August 31, 2023 • 37 mins
In the latest episode of the Modern Car Wash podcast, co-hosts Kevin Zalaznik and Shane Groff are joined by FasterLines Founder & CEO Rob Meng.
FasterLines is assisting car wash operators by harnessing technology to decode the challenges customers encounter in queues. Join us as Rob delves into the realm of speed, convenience, and service, and how they are connected in the car wash experience.
Rob also provides insights into enhancing operational efficiency in your wash and how to save time and resources without compromising quality.
This episode is your backstage pass to the intersection of innovation and efficiency.
🚀 Don't forget to subscribe and keep an ear out for more captivating car wash conversations on our podcast.Â
Follow us on Instagram
Follow us on YouTube
Our Products
innovateITCarwash.com
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Kevin Zalaznik (00:10):
Hey everyone.
Welcome to the Modern Car WashPodcast.
I'm your host, Kevin Leszek,joining with my guest.
Host, co-host Shane Groff.
Shane, how are you?
Shane's usually, uh, in theoffice with me, but, uh, Shane,
are you in vacation?
What's going on there?
Oh, I'm in my office at homeright now.
(00:31):
Yeah.
So for those who are watchingthe video stream of this, Shane
is surrounded by, uh, I wouldcall it wood paneling, but I
think it's actually wood pine,individual pieces of wood.
Uh, Can you confirm or denythat?
Yeah.
Rob Meng (00:47):
Yeah.
It's just going.
Uh, Berg.
Kevin Zalaznik (00:51):
Our guest today is Rob Lang from Faster Lines.
Rob, welcome.
Rob Meng (00:56):
Hey guys.
Uh, pleasure to be here.
Excited to, uh, talk about carshoot you guys today.
Yeah, so
Kevin Zalaznik (01:03):
our whole, I guess our whole spiel or stick
is that, you know, it's verymodern, it's very technology
first, very, uh, uh, Progressivein the thinking of how car wash
is, are advancing and uh, fasterlines.
Seems like it's one of thesecompanies kind of there on the
forefront.
Can you give us some background,uh, on you, uh, and also what is
(01:26):
faster lines?
Rob Meng (01:27):
Yeah, you bet.
So, uh, first it, it actuallystarts with my dad.
I've been getting my feet wetand car washes since pretty much
I could walk.
My dad started working forHannah Car Wash way back in the
day, one of the original.
Multi-location car washcompanies up in Portland,
Oregon.
Um, and, uh, he, he actually wasmanaging a car wash by the time
(01:48):
he was 16 years old, which ispretty cool.
And, uh, so my, a lot of my carwash theory came, uh, rubbed off
on me, my dad, um, I spent a lotof time with car washes, but
then also selling technology.
Um, and learning about, uh,small improvements, making a
huge impact, uh, in like the,um, call center space.
(02:10):
Uh, then about 15 years ago, wewere sitting in line at an auto
Bell car wash in Raleigh, NorthCarolina, and the line wasn't
moving.
We were just sitting there likedying in line, waiting to get
her car washed.
And my wife looked at me andsaid, you know, the manager
should know that this ishappening.
Like this is.
And somebody should be able totell'em that this is happening.
And I was like, oh yeah,somebody should be able to tell
(02:33):
'em that the line's not moving.
That's a good idea.
Uh, I ended up talking to theowners of Auto Bell, uh, which,
uh, auto Bell's Great.
They're a third generationfamily owned business.
Taught to Chuck and Carl Howard.
And said, do you know you havethis issue where the cars don't
move into the conveyor and, andjust get stuck and, and
customers are just waiting inline.
(02:53):
And they said, we do know wehave that problem.
And I said, do you know how badthe problem is?
And they're like, no.
And I said, do you wanna knowhow bad the co the problem is?
'cause some people don't want toknow.
And luckily, uh, autobill ISS agreat organization.
They're really focused onquality process.
And so they said they wereinterested and we worked
together to figure out how tokeep track of those cars and.
Tell people when the line wasn'tmoving and that ended up helping
(03:15):
their managers understand whereto put people and how to get
people and, and move in cars.
And they wash a lot more carsnow because of that.
So we've been doing it for 14years and uh, it's been great.
They're still a customer and westill help'em watch the line.
Kevin Zalaznik (03:30):
What's crazy when you think about it is, I
mean, that was 14, 15 years ago,and you think of the, the sense
of urgency is only increased.
And I'll give you the, I was inTarget the other day and.
I always do self-checkout.
I, I think it's the mostofficial way to do it.
So I get in line and there'sfour kiosks.
Uh, two of them are not working.
(03:53):
Uh, there's a woman at the far,the far one, and she had the
call, the help button threetimes.
Uh, the woman closest to me, sothe other working kiosk, she had
issues.
So she had to call the helpbutton and the whole time the
lines backed up and, um, Youknow, I, I understand this is
targeted.
(04:13):
It's, it's, uh, uh, you know,people were, I, I don't know how
much business they're losing onthis, but, uh, I certainly was,
I was frustrated.
It was annoying.
And it's just the world we livein, like we want fast processes.
Um, so it completely makessense.
(04:33):
And I think in the car washindustry, when you look at it,
It's very much, there's probablymore competition, uh, involved
in, in
Rob Meng (04:42):
customer satisfaction.
And,
Kevin Zalaznik (04:44):
um, so I'm curious, when you, when you were
able to, when you went to, um,to Autobell and you said, Hey,
do you want to know what effectthis is having on it?
How are they able to, to improvetheir process?
And, and what, what were the, Iguess what were the key
performance indexes that youlooked at that said, Hey, this
(05:04):
is
Rob Meng (05:04):
working.
Yeah, so we looked originally,we, first of all, we did a lot
of status quo.
We developed the solution first.
Uh, we tried to use laser andradar and, uh, a bunch of
different ways of tracking thevehicle.
Um, the problem with all thoseissues was it was a single
point.
And, and, you know, with the carwash, the car's never in the
(05:25):
same place, right?
They never stop in the samespot.
And so we realized that we hadto do video and, and have an
analog shot where we can seemultiple cars.
So we measure multiple cars.
Um, for most of our customers,we're really focused on the cars
that are not on the correlatoryet.
So, so not the cars that arebeing prepped or, or, you know,
already on the conveyor, butthose cars that are waiting in
(05:47):
line.
And that's really importantbecause we're not looking at the
car that's being served.
We're wa wait looking at thosecustomers who are waiting to be
served, and those are the oneswho are waiting to be waved at
and smiled at and moved forward.
Um, and so at first when westarted measuring based on the,
the timeframes that Autobellgave us, Um, they were not
(06:07):
meeting their time standards 40%of the time.
Uh, and so that's a lot of carsjust sitting, not moving.
Um, within months ofidentifying, telling the team
about it, knowing that they'rebeing measured that way, we were
able to get a lot of theirlocations down into the teens.
(06:27):
Um, 14 years later, we'vereduced their time standard
eight different times.
Each time there's a bump in, youknow, number of alerts and
number of delays, but then theydrive again back down toward
that time standard and keepmoving the line.
Um, so it's, it's, we movethousands of additional cars
through the line Now because ofthe time standard and because of
(06:49):
pushing and we even did theexperiment a while, you know, in
after a couple of years and.
Um, we wanted to know, didpeople learn, right?
Or, or did, did you need thesystem still on or did people
get it?
And, and, and understand.
And so Carl and I talked aboutit and we actually, we turned
the system off.
(07:10):
We had a, we had a softwareupdate we were doing, and we
turned the system off, whichmeant that we just quit telling
the team about the data and wekept collecting the data.
And it was about a week later,Carl called me, he's like, turn
it back on.
So all of'em went back.
Because it's just hard.
It's such a focal part.
It's a, it's a human process.
It's a human dynamic, whetheryou have auto rollers up, um,
(07:33):
whether you gotta punch abutton, whether you're prepping
or not prepping, there's a partof it that's always human.
And that big part of it isacknowledging the customer,
waving them up and getting themto pull forward.
And if your team's not focusedon that, the car just sits
there.
And whether it's an extra twoseconds, whether it's an extra
10 seconds.
I mean, if you're talking about10 seconds during, during the
(07:55):
day, you're an exterior onlywash and you're trying to wash
120 cars an hour every time thatcar sits for 10 seconds, that's
a third of a car.
That happens a couple of timesin an hour.
And now you've got six cars,seven cars, 10 cars extra that
you could have washed if youjust pulled people forward and,
and, you know, kept that linemoving.
Yeah.
Hey, it's interesting
Kevin Zalaznik (08:15):
in the, um, You said like 10 seconds, a third of
a car or whatever it is, is, um,you know, data is data's great
if you know what to do with it.
Um, right.
And you can have all the data inthe world if you don't know what
to do with it.
So it sounds like really it wasmore, there was an
accountability aspect to it.
Um, you know, here's a metric,let's try and hit it and let's
(08:38):
go and get it.
So, uh, Shane was, uh, he wastelling the story.
You know, McDonald's hassomething very similar to this
Rob Meng (08:46):
where, uh, and I'm sure you're aware,
Kevin Zalaznik (08:48):
you know, the, it comes up on the, on the
screen and the employee, as theorder's filled, they, they mark
it off and it's way of, uh, justkeeping track of it.
Well, it's all, it's all fine,but when the employee.
Knocks it off just to get offthe board.
They're kind of gaming thesystem.
(09:09):
Um, and I think we've seen thisin other industries as well.
Uh, but it sounds like, um, kindof your system and how you have
it set up, it's more, there's nogaming.
You're, you're actually readingthe vehicle.
Rob Meng (09:22):
Yep.
Well, yeah, it's, it's about themultiple vehicles.
If you're just looking at onethat the employees can figure
out where we're measuring and,and try and move the car, keep
the car further back, which iseven worse, right?
You want as close spacing aspossible.
So it's about making sure thatyou're measuring multiple cars
so that there isn't a way togame.
Gaming's good.
It's just human dynamic.
It's just trying to, it's tryingto get, uh, you know, do
(09:44):
positive with how you're beingmeasured.
Um, and, and, but we, yeah,we've definitely figured out how
to operationalize the data, helpthe team know how they're being
measured, and then keep'em fromtricking the system.
So that, and with car wash, it'sgreat because the answer is, is
it on the conveyor?
Not, is the car moving throughthe car was or not?
But it's really difficult to,you know, it's not like, uh,
(10:04):
drive through restaurants whereyou can have a pull forward and
then bring that bag out.
I.
It's either in the car washtunnel getting washed or it's
not.
So it's, it's pretty clear inthe car wash
Kevin Zalaznik (10:12):
area.
What do you think the biggestchallenges that operators face
as far as keeping the linemoving?
Rob Meng (10:18):
Yeah, so there's two, um, one, uh, is we found that
there's this kind of magic timearound 90 minutes where
employees start to kind of fadeoff.
It's, it's a, it's a repeatingprocess, right?
It's over and over again.
You're washing cars, you'removing cars forward, you're
acknowledging your greeting.
Somewhere around 90 minutes,even the best employee starts to
(10:40):
lose that, you know, that thatverve, that that excitement.
Um, and so it's really importantto start to transition people
into other places, moving themup, you know, to, to sales.
Moving up to greeting.
I.
Uh, giving them a break and, andthen getting them dialed in.
So that's the first thing.
Um, the second thing is, is thatthere's a lot of focus on sales,
right?
(11:01):
And, and monthly passes.
And we've helped a lot of ourclients figure out how to do
that offline.
Um, not stop the entire process,stop the entire line for a
minute or two while you'reprocessing that monthly pass
member, but get them through thewash and actually process that
monthly pass on the other end ofthe car wash.
(11:21):
Uh, in the vacuum area or in aspecific area that, that you
have for monthly past members?
Um, so those are two of the bigones that we see as huge delays.
And we had, we, we have a clientthat was telling us, well, we
need to go to like 90 secondsfor their sales area.
'cause we measure sales area.
We also measure the entranceinto the car wash tunnel.
We're like, no, don't do that.
(11:41):
'cause you, there's a magicthing that happens at 60 seconds
with customers if they sit therewithout moving for 60 seconds.
Only like three bad things canhappen.
Uh, no good things can happen.
Only three bad things.
The first bad thing is, um, theystart doing fuzzy math and they
start looking and they're like,I'm gonna be here forever.
(12:02):
There's 10 cars in line.
It's gonna take me an hour.
No, it's not gonna take an hour.
It's gonna take like sixminutes.
Like, but that's not what theirperception is.
So you start to have a negativeperception.
Number two, maybe even worse,they pick up their cell phone
and they start looking at it.
If they do that, then they'renot paying attention and they're
gonna, it's gonna screw up yourflow and, and things just slow
(12:22):
down.
And the last bad thing is theyfigure out how to get outta line
and they leave.
And that's, that, that's, 60seconds is a really magical
time.
And so it's really important,whether they're in the sales
area or whether they're, youknow, getting ready to go into
the car wash tunnel, that theydon't have that opportunity to
sit there.
And no car wash operator wantsthat anyways.
(12:43):
If they're sitting there for 60seconds, the best you can do is
60 cars an hour, right?
You, you want, almost every carwash wants to be loaded.
The conveyor faster than that.
And so that's something that wereally focus on.
That's something that we helpoperationalize with the team.
And again, it's about us helpingserve the data as a service to
the team so that they knowwhat's going on so that, that
(13:05):
they can take that data and helpserve their customer that much
faster.
And.
When you really focus on thepeople, you don't use it as a,
you know, character sticker.
It's, it's really about helpingthe team know.
And once the team knows theywant to do something about it,
'cause they know the expectationis to move the line and, and it
makes a huge impact.
Not only that, but it's that,that extra money, that's the
(13:25):
gravy, right?
The site's already paid for, thepower's already paid for.
The water's already paid for.
You got a little bit of soap,the employee's already there.
You, you pack those extra TEDcustomers into an hour.
It, it's, it that's, that's ahuge amount of the actual
profitability of the site.
That, that, that's, that's whywe think it's so exciting.
'cause it, it really adds tothat extra top line that, that
(13:48):
good number.
Kevin Zalaznik (13:49):
Rob, do you, do you think there's a, um, maybe
like a tipping point foroperators in your experience
where they're like, you knowwhat, we need to need to take
this serious.
Like, we really need to start
Rob Meng (14:00):
looking at this.
It's so funny.
Um, we just helped serve a, a, aclient fast track car wash out
in Eugene, Oregon.
They have two sites they've beenoperating for more than 10
years.
They've got a great generalmanager, Ivan, who's out there.
He is fantastic.
Um, but they were really stuckand constantly the owners and
Ivan were arguing about how manycars can they wash an hour?
(14:20):
Right?
And it's an exterior only wash.
They were averaging about 52seconds between cars.
So they, they were hardly evergetting the 60 cars an hour.
Um, and we sat down, we lookedat'em.
Their, their, their wash is setup right.
Their chemical's good.
The only thing they weren'tdoing is they were prepping the
entire car before they sent thedang car.
And so all we talked about wasjust getting through the
(14:43):
driver's door and hitting thebutton so that the car starts
moving, finishing prep while thecar's rolling.
And now all of a sudden thoseguys are washing 80, 90 cars an
hour, and it's just that littlething.
Then the next thing they had tostart working on was getting
their guys' head from preppingand looking at the car to
smiling, waving, and pullingthat next customer forward.
And so those two little thingsmake all the difference, right?
(15:05):
The line starts moving and nowall of a sudden, so the 60 cars
an hour or 50 cars an hour,you're washing 70, 80 cars an
hour and, and it's a hugeimprovement, and it's not just
the numbers.
It's convenience.
Speed is convenience, andconvenience is customer service,
and customer service is customersatisfaction, and we know that
(15:27):
they're turning over more ofthose customers into monthly
past members because.
The customer's feeling thatspeed, they're feeling that
convenience.
And so they're gonna come backmore often.
They're gonna end up buying thatmonthly pass.
And, and then all the stuffShane was talking about, about
that monthly pass member now isa part of your organization.
They're part of your team.
They, they understand theprocess.
They understand they're notgonna pick their cell phone up,
(15:47):
they're paying attention'causethey know you're a high
performance organization andthey were, they're there to
quickly get their car washed andmove on so that the other
customers can quickly get theircar washed and move on.
So it's all recursive, it's allgood stuff.
Kevin Zalaznik (16:01):
Is there a way to, to leverage technology, your
technology or something similarto it as far as labor management
and, um, what, what's that looklike?
Rob Meng (16:12):
Yeah, so that's, that's one of the interesting
things, right?
So, uh, back to Auto Bell.
Autobell used to staffThursdays, like they were slow
day, right?
Wednesday, Thursdays were kindof their middle of the week kind
of slow.
And we started watching theline.
We started watching thesedelays.
Well, they were slow.
Because they didn't have anystaff.
They didn't have anybody moving.
(16:32):
They didn't have any focus.
And so as soon as we identifiedthat there was delays in line on
Thursdays, there was customerswho were in line but wanted to
be served.
They changed their staffing,their scheduling, so that
Thursdays were like Fridays.
And guess what?
They washed a bunch more cars.
Their customers were there, theyjust didn't know.
And whether you're a carwash ora drive through, that's one of
(16:53):
the traditional challenges,right?
You know, and you can plan, andyou can train and you can
schedule based on what you did,what you sold, but you don't
really know what the opportunitywas.
And so if you're looking back atlast year in August, and the
weather's the same, right?
You go, oh, well we washed, youknow, 50 cars that hour, but you
had 60 or 70 cars that werethere that wanted to get washed.
(17:15):
You
just didn't move them through the line.
And so when we start to actuallyidentify delay, we match that up
with scheduling.
And we start to turn up thatknob, that knob, right?
You, the, the operator, theowner, the, the management team
starts to understand, oh, we caninvest for another greeter.
We can invest for another prep.
We can invest somebody else outthere to help move the line,
(17:36):
because if we invest that extraperson, we're gonna wash 10 more
cars.
And so that hour, it makes senseto put that person out there.
Vice versa.
We had a customer, it wasactually a drive through
customer that was out in Omaha,Nebraska.
And they were doing breakfastand they started breakfast at
eight and, and we did the math.
They weren't serving anycustomers breakfast.
(17:58):
They had this whole team thereto do breakfast and, and they
just had this minuscule numberof customers they were serving.
And so we did the vice theopposite.
They could invest those hoursinto their busy lunch and
dinnertime and quit wasting manhours on, on a time that they're
not busy.
So both of those end up.
Feeding into the scheduleschedule's a huge impact for
what we do.
And then training and thenprocess improvement after that.
(18:21):
And, and those are kind of thethree steps to, to really
dialing it in, um, and gettingthe most out of, of that
location, that district, thatregion and, and driving it
forward
Kevin Zalaznik (18:31):
seems like, um, you know, when I look at.
Some of these, some technologycompanies that have come into
the car wash industry.
And I think a lot of it is, youknow, uh, entrepreneurs, venture
capitalists, you know, put theirfinger in there and they're
like, oh, car wash, look out.
Like this industry is growing,but you've actually, you've been
(18:52):
in it for quite some time.
You've, you've kind of therecent boom.
Um, have you found otherapplications though, or other
industries that, uh, That aresimilar, um, uh, where that, you
know, things
Rob Meng (19:07):
like this apply.
Yeah, so we actually startedwatching people about six years
ago.
Uh, and so we have moved intorestaurant hospitality, oil
change.
Um, so we're seeing all those,but really it all comes back to
car wash.
Car wash gave us a really uniqueopportunity, um, the, the
restaurant industry and, andlike we talked about McDonald's
(19:28):
and their little board on thewall that shows time.
They're all, they were allfocused on a time from order to
delivery.
And this total time of service,which is, is really difficult
for employees to understand.
We do it differently, and westarted with carwash and so it
made sense.
We broke it down to for flow,and we were looking for how many
opportunities there were for thecar to move forward, and how
(19:49):
many times the car had to moveand how far that had to move in
order to get your flow and getyour, get your line moving
correctly.
And so instead of this like 300seconds of total time of
service, which is difficult foran employee to understand, we
talk about this delay metricwhere if a car sits for too long
beyond our time standard, it it,we've missed an opportunity.
(20:11):
And that delay metric is areally much easier operational
point to manage employees to.
We talked to a bunch ofStarbucks employees and
McDonald's employees and allover the place with these timers
that were on the wall.
And you'd go, what is that?
And they'd go, I don't know.
That's something my managerdeals with.
That's something my districtmanager
deals
with.
You'd be like, what's 256seconds?
(20:32):
I have no idea.
I don't even know what thatmeans, like, right.
But when you have, we actuallyput a a, a 10 inch screen up,
you know, at the entrance intothe car wash tunnel, and it
tells you how many times therewas delays.
And delays turn into missedcars.
And it's just a clear, reallyeasy number for them to
understand.
We change the color so that theycan see it, but as you look and
(20:54):
you're like, oh, I've had 10delays in the last hour, that
means I, I missed three cars.
I could've washed that.
That's a, that's a big deal.
And they understand it.
They can get their hands aroundit.
Um, and you can really talk toit.
And then the most importantthing is, is having that
expectation, having thatconversation with your team so
that they know what that meansand what our goal is and why
(21:14):
we're trying to move cars atthat time.
And that it's not just aboutmaking money.
It's that again, speed isconvenience, and convenience and
service.
And service is how we serve ourcustomers.
And that conversation reallyresonates.
It help pe helps peopleunderstand why we're doing what
we're doing.
So what, how would you define
Kevin Zalaznik (21:32):
a delay?
What's a delay look
Rob Meng (21:33):
like?
So a delay is anytime that thecar's just sitting, not moving,
right?
So the ideal car wash is yourconveyor set to the perfect
speed and everything's working,and every car just rolls with
that.
You know that that three footspacing and the thing just keeps
moving and.
Infinite them, right?
It just keeps rolling throughthe, the tunnel and the tunnels
set up the right way ateverything and you end up with
(21:55):
clean cars at the other end.
But that's not reality.
'cause there's a, there's ahuman dynamic, whether it's the
customer in the car hittingtheir brake and not paying
attention, whether it's theemployee not pulling them up and
making'em feel, uh, you know,seen and identified and, and
move forward.
And so anytime that there's thatstop and you're missing that
time when that car's justsitting there not moving.
(22:15):
It.
That's when everything breaksdown with, that's when things
aren't working correctly.
And it's when the customerstarts to identify, Ooh, how
long am I sitting here?
How this is?
And if anybody's just sat for 60seconds in complete silence, it
feels like an eternity.
It's so long and we've all feltit, right?
That's the cool thing about whatwe do, is it's universal.
We've all sat in drive-throughs,you know, waiting for your
(22:37):
coffee, waiting for your burger,and you're like, how long am I
gonna sit here without moving?
This would drive me insane.
That's, that's what we'redealing with.
That's what we're trying to fixevery day, is helping people
realize, okay, let's move theline.
Let's serve the customer alittle bit better.
Let's, let's take care of ourclients the way we need to.
Um, and that's what we do.
And we do it again as data, as aservice.
(22:58):
So we don't have to install awhole new video system.
We come in and implement it.
We, we put our box in, we putour sensors in.
We collect the data, we give thedata to the team real time.
We collect it up and, and helpyou guys analyze it, help the
help the client analyze it,because there's a lot of
technology out there, but we'vealready helped customers replace
(23:19):
bad technology where they boughtboxes and the boxes showed up.
Then they were expected to do itright.
Nobody's got time to do that.
Nobody's got time to goimplement anything.
They're managing their business.
They're, they're, they'rewashing their cars, they're
managing their employees,they're adding head count.
They're doing all those things.
So when we can come in and wecan tell you, Hey, for seven
(23:41):
bucks a day, we manage all thisand that seven bucks turns into
70, 80, 90, a hundred dollars aday in cars wash.
And let our team be anextension, be your team so that
we can focus on that, and youcan keep focusing on taking care
of your customers.
That, that's, that's how itworks.
So
Kevin Zalaznik (23:57):
the, the cynic in me, uh, looks at this and,
uh, and not just yours, justthe, you know, and we go back
to, um, the McDonald's story andthe employee gaming the system,
right?
So now I've implemented somesort of metric, some sort of
standard of we need to have xamount of cars rolled through,
or, you know, We're only allowedone delay.
(24:21):
It's possible you could have theinverse effect where now the
employees are so focused on itthat they're not gonna take the
time to actually stop and talkto the customer who has a
question, have them stop.
I.
Where now they're just fullfocus on, I gotta get these cars
going through.
So it's certainly a balancingact.
Uh,
Rob Meng (24:38):
yeah, in that sense.
Yeah.
I don't, I don't, um, I thinkthat balancing act really plays
out the most during the salesprocess.
Um, not so much the entranceinto the car wash tunnel.
We don't see that every once ina while, a customer will stop,
roll their window down and, andask a question.
That's not a huge delay point.
Usually what we see is thatthose questions happen in the
sales process, and that's whereyou need to start to identify.
(25:01):
Are we doing two lanes or isthere three lanes?
Is there room for three lanes?
And designing your process atthe beginning so that you don't
have these funnels that stop.
Right?
So if if we have enough room onour lot, can we do a.
Three lines of selling, so thatif we do have a monthly pass or
we do have a customer withquestions, we can spend that
time and talk to'em.
(25:21):
But it doesn't have to cut downon our 120 cars now that we're
trying to process.
Um, and there's always the, it,it, there's always that
struggle.
I.
But for too long, the struggle'salways been on the side of let's
wait and let's waste time andlet's, and let's, and let's
spend too much time with everycustomer and let's reduce
(25:42):
throughput.
Whereas now we can measure itand we can start to make
intelligent decisions like wechange our menu board, Ooh, that
confused customers.
It takes'em an extra 30 secondsto process our transaction or we
change our credit card readersand all of a sudden it's extra
19 seconds every time we do acredit card transaction.
Let's have the data so that wecan make those decisions.
(26:02):
So we can see where there'splaces for process and
improvement.
Before there wasn't the data,and so you just have to rely on
how many customers did we serve?
And that's not the whole story.
The the story is how manycustomers wanted to be served.
And the last thing, especiallyfor car washes, it's about the
golden hours.
It's not about every hour, it'sabout the golden hours.
(26:22):
It's about those two or threehours every day where you have
the most customers who want tobe served.
It, it's probably not twoo'clock in the afternoon, unless
maybe that's on a Saturday.
Um, it's about making sure we'reoptimizing our system and we're
optimizing our training andwe're optimizing our team so
that when there are thoseopportunities to wash a hundred
cars, we're ready to do it andwe can execute and we actually
(26:44):
do that.
So
Kevin Zalaznik (26:46):
we're the, we've talked about this issue on the
podcast before, is that.
It's an exciting time if you'rereally in the technology and
really into the good thatartificial intelligence could
have.
Um, in that sense,
Rob Meng (27:02):
where
Kevin Zalaznik (27:03):
do you see AI in the car wash industry having a
positive effect in the nextyear, five years,
Rob Meng (27:10):
et cetera?
There's some hard, there's somethings I didn't think were gonna
be possible, um, that arebecoming possible.
Things like identifyingcollision opportunities in the
car wash tunnel is somethingthat's happening today, uh, with
other, with other tools, whichare, which are great.
Um, I see in the future, andwe're already working with some
of our clients on some solutionsaround damage claims and, and
(27:32):
seeing some anomalies there.
I think that there'll be moreand more opportunity to figure
out where people are and whenthey're in the right spot and
when they're not.
So I think those are the thingsthat are, that are on the near
horizon just within the nextcouple of years.
Um, another thing that our datapoint does is push people back
into their video system, right?
(27:52):
And so it, there's that, there'sthat bridge between the data,
the ai, and then the actualpeople.
And when we take our data and wesay, Hey, there was issues
happening.
And a manager or districtmanager goes into the video
system and they actually gowatch what was happening.
You get this human dynamic whereyou're like, oh, this was, this
is the problem.
This is what's ha, this is how Igo talk to my people.
(28:14):
This is how I, how I use this asgame film and go change what
we're doing.
Um, and so that's that bridgebetween the technology and the
people, and that's how you makeit work.
The best, uh, is, is using itto, to make that human
interaction better.
To make the, to, to make theteam know what's happening,
what's supposed to be happening,uh, and what isn't happening.
And so it's, it's exciting.
(28:35):
It's an exciting time.
Um, Other things that I thinkwill happen in the near future
is more, um, potentially moreinteraction between systems like
video systems and the actualcarwash controller.
Right?
Um, right now so much is manual,like if I wanna change how many
(28:56):
rollers I'm sending and, andhow, and how fast the conveyor
is actually going.
Um, I could really see long-termsomething where the data is
feeding the carwash controllerand you have a maximum speed of,
of the conveyor and maybe aminimum speed of the conveyor,
and you're moving between thosethings throughout the course of
the day so that you'remaximizing the throughput, but
(29:17):
still not taking away from thequality of the actual wash
output.
Shane Intubated has, go ahead.
Kevin Zalaznik (29:24):
Our tunnel controller does adjust the, um,
basically about every 200millisecond, uh, based on, uh,
coming
Rob Meng (29:36):
from the point of sale.
I think other industries havecome in and, and influenced car
wash.
Uh, car wash is growing in such,um, so dynamically that I see it
starting to go the other way,where people are starting to see
car wash and some of theexpertise that the folks in car
Wash have and driving it into,you know, the drive-through
space and some of these other,the, these other spaces.
(29:58):
And it's exciting to seebecause, uh, you can't just take
somebody out of like aMcDonald's and pop'em into a car
wash and, and have that besuccessful.
Right.
I've, I've seen a bunch oforganizations try and do that,
and it has not been usually arecipe for, uh, massive
improvement or success.
It's fact, sometimes it's theother way.
Um, and so it is, it's a, we'rewe're, it's a different animal.
(30:20):
Car wash is a different animal,and.
Um, you really do have to haveyour feet.
You gotta get your feet wet.
You gotta get into a, a, a, atunnel and understand what's
going on, what the customerexperiences before all the data
and all this other stuff canreally, you know, come into,
come into play and make hugepositive impact.
Kevin Zalaznik (30:39):
Robin, in the last probably five years,
Hoffman car Wash, we've made atransition to go more kiosk, uh,
pay station focused.
I'm curious if you've seen, uh,this.
In
Rob Meng (30:52):
your data, does that increase
Kevin Zalaznik (30:56):
throughput
Rob Meng (30:56):
or is that actually hindrance?
Yeah, so it depends.
You, you, um, I'm a person whobelieves you have to have two or
three lanes if you, if you'regonna automate, um, there is,
uh, a risk of not having thathuman interaction, I think is a,
you, you have a lot of folksthat up putting in kiosks and
they still man them.
And so then you have a question,okay, do, am I manning a kiosk
(31:19):
and.
There's still a person there.
And one of the benefits used tobe that we talked about was
reducing your, your payroll andstuff, but now all of a sudden
you're like, oh, am I doingthat?
I don't know.
Um, it's also a lot aboutdesign, right?
Like how am I interfacing withthe customer, whether it's human
or whether it's on the screen.
What are they seeing?
How simple is it?
How easy is it?
How comfortable are they?
(31:41):
Um, and then how does thatimpact my transition to monthly
passes, which is such a criticalpart of our industry at this
point.
So, um, let me give you anexample.
We're working with Zaxby's inthe southeast for, you know,
which is a great chicken chain.
They average 35 seconds at theorder speaker box with their
(32:01):
menu.
Um, you put the tablets outthere to start line busting
during their busy hours, andthey average closer to 60
seconds per order.
And the reason is pretty easy.
There's no menu.
It's really difficult.
The, the employee has to be waymore engaged with the
conversation and talking.
Yeah, they still have theirregulars who show up and they
want their chicken sandwich.
They know exactly what they wantand it's still 35 seconds.
(32:23):
But a bunch of the customers donot take 35 seconds.
And so now all of a sudden youhave to have two tablets out
there instead of one speakerbox.
You have to, you have toorchestrate that correctly so
it's working properly with thehuman dynamic.
Um, And so there's no perfectanswer to that.
Sometimes that human dynamic isbetter.
Sometimes you, you know, your,your pay station, um, unmanned
(32:46):
is, is a, is a great option andit works great, but there's
somewhere in between.
And the most important thing Iwould say is whether it's a
system like mine or justwatching the video or going back
and seeing.
You've gotta go look at what'shappening.
You have to go watch thetransaction.
You have to go see what thecustomer's experiencing and
where there's those choke pointsthat are making a, a negative
impact.
(33:07):
Um, and then you gotta, yougotta get their sander out.
You gotta buff those edges.
You gotta, you gotta, you gottatake the sharp out of there so
that they can be comfortable asthey're going through the
process.
And it makes it as easy aspossible for them to go.
This is great.
I need to do this once a week.
Let's be a monthly pass member.
Let's go.
Right?
And that's, that's what you'relooking for on the whole, the
whole thing.
(33:27):
Whether it's the processing, thetransaction, the interaction
with the employee, loading intothe conveyor, um, making them
comfortable that the correlatorbig enough that their tires
aren't gonna get, like all thosethings are those friction points
that keep the customer fromfeeling confident that they're
gonna want to come back over andover again.
And those are all the things yougotta buff out and fix.
(33:47):
And, and we love our databecause we help customers see
those cha, those human impactpoints that need the sander that
need to get buffed out, thatneed to get smooth.
Um, so that we do that, weincrease that speed, we can
increase that convenience so thecustomer goes, ah, this is
great.
I gotta do this all the time.
This is wonderful.
Alright Rob,
Kevin Zalaznik (34:07):
we've, we've taken up probably too much of
your time, but I do gotta ask'cause we asked all our guests,
this is basically what are youbinge watching
Rob Meng (34:14):
right now?
Oh man.
Um, I have two, uh, two real,uh, things that I love to watch
when I've got time to watch tv.
Uh, I love alone, uh, and I'mwatching alone.
I just got the, just got donewith what one of their new
seasons and they're doing aloneAustralia.
So I really dig that.
I like watching the humancondition play out and, and, and
(34:36):
what people are doing right andsuffering a little.
Oh, that's terrible.
Anyways.
And, uh, and then I'm a big fanof, uh, you know, watching chefs
compete.
So I watch a lot of Top Chefand, and really enjoy that as
well.
So those are, those are my two,probably my two favorites.
Kevin Zalaznik (34:52):
It's my, uh, I have a seven year old and, um,
it's not that she's like crazyin the Barbie, but.
You know, the whole Barbiecrease is happening right now.
So we just started watching likeextreme makeover, like Barbie
edition.
But the reason I brought it upwas one of the chefs from Top
Chef is on that show, and I'mlike, why is she on this show?
(35:14):
But anyways, what's so crazy?
That's
Rob Meng (35:16):
great.
Yeah.
Yeah.
That's fantastic.
Kevin Zalaznik (35:18):
Yeah, I love it.
I, I just finished watching.
Um, uh, Netflix has a series.
It's called, I think it'scalled, um, Untold and it looks
at different sports, uh, events.
And the Johnny Menzel one was,was pretty fascinating'cause I
did not like him.
I didn't like his whole being,uh, and his arrogance.
But like watching it, you kindof have a, a different
(35:40):
appreciation for how good he wasand like just the struggle that
he was going
Rob Meng (35:45):
through.
Like, oh, I'm gonna have tocheck that out.
Yeah, that sounds really great.
Yeah, he's a really interestingcharacter.
Um, I did watch another onethat's really interesting called
Just One Mile.
Um, and it's a, it's a look thatone up, just one mile.
Uh, I think it's on Prime rightnow.
And it's a documentary about a,uh, a race that's a single mile,
but they keep running it untilthe last person Oh, yeah.
(36:07):
Can't run it anymore.
Yeah.
And it's, uh, it's pretty,pretty remarkable.
Again, it's that, it's thathuman condition, right?
So those people, watching peoplego through this, this challenge
and push themselves, that's,that's, uh, And it's what we do
in car wash every day, right?
It's what you're, you'reliterally, you're struggling and
it's the end and you're like, Ijust gotta get to the end of the
day and then we can go fix thatwrap.
Or we can go, we can go dealwith this issue and I can go get
(36:28):
a drink and, and, and all that.
So, uh, that human condition'salways something really fun to
watch.
Just one
Kevin Zalaznik (36:35):
more car.
Just one more car.
Just one more.
That's right.
Rob.
Thank you so much.
This was great, great insight.
Uh, wish you all the best andum, thanks for coming on.
Rob Meng (36:46):
Appreciate it, guys can can check out faster
lights.com and and see a littlebit more about what we're
passionate about and this was agreat conversation.
I love talking car wash.
And Kevin and Shane, thanks forthe time today.
Really appreciate it.
All right, thanks.
Bye.
Hey everyone.
Welcome to the Modern Car WashPodcast.
I'm your host, Kevin Leszek,joining with my guest.
Host, co-host Shane Groff.
Shane, how are you?
Shane's usually, uh, in theoffice with me, but, uh, Shane,
are you in vacation?
What's going on there?
Oh, I'm in my office at homeright now.
(00:31):
Yeah.
So for those who are watchingthe video stream of this, Shane
is surrounded by, uh, I wouldcall it wood paneling, but I
think it's actually wood pine,individual pieces of wood.
Uh, Can you confirm or denythat?
Yeah.
Rob Meng (00:47):
Yeah.
It's just going.
Uh, Berg.
Kevin Zalaznik (00:51):
Our guest today is Rob Lang from Faster Lines.
Rob, welcome.
Rob Meng (00:56):
Hey guys.
Uh, pleasure to be here.
Excited to, uh, talk about carshoot you guys today.
Yeah, so
Kevin Zalaznik (01:03):
our whole, I guess our whole spiel or stick
is that, you know, it's verymodern, it's very technology
first, very, uh, uh, Progressivein the thinking of how car wash
is, are advancing and uh, fasterlines.
Seems like it's one of thesecompanies kind of there on the
forefront.
Can you give us some background,uh, on you, uh, and also what is
(01:26):
faster lines?
Rob Meng (01:27):
Yeah, you bet.
So, uh, first it, it actuallystarts with my dad.
I've been getting my feet wetand car washes since pretty much
I could walk.
My dad started working forHannah Car Wash way back in the
day, one of the original.
Multi-location car washcompanies up in Portland,
Oregon.
Um, and, uh, he, he actually wasmanaging a car wash by the time
(01:48):
he was 16 years old, which ispretty cool.
And, uh, so my, a lot of my carwash theory came, uh, rubbed off
on me, my dad, um, I spent a lotof time with car washes, but
then also selling technology.
Um, and learning about, uh,small improvements, making a
huge impact, uh, in like the,um, call center space.
(02:10):
Uh, then about 15 years ago, wewere sitting in line at an auto
Bell car wash in Raleigh, NorthCarolina, and the line wasn't
moving.
We were just sitting there likedying in line, waiting to get
her car washed.
And my wife looked at me andsaid, you know, the manager
should know that this ishappening.
Like this is.
And somebody should be able totell'em that this is happening.
And I was like, oh yeah,somebody should be able to tell
(02:33):
'em that the line's not moving.
That's a good idea.
Uh, I ended up talking to theowners of Auto Bell, uh, which,
uh, auto Bell's Great.
They're a third generationfamily owned business.
Taught to Chuck and Carl Howard.
And said, do you know you havethis issue where the cars don't
move into the conveyor and, andjust get stuck and, and
customers are just waiting inline.
(02:53):
And they said, we do know wehave that problem.
And I said, do you know how badthe problem is?
And they're like, no.
And I said, do you wanna knowhow bad the co the problem is?
'cause some people don't want toknow.
And luckily, uh, autobill ISS agreat organization.
They're really focused onquality process.
And so they said they wereinterested and we worked
together to figure out how tokeep track of those cars and.
Tell people when the line wasn'tmoving and that ended up helping
(03:15):
their managers understand whereto put people and how to get
people and, and move in cars.
And they wash a lot more carsnow because of that.
So we've been doing it for 14years and uh, it's been great.
They're still a customer and westill help'em watch the line.
Kevin Zalaznik (03:30):
What's crazy when you think about it is, I
mean, that was 14, 15 years ago,and you think of the, the sense
of urgency is only increased.
And I'll give you the, I was inTarget the other day and.
I always do self-checkout.
I, I think it's the mostofficial way to do it.
So I get in line and there'sfour kiosks.
Uh, two of them are not working.
(03:53):
Uh, there's a woman at the far,the far one, and she had the
call, the help button threetimes.
Uh, the woman closest to me, sothe other working kiosk, she had
issues.
So she had to call the helpbutton and the whole time the
lines backed up and, um, Youknow, I, I understand this is
targeted.
(04:13):
It's, it's, uh, uh, you know,people were, I, I don't know how
much business they're losing onthis, but, uh, I certainly was,
I was frustrated.
It was annoying.
And it's just the world we livein, like we want fast processes.
Um, so it completely makessense.
(04:33):
And I think in the car washindustry, when you look at it,
It's very much, there's probablymore competition, uh, involved
in, in
Rob Meng (04:42):
customer satisfaction.
And,
Kevin Zalaznik (04:44):
um, so I'm curious, when you, when you were
able to, when you went to, um,to Autobell and you said, Hey,
do you want to know what effectthis is having on it?
How are they able to, to improvetheir process?
And, and what, what were the, Iguess what were the key
performance indexes that youlooked at that said, Hey, this
(05:04):
is
Rob Meng (05:04):
working.
Yeah, so we looked originally,we, first of all, we did a lot
of status quo.
We developed the solution first.
Uh, we tried to use laser andradar and, uh, a bunch of
different ways of tracking thevehicle.
Um, the problem with all thoseissues was it was a single
point.
And, and, you know, with the carwash, the car's never in the
(05:25):
same place, right?
They never stop in the samespot.
And so we realized that we hadto do video and, and have an
analog shot where we can seemultiple cars.
So we measure multiple cars.
Um, for most of our customers,we're really focused on the cars
that are not on the correlatoryet.
So, so not the cars that arebeing prepped or, or, you know,
already on the conveyor, butthose cars that are waiting in
(05:47):
line.
And that's really importantbecause we're not looking at the
car that's being served.
We're wa wait looking at thosecustomers who are waiting to be
served, and those are the oneswho are waiting to be waved at
and smiled at and moved forward.
Um, and so at first when westarted measuring based on the,
the timeframes that Autobellgave us, Um, they were not
(06:07):
meeting their time standards 40%of the time.
Uh, and so that's a lot of carsjust sitting, not moving.
Um, within months ofidentifying, telling the team
about it, knowing that they'rebeing measured that way, we were
able to get a lot of theirlocations down into the teens.
(06:27):
Um, 14 years later, we'vereduced their time standard
eight different times.
Each time there's a bump in, youknow, number of alerts and
number of delays, but then theydrive again back down toward
that time standard and keepmoving the line.
Um, so it's, it's, we movethousands of additional cars
through the line Now because ofthe time standard and because of
(06:49):
pushing and we even did theexperiment a while, you know, in
after a couple of years and.
Um, we wanted to know, didpeople learn, right?
Or, or did, did you need thesystem still on or did people
get it?
And, and, and understand.
And so Carl and I talked aboutit and we actually, we turned
the system off.
(07:10):
We had a, we had a softwareupdate we were doing, and we
turned the system off, whichmeant that we just quit telling
the team about the data and wekept collecting the data.
And it was about a week later,Carl called me, he's like, turn
it back on.
So all of'em went back.
Because it's just hard.
It's such a focal part.
It's a, it's a human process.
It's a human dynamic, whetheryou have auto rollers up, um,
(07:33):
whether you gotta punch abutton, whether you're prepping
or not prepping, there's a partof it that's always human.
And that big part of it isacknowledging the customer,
waving them up and getting themto pull forward.
And if your team's not focusedon that, the car just sits
there.
And whether it's an extra twoseconds, whether it's an extra
10 seconds.
I mean, if you're talking about10 seconds during, during the
(07:55):
day, you're an exterior onlywash and you're trying to wash
120 cars an hour every time thatcar sits for 10 seconds, that's
a third of a car.
That happens a couple of timesin an hour.
And now you've got six cars,seven cars, 10 cars extra that
you could have washed if youjust pulled people forward and,
and, you know, kept that linemoving.
Yeah.
Hey, it's interesting
Kevin Zalaznik (08:15):
in the, um, You said like 10 seconds, a third of
a car or whatever it is, is, um,you know, data is data's great
if you know what to do with it.
Um, right.
And you can have all the data inthe world if you don't know what
to do with it.
So it sounds like really it wasmore, there was an
accountability aspect to it.
Um, you know, here's a metric,let's try and hit it and let's
(08:38):
go and get it.
So, uh, Shane was, uh, he wastelling the story.
You know, McDonald's hassomething very similar to this
Rob Meng (08:46):
where, uh, and I'm sure you're aware,
Kevin Zalaznik (08:48):
you know, the, it comes up on the, on the
screen and the employee, as theorder's filled, they, they mark
it off and it's way of, uh, justkeeping track of it.
Well, it's all, it's all fine,but when the employee.
Knocks it off just to get offthe board.
They're kind of gaming thesystem.
(09:09):
Um, and I think we've seen thisin other industries as well.
Uh, but it sounds like, um, kindof your system and how you have
it set up, it's more, there's nogaming.
You're, you're actually readingthe vehicle.
Rob Meng (09:22):
Yep.
Well, yeah, it's, it's about themultiple vehicles.
If you're just looking at onethat the employees can figure
out where we're measuring and,and try and move the car, keep
the car further back, which iseven worse, right?
You want as close spacing aspossible.
So it's about making sure thatyou're measuring multiple cars
so that there isn't a way togame.
Gaming's good.
It's just human dynamic.
It's just trying to, it's tryingto get, uh, you know, do
(09:44):
positive with how you're beingmeasured.
Um, and, and, but we, yeah,we've definitely figured out how
to operationalize the data, helpthe team know how they're being
measured, and then keep'em fromtricking the system.
So that, and with car wash, it'sgreat because the answer is, is
it on the conveyor?
Not, is the car moving throughthe car was or not?
But it's really difficult to,you know, it's not like, uh,
(10:04):
drive through restaurants whereyou can have a pull forward and
then bring that bag out.
I.
It's either in the car washtunnel getting washed or it's
not.
So it's, it's pretty clear inthe car wash
Kevin Zalaznik (10:12):
area.
What do you think the biggestchallenges that operators face
as far as keeping the linemoving?
Rob Meng (10:18):
Yeah, so there's two, um, one, uh, is we found that
there's this kind of magic timearound 90 minutes where
employees start to kind of fadeoff.
It's, it's a, it's a repeatingprocess, right?
It's over and over again.
You're washing cars, you'removing cars forward, you're
acknowledging your greeting.
Somewhere around 90 minutes,even the best employee starts to
(10:40):
lose that, you know, that thatverve, that that excitement.
Um, and so it's really importantto start to transition people
into other places, moving themup, you know, to, to sales.
Moving up to greeting.
I.
Uh, giving them a break and, andthen getting them dialed in.
So that's the first thing.
Um, the second thing is, is thatthere's a lot of focus on sales,
right?
(11:01):
And, and monthly passes.
And we've helped a lot of ourclients figure out how to do
that offline.
Um, not stop the entire process,stop the entire line for a
minute or two while you'reprocessing that monthly pass
member, but get them through thewash and actually process that
monthly pass on the other end ofthe car wash.
(11:21):
Uh, in the vacuum area or in aspecific area that, that you
have for monthly past members?
Um, so those are two of the bigones that we see as huge delays.
And we had, we, we have a clientthat was telling us, well, we
need to go to like 90 secondsfor their sales area.
'cause we measure sales area.
We also measure the entranceinto the car wash tunnel.
We're like, no, don't do that.
(11:41):
'cause you, there's a magicthing that happens at 60 seconds
with customers if they sit therewithout moving for 60 seconds.
Only like three bad things canhappen.
Uh, no good things can happen.
Only three bad things.
The first bad thing is, um, theystart doing fuzzy math and they
start looking and they're like,I'm gonna be here forever.
(12:02):
There's 10 cars in line.
It's gonna take me an hour.
No, it's not gonna take an hour.
It's gonna take like sixminutes.
Like, but that's not what theirperception is.
So you start to have a negativeperception.
Number two, maybe even worse,they pick up their cell phone
and they start looking at it.
If they do that, then they'renot paying attention and they're
gonna, it's gonna screw up yourflow and, and things just slow
(12:22):
down.
And the last bad thing is theyfigure out how to get outta line
and they leave.
And that's, that, that's, 60seconds is a really magical
time.
And so it's really important,whether they're in the sales
area or whether they're, youknow, getting ready to go into
the car wash tunnel, that theydon't have that opportunity to
sit there.
And no car wash operator wantsthat anyways.
(12:43):
If they're sitting there for 60seconds, the best you can do is
60 cars an hour, right?
You, you want, almost every carwash wants to be loaded.
The conveyor faster than that.
And so that's something that wereally focus on.
That's something that we helpoperationalize with the team.
And again, it's about us helpingserve the data as a service to
the team so that they knowwhat's going on so that, that
(13:05):
they can take that data and helpserve their customer that much
faster.
And.
When you really focus on thepeople, you don't use it as a,
you know, character sticker.
It's, it's really about helpingthe team know.
And once the team knows theywant to do something about it,
'cause they know the expectationis to move the line and, and it
makes a huge impact.
Not only that, but it's that,that extra money, that's the
(13:25):
gravy, right?
The site's already paid for, thepower's already paid for.
The water's already paid for.
You got a little bit of soap,the employee's already there.
You, you pack those extra TEDcustomers into an hour.
It, it's, it that's, that's ahuge amount of the actual
profitability of the site.
That, that, that's, that's whywe think it's so exciting.
'cause it, it really adds tothat extra top line that, that
(13:48):
good number.
Kevin Zalaznik (13:49):
Rob, do you, do you think there's a, um, maybe
like a tipping point foroperators in your experience
where they're like, you knowwhat, we need to need to take
this serious.
Like, we really need to start
Rob Meng (14:00):
looking at this.
It's so funny.
Um, we just helped serve a, a, aclient fast track car wash out
in Eugene, Oregon.
They have two sites they've beenoperating for more than 10
years.
They've got a great generalmanager, Ivan, who's out there.
He is fantastic.
Um, but they were really stuckand constantly the owners and
Ivan were arguing about how manycars can they wash an hour?
(14:20):
Right?
And it's an exterior only wash.
They were averaging about 52seconds between cars.
So they, they were hardly evergetting the 60 cars an hour.
Um, and we sat down, we lookedat'em.
Their, their, their wash is setup right.
Their chemical's good.
The only thing they weren'tdoing is they were prepping the
entire car before they sent thedang car.
And so all we talked about wasjust getting through the
(14:43):
driver's door and hitting thebutton so that the car starts
moving, finishing prep while thecar's rolling.
And now all of a sudden thoseguys are washing 80, 90 cars an
hour, and it's just that littlething.
Then the next thing they had tostart working on was getting
their guys' head from preppingand looking at the car to
smiling, waving, and pullingthat next customer forward.
And so those two little thingsmake all the difference, right?
(15:05):
The line starts moving and nowall of a sudden, so the 60 cars
an hour or 50 cars an hour,you're washing 70, 80 cars an
hour and, and it's a hugeimprovement, and it's not just
the numbers.
It's convenience.
Speed is convenience, andconvenience is customer service,
and customer service is customersatisfaction, and we know that
(15:27):
they're turning over more ofthose customers into monthly
past members because.
The customer's feeling thatspeed, they're feeling that
convenience.
And so they're gonna come backmore often.
They're gonna end up buying thatmonthly pass.
And, and then all the stuffShane was talking about, about
that monthly pass member now isa part of your organization.
They're part of your team.
They, they understand theprocess.
They understand they're notgonna pick their cell phone up,
(15:47):
they're paying attention'causethey know you're a high
performance organization andthey were, they're there to
quickly get their car washed andmove on so that the other
customers can quickly get theircar washed and move on.
So it's all recursive, it's allgood stuff.
Kevin Zalaznik (16:01):
Is there a way to, to leverage technology, your
technology or something similarto it as far as labor management
and, um, what, what's that looklike?
Rob Meng (16:12):
Yeah, so that's, that's one of the interesting
things, right?
So, uh, back to Auto Bell.
Autobell used to staffThursdays, like they were slow
day, right?
Wednesday, Thursdays were kindof their middle of the week kind
of slow.
And we started watching theline.
We started watching thesedelays.
Well, they were slow.
Because they didn't have anystaff.
They didn't have anybody moving.
(16:32):
They didn't have any focus.
And so as soon as we identifiedthat there was delays in line on
Thursdays, there was customerswho were in line but wanted to
be served.
They changed their staffing,their scheduling, so that
Thursdays were like Fridays.
And guess what?
They washed a bunch more cars.
Their customers were there, theyjust didn't know.
And whether you're a carwash ora drive through, that's one of
(16:53):
the traditional challenges,right?
You know, and you can plan, andyou can train and you can
schedule based on what you did,what you sold, but you don't
really know what the opportunitywas.
And so if you're looking back atlast year in August, and the
weather's the same, right?
You go, oh, well we washed, youknow, 50 cars that hour, but you
had 60 or 70 cars that werethere that wanted to get washed.
(17:15):
You
just didn't move them through the line.
And so when we start to actuallyidentify delay, we match that up
with scheduling.
And we start to turn up thatknob, that knob, right?
You, the, the operator, theowner, the, the management team
starts to understand, oh, we caninvest for another greeter.
We can invest for another prep.
We can invest somebody else outthere to help move the line,
(17:36):
because if we invest that extraperson, we're gonna wash 10 more
cars.
And so that hour, it makes senseto put that person out there.
Vice versa.
We had a customer, it wasactually a drive through
customer that was out in Omaha,Nebraska.
And they were doing breakfastand they started breakfast at
eight and, and we did the math.
They weren't serving anycustomers breakfast.
(17:58):
They had this whole team thereto do breakfast and, and they
just had this minuscule numberof customers they were serving.
And so we did the vice theopposite.
They could invest those hoursinto their busy lunch and
dinnertime and quit wasting manhours on, on a time that they're
not busy.
So both of those end up.
Feeding into the scheduleschedule's a huge impact for
what we do.
And then training and thenprocess improvement after that.
(18:21):
And, and those are kind of thethree steps to, to really
dialing it in, um, and gettingthe most out of, of that
location, that district, thatregion and, and driving it
forward
Kevin Zalaznik (18:31):
seems like, um, you know, when I look at.
Some of these, some technologycompanies that have come into
the car wash industry.
And I think a lot of it is, youknow, uh, entrepreneurs, venture
capitalists, you know, put theirfinger in there and they're
like, oh, car wash, look out.
Like this industry is growing,but you've actually, you've been
(18:52):
in it for quite some time.
You've, you've kind of therecent boom.
Um, have you found otherapplications though, or other
industries that, uh, That aresimilar, um, uh, where that, you
know, things
Rob Meng (19:07):
like this apply.
Yeah, so we actually startedwatching people about six years
ago.
Uh, and so we have moved intorestaurant hospitality, oil
change.
Um, so we're seeing all those,but really it all comes back to
car wash.
Car wash gave us a really uniqueopportunity, um, the, the
restaurant industry and, andlike we talked about McDonald's
(19:28):
and their little board on thewall that shows time.
They're all, they were allfocused on a time from order to
delivery.
And this total time of service,which is, is really difficult
for employees to understand.
We do it differently, and westarted with carwash and so it
made sense.
We broke it down to for flow,and we were looking for how many
opportunities there were for thecar to move forward, and how
(19:49):
many times the car had to moveand how far that had to move in
order to get your flow and getyour, get your line moving
correctly.
And so instead of this like 300seconds of total time of
service, which is difficult foran employee to understand, we
talk about this delay metricwhere if a car sits for too long
beyond our time standard, it it,we've missed an opportunity.
(20:11):
And that delay metric is areally much easier operational
point to manage employees to.
We talked to a bunch ofStarbucks employees and
McDonald's employees and allover the place with these timers
that were on the wall.
And you'd go, what is that?
And they'd go, I don't know.
That's something my managerdeals with.
That's something my districtmanager
deals
with.
You'd be like, what's 256seconds?
(20:32):
I have no idea.
I don't even know what thatmeans, like, right.
But when you have, we actuallyput a a, a 10 inch screen up,
you know, at the entrance intothe car wash tunnel, and it
tells you how many times therewas delays.
And delays turn into missedcars.
And it's just a clear, reallyeasy number for them to
understand.
We change the color so that theycan see it, but as you look and
(20:54):
you're like, oh, I've had 10delays in the last hour, that
means I, I missed three cars.
I could've washed that.
That's a, that's a big deal.
And they understand it.
They can get their hands aroundit.
Um, and you can really talk toit.
And then the most importantthing is, is having that
expectation, having thatconversation with your team so
that they know what that meansand what our goal is and why
(21:14):
we're trying to move cars atthat time.
And that it's not just aboutmaking money.
It's that again, speed isconvenience, and convenience and
service.
And service is how we serve ourcustomers.
And that conversation reallyresonates.
It help pe helps peopleunderstand why we're doing what
we're doing.
So what, how would you define
Kevin Zalaznik (21:32):
a delay?
What's a delay look
Rob Meng (21:33):
like?
So a delay is anytime that thecar's just sitting, not moving,
right?
So the ideal car wash is yourconveyor set to the perfect
speed and everything's working,and every car just rolls with
that.
You know that that three footspacing and the thing just keeps
moving and.
Infinite them, right?
It just keeps rolling throughthe, the tunnel and the tunnels
set up the right way ateverything and you end up with
(21:55):
clean cars at the other end.
But that's not reality.
'cause there's a, there's ahuman dynamic, whether it's the
customer in the car hittingtheir brake and not paying
attention, whether it's theemployee not pulling them up and
making'em feel, uh, you know,seen and identified and, and
move forward.
And so anytime that there's thatstop and you're missing that
time when that car's justsitting there not moving.
(22:15):
It.
That's when everything breaksdown with, that's when things
aren't working correctly.
And it's when the customerstarts to identify, Ooh, how
long am I sitting here?
How this is?
And if anybody's just sat for 60seconds in complete silence, it
feels like an eternity.
It's so long and we've all feltit, right?
That's the cool thing about whatwe do, is it's universal.
We've all sat in drive-throughs,you know, waiting for your
(22:37):
coffee, waiting for your burger,and you're like, how long am I
gonna sit here without moving?
This would drive me insane.
That's, that's what we'redealing with.
That's what we're trying to fixevery day, is helping people
realize, okay, let's move theline.
Let's serve the customer alittle bit better.
Let's, let's take care of ourclients the way we need to.
Um, and that's what we do.
And we do it again as data, as aservice.
(22:58):
So we don't have to install awhole new video system.
We come in and implement it.
We, we put our box in, we putour sensors in.
We collect the data, we give thedata to the team real time.
We collect it up and, and helpyou guys analyze it, help the
help the client analyze it,because there's a lot of
technology out there, but we'vealready helped customers replace
(23:19):
bad technology where they boughtboxes and the boxes showed up.
Then they were expected to do itright.
Nobody's got time to do that.
Nobody's got time to goimplement anything.
They're managing their business.
They're, they're, they'rewashing their cars, they're
managing their employees,they're adding head count.
They're doing all those things.
So when we can come in and wecan tell you, Hey, for seven
(23:41):
bucks a day, we manage all thisand that seven bucks turns into
70, 80, 90, a hundred dollars aday in cars wash.
And let our team be anextension, be your team so that
we can focus on that, and youcan keep focusing on taking care
of your customers.
That, that's, that's how itworks.
So
Kevin Zalaznik (23:57):
the, the cynic in me, uh, looks at this and,
uh, and not just yours, justthe, you know, and we go back
to, um, the McDonald's story andthe employee gaming the system,
right?
So now I've implemented somesort of metric, some sort of
standard of we need to have xamount of cars rolled through,
or, you know, We're only allowedone delay.
(24:21):
It's possible you could have theinverse effect where now the
employees are so focused on itthat they're not gonna take the
time to actually stop and talkto the customer who has a
question, have them stop.
I.
Where now they're just fullfocus on, I gotta get these cars
going through.
So it's certainly a balancingact.
Uh,
Rob Meng (24:38):
yeah, in that sense.
Yeah.
I don't, I don't, um, I thinkthat balancing act really plays
out the most during the salesprocess.
Um, not so much the entranceinto the car wash tunnel.
We don't see that every once ina while, a customer will stop,
roll their window down and, andask a question.
That's not a huge delay point.
Usually what we see is thatthose questions happen in the
sales process, and that's whereyou need to start to identify.
(25:01):
Are we doing two lanes or isthere three lanes?
Is there room for three lanes?
And designing your process atthe beginning so that you don't
have these funnels that stop.
Right?
So if if we have enough room onour lot, can we do a.
Three lines of selling, so thatif we do have a monthly pass or
we do have a customer withquestions, we can spend that
time and talk to'em.
(25:21):
But it doesn't have to cut downon our 120 cars now that we're
trying to process.
Um, and there's always the, it,it, there's always that
struggle.
I.
But for too long, the struggle'salways been on the side of let's
wait and let's waste time andlet's, and let's, and let's
spend too much time with everycustomer and let's reduce
(25:42):
throughput.
Whereas now we can measure itand we can start to make
intelligent decisions like wechange our menu board, Ooh, that
confused customers.
It takes'em an extra 30 secondsto process our transaction or we
change our credit card readersand all of a sudden it's extra
19 seconds every time we do acredit card transaction.
Let's have the data so that wecan make those decisions.
(26:02):
So we can see where there'splaces for process and
improvement.
Before there wasn't the data,and so you just have to rely on
how many customers did we serve?
And that's not the whole story.
The the story is how manycustomers wanted to be served.
And the last thing, especiallyfor car washes, it's about the
golden hours.
It's not about every hour, it'sabout the golden hours.
(26:22):
It's about those two or threehours every day where you have
the most customers who want tobe served.
It, it's probably not twoo'clock in the afternoon, unless
maybe that's on a Saturday.
Um, it's about making sure we'reoptimizing our system and we're
optimizing our training andwe're optimizing our team so
that when there are thoseopportunities to wash a hundred
cars, we're ready to do it andwe can execute and we actually
(26:44):
do that.
So
Kevin Zalaznik (26:46):
we're the, we've talked about this issue on the
podcast before, is that.
It's an exciting time if you'rereally in the technology and
really into the good thatartificial intelligence could
have.
Um, in that sense,
Rob Meng (27:02):
where
Kevin Zalaznik (27:03):
do you see AI in the car wash industry having a
positive effect in the nextyear, five years,
Rob Meng (27:10):
et cetera?
There's some hard, there's somethings I didn't think were gonna
be possible, um, that arebecoming possible.
Things like identifyingcollision opportunities in the
car wash tunnel is somethingthat's happening today, uh, with
other, with other tools, whichare, which are great.
Um, I see in the future, andwe're already working with some
of our clients on some solutionsaround damage claims and, and
(27:32):
seeing some anomalies there.
I think that there'll be moreand more opportunity to figure
out where people are and whenthey're in the right spot and
when they're not.
So I think those are the thingsthat are, that are on the near
horizon just within the nextcouple of years.
Um, another thing that our datapoint does is push people back
into their video system, right?
(27:52):
And so it, there's that, there'sthat bridge between the data,
the ai, and then the actualpeople.
And when we take our data and wesay, Hey, there was issues
happening.
And a manager or districtmanager goes into the video
system and they actually gowatch what was happening.
You get this human dynamic whereyou're like, oh, this was, this
is the problem.
This is what's ha, this is how Igo talk to my people.
(28:14):
This is how I, how I use this asgame film and go change what
we're doing.
Um, and so that's that bridgebetween the technology and the
people, and that's how you makeit work.
The best, uh, is, is using itto, to make that human
interaction better.
To make the, to, to make theteam know what's happening,
what's supposed to be happening,uh, and what isn't happening.
And so it's, it's exciting.
(28:35):
It's an exciting time.
Um, Other things that I thinkwill happen in the near future
is more, um, potentially moreinteraction between systems like
video systems and the actualcarwash controller.
Right?
Um, right now so much is manual,like if I wanna change how many
(28:56):
rollers I'm sending and, andhow, and how fast the conveyor
is actually going.
Um, I could really see long-termsomething where the data is
feeding the carwash controllerand you have a maximum speed of,
of the conveyor and maybe aminimum speed of the conveyor,
and you're moving between thosethings throughout the course of
the day so that you'remaximizing the throughput, but
(29:17):
still not taking away from thequality of the actual wash
output.
Shane Intubated has, go ahead.
Kevin Zalaznik (29:24):
Our tunnel controller does adjust the, um,
basically about every 200millisecond, uh, based on, uh,
coming
Rob Meng (29:36):
from the point of sale.
I think other industries havecome in and, and influenced car
wash.
Uh, car wash is growing in such,um, so dynamically that I see it
starting to go the other way,where people are starting to see
car wash and some of theexpertise that the folks in car
Wash have and driving it into,you know, the drive-through
space and some of these other,the, these other spaces.
(29:58):
And it's exciting to seebecause, uh, you can't just take
somebody out of like aMcDonald's and pop'em into a car
wash and, and have that besuccessful.
Right.
I've, I've seen a bunch oforganizations try and do that,
and it has not been usually arecipe for, uh, massive
improvement or success.
It's fact, sometimes it's theother way.
Um, and so it is, it's a, we'rewe're, it's a different animal.
(30:20):
Car wash is a different animal,and.
Um, you really do have to haveyour feet.
You gotta get your feet wet.
You gotta get into a, a, a, atunnel and understand what's
going on, what the customerexperiences before all the data
and all this other stuff canreally, you know, come into,
come into play and make hugepositive impact.
Kevin Zalaznik (30:39):
Robin, in the last probably five years,
Hoffman car Wash, we've made atransition to go more kiosk, uh,
pay station focused.
I'm curious if you've seen, uh,this.
In
Rob Meng (30:52):
your data, does that increase
Kevin Zalaznik (30:56):
throughput
Rob Meng (30:56):
or is that actually hindrance?
Yeah, so it depends.
You, you, um, I'm a person whobelieves you have to have two or
three lanes if you, if you'regonna automate, um, there is,
uh, a risk of not having thathuman interaction, I think is a,
you, you have a lot of folksthat up putting in kiosks and
they still man them.
And so then you have a question,okay, do, am I manning a kiosk
(31:19):
and.
There's still a person there.
And one of the benefits used tobe that we talked about was
reducing your, your payroll andstuff, but now all of a sudden
you're like, oh, am I doingthat?
I don't know.
Um, it's also a lot aboutdesign, right?
Like how am I interfacing withthe customer, whether it's human
or whether it's on the screen.
What are they seeing?
How simple is it?
How easy is it?
How comfortable are they?
(31:41):
Um, and then how does thatimpact my transition to monthly
passes, which is such a criticalpart of our industry at this
point.
So, um, let me give you anexample.
We're working with Zaxby's inthe southeast for, you know,
which is a great chicken chain.
They average 35 seconds at theorder speaker box with their
(32:01):
menu.
Um, you put the tablets outthere to start line busting
during their busy hours, andthey average closer to 60
seconds per order.
And the reason is pretty easy.
There's no menu.
It's really difficult.
The, the employee has to be waymore engaged with the
conversation and talking.
Yeah, they still have theirregulars who show up and they
want their chicken sandwich.
They know exactly what they wantand it's still 35 seconds.
(32:23):
But a bunch of the customers donot take 35 seconds.
And so now all of a sudden youhave to have two tablets out
there instead of one speakerbox.
You have to, you have toorchestrate that correctly so
it's working properly with thehuman dynamic.
Um, And so there's no perfectanswer to that.
Sometimes that human dynamic isbetter.
Sometimes you, you know, your,your pay station, um, unmanned
(32:46):
is, is a, is a great option andit works great, but there's
somewhere in between.
And the most important thing Iwould say is whether it's a
system like mine or justwatching the video or going back
and seeing.
You've gotta go look at what'shappening.
You have to go watch thetransaction.
You have to go see what thecustomer's experiencing and
where there's those choke pointsthat are making a, a negative
impact.
(33:07):
Um, and then you gotta, yougotta get their sander out.
You gotta buff those edges.
You gotta, you gotta, you gottatake the sharp out of there so
that they can be comfortable asthey're going through the
process.
And it makes it as easy aspossible for them to go.
This is great.
I need to do this once a week.
Let's be a monthly pass member.
Let's go.
Right?
And that's, that's what you'relooking for on the whole, the
whole thing.
(33:27):
Whether it's the processing, thetransaction, the interaction
with the employee, loading intothe conveyor, um, making them
comfortable that the correlatorbig enough that their tires
aren't gonna get, like all thosethings are those friction points
that keep the customer fromfeeling confident that they're
gonna want to come back over andover again.
And those are all the things yougotta buff out and fix.
(33:47):
And, and we love our databecause we help customers see
those cha, those human impactpoints that need the sander that
need to get buffed out, thatneed to get smooth.
Um, so that we do that, weincrease that speed, we can
increase that convenience so thecustomer goes, ah, this is
great.
I gotta do this all the time.
This is wonderful.
Alright Rob,
Kevin Zalaznik (34:07):
we've, we've taken up probably too much of
your time, but I do gotta ask'cause we asked all our guests,
this is basically what are youbinge watching
Rob Meng (34:14):
right now?
Oh man.
Um, I have two, uh, two real,uh, things that I love to watch
when I've got time to watch tv.
Uh, I love alone, uh, and I'mwatching alone.
I just got the, just got donewith what one of their new
seasons and they're doing aloneAustralia.
So I really dig that.
I like watching the humancondition play out and, and, and
(34:36):
what people are doing right andsuffering a little.
Oh, that's terrible.
Anyways.
And, uh, and then I'm a big fanof, uh, you know, watching chefs
compete.
So I watch a lot of Top Chefand, and really enjoy that as
well.
So those are, those are my two,probably my two favorites.
Kevin Zalaznik (34:52):
It's my, uh, I have a seven year old and, um,
it's not that she's like crazyin the Barbie, but.
You know, the whole Barbiecrease is happening right now.
So we just started watching likeextreme makeover, like Barbie
edition.
But the reason I brought it upwas one of the chefs from Top
Chef is on that show, and I'mlike, why is she on this show?
(35:14):
But anyways, what's so crazy?
That's
Rob Meng (35:16):
great.
Yeah.
Yeah.
That's fantastic.
Kevin Zalaznik (35:18):
Yeah, I love it.
I, I just finished watching.
Um, uh, Netflix has a series.
It's called, I think it'scalled, um, Untold and it looks
at different sports, uh, events.
And the Johnny Menzel one was,was pretty fascinating'cause I
did not like him.
I didn't like his whole being,uh, and his arrogance.
But like watching it, you kindof have a, a different
(35:40):
appreciation for how good he wasand like just the struggle that
he was going
Rob Meng (35:45):
through.
Like, oh, I'm gonna have tocheck that out.
Yeah, that sounds really great.
Yeah, he's a really interestingcharacter.
Um, I did watch another onethat's really interesting called
Just One Mile.
Um, and it's a, it's a look thatone up, just one mile.
Uh, I think it's on Prime rightnow.
And it's a documentary about a,uh, a race that's a single mile,
but they keep running it untilthe last person Oh, yeah.
(36:07):
Can't run it anymore.
Yeah.
And it's, uh, it's pretty,pretty remarkable.
Again, it's that, it's thathuman condition, right?
So those people, watching peoplego through this, this challenge
and push themselves, that's,that's, uh, And it's what we do
in car wash every day, right?
It's what you're, you'reliterally, you're struggling and
it's the end and you're like, Ijust gotta get to the end of the
day and then we can go fix thatwrap.
Or we can go, we can go dealwith this issue and I can go get
(36:28):
a drink and, and, and all that.
So, uh, that human condition'salways something really fun to
watch.
Just one
Kevin Zalaznik (36:35):
more car.
Just one more car.
Just one more.
That's right.
Rob.
Thank you so much.
This was great, great insight.
Uh, wish you all the best andum, thanks for coming on.
Rob Meng (36:46):
Appreciate it, guys can can check out faster
lights.com and and see a littlebit more about what we're
passionate about and this was agreat conversation.
I love talking car wash.
And Kevin and Shane, thanks forthe time today.
Really appreciate it.
All right, thanks.
Bye.
Popular Podcasts
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Special Summer Offer: Exclusively on Apple Podcasts, try our Dateline Premium subscription completely free for one month! With Dateline Premium, you get every episode ad-free plus exclusive bonus content.
The Breakfast Club
The World's Most Dangerous Morning Show, The Breakfast Club, With DJ Envy, Jess Hilarious, And Charlamagne Tha God!
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.