points
are.
And the first place I'm goingto go is, well, after the
conversation is let's look atyour data and if it's in one
(03:24):
department or all thedepartments, let's do that
review.
And, as you know from doingthis for a number of years,
managing data, even in the oldschool ways and even with AI is
still not an easy task, so wewant to work smarter, not harder
, and I know I probably saidthat the last couple of
podcasts- it goes almost todaywithout saying One of the
(03:50):
interesting things.
Speaker 1 (03:52):
Looking from my perspective, companies and
people that do not supplementtheir knowledge and skills with
artificial intelligence aregoing to be left behind.
Oh, absolutely yes, and sopackage that up a little bit.
Why is it that you think thatAI enhances your skills,
(04:17):
knowledge and ability in whatyou do?
Speaker 2 (04:22):
Well, it takes 40 years of tribal knowledge.
Okay, and tribal knowledge,some, you know, some people
don't like that word, but it'sperfect, it is a market word,
it's, it's right.
It's not meant any form ofdisrespect or anybody being
overly sensitive.
Think about it, though Everygroup, every business, every
(04:45):
community, there's tribalknowledge that gets accumulated,
but it doesn't always getaccess or it's not accessible,
probably is the better way tosay that.
So, for me, my why as to who Iam today and how I go to market,
is how do I take 40 years ofknowledge?
(05:05):
Gut instinct, intuition, youknow, learning before learning
without scars was a thing.
You know all those scars thatcame from learning the hard way,
the school of hard knocks.
You know the, the, the, themistakes, the failures.
All those things havequantitative value, and there's
(05:27):
that value word again that we'regoing to talk about, and for me
, it allows me to navigate thevarious different entities or
markets that I go into, whichisn't just the dealer world.
I cross over into several otherindustries just simply due to
my background, and now I'mtaking that knowledge base and
(05:51):
I'm using AI to look at theproblem, using my tribal
knowledge, and then I go in andI use agentic AI or write an
agent for me to go focus on thisparticular problem.
And had I not, if I just hadthe AI side of the conversation,
(06:13):
only that knowledge base, Iwouldn't be near as effective.
So what I'm describing, whatI'm bundling up here for you, is
Troy Otmer is now an augmentedindividual with an expanded
toolbox.
I started my career as atechnician still have a lot of
those same tools, a couple ofsame toolboxes that I'm in
(06:35):
around.
So you know, 40 years ago.
Now, fast forward to today, Istill have those toolboxes.
Don't use them like I used touse them at all.
However, my new toolboxesinclude all the data process
management that I learned alongthe way.
Now AI is taking that and I'mcoming full circle.
(06:57):
To put the cherry on the top,which is I come fully dressed,
ready to work, ready to attackany problem and look at it
objectively.
And yes, an AI again, you putdata in.
That doesn't make sense.
You're asked a silly question,you get a silly answer, but if
(07:18):
you structure your experiencesaround the task at hand, you can
generally come out with a verystrong product.
And, of course, you still proofit out, you still validate it.
You don't just roll with it.
But you know that's how I wouldbundle myself.
And, as a matter of fact, in arecent conversation yesterday,
you know, I was asked a verysimilar question.
(07:40):
Well, how do you see AI helpingthis client?
And I said I see AI as meunderstanding your business in a
very expeditious manner, veryquickly.
However, it also allows me topull in your HR data and
understand your surveys and youremployee experiences.
(08:00):
Oh, and now I can pull in yourcustomer data, your Google
reviews, and then I can compareall that and I can build a
platform, or, with partners, Ibuild a platform.
I'm not building all thesethings myself, but, in a very
basic sense, I can now give youa better idea of what a 360
(08:21):
synopsis of your dealership oryour business looks like.
So that's how I would bundlewhat 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 tounderstand.
Speaker 1 (08:40):
And that comes from the tribal knowledge, and I
don't think there's anythingwrong with that terminology,
because everything that we havedone and learned started
thousands and thousands of yearsago in tribes, correct, and we
throw out things that aren'tapplicable anymore.
And there's a lot of that.
And you know my metaphor theelectric engine replacing the
(09:02):
steam engine and how long ittakes people to adapt.
But before we can do anything,we have to understand what the
heck it is we're trying to doand what they're trying to do
and all the rest.
And I I translate that and saywe have to understand before we
can be understood, correct?
So if I'm going to communicatewith somebody, as you do, going
(09:24):
to the data and as an augmentedperson, you're filtering that
data to the point that you cancommunicate to that customer
with better knowledge and, inmany cases, more knowledge of
their business than they have.
Speaker 2 (09:38):
Yes, fair comment.
Fair comment.
Spot on yes.
Speaker 1 (09:42):
And the dilemma that we have is with using artificial
intelligence.
We need a new skill set Askingquestions.
How do I know what I need toknow?
I have to ask a question.
Now.
I can ask AI, copilot, gemini,a whole bunch of different tools
Right, and they can give meanswers.
Well, gee, that wasn't theright question, so we have two
(10:06):
paths coming down here.
Most social media deals withalgorithms.
The algorithms are made bypeople.
Some of them are biased, someof them aren't.
It's hard like hell to know thedifference, but you can't take
what you see as fact withoutverification anymore.
There's so much, like you said,noise out there.
(10:31):
So when you're looking at acompany back in 80, when I
started, I used to say to peoplewhen 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'skind of a screwed up way to it
worked at the time because itwas kind of cute.
But that doesn't work anymore.
And if you're talking to acompany and you know their
(10:51):
business better than they do,first of all, that bothers them.
It does, yes, so let me go intoa different direction.
Business systems at use in thecapital, goods industries,
dealers and others distributorsand others are used probably 40
(11:13):
percent of the capability of thesystem, and the employee is the
one that's making that decision, not the company, because they
find what they need and we'reall guilty of this what they
need to do their job and that'sas far as they go.
If I'm working the counterselling parts, I know how to
(11:36):
find the price, I know how tofind the availability.
That's about all I need to know.
The customer calls me up, I askwho they are.
Maybe I have help on the phonebecause I can see who the phone
number is, but there's privacythings to get in the way, so I
have to ask who you are.
That's a wonderful way to starta relationship with somebody
who wants to buy something fromwho the hell are you?
(11:58):
Yeah, and then the next questionis 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 for100 years.
Yes, sir, and I classify.
I call that paper to glass.
We took a manual system.
We just put it on a screen andinstead of writing it, we typed
(12:21):
it.
So now I got fat fingers andguys that we didn't have typing
on when we were in school.
And how do I break through tothe customer, the person you're
talking with, that youunderstand their business and
you looked at different aspectsthe customers, the employees,
the payables, the processes andwhat's their pain point, what
(12:48):
keeps them up at night.
And you start talking about howthat 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
(13:11):
talking to.
Speaker 2 (13:13):
Sometimes well, I think I've experienced all of
those situations and sometimesat the same time it's by the
look on their face and it goesback to part of the problem has
nothing to do with AI the waythe dealers have ran.
(13:37):
One of the problems is we'vegotten away from value-added
selling.
We've stopped teaching thefront counter people to ask
those important questions.
I walked into a dealership theother day for a meeting and
nobody knew why I was there orwho I was.
No one asked to help me.
How may I help you?
(13:57):
Who are you here to see?
You know you're here to look atsomething.
No one asked me a word.
I sent a text message.
I'm here.
Somebody came to get me and I'mlike okay, I learned a whole
lot about that business rightthere, where there's a big old
fancy service counter and a bigold fancy car counter, and I
(14:20):
could have been some bum off thestreet right and or I could
have been the most importantclient they'll have all year.
I'd like to think, if I do getto work with this particular
group, that maybe I'd help themfix that particular problem.
But that's not uncommon to allthe dealers and I've had the
good fortune in the last five to10 years to not only work for
(14:42):
dealers but also be on thecustomer side and walk into
dealers, and everything you'resaying right now is exactly the
problem.
I'd walk in and the customerexperience 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 dowe handle that.
(15:03):
So part of this problem istraining related.
It's a culture problem andwe're at definitely, dealerships
I was going to say they're atan inflection point.
No, they've been at aninflection point for a long time
for a lot of reasons.
At an inflection point for along time for a lot of reasons,
(15:24):
and AI is not their saviorsimply by saying, hey, we have
AI now.
Now you can work smarter, notharder.
There has to be some collectivetraining and processing and,
yes, it can do simplified tasks,but how do we implement that?
So when I go to talk to adealer, I'm not leading with hey
, ai is going to save you andTroy and AI plus, you know,
(15:46):
together combined, that's notthe answers.
I will use AI.
I make no secret of that.
I use it to give you answers inreal time, so I don't have to
wait until a quarterly reportcomes out, so I don't have to
wait till an orderly reportcomes out.
I can tell you at maybe sameday.
Some business systems can allowthat processing to happen, but
by the next morning I can prettymuch have you an answer of what
(16:09):
happened in the previous threeto five days and how the month
is going to look.
I know you and I talked aboutbefore 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 aworld that you can have
(16:29):
predictive analytics, even in aworld without ai and no question
, and and and.
Speaker 1 (16:35):
the problem that you're exposing, troy, I think,
relates in a different way.
Every 20 years, the number ofdealers that we're competing
with in the marketplace and Idon't care if it's equipment,
forestry, mining, marine,whatever it is is reduced by
half.
And you want to talk about afailure of leadership.
(16:59):
Hello, so you know.
Translate that and this is 2025.
In 1985, we start with 100customers.
2005, we got 50.
Now, 2025, we got 25.
And leadership looks at therevenue line.
Yeah, revenue is going up.
I'm okay.
(17:19):
Well, it better go up.
You're only dealing with aquarter of the people you're
competing with anymore.
So there's an interestingstatement, and the one that
becomes more.
I think telling your job nowinvolves a lot of learning.
(17:40):
It involves a lot of time inyour head, thinking the
operating leadership of adealership doesn't have time to
do nothing, baby.
No, they're putting out firesall day long.
The phone rings, let's get outof here.
And we've been.
That's why I think we've beenreducing the number of
(18:01):
dealerships so much.
We've been putting profitsahead of people, cutting back on
the number of people.
Everybody says customer loyaltyis gone.
Well, we haven't treatedcustomers very well to make them
be loyal, true?
So all of that combined.
And here comes ai, and and I'mgoing to use it, as I think you
do, as an excuse we could havedone all of this stuff manually,
there's no question about it.
(18:22):
We didn't know what we neededto do.
And today, I think, thebusiness of equipment dealers
whether it's on highway trucks,whether it's tractors, whether
it's lawnmowers, whether it'sair conditioners in your house,
the dealers it's now business tobusiness, it's not person to
(18:45):
person, and they haven't figuredout how to work that yet.
Speaker 2 (18:51):
Well, it's a dynamic that I think.
Ai is certainly applicable toall these conversations we're
having and part of it.
If you look at Learning WithoutScars business model of the
training platforms you guys havedeveloped over the last handful
of years, you're really takingthis to a whole new level and
(19:15):
the type of education you canprovide now to dealers and've
always I'm a product of some ofyour early education programs
and you've always provided goodinformation.
But the tools today are evenbetter, more robust, and you can
certainly take a counter person, um and or a service person and
(19:37):
you can move them through thetraining curriculum relatively
quickly or self-paced, but stillvery fast.
And, and you know, dealersshould invest and I well, that's
a plug for your program it'sdealers aren't investing with
anybody to a high degree.
Their training is limited tooem type training or vendor
(20:00):
specific training.
Well, that's all self-servingfor the OEM and vendor.
Yes, you need to know some ofthose nuances, but that's really
not the training I'm talkingabout.
True, you know, down in thetrenches, get your fingers dirty
, type.
Okay, how do you teach thesepeople to sell better when a
customer walks into thedealership?
(20:20):
Welcome to ronsley dealership,right?
How may I help you oh, can youneed parts here?
Let me walk you over to theparts department and so on.
Um, you know it's.
It comes back to you know one ofthe notes I put down for
conventional dealer operations.
You know the strengths.
You know that dealers have is.
(20:42):
You know they have processes,they have OEM support and, in
theory, they have experiencedstaff.
Well, a lot of the experiencedstaff is retiring.
They're older, they're notcoming back.
And how are we training thenewer generation to come into
the dealer world, not only thetechnicians, but everybody else
(21:03):
that plays a critical role.
You know things in the old dayswere reactive.
You know silos betweendepartments, silos, silos are
more prevalent today due to thenoise that comes from all the
data within each silo.
It's maddening in my mind,right.
And you know tribal knowledgeversus scalable systems.
(21:25):
You know I think you need both.
You can't.
Tribal knowledge should neverbe discarded and in scalable
systems or AI and other type ofsystems should not be ignored
either.
You need to bring thesetogether, not one versus the
other.
You know, and you know limitedforecasting or predictive
(21:46):
ability.
You know we're living in an agewhere predictive maintenance is
something we can really do.
Very well, we've been able todo it very well for a long time.
I think we can do it evenbetter now.
Speaker 1 (22:02):
And what's remarkable by picking on maintenance for a
moment, is survey data for thelast 40 years that I've seen and
associated equipmentdistributors that surveys every
five years for the longest timeMaintenance the dealer gets less
than 5% of the maintenancehours.
Yep, and the primary reasonthat is given by the customers
(22:27):
in those surveys is well, theycharge the same thing for a
journeyman mechanic as they dofor a maintenance mechanic.
And so we go to the dealers andsay, well, why the heck do you
do that?
Well, I get more money if I dorepairs.
The customer repaired themachines down.
That's more important thandoing an oil change, really no.
(22:48):
So you know again the modelsthat we're working with.
I used to do the same thing anytime 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 havea cup of coffee with them and
just shoot the breeze.
Know me from Adam and you findout more in 30 minutes talking
(23:14):
to people and walking aroundthrough their shop.
They used to kick me off theproperty after a while because
it became clear who are you?
What are you doing back here.
Well, I'm just, you know, havinga look at what you got
available, how many of thesefields.
I mean, you got a lot of fieldtrucks here.
It's eight o'clock in themorning.
How come they're not outworking Getting organized?
(23:34):
Oh, are they on a customer jobalready?
Oh yeah.
Oh, so you're charging themwhile you're sitting here
getting ready, oh yeah, and theydon't recognize the idiocy that
we're exposing.
You know a standard thing thatused to drive me crazy the OEM
(23:55):
sets the benchmarks ofperformance for your dealership.
Right.
If you want to continue to be adealer, here's the things you
have to do, and one of them isyou have to hold, let's say, 80%
parts availability.
The only part that's importantto the customer is the one you
don't have.
Speaker 2 (24:12):
That's right, and nobody pays attention to how
long it takes to get the backorder here.
Well, and that's where theadvanced analytics that we have
capability to do today reallycan play a big role in improving
the customer experience.
But at the end of the day, ifwe don't have customers, we
(24:34):
don't have a business right, wedon't need employees.
And I'm not saying that youhave to just bend over backwards
and everything the customerdemands they get.
They're not always right, eventhough they are the customer,
but you have to articulate howyou say no, when you say no, and
the why behind saying no andwhat that means.
(24:54):
Right, and I really likeengaging with customers.
So it's not just me over herearmchair quarterbacking.
You know this is me speakingfrom.
You know, real time activities.
And then our last conversationI think it was that one I
mentioned I'd spend one day aweek, the entire day, on the
(25:15):
road either making sales callsby myself or with the sales
person or persons or differentones, you know and I would want
to go see customers thatrecently had purchases large
purchases, medium, small and orangry upset customers.
I want to do a follow-up and alot of times I'd walk in and
(25:35):
they were chewing on me as Ientered the building and, as you
know, we were leaving thebuilding, they were shaking my
hand, saying thank you,Appreciate the time.
You know, and we'll see younext time at the dealership.
And you know that.
You know, and they weren't allthat easy, but a lot of them
were, and it's just really beingwilling to ask the questions.
(25:55):
And when I had people that Irode with, I would, I would talk
to them about, hey, get to knowyour customer.
And where I'm going with thislittle rant is using AI and a
system that has good alignment.
It has limited noise, where theCRM is not noisy, where your
(26:19):
DMS and your business system andthe CRM are aligned.
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 customersatisfaction index score for you
is listed here.
(26:39):
Why did we get a bad rating?
Why did we get a good rating?
You know all those things.
Go out there with that knowledgeand today you can in every
dealer.
You should be able to get thatin real time and you know,
within, let's say, within a weekof it happening.
So real time, five days, youshould be able to go out and see
(27:03):
the customer and you shouldembrace that, and I think that's
one thing.
That and the dealers they'restill not teaching their leaders
.
They fast track people intopositions that are beyond their
skillset to lead.
Next thing, you know, you endup and I'm not opposed to young
people or anybody gettingpromoted.
What I'm simply saying is don'tput people in positions where
(27:26):
they struggle too much and failand because when they're failing
and struggling, they're nottaking care of the rest of the
team because they're trying tosurvive.
And while this podcast iscentered around AI and things
like that, I still in myconsulting and my conversations.
(27:48):
The human element is criticallyimportant and I'm not a fan of
the thought process that AI isgonna replace everybody on the
planet and we're all out of ajob.
Yes, some jobs will bedisplaced, but new jobs will
come in support of all theseother things.
So it's going to come down to amatter of either you learn new
(28:09):
skills or you will get leftbehind.
So that statement I do agreewith, but I don't think it's all
doom and gloom.
So, somebody used the term theother day.
Yeah, it's just going to belike 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 Idon't see it going that
(28:33):
direction either.
Speaker 1 (28:35):
It's the whole nature of business and development and
technology.
At one point in time, anautomotive production line
needed 20 years of use before itbroke even.
Yeah, imagine.
So here we've got.
A couple of weeks ago I waskind of intrigued NVIDIA
announced a new robotic chip andit's $2,900.
(29:00):
But if you buy more than $100,it's 2,900 bucks.
But if you buy more than ahundred, it's 1,900 bucks.
And that got my little headgoing.
Well, darn it.
Every joint on a robot has tohave a chip Correct.
So you probably got a hundred200 chips in a robot.
Now we're back to the productionline of 20 years before it
breaks even.
How much is that robot got tobe displacing replacing in order
(29:24):
to pay for itself?
But everything you're doing andeverything that we're kind of
blaming or using AI as the stick, it's about building
relationships.
It's about getting the customerto trust you, because they
don't know what the heck's goingon either.
(29:46):
They look at you as a savior.
How are you going to do that?
You know it's sitting talkingto those people.
Somebody comes in the frontdoor within 10 seconds.
You better acknowledge them.
Just stick your hand up ifyou're 10 seconds.
You better acknowledge them.
Just stick your hand up ifyou're on the phone and wave at
them, it doesn't matter, it'sbeing people first.
Speaker 2 (30:08):
Well it's going down to.
One of my notes is I wrote AIas the game changer.
Right, it's an operationalprocess.
Right, we still have tointeract with people.
Right, and you can go to marketwith all the different things
predicted maintenance,telematics, ai parts stocking
(30:29):
and dynamic pricing.
Some of those things have beenalready out there for a handful
of years to some degree.
Smart technician scheduling,capacity planning, all those
things you can give.
Everything I just mentionedleads to improved market
intelligence and lead scoring.
(30:50):
So now, when you understandyour market and you're scoring
all the leads, you know which,the probability of success, all
these different things based onall these different factors, now
you're moving your operation atthe same pace as as well faster
, but with the people along forthe ride.
They're not just on thesideline watching it all go by
(31:13):
and then you, then you bring itforward.
Where you use the buzzwordtoday is agentic AI.
So that's just a fancy way ofsaying hey, that's you know, you
building these little agents towork together.
So that's Troy Otmer, againbeing augmented by three or four
different agents running.
(31:34):
In our last podcast, ourreference I was actually in the
middle.
It was running while you and Iwere talking.
It was distilling data based ona very complex, prompt
structure that I wrote, thatwent out there and gathered all
this data.
And now this data is part of apresentation for a project I've
(31:55):
been working on, and you know.
And of course, there'svalidation processes.
But guess what?
You write these agent AIplatforms to help you validate.
Because you read it I read alot too, man.
I have thousands, maybemillions of words, but you know
it's really good.
(32:16):
So what does this do for thehumans?
Well, it enables the leaders,the managers, the technicians,
the part sales, new sales teams.
They can upskill and increasetheir throughput because, ron,
if you want more output, youneed better throughput
capabilities.
Right, you know, and we can godown the rabbit hole of Six
Sigma lean process management,all that rabbit hole of Six
(32:41):
Sigma lean process management,all that you know.
But at the end of the day, youwant more output.
You got to have improvedthroughput and you got to quiet
the noise, and you know.
And you want your employees toengage your customers better and
you got to give them the bettertools to do that and you got to
train them, you got to leadthem.
And you have a saying JohnDowling mentioned it the other
day when he was presenting.
He said you know, ron says wemanage processes, we lead people
(33:07):
, and I wholeheartedly supportthat and you know.
So he was out there quoting you, by the way.
Speaker 1 (33:16):
I pay him a lot of money for that.
Speaker 2 (33:18):
I know that's a good point.
Speaker 1 (33:22):
No, but the thing that you're exposing again it
goes back and I mentioned it.
We've got to know to deliver toyou information not data,
information Correct that youcould translate into action.
(33:45):
Yes, and training is importantand something that we have been
terrible at in the 90s is whenit really became prominent.
In the 90s, almost everybodyAED Caterpillar.
Everybody stopped trainingbecause it was too expensive and
(34:06):
that's when we started it.
I sat in front of the computerand I talked for the summer and
created eight textbooks, 250pages each, and in those days I
could talk for 30 minutes andI'd leave the computer and it
would take them an hour and ahalf to catch up with me with
voice recognition stuff.
Today it's instantaneous.
I pick up another piece ofsoftware a couple of three years
(34:31):
ago that it was limited to 5000words in a product.
It was an audio track type ofproduct that created subtitles.
At the same time, last week itbecame 20,000 words.
Well, all of a sudden you canbe talking about books.
Speaker 2 (34:52):
Yeah.
Speaker 1 (34:53):
So I can have, I can turn around and I can take an
audio book and I can run thatthrough the computer with voice
recognition and turn it into myown document that I can then put
through Copilot and make itmore casual or make it more
formal or make it sexier orwhatever.
It's all kinds of differentthings, right?
(35:13):
The problem that I see withartificial intelligence which,
by the way, was first introducedto the world in 1950, is that
and I mentioned it earlier wehave to learn how to ask
(35:33):
questions and as you're evolving, you're finding better ways to
ask those questions to get theanswer you're looking for.
And you do it by makingmistakes.
Yep, yeah, I have to go.
Oh, that's no good.
So just imagine that I can takethe dollar value of a
transaction and the time betweenthe transactions, so I can say
(35:54):
transactions once a week, onceevery two weeks, once a month,
once a quarter, and dollarvalues of 50 bucks, 500 bucks,
5,000 bucks, and I can build agrid for every customer, for
every dealership, right?
And if that buying patternchanges, I want the customer
(36:16):
names delivered to the personthe next morning.
So the day it changes within 24hours.
You missed a day, you missed adollar 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 alittle bit of a difference on
(36:36):
your account.
Is something going on in thecompany at the moment?
And what I'm trying to conveyto the customer and how I
communicate, that is I care, I'mhere to help you.
What do you need from me rightnow?
Is something going on I canhelp you with, and it's a
completely different sales gig,isn't it?
Speaker 2 (36:57):
Oh yeah, well, Ron, it comes down to dealers
oftentimes that they they comeup 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
(37:17):
inaccurate.
Yes, your job is to take careof your customer, your installed
base, the people you're sellingproduct to, newport, et cetera.
And yes, you have to run yourbusiness in a profitable manner.
Enough on reducing theirdowntime and or, and like we
(37:38):
said earlier, customers don'tuse the dealer maintenance
services because they're sendingout a level five tech at the
highest rate when you should beusing a level one or two or
journeyman or what have you, ata different rate.
You know, I, you know, I hadthat philosophy when you and I
first met many years ago and Ifollowed that same thought
(37:59):
process by adapting, you know,to those market needs from a
maintenance side.
And look, I made more money atthe end of the day for the
dealer groups I've representedby focusing on driving high
levels of maintenance and havingtechnicians working, and
(38:21):
occasionally you would have ahigh-end tech on a project, for
whatever reason it happens, butthe goal was never to have those
people on changing oil andfilters or basic maintenance
right, and you know, and I putthem 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 inthe field, I don't want to see
them in the shop, let's go tothe customer.
So you know, field service.
(38:42):
You know, I don't want mytrucks coming into the shop
every morning at 8 o'clock to bedispatched.
No, they're mobile, they candispatch from home and they go
straight and we'll run parts tothem.
You know, and all thosedifferent things.
So I mean dealers shouldn'tjust focus on hey, we need to
(39:02):
sell labor or we need to sellparts.
No, you need to reduce yourcustomer downtime.
You need to improve thatexperience.
You need to improve your firsttime fixed rate.
Uh, you know, so it's now.
You don't have to go out threetimes to fix a problem.
You do it the first time, youknow.
And then you know, targettargeted sales wins every time.
(39:23):
You know, have a plan, executeyour plan Right, you know.
And then, with, with AI and youcan, you can validate the ROI,
like you were mentioning.
Hey, within within a day'snotice, or within that same day,
from the morning to the eveningyou can say hey, what happened
to your business today?
You're trending down and yousee that in real time.
(39:44):
So, and look, if you get thatanswer in one to two hours,
that's real time, right, youknow, versus, I'll get an update
on Monday morning and it'sTuesday now, but next Monday
morning I'll have an update.
You can't run your businesseffectively Tuesday now, but
next Monday morning I'll have anupdate.
You can't run your businesseffectively and that's why, you
know, we had to be creative byand creating queries to mimic
(40:08):
what AI can do for us veryeasily today, and there's a lot
of hard efforts behind thescenes.
But you know, to me, this AIadoption is a leadership
opportunity.
And I say leadership I'm notjust talking about your general
manager, parts and servicemanagers, et cetera.
I'm talking about dealerprincipals or ownership groups,
(40:29):
private equity included, and Iknow PE and others like them.
They have a different mode ofoperation and profit before
people does happen and whilethey're not publicly traded,
they're very similar into, youknow, focusing on shareholder
value, and it's easy to keep theshareholder in front of the
(40:49):
customer because, remember,shareholders, you have no value
if you have no customers.
Speaker 1 (40:55):
I used to have fun using, you know, customer
retention as a tool.
Harvard, in the 80s, made thecomment that customer retention
was the single most importantthing to drive profit.
So then you know, in yourthinking and mine relative to
maintenance, I'd sit down with agroup of people at the
(41:16):
dealership and say you know howmany hours does it take?
I got 2000 hours on my machineevery year.
How many hours should I bespending on maintenance?
And we'd look at it in thosedays 250, 500, 1500, blah, blah,
blah.
And we come back with a numberthat was 40 to 50.
To make this arithmetic easy,let's use 50.
Speaker 2 (41:35):
Right.
Speaker 1 (41:36):
And then I'd say to them well, what, what's your
working machine population outthere?
What do you think it is?
They don't know, which is a bigproblem, but well, 5,000
machines.
Okay, how many people does thatmean there's doing maintenance
(42:06):
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 83are working with?
Or 93 are working with?
Oh well, wait a second.
How much do we make in incomeon 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 throughanother, that's $100, so I
charge $50 for maintenance, 50hours times 50, that's $2,500.
And that much parts, that's$5,000.
So $5,000 per machine formaintenance, and instead of $93,
(42:27):
let's just say it's $100.
How much business have you lost.
Speaker 2 (42:33):
Yeah.
Speaker 1 (42:35):
And so you know one of my favorite little things to
do.
I always checked it first, butI'd go out into the shop and
look at the machines that are inthe shop and find how many of
them had competitive filters.
Oil filters, no others, justthe oil filter.
And in many cases it's a bignumber 60, 70, 80% of the
machines in the shop have acompetitive filter.
(42:55):
I said are you going to doanything about that?
Well, what do you mean?
Well, that guy's got acompetitive filter.
I said are you going to doanything about that?
Well, what do you mean?
Well, that guy's got acompetitive filter on this
machine.
Don't you want to get him touse your stuff?
Yeah, but our filter is reallyexpensive.
I said fine, put it on fornothing.
Call him up and say do you mindif I change your engine oil
(43:15):
filter?
I'm going to put one of mine oninstead of yours.
I'm not going to charge you forit.
Oh, that's okay, why do youwant to do that?
And then I can start talkingabout the features and benefits.
I can talk about what happens.
What is it?
You know, particulates.
And here we go, and all of asudden the guy is by the way.
Who chooses that filter?
The guy that does mymaintenance.
Do you tell him what filter touse?
(43:36):
No, he picks his own.
Wait a second.
This whole thing's upside down,yes, and it's been that way
forever.
Here comes artificialintelligence, and I'm going to
use that as an excuse now, causeI'm going to know I got 5,000
machines out there and they'reaveraging 2000 hours.
That's eight of these filtersevery machine every year.
(43:58):
That's 40,.
Eight of these filters everymachine every year.
That's 40 000 of those filtersI should sell.
I only sold 372, right, what'sgoing on here?
And I can do that for hose, Ican do it for batteries, I can
do it for undercarriage, I cando tips, I can do it with darn
near everything because of aicorrect, it was hard before and
(44:19):
you and I've done it beforemanually.
It's a bear, it is.
But if you want to do thebusiness properly, you got to
use it, and that's why I sayit's a bit of an, it's an
opportunity, it's an excuse.
Let's get looking at thebusiness differently.
Speaker 2 (44:35):
Well, it's one thing you said and I know we're
getting close to time, I believebut in closing, you know, not
understanding what your OEMinstalled base is in your market
is a problem, and the secondpart of that problem is not
understanding what yourcompetition's installed base is
(44:57):
in your respective market isalso a problem.
And, in closing, what I wouldsay to that would be real simple
you need to know what theentire machine population looks
like.
Now you may not be able to gochase all of it because it's OEM
specific warranty, blah, blah,blah specific warranty blah blah
(45:21):
, blah.
But make no mistake, a lot ofthe maintenance that a dealer
can do will be on non-oemspecific product.
And that's how you transition acustomer to your oem product at
some point down the road bygoing out and showing them, hey,
how well you take if you're acat dealer, how well you take
care of their john deereequipment, and when it's time to
trade them out, boom, you tradethem out, they roll them into a
(45:42):
cat or vice versa.
And you know some of the secondtier type products that came
along, like hyundai, etc.
They've made a lot of marketshare gains against cat john
deere, volvo, kamatsu by playingthat game and you know saying,
hey, we're going to be what'sour, we can't go get them
head-to-head.
So how can we gain market shareand or wallet share on them?
Speaker 1 (46:04):
And that's just some of the methods to do that.
Yeah, and the interesting thingis there's tools out there
Equipment Data Associates, edaany machine that's financed.
There's a report.
I can buy it, I can do it bycounty, 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?
(46:25):
The first thing that comes backat me when I ask that question
is well, it's hard because theyput the name in differently than
we have it in our profile.
Uh, okay, so technology has tocome into play here.
But but there's a whole host ofthings and it leads the
discussion into a differentplace.
Underneath this, I'm askingabout AI, and there's lots of
(46:50):
iterations, there's lots ofthings to consider, but it's not
really AI at all.
It's about doing the businesswell.
Correct.
And your comment about sellingto john deere replacing a john
deere machine and here comeshyundai, and hyundai's done a
particularly good job at it, andit's because of their
experience in the car business,correct?
(47:12):
And who was the first one to dothat?
Toyota, yep, toyota createdLexus.
The top of the Toyota brandline is Camry.
The most expensive.
Camry is the cheapest Lexus andeverywhere we do it's the same
thing and they learned thatlesson.
(47:33):
Well, we didn't learn that.
Speaker 2 (47:38):
Well, funny story on Hyundai.
When, as a young tech in the80s, when Hyundai came to the
market, obviously Toyota andHonda, you know, had a good
reputation, good quality product, you know, and I was fairly new
, so guess, what I got to workon was Hyundai and and I thought
that was going to be a curse.
Well, I've, really, I'verealized very quickly that this
(48:01):
is a quality product and it'seasier to work on than the
American counterpart and I'mlike, wow, this is interesting
and to see them continue toprogress the way they have.
They pay attention to whatmakes their customers happy and
(48:21):
their maintenance and support.
And then you know the spinofflines that come from it, their
luxury line, you know, hyundaigot one of the premier luxury
lines.
Now, same thing Quality of theproduct, right.
Speaker 1 (48:34):
What's the luxury line called from Hyundai?
Speaker 2 (48:37):
It is Genesis.
Speaker 1 (48:39):
Yep.
Speaker 2 (48:40):
Yeah.
Speaker 1 (48:40):
I had a Genesis that I bought in California and
shipped here and the dealer wasgoing to have to pay for it the
next week.
So I got a pretty good deal andat that time Genesis had two
products.
Today they've got six, and theprice differential to Lexus,
(49:03):
cadillac, all of the premierlines, was $40,000.
Yep, and if anybody is going tothrow away 40 grand just to
have an ornament on your car,then you know I'm Scottish for a
(49:23):
reason.
But you know this takes us downanother path, troy, that I
think we need to have anotherone down the way, but it won't
be AI driven anymore, it'll bethe analytics, yes, yeah anymore
, it'll be the analytics.
Speaker 2 (49:39):
Yes, yeah, and analytics.
You know, ron, we're going tohave to train people to
understand analytics and notover complicate it either.
Right, that's part of it.
Speaker 1 (49:51):
I'm almost in a place that we can't train them on
analytics.
We have to give them theanalytics and tell them how to
use the tool.
Speaker 2 (49:59):
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 optimisticabout a handful of folks I'm
working with that I think havethe capability to learn it.
But for the vast majority ofpeople you're probably right,
it's a plug and play Plug it inand play.
Speaker 1 (50:23):
Well, yeah, I agree with you 100%.
One of the things that'sinteresting the other day I had
a chat with somebody who runsone of the dealer management
systems businesses and they'rehaving a hard time getting
people, as everybody is.
And I said, well, you knowevery install that you get to.
Why don't you make a deal withyour customer that you're going
to take George and Mary for ayear on your payroll and you're
going to have them go out and docustomer service for you and
(50:45):
installs for you and expandtheir knowledge and
understanding of your system?
You're going to pay for themand 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 companyasset for your company.
And it's kind of putting on theear like, if I'm if I'm a
dealer, maybe I want to providethem.
If they've got their ownmechanics, maybe I want to give
(51:06):
them a mechanic and I'll takeone of theirs.
Yeah, right, ultimately, comeback and say, well, why the heck
do we want to have thatmechanic on your payroll?
And if you really want to getnasty, I won't pay an equipment
salesman any commission for asale when he replaces the same
brand that I'm representing.
I'll pay him a lot of money ifhe replaces a competitive brand,
because if you look at thedealers, they're in their 30%
(51:30):
hole and they stay there.
You're right, yep, and mygoodness, it's so easy.
John Deere and Caterpillar havebetween 70 and 80% of the
markets here on equipment.
Volvo, camacho and everybodyelse is fighting for the other
20 or 30.
Right, that's.
That's like standing at thebeginning of a race knowing
you're going to lose.
Speaker 2 (51:59):
I've never looked at being a John Deere dealer
predominantly the cat dealeralways had us 10 to 1 in terms
of size in almost every market.
But that to me, was not anegative.
It was an opportunity to exposetheir weaknesses.
And look, cat dealers are verystrong, but every dealer, no
matter how good you are, how toptier your OEM is, there are
(52:22):
weaknesses that can be exploited.
And that's where data analyticswill come in to help you open
up and kind of peek behind thecurtain of what the market truly
looks like and where there'sopportunity.
And for a dealer to besuccessful at any dealer large,
small, medium, everything inbetween they have to be willing
(52:44):
to take a look in the mirror andutilize the AI or data
analytics dashboards.
What have you to?
You know, have that bit ofreflection.
And you know, let's start nowor are you going to get left
behind, right?
You know, let's start now orare you going to get left behind
, right?
And if you want to grow yourbusiness, you know, if it's a
multi-generational business, youknow they usually when they hit
(53:07):
the fourth generation, they'reprobably 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 changethat.
That's paradigm shift.
Let's get busy and, you know,let's augment our workforce with
the best tools we can give themtoday.
Speaker 1 (53:26):
Let's wrap this this way In Canada, when I started at
the dealership, there were 10dealers.
Today there's two.
Yep In the United States, whenI started with the Caterpillar
family, there were 50 dealers.
Their goal today is to be under20.
And part of that is because ofthe cost of the equipment, the
money that's required to operatethese dealerships.
(53:46):
Same thing's true with JohnDeere.
Rush is one of the largest inthe country.
You know, rdo up north is thesame thing, branton, canada,
it's the whole country.
So all of these dynamics havechanged and analytics is going
to get us there.
But it's going back to basics,troy.
Yeah, it's very fundamentalthings.
(54:07):
You need a part.
I have the part, I don't havethe part.
Oh, the guy at the counter.
How much is that?
Filter 15 bucks, boy, that'sexpensive.
Then the guy at the counterdoesn't know what to say.
Filter 15 bucks, boy, that'sexpensive.
Then the guy at the counterdoesn't know what to say.
So we have a lot of work aheadof us and you're going to have a
lot of fun.
You got 20 years on me now,buddy, you better be looking
(54:28):
after it properly.
So you know, troy, thanks foryour time and fellas and people
out there listening to us.
I hope that our goal with thesepodcasts is to get you thinking
, and I hope we succeeded atdoing that and I look forward to
having you with us at anotherpodcast, another kind of
conversation, in the near future, mahalo.
Aloha and welcome to another candid conversation.
We're continuing our artificialintelligence discussions again
today with Troy Otware.
We did one with Troy a coupleof three weeks ago where he gave
us his background, starting asa mechanic in trucking and
moving into dealerships, etcetera now in consulting, and
(00:24):
one of the things that hepointed out when we last talked
was how he went to data beforehe went to the market, and I'd
like to use that as a startingpoint on how he operates now in
the consulting world, how hehelps people.
So with that, troy, as a prettyweak entry, but giving you all
(00:46):
kinds of landscape to play in,let's go.
Speaker 2 (00:50):
Well, ron, thanks for having me back again Always a
pleasure and, as we were sayingprior to recording the recent
podcast you've had on thevarious angles that people are
approaching from AI, I'm excitedto talk about that today and I
think for me, being aconventional dealer operations
(01:14):
guy coming out of the 90s andmanaging my way up to this point
, you know what you just said inthe opening statement was I
never did anything withoutreviewing the data and obviously
AI was not an applicable itemfor any of us in the 90s, 2000s
and so on up until recently.
(01:35):
But I'm still approaching it inthe same method.
I'm not just going straight toAI 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 myproblem.
Give me the answer, and then Irun with that answer and say,
hey, dealer, principal, here'swhat we have, let's go, here's
(01:56):
the solution to all yourproblems.
There's still a validationprocess that we must go through
and one of the common phraseswe're all using data is noisy
and I've had a number ofconversations in the last 10
business days with people fromwithin the sector.
We're talking about the dealerworld and outside, and everyone
uses data, and they use data insuch a way that they don't even
(02:19):
realize they're using data.
Every decision is database.
Now, there's a lot of emotionthat goes into decision making a
lot of times too, and you knowyou got to try to remove that.
And my approach from being aconventional dealer operations
guy to becoming a consultant ishow do I want to make a
(02:39):
difference in the world aroundme?
And, as I find myself sayingthis a lot, I want to leave my
clients better than I found themand what value do I bring to
them.
Obviously, as a consultant, youdo freak people out a little
Like oh that consultant peopleis expensive, yes, but probably
(03:04):
no in a lot of cases.
And if you can get through thatdiscovery phase, what I call it
, when I do a dealer review orI'm having a conversation about
being hired, I want tounderstand what your pain points
are.
And the first place I'm goingto go is, well, after the
conversation is let's look atyour data and if it's in one
(03:24):
department or all thedepartments, let's do that
review.
And, as you know from doingthis for a number of years,
managing data, even in the oldschool ways and even with AI is
still not an easy task, so wewant to work smarter, not harder
, and I know I probably saidthat the last couple of
podcasts- it goes almost todaywithout saying One of the
(03:50):
interesting things.
Speaker 1 (03:52):
Looking from my perspective, companies and
people that do not supplementtheir knowledge and skills with
artificial intelligence aregoing to be left behind.
Oh, absolutely yes, and sopackage that up a little bit.
Why is it that you think thatAI enhances your skills,
(04:17):
knowledge and ability in whatyou do?
Speaker 2 (04:22):
Well, it takes 40 years of tribal knowledge.
Okay, and tribal knowledge,some, you know, some people
don't like that word, but it'sperfect, it is a market word,
it's, it's right.
It's not meant any form ofdisrespect or anybody being
overly sensitive.
Think about it, though Everygroup, every business, every
(04:45):
community, there's tribalknowledge that gets accumulated,
but it doesn't always getaccess or it's not accessible,
probably is the better way tosay that.
So, for me, my why as to who Iam today and how I go to market,
is how do I take 40 years ofknowledge?
(05:05):
Gut instinct, intuition, youknow, learning before learning
without scars was a thing.
You know all those scars thatcame from learning the hard way,
the school of hard knocks.
You know the, the, the, themistakes, the failures.
All those things havequantitative value, and there's
(05:27):
that value word again that we'regoing to talk about, and for me
, it allows me to navigate thevarious different entities or
markets that I go into, whichisn't just the dealer world.
I cross over into several otherindustries just simply due to
my background, and now I'mtaking that knowledge base and
(05:51):
I'm using AI to look at theproblem, using my tribal
knowledge, and then I go in andI use agentic AI or write an
agent for me to go focus on thisparticular problem.
And had I not, if I just hadthe AI side of the conversation,
(06:13):
only that knowledge base, Iwouldn't be near as effective.
So what I'm describing, whatI'm bundling up here for you, is
Troy Otmer is now an augmentedindividual with an expanded
toolbox.
I started my career as atechnician still have a lot of
those same tools, a couple ofsame toolboxes that I'm in
(06:35):
around.
So you know, 40 years ago.
Now, fast forward to today, Istill have those toolboxes.
Don't use them like I used touse them at all.
However, my new toolboxesinclude all the data process
management that I learned alongthe way.
Now AI is taking that and I'mcoming full circle.
(06:57):
To put the cherry on the top,which is I come fully dressed,
ready to work, ready to attackany problem and look at it
objectively.
And yes, an AI again, you putdata in.
That doesn't make sense.
You're asked a silly question,you get a silly answer, but if
(07:18):
you structure your experiencesaround the task at hand, you can
generally come out with a verystrong product.
And, of course, you still proofit out, you still validate it.
You don't just roll with it.
But you know that's how I wouldbundle myself.
And, as a matter of fact, in arecent conversation yesterday,
you know, I was asked a verysimilar question.
(07:40):
Well, how do you see AI helpingthis client?
And I said I see AI as meunderstanding your business in a
very expeditious manner, veryquickly.
However, it also allows me topull in your HR data and
understand your surveys and youremployee experiences.
(08:00):
Oh, and now I can pull in yourcustomer data, your Google
reviews, and then I can compareall that and I can build a
platform, or, with partners, Ibuild a platform.
I'm not building all thesethings myself, but, in a very
basic sense, I can now give youa better idea of what a 360
(08:21):
synopsis of your dealership oryour business looks like.
So that's how I would bundlewhat 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 tounderstand.
Speaker 1 (08:40):
And that comes from the tribal knowledge, and I
don't think there's anythingwrong with that terminology,
because everything that we havedone and learned started
thousands and thousands of yearsago in tribes, correct, and we
throw out things that aren'tapplicable anymore.
And there's a lot of that.
And you know my metaphor theelectric engine replacing the
(09:02):
steam engine and how long ittakes people to adapt.
But before we can do anything,we have to understand what the
heck it is we're trying to doand what they're trying to do
and all the rest.
And I I translate that and saywe have to understand before we
can be understood, correct?
So if I'm going to communicatewith somebody, as you do, going
(09:24):
to the data and as an augmentedperson, you're filtering that
data to the point that you cancommunicate to that customer
with better knowledge and, inmany cases, more knowledge of
their business than they have.
Speaker 2 (09:38):
Yes, fair comment.
Fair comment.
Spot on yes.
Speaker 1 (09:42):
And the dilemma that we have is with using artificial
intelligence.
We need a new skill set Askingquestions.
How do I know what I need toknow?
I have to ask a question.
Now.
I can ask AI, copilot, gemini,a whole bunch of different tools
Right, and they can give meanswers.
Well, gee, that wasn't theright question, so we have two
(10:06):
paths coming down here.
Most social media deals withalgorithms.
The algorithms are made bypeople.
Some of them are biased, someof them aren't.
It's hard like hell to know thedifference, but you can't take
what you see as fact withoutverification anymore.
There's so much, like you said,noise out there.
(10:31):
So when you're looking at acompany back in 80, when I
started, I used to say to peoplewhen 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'skind of a screwed up way to it
worked at the time because itwas kind of cute.
But that doesn't work anymore.
And if you're talking to acompany and you know their
(10:51):
business better than they do,first of all, that bothers them.
It does, yes, so let me go intoa different direction.
Business systems at use in thecapital, goods industries,
dealers and others distributorsand others are used probably 40
(11:13):
percent of the capability of thesystem, and the employee is the
one that's making that decision, not the company, because they
find what they need and we'reall guilty of this what they
need to do their job and that'sas far as they go.
If I'm working the counterselling parts, I know how to
(11:36):
find the price, I know how tofind the availability.
That's about all I need to know.
The customer calls me up, I askwho they are.
Maybe I have help on the phonebecause I can see who the phone
number is, but there's privacythings to get in the way, so I
have to ask who you are.
That's a wonderful way to starta relationship with somebody
who wants to buy something fromwho the hell are you?
(11:58):
Yeah, and then the next questionis 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 for100 years.
Yes, sir, and I classify.
I call that paper to glass.
We took a manual system.
We just put it on a screen andinstead of writing it, we typed
(12:21):
it.
So now I got fat fingers andguys that we didn't have typing
on when we were in school.
And how do I break through tothe customer, the person you're
talking with, that youunderstand their business and
you looked at different aspectsthe customers, the employees,
the payables, the processes andwhat's their pain point, what
(12:48):
keeps them up at night.
And you start talking about howthat 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
(13:11):
talking to.
Speaker 2 (13:13):
Sometimes well, I think I've experienced all of
those situations and sometimesat the same time it's by the
look on their face and it goesback to part of the problem has
nothing to do with AI the waythe dealers have ran.
(13:37):
One of the problems is we'vegotten away from value-added
selling.
We've stopped teaching thefront counter people to ask
those important questions.
I walked into a dealership theother day for a meeting and
nobody knew why I was there orwho I was.
No one asked to help me.
How may I help you?
(13:57):
Who are you here to see?
You know you're here to look atsomething.
No one asked me a word.
I sent a text message.
I'm here.
Somebody came to get me and I'mlike okay, I learned a whole
lot about that business rightthere, where there's a big old
fancy service counter and a bigold fancy car counter, and I
(14:20):
could have been some bum off thestreet right and or I could
have been the most importantclient they'll have all year.
I'd like to think, if I do getto work with this particular
group, that maybe I'd help themfix that particular problem.
But that's not uncommon to allthe dealers and I've had the
good fortune in the last five to10 years to not only work for
(14:42):
dealers but also be on thecustomer side and walk into
dealers, and everything you'resaying right now is exactly the
problem.
I'd walk in and the customerexperience 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 dowe handle that.
(15:03):
So part of this problem istraining related.
It's a culture problem andwe're at definitely, dealerships
I was going to say they're atan inflection point.
No, they've been at aninflection point for a long time
for a lot of reasons.
At an inflection point for along time for a lot of reasons,
(15:24):
and AI is not their saviorsimply by saying, hey, we have
AI now.
Now you can work smarter, notharder.
There has to be some collectivetraining and processing and,
yes, it can do simplified tasks,but how do we implement that?
So when I go to talk to adealer, I'm not leading with hey
, ai is going to save you andTroy and AI plus, you know,
(15:46):
together combined, that's notthe answers.
I will use AI.
I make no secret of that.
I use it to give you answers inreal time, so I don't have to
wait until a quarterly reportcomes out, so I don't have to
wait till an orderly reportcomes out.
I can tell you at maybe sameday.
Some business systems can allowthat processing to happen, but
by the next morning I can prettymuch have you an answer of what
(16:09):
happened in the previous threeto five days and how the month
is going to look.
I know you and I talked aboutbefore 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 aworld that you can have
(16:29):
predictive analytics, even in aworld without ai and no question
, and and and.
Speaker 1 (16:35):
the problem that you're exposing, troy, I think,
relates in a different way.
Every 20 years, the number ofdealers that we're competing
with in the marketplace and Idon't care if it's equipment,
forestry, mining, marine,whatever it is is reduced by
half.
And you want to talk about afailure of leadership.
(16:59):
Hello, so you know.
Translate that and this is 2025.
In 1985, we start with 100customers.
2005, we got 50.
Now, 2025, we got 25.
And leadership looks at therevenue line.
Yeah, revenue is going up.
I'm okay.
(17:19):
Well, it better go up.
You're only dealing with aquarter of the people you're
competing with anymore.
So there's an interestingstatement, and the one that
becomes more.
I think telling your job nowinvolves a lot of learning.
(17:40):
It involves a lot of time inyour head, thinking the
operating leadership of adealership doesn't have time to
do nothing, baby.
No, they're putting out firesall day long.
The phone rings, let's get outof here.
And we've been.
That's why I think we've beenreducing the number of
(18:01):
dealerships so much.
We've been putting profitsahead of people, cutting back on
the number of people.
Everybody says customer loyaltyis gone.
Well, we haven't treatedcustomers very well to make them
be loyal, true?
So all of that combined.
And here comes ai, and and I'mgoing to use it, as I think you
do, as an excuse we could havedone all of this stuff manually,
there's no question about it.
(18:22):
We didn't know what we neededto do.
And today, I think, thebusiness of equipment dealers
whether it's on highway trucks,whether it's tractors, whether
it's lawnmowers, whether it'sair conditioners in your house,
the dealers it's now business tobusiness, it's not person to
(18:45):
person, and they haven't figuredout how to work that yet.
Speaker 2 (18:51):
Well, it's a dynamic that I think.
Ai is certainly applicable toall these conversations we're
having and part of it.
If you look at Learning WithoutScars business model of the
training platforms you guys havedeveloped over the last handful
of years, you're really takingthis to a whole new level and
(19:15):
the type of education you canprovide now to dealers and've
always I'm a product of some ofyour early education programs
and you've always provided goodinformation.
But the tools today are evenbetter, more robust, and you can
certainly take a counter person, um and or a service person and
(19:37):
you can move them through thetraining curriculum relatively
quickly or self-paced, but stillvery fast.
And, and you know, dealersshould invest and I well, that's
a plug for your program it'sdealers aren't investing with
anybody to a high degree.
Their training is limited tooem type training or vendor
(20:00):
specific training.
Well, that's all self-servingfor the OEM and vendor.
Yes, you need to know some ofthose nuances, but that's really
not the training I'm talkingabout.
True, you know, down in thetrenches, get your fingers dirty
, type.
Okay, how do you teach thesepeople to sell better when a
customer walks into thedealership?
(20:20):
Welcome to ronsley dealership,right?
How may I help you oh, can youneed parts here?
Let me walk you over to theparts department and so on.
Um, you know it's.
It comes back to you know one ofthe notes I put down for
conventional dealer operations.
You know the strengths.
You know that dealers have is.
(20:42):
You know they have processes,they have OEM support and, in
theory, they have experiencedstaff.
Well, a lot of the experiencedstaff is retiring.
They're older, they're notcoming back.
And how are we training thenewer generation to come into
the dealer world, not only thetechnicians, but everybody else
(21:03):
that plays a critical role.
You know things in the old dayswere reactive.
You know silos betweendepartments, silos, silos are
more prevalent today due to thenoise that comes from all the
data within each silo.
It's maddening in my mind,right.
And you know tribal knowledgeversus scalable systems.
(21:25):
You know I think you need both.
You can't.
Tribal knowledge should neverbe discarded and in scalable
systems or AI and other type ofsystems should not be ignored
either.
You need to bring thesetogether, not one versus the
other.
You know, and you know limitedforecasting or predictive
(21:46):
ability.
You know we're living in an agewhere predictive maintenance is
something we can really do.
Very well, we've been able todo it very well for a long time.
I think we can do it evenbetter now.
Speaker 1 (22:02):
And what's remarkable by picking on maintenance for a
moment, is survey data for thelast 40 years that I've seen and
associated equipmentdistributors that surveys every
five years for the longest timeMaintenance the dealer gets less
than 5% of the maintenancehours.
Yep, and the primary reasonthat is given by the customers
(22:27):
in those surveys is well, theycharge the same thing for a
journeyman mechanic as they dofor a maintenance mechanic.
And so we go to the dealers andsay, well, why the heck do you
do that?
Well, I get more money if I dorepairs.
The customer repaired themachines down.
That's more important thandoing an oil change, really no.
(22:48):
So you know again the modelsthat we're working with.
I used to do the same thing anytime 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 havea cup of coffee with them and
just shoot the breeze.
Know me from Adam and you findout more in 30 minutes talking
(23:14):
to people and walking aroundthrough their shop.
They used to kick me off theproperty after a while because
it became clear who are you?
What are you doing back here.
Well, I'm just, you know, havinga look at what you got
available, how many of thesefields.
I mean, you got a lot of fieldtrucks here.
It's eight o'clock in themorning.
How come they're not outworking Getting organized?
(23:34):
Oh, are they on a customer jobalready?
Oh yeah.
Oh, so you're charging themwhile you're sitting here
getting ready, oh yeah, and theydon't recognize the idiocy that
we're exposing.
You know a standard thing thatused to drive me crazy the OEM
(23:55):
sets the benchmarks ofperformance for your dealership.
Right.
If you want to continue to be adealer, here's the things you
have to do, and one of them isyou have to hold, let's say, 80%
parts availability.
The only part that's importantto the customer is the one you
don't have.
Speaker 2 (24:12):
That's right, and nobody pays attention to how
long it takes to get the backorder here.
Well, and that's where theadvanced analytics that we have
capability to do today reallycan play a big role in improving
the customer experience.
But at the end of the day, ifwe don't have customers, we
(24:34):
don't have a business right, wedon't need employees.
And I'm not saying that youhave to just bend over backwards
and everything the customerdemands they get.
They're not always right, eventhough they are the customer,
but you have to articulate howyou say no, when you say no, and
the why behind saying no andwhat that means.
(24:54):
Right, and I really likeengaging with customers.
So it's not just me over herearmchair quarterbacking.
You know this is me speakingfrom.
You know, real time activities.
And then our last conversationI think it was that one I
mentioned I'd spend one day aweek, the entire day, on the
(25:15):
road either making sales callsby myself or with the sales
person or persons or differentones, you know and I would want
to go see customers thatrecently had purchases large
purchases, medium, small and orangry upset customers.
I want to do a follow-up and alot of times I'd walk in and
(25:35):
they were chewing on me as Ientered the building and, as you
know, we were leaving thebuilding, they were shaking my
hand, saying thank you,Appreciate the time.
You know, and we'll see younext time at the dealership.
And you know that.
You know, and they weren't allthat easy, but a lot of them
were, and it's just really beingwilling to ask the questions.
(25:55):
And when I had people that Irode with, I would, I would talk
to them about, hey, get to knowyour customer.
And where I'm going with thislittle rant is using AI and a
system that has good alignment.
It has limited noise, where theCRM is not noisy, where your
(26:19):
DMS and your business system andthe CRM are aligned.
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 customersatisfaction index score for you
is listed here.
(26:39):
Why did we get a bad rating?
Why did we get a good rating?
You know all those things.
Go out there with that knowledgeand today you can in every
dealer.
You should be able to get thatin real time and you know,
within, let's say, within a weekof it happening.
So real time, five days, youshould be able to go out and see
(27:03):
the customer and you shouldembrace that, and I think that's
one thing.
That and the dealers they'restill not teaching their leaders
.
They fast track people intopositions that are beyond their
skillset to lead.
Next thing, you know, you endup and I'm not opposed to young
people or anybody gettingpromoted.
What I'm simply saying is don'tput people in positions where
(27:26):
they struggle too much and failand because when they're failing
and struggling, they're nottaking care of the rest of the
team because they're trying tosurvive.
And while this podcast iscentered around AI and things
like that, I still in myconsulting and my conversations.
(27:48):
The human element is criticallyimportant and I'm not a fan of
the thought process that AI isgonna replace everybody on the
planet and we're all out of ajob.
Yes, some jobs will bedisplaced, but new jobs will
come in support of all theseother things.
So it's going to come down to amatter of either you learn new
(28:09):
skills or you will get leftbehind.
So that statement I do agreewith, but I don't think it's all
doom and gloom.
So, somebody used the term theother day.
Yeah, it's just going to belike 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 Idon't see it going that
(28:33):
direction either.
Speaker 1 (28:35):
It's the whole nature of business and development and
technology.
At one point in time, anautomotive production line
needed 20 years of use before itbroke even.
Yeah, imagine.
So here we've got.
A couple of weeks ago I waskind of intrigued NVIDIA
announced a new robotic chip andit's $2,900.
(29:00):
But if you buy more than $100,it's 2,900 bucks.
But if you buy more than ahundred, it's 1,900 bucks.
And that got my little headgoing.
Well, darn it.
Every joint on a robot has tohave a chip Correct.
So you probably got a hundred200 chips in a robot.
Now we're back to the productionline of 20 years before it
breaks even.
How much is that robot got tobe displacing replacing in order
(29:24):
to pay for itself?
But everything you're doing andeverything that we're kind of
blaming or using AI as the stick, it's about building
relationships.
It's about getting the customerto trust you, because they
don't know what the heck's goingon either.
(29:46):
They look at you as a savior.
How are you going to do that?
You know it's sitting talkingto those people.
Somebody comes in the frontdoor within 10 seconds.
You better acknowledge them.
Just stick your hand up ifyou're 10 seconds.
You better acknowledge them.
Just stick your hand up ifyou're on the phone and wave at
them, it doesn't matter, it'sbeing people first.
Speaker 2 (30:08):
Well it's going down to.
One of my notes is I wrote AIas the game changer.
Right, it's an operationalprocess.
Right, we still have tointeract with people.
Right, and you can go to marketwith all the different things
predicted maintenance,telematics, ai parts stocking
(30:29):
and dynamic pricing.
Some of those things have beenalready out there for a handful
of years to some degree.
Smart technician scheduling,capacity planning, all those
things you can give.
Everything I just mentionedleads to improved market
intelligence and lead scoring.
(30:50):
So now, when you understandyour market and you're scoring
all the leads, you know which,the probability of success, all
these different things based onall these different factors, now
you're moving your operation atthe same pace as as well faster
, but with the people along forthe ride.
They're not just on thesideline watching it all go by
(31:13):
and then you, then you bring itforward.
Where you use the buzzwordtoday is agentic AI.
So that's just a fancy way ofsaying hey, that's you know, you
building these little agents towork together.
So that's Troy Otmer, againbeing augmented by three or four
different agents running.
(31:34):
In our last podcast, ourreference I was actually in the
middle.
It was running while you and Iwere talking.
It was distilling data based ona very complex, prompt
structure that I wrote, thatwent out there and gathered all
this data.
And now this data is part of apresentation for a project I've
(31:55):
been working on, and you know.
And of course, there'svalidation processes.
But guess what?
You write these agent AIplatforms to help you validate.
Because you read it I read alot too, man.
I have thousands, maybemillions of words, but you know
it's really good.
(32:16):
So what does this do for thehumans?
Well, it enables the leaders,the managers, the technicians,
the part sales, new sales teams.
They can upskill and increasetheir throughput because, ron,
if you want more output, youneed better throughput
capabilities.
Right, you know, and we can godown the rabbit hole of Six
Sigma lean process management,all that rabbit hole of Six
(32:41):
Sigma lean process management,all that you know.
But at the end of the day, youwant more output.
You got to have improvedthroughput and you got to quiet
the noise, and you know.
And you want your employees toengage your customers better and
you got to give them the bettertools to do that and you got to
train them, you got to leadthem.
And you have a saying JohnDowling mentioned it the other
day when he was presenting.
He said you know, ron says wemanage processes, we lead people
(33:07):
, and I wholeheartedly supportthat and you know.
So he was out there quoting you, by the way.
Speaker 1 (33:16):
I pay him a lot of money for that.
Speaker 2 (33:18):
I know that's a good point.
Speaker 1 (33:22):
No, but the thing that you're exposing again it
goes back and I mentioned it.
We've got to know to deliver toyou information not data,
information Correct that youcould translate into action.
(33:45):
Yes, and training is importantand something that we have been
terrible at in the 90s is whenit really became prominent.
In the 90s, almost everybodyAED Caterpillar.
Everybody stopped trainingbecause it was too expensive and
(34:06):
that's when we started it.
I sat in front of the computerand I talked for the summer and
created eight textbooks, 250pages each, and in those days I
could talk for 30 minutes andI'd leave the computer and it
would take them an hour and ahalf to catch up with me with
voice recognition stuff.
Today it's instantaneous.
I pick up another piece ofsoftware a couple of three years
(34:31):
ago that it was limited to 5000words in a product.
It was an audio track type ofproduct that created subtitles.
At the same time, last week itbecame 20,000 words.
Well, all of a sudden you canbe talking about books.
Speaker 2 (34:52):
Yeah.
Speaker 1 (34:53):
So I can have, I can turn around and I can take an
audio book and I can run thatthrough the computer with voice
recognition and turn it into myown document that I can then put
through Copilot and make itmore casual or make it more
formal or make it sexier orwhatever.
It's all kinds of differentthings, right?
(35:13):
The problem that I see withartificial intelligence which,
by the way, was first introducedto the world in 1950, is that
and I mentioned it earlier wehave to learn how to ask
(35:33):
questions and as you're evolving, you're finding better ways to
ask those questions to get theanswer you're looking for.
And you do it by makingmistakes.
Yep, yeah, I have to go.
Oh, that's no good.
So just imagine that I can takethe dollar value of a
transaction and the time betweenthe transactions, so I can say
(35:54):
transactions once a week, onceevery two weeks, once a month,
once a quarter, and dollarvalues of 50 bucks, 500 bucks,
5,000 bucks, and I can build agrid for every customer, for
every dealership, right?
And if that buying patternchanges, I want the customer
(36:16):
names delivered to the personthe next morning.
So the day it changes within 24hours.
You missed a day, you missed adollar 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 alittle bit of a difference on
(36:36):
your account.
Is something going on in thecompany at the moment?
And what I'm trying to conveyto the customer and how I
communicate, that is I care, I'mhere to help you.
What do you need from me rightnow?
Is something going on I canhelp you with, and it's a
completely different sales gig,isn't it?
Speaker 2 (36:57):
Oh yeah, well, Ron, it comes down to dealers
oftentimes that they they comeup 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
(37:17):
inaccurate.
Yes, your job is to take careof your customer, your installed
base, the people you're sellingproduct to, newport, et cetera.
And yes, you have to run yourbusiness in a profitable manner.
Enough on reducing theirdowntime and or, and like we
(37:38):
said earlier, customers don'tuse the dealer maintenance
services because they're sendingout a level five tech at the
highest rate when you should beusing a level one or two or
journeyman or what have you, ata different rate.
You know, I, you know, I hadthat philosophy when you and I
first met many years ago and Ifollowed that same thought
(37:59):
process by adapting, you know,to those market needs from a
maintenance side.
And look, I made more money atthe end of the day for the
dealer groups I've representedby focusing on driving high
levels of maintenance and havingtechnicians working, and
(38:21):
occasionally you would have ahigh-end tech on a project, for
whatever reason it happens, butthe goal was never to have those
people on changing oil andfilters or basic maintenance
right, and you know, and I putthem 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 inthe field, I don't want to see
them in the shop, let's go tothe customer.
So you know, field service.
(38:42):
You know, I don't want mytrucks coming into the shop
every morning at 8 o'clock to bedispatched.
No, they're mobile, they candispatch from home and they go
straight and we'll run parts tothem.
You know, and all thosedifferent things.
So I mean dealers shouldn'tjust focus on hey, we need to
(39:02):
sell labor or we need to sellparts.
No, you need to reduce yourcustomer downtime.
You need to improve thatexperience.
You need to improve your firsttime fixed rate.
Uh, you know, so it's now.
You don't have to go out threetimes to fix a problem.
You do it the first time, youknow.
And then you know, targettargeted sales wins every time.
(39:23):
You know, have a plan, executeyour plan Right, you know.
And then, with, with AI and youcan, you can validate the ROI,
like you were mentioning.
Hey, within within a day'snotice, or within that same day,
from the morning to the eveningyou can say hey, what happened
to your business today?
You're trending down and yousee that in real time.
(39:44):
So, and look, if you get thatanswer in one to two hours,
that's real time, right, youknow, versus, I'll get an update
on Monday morning and it'sTuesday now, but next Monday
morning I'll have an update.
You can't run your businesseffectively Tuesday now, but
next Monday morning I'll have anupdate.
You can't run your businesseffectively and that's why, you
know, we had to be creative byand creating queries to mimic
(40:08):
what AI can do for us veryeasily today, and there's a lot
of hard efforts behind thescenes.
But you know, to me, this AIadoption is a leadership
opportunity.
And I say leadership I'm notjust talking about your general
manager, parts and servicemanagers, et cetera.
I'm talking about dealerprincipals or ownership groups,
(40:29):
private equity included, and Iknow PE and others like them.
They have a different mode ofoperation and profit before
people does happen and whilethey're not publicly traded,
they're very similar into, youknow, focusing on shareholder
value, and it's easy to keep theshareholder in front of the
(40:49):
customer because, remember,shareholders, you have no value
if you have no customers.
Speaker 1 (40:55):
I used to have fun using, you know, customer
retention as a tool.
Harvard, in the 80s, made thecomment that customer retention
was the single most importantthing to drive profit.
So then you know, in yourthinking and mine relative to
maintenance, I'd sit down with agroup of people at the
(41:16):
dealership and say you know howmany hours does it take?
I got 2000 hours on my machineevery year.
How many hours should I bespending on maintenance?
And we'd look at it in thosedays 250, 500, 1500, blah, blah,
blah.
And we come back with a numberthat was 40 to 50.
To make this arithmetic easy,let's use 50.
Speaker 2 (41:35):
Right.
Speaker 1 (41:36):
And then I'd say to them well, what, what's your
working machine population outthere?
What do you think it is?
They don't know, which is a bigproblem, but well, 5,000
machines.
Okay, how many people does thatmean there's doing maintenance
(42:06):
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 83are working with?
Or 93 are working with?
Oh well, wait a second.
How much do we make in incomeon 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 throughanother, that's $100, so I
charge $50 for maintenance, 50hours times 50, that's $2,500.
And that much parts, that's$5,000.
So $5,000 per machine formaintenance, and instead of $93,
(42:27):
let's just say it's $100.
How much business have you lost.
Speaker 2 (42:33):
Yeah.
Speaker 1 (42:35):
And so you know one of my favorite little things to
do.
I always checked it first, butI'd go out into the shop and
look at the machines that are inthe shop and find how many of
them had competitive filters.
Oil filters, no others, justthe oil filter.
And in many cases it's a bignumber 60, 70, 80% of the
machines in the shop have acompetitive filter.
(42:55):
I said are you going to doanything about that?
Well, what do you mean?
Well, that guy's got acompetitive filter.
I said are you going to doanything about that?
Well, what do you mean?
Well, that guy's got acompetitive filter on this
machine.
Don't you want to get him touse your stuff?
Yeah, but our filter is reallyexpensive.
I said fine, put it on fornothing.
Call him up and say do you mindif I change your engine oil
(43:15):
filter?
I'm going to put one of mine oninstead of yours.
I'm not going to charge you forit.
Oh, that's okay, why do youwant to do that?
And then I can start talkingabout the features and benefits.
I can talk about what happens.
What is it?
You know, particulates.
And here we go, and all of asudden the guy is by the way.
Who chooses that filter?
The guy that does mymaintenance.
Do you tell him what filter touse?
(43:36):
No, he picks his own.
Wait a second.
This whole thing's upside down,yes, and it's been that way
forever.
Here comes artificialintelligence, and I'm going to
use that as an excuse now, causeI'm going to know I got 5,000
machines out there and they'reaveraging 2000 hours.
That's eight of these filtersevery machine every year.
(43:58):
That's 40,.
Eight of these filters everymachine every year.
That's 40 000 of those filtersI should sell.
I only sold 372, right, what'sgoing on here?
And I can do that for hose, Ican do it for batteries, I can
do it for undercarriage, I cando tips, I can do it with darn
near everything because of aicorrect, it was hard before and
(44:19):
you and I've done it beforemanually.
It's a bear, it is.
But if you want to do thebusiness properly, you got to
use it, and that's why I sayit's a bit of an, it's an
opportunity, it's an excuse.
Let's get looking at thebusiness differently.
Speaker 2 (44:35):
Well, it's one thing you said and I know we're
getting close to time, I believebut in closing, you know, not
understanding what your OEMinstalled base is in your market
is a problem, and the secondpart of that problem is not
understanding what yourcompetition's installed base is
(44:57):
in your respective market isalso a problem.
And, in closing, what I wouldsay to that would be real simple
you need to know what theentire machine population looks
like.
Now you may not be able to gochase all of it because it's OEM
specific warranty, blah, blah,blah specific warranty blah blah
(45:21):
, blah.
But make no mistake, a lot ofthe maintenance that a dealer
can do will be on non-oemspecific product.
And that's how you transition acustomer to your oem product at
some point down the road bygoing out and showing them, hey,
how well you take if you're acat dealer, how well you take
care of their john deereequipment, and when it's time to
trade them out, boom, you tradethem out, they roll them into a
(45:42):
cat or vice versa.
And you know some of the secondtier type products that came
along, like hyundai, etc.
They've made a lot of marketshare gains against cat john
deere, volvo, kamatsu by playingthat game and you know saying,
hey, we're going to be what'sour, we can't go get them
head-to-head.
So how can we gain market shareand or wallet share on them?
Speaker 1 (46:04):
And that's just some of the methods to do that.
Yeah, and the interesting thingis there's tools out there
Equipment Data Associates, edaany machine that's financed.
There's a report.
I can buy it, I can do it bycounty, 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?
(46:25):
The first thing that comes backat me when I ask that question
is well, it's hard because theyput the name in differently than
we have it in our profile.
Uh, okay, so technology has tocome into play here.
But but there's a whole host ofthings and it leads the
discussion into a differentplace.
Underneath this, I'm askingabout AI, and there's lots of
(46:50):
iterations, there's lots ofthings to consider, but it's not
really AI at all.
It's about doing the businesswell.
Correct.
And your comment about sellingto john deere replacing a john
deere machine and here comeshyundai, and hyundai's done a
particularly good job at it, andit's because of their
experience in the car business,correct?
(47:12):
And who was the first one to dothat?
Toyota, yep, toyota createdLexus.
The top of the Toyota brandline is Camry.
The most expensive.
Camry is the cheapest Lexus andeverywhere we do it's the same
thing and they learned thatlesson.
(47:33):
Well, we didn't learn that.
Speaker 2 (47:38):
Well, funny story on Hyundai.
When, as a young tech in the80s, when Hyundai came to the
market, obviously Toyota andHonda, you know, had a good
reputation, good quality product, you know, and I was fairly new
, so guess, what I got to workon was Hyundai and and I thought
that was going to be a curse.
Well, I've, really, I'verealized very quickly that this
(48:01):
is a quality product and it'seasier to work on than the
American counterpart and I'mlike, wow, this is interesting
and to see them continue toprogress the way they have.
They pay attention to whatmakes their customers happy and
(48:21):
their maintenance and support.
And then you know the spinofflines that come from it, their
luxury line, you know, hyundaigot one of the premier luxury
lines.
Now, same thing Quality of theproduct, right.
Speaker 1 (48:34):
What's the luxury line called from Hyundai?
Speaker 2 (48:37):
It is Genesis.
Speaker 1 (48:39):
Yep.
Speaker 2 (48:40):
Yeah.
Speaker 1 (48:40):
I had a Genesis that I bought in California and
shipped here and the dealer wasgoing to have to pay for it the
next week.
So I got a pretty good deal andat that time Genesis had two
products.
Today they've got six, and theprice differential to Lexus,
(49:03):
cadillac, all of the premierlines, was $40,000.
Yep, and if anybody is going tothrow away 40 grand just to
have an ornament on your car,then you know I'm Scottish for a
(49:23):
reason.
But you know this takes us downanother path, troy, that I
think we need to have anotherone down the way, but it won't
be AI driven anymore, it'll bethe analytics, yes, yeah anymore
, it'll be the analytics.
Speaker 2 (49:39):
Yes, yeah, and analytics.
You know, ron, we're going tohave to train people to
understand analytics and notover complicate it either.
Right, that's part of it.
Speaker 1 (49:51):
I'm almost in a place that we can't train them on
analytics.
We have to give them theanalytics and tell them how to
use the tool.
Speaker 2 (49:59):
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 optimisticabout a handful of folks I'm
working with that I think havethe capability to learn it.
But for the vast majority ofpeople you're probably right,
it's a plug and play Plug it inand play.
Speaker 1 (50:23):
Well, yeah, I agree with you 100%.
One of the things that'sinteresting the other day I had
a chat with somebody who runsone of the dealer management
systems businesses and they'rehaving a hard time getting
people, as everybody is.
And I said, well, you knowevery install that you get to.
Why don't you make a deal withyour customer that you're going
to take George and Mary for ayear on your payroll and you're
going to have them go out and docustomer service for you and
(50:45):
installs for you and expandtheir knowledge and
understanding of your system?
You're going to pay for themand 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 companyasset for your company.
And it's kind of putting on theear like, if I'm if I'm a
dealer, maybe I want to providethem.
If they've got their ownmechanics, maybe I want to give
(51:06):
them a mechanic and I'll takeone of theirs.
Yeah, right, ultimately, comeback and say, well, why the heck
do we want to have thatmechanic on your payroll?
And if you really want to getnasty, I won't pay an equipment
salesman any commission for asale when he replaces the same
brand that I'm representing.
I'll pay him a lot of money ifhe replaces a competitive brand,
because if you look at thedealers, they're in their 30%
(51:30):
hole and they stay there.
You're right, yep, and mygoodness, it's so easy.
John Deere and Caterpillar havebetween 70 and 80% of the
markets here on equipment.
Volvo, camacho and everybodyelse is fighting for the other
20 or 30.
Right, that's.
That's like standing at thebeginning of a race knowing
you're going to lose.
Speaker 2 (51:59):
I've never looked at being a John Deere dealer
predominantly the cat dealeralways had us 10 to 1 in terms
of size in almost every market.
But that to me, was not anegative.
It was an opportunity to exposetheir weaknesses.
And look, cat dealers are verystrong, but every dealer, no
matter how good you are, how toptier your OEM is, there are
(52:22):
weaknesses that can be exploited.
And that's where data analyticswill come in to help you open
up and kind of peek behind thecurtain of what the market truly
looks like and where there'sopportunity.
And for a dealer to besuccessful at any dealer large,
small, medium, everything inbetween they have to be willing
(52:44):
to take a look in the mirror andutilize the AI or data
analytics dashboards.
What have you to?
You know, have that bit ofreflection.
And you know, let's start nowor are you going to get left
behind, right?
You know, let's start now orare you going to get left behind
, right?
And if you want to grow yourbusiness, you know, if it's a
multi-generational business, youknow they usually when they hit
(53:07):
the fourth generation, they'reprobably 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 changethat.
That's paradigm shift.
Let's get busy and, you know,let's augment our workforce with
the best tools we can give themtoday.
Speaker 1 (53:26):
Let's wrap this this way In Canada, when I started at
the dealership, there were 10dealers.
Today there's two.
Yep In the United States, whenI started with the Caterpillar
family, there were 50 dealers.
Their goal today is to be under20.
And part of that is because ofthe cost of the equipment, the
money that's required to operatethese dealerships.
(53:46):
Same thing's true with JohnDeere.
Rush is one of the largest inthe country.
You know, rdo up north is thesame thing, branton, canada,
it's the whole country.
So all of these dynamics havechanged and analytics is going
to get us there.
But it's going back to basics,troy.
Yeah, it's very fundamentalthings.
(54:07):
You need a part.
I have the part, I don't havethe part.
Oh, the guy at the counter.
How much is that?
Filter 15 bucks, boy, that'sexpensive.
Then the guy at the counterdoesn't know what to say.
Filter 15 bucks, boy, that'sexpensive.
Then the guy at the counterdoesn't know what to say.
So we have a lot of work aheadof us and you're going to have a
lot of fun.
You got 20 years on me now,buddy, you better be looking
(54:28):
after it properly.
So you know, troy, thanks foryour time and fellas and people
out there listening to us.
I hope that our goal with thesepodcasts is to get you thinking
, and I hope we succeeded atdoing that and I look forward to
having you with us at anotherpodcast, another kind of
conversation, in the near future, mahalo.
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