Unraveling Supply Chain Mysteries: Insights from Expert Jason Miller

What's the real story behind the recent turmoil in the supply chain industry? Join us as we uncover the truth with Jason Miller, a full professor at Michigan State University. This episode kicks off with Jason's riveting analysis of a Census Bureau graph showing dramatic shifts in manufacturing plants' material supply since 2021. By leveraging economic theory and robust data, Jason debunks common industry myths and reveals the profound implications of these trends for retailers and logistics professionals alike.

Ever wondered how the trucking industry cycles through boom and bust periods? We trace the intricate dynamics of freight demand and spot rates over the past decade, shining a spotlight on pivotal moments like the 2019 bear market and the COVID-19 surge. Jason illuminates how consumer spending spikes, influenced by government stimulus, led to current market normalization challenges. We also dissect the overlooked impacts of trade wars and domestic demand, offering a nuanced perspective on global manufacturing export trends and their ripple effects across the supply chain.

Seasonality in logistics and the evolving landscape of the trucking industry take center stage as we explore the impact of fluctuating demand for frozen desserts and the growth of non-employer trucking businesses. Jason provides a compelling contrast between large carriers and owner-operators, highlighting their unique challenges and the surprising resilience of smaller firms. We wrap up with an insightful discussion on forecasting models like ARIMA, their predictive prowess, and their limitations during volatile periods. This episode is a treasure trove of expert insights for anyone navigating the complexities of the modern supply chain.

Episode Transcript

Dr. Matt Waller (00:10):
Welcome to the Matt Waller podcast, where we
look at success at theintersection of technology,
logistics, supply chain, retailand CPG, also known as the
retail value chain.
I want to clarify that thispodcast is distinct from my
responsibilities as a professorin the Sam M Walton College of
Business.
Nonetheless, it aligns with myaspiration to provide practical

(00:31):
insights to professionals andbusiness by showcasing companies
and people that can enhanceyour ability to manage, lead and
strategize and marketeffectively in the retail value
chain.
Before we dive into today'sexciting episode, I'd like to
thank our sponsor, new RoadCapital Partners.
New Road invests in proventechnologies, services and

(00:53):
products that serve unmet needsin the marketplace.
They look for companies insupply chain and logistics, as
well as consumer-orientedcompanies.
For more information, go tonewroadcpcom.
I would also like to disclosethat I am a strategic advisor to
New Road.
I'd also like to recognizepodcastvideoscom for the

(01:18):
services they provide for thesepodcasts.
I'm very pleased with theirservices and now, without
further ado, let's get into theexciting episode.
I have with me today JasonMiller, who is a full professor
at Michigan State University insupply chain management.
He's also interim departmentchair, so Jason has over 40,000

(01:44):
followers on LinkedIn and I'mone of them and there is no one
I follow closer personally onLinkedIn.
I read his post every day.
One thing Jason does that isreally interesting.

(02:04):
So he's an expert in supplychain management, especially
logistics and transportation,but he also understands economic
theory really well and appliesthose kinds of tools to freight
and logistics logistics.

(02:30):
And if you read his post whichI would encourage you to do and
I have a link to his profilepage on my post about this
podcast but if you read them,you see that he uses data and he
uses that data and explainssomething that's really
important to industry, not justtrucking.
It's much broader than that, asyou will hear when you listen

(02:54):
to this podcast.
In this podcast, we go deep,and one of the things that I
really like about Jason's postsand what he does is he uncovers
fallacies, that people believe,rules of thumb that just aren't
true, and the data shows it.
And you'll see that when youlisten to this podcast and if

(03:19):
you typically listen to thispodcast, you might want to watch
it on the YouTube channel.
You don't have to.
You can understand it becausewe describe every graph we talk
about, but if you actually wantto see the graphs, you can watch
it on YouTube, but it's veryinsightful.

(03:41):
We went for quite a while.
We could have gone twice aslong.
It was a very interestingconversation.
If you are a shipper, if you'rea carrier, if you're a broker,
if you're a student of supplychain management, I really think
you should watch this.
I also think Jason is sort of aparagon of professor and

(04:06):
business, because a lot of timeswhen you hear the word theory,
professors are known to usetheory.
Many times people think that'suseless, what's really happening
.
But good theory not only candescribe, explain phenomena that
we see in logistics and supplychain management, but it can
also predict it, and Jason'swork does that.

(04:29):
And so what's interesting isJason's being.
He's a very successfulprofessor in terms of publishing
academic journals andpeer-reviewed journals, but he
also has a huge following inindustry, and to me that's like
the quintessential goal of abusiness professor to have

(04:52):
something that's so relevantthat it's not just relevant to
the academic community, it'salso relevant to practice, and
Jason demonstrates that.
So it's a really excitingepisode.
I think you're going to enjoyit.
Thank you so much, jason, forjoining me today.
I really appreciate it.

Jason Miller (05:10):
Hey, thank you for having me on, Matt.
It's a great chance to chat andcatch up.

Dr. Matt Waller (05:14):
Well, jason, I want to jump right into a graph.
So this is a really interestingchart and it then the vertical
axis is proportion of plantsthat are saying there's

(05:50):
insufficient supply of materialsand that's why they're
operating below full capacity.
And these lines, the verticallines on each dot, are the 80%
confidence intervals.
So this is a really you know,telling graph, but explain it to
us a little bit, a little bitmore about the source of the

(06:11):
data and what it's telling us.

Jason Miller (06:13):
Yeah, so this is data from a program the Census
Bureau does called the QuarterlySurvey of Plant Capacity
Utilization.
It is a legally mandated surveythat if you are a plant in the
United States and selected toparticipate, you must fill this
out per requirement.
A lot of that is because theDepartment of Defense and the

(06:34):
Federal Reserve Board need thesedata for some of the projects
that they work on.
But what the Census Bureau doesis, each quarter, they ask
about 7,500 manufacturing plantsIf you're operating below your
essentially full capacity, andthey define that basically as if
you had normal conditions youknow normal, maybe even a strong

(06:54):
market condition and you didn'thave equipment issues.
What are reasons?
Maybe you're not operating atthat level and one of the things
that can be checked isinsufficient supply of materials
, and what you see is this datais really boring up till about
2017.
Folks are saying this 5% of thetime, so it's very minimal.

(07:16):
Then it jumps a little bitduring our manufacturing burst
that we had due to strongcommodity markets, strong global
demand.
That we had due to strongcommodity markets, strong global
demand, from 2017 to 2018, itgets up to about 10% by mid-2018
.
Then we have a manufacturingrecession in 2019, falls back to
like 7% again, and then we getto the good old 2020.

(07:36):
And actually we don't see muchexciting happening in 2020 until
about Q4.
But then we get to 2021.
And, starting in the firstquarter that year, this series
just takes off.
It goes from 15% all the way to25%, and that first quarter of
the year was when we had thathorrible polar vortex that

(07:59):
caused massive disruption andchemical production, which
cascaded downstream to plasticproducts and paper products, et
cetera.
And then this series just keptgetting worse and worse and
worse.
It reached a peak in the fourthquarter of 2021 of almost 45%
of manufacturing plants sayingthat a lack of materials was a

(08:20):
reason they weren't producing asmuch as they could have.
Again, pre-covid, that numberwas a peak of 10%.
So this is 4x worse.
First half of 2022, things arefairly rough, but then things
started to improve, you know,essentially smooth and steadily,
all through 2022, through 2023.

(08:40):
And the data point that for me,was the most interesting was
going to be the first quarter of2024.
Now there's about a 75-day lagbetween the end of the referent
quarter and when these data arereleased, so we got these data
around June 16th or so,somewhere in that space.
I was honestly expecting anuptick a little bit with the Red
Sea crisis, panama Canal waterlevels and all of these things

(09:05):
crisis, panama Canal waterlevels and all of these things
but we actually saw a nice dropagain to bring the series down
to 10%, which is the lowest it'sbeen since the fourth quarter
of 2020, and actually comparableto the second and third quarter
of 2018.
And the reason I say that theseideas are important is one was
a concern I'd always had withthe Census Bureau data was maybe

(09:25):
we had primed people to thinkabout insufficient supply of
materials and I'm like they'rejust always going to check this
box more than what they didbefore.
Well, that doesn't appear to bethe case, because certainly, if
we had primed people, theyshould not have been checking
that box less in the firstquarter of 2024.
Checking that box less in thefirst quarter of 2024.

(09:49):
But it also just shows that,even with all the discussion of
the Red Sea crisis andeverything else, we are not
seeing anywhere near the type ofdisruptive effects that we saw
in 2021, which really then makesus think okay, we see container
spot prices today are at levelswhere they were actually at in
the first half of 2021, butwe're not seeing anywhere the

(10:10):
same type of disruption, and sothat just forces us, as we think
as academics or as managers, tounderstand what is it about the
current situation today that isso different?
Because, clearly, this is notaffecting plants receiving
inputs, and a lot of what we dobring in in containers is an
input to a further productionprocess.

(10:30):
And so this data it took me alittle bit by surprise, and it's
very precisely estimated by theCensus Bureau, and so we know
that this is basically 10.3%,plus or minus about one
percentage point is basically10.3%, plus or minus about one
percentage point.

Dr. Matt Waller (10:49):
That is amazing and of course, your other chart
verifies this in a differentway.

Jason Miller (10:55):
Looking at transportation logistics
constraints yeah, we see theexact same pattern emerge.
I mean, these two seriescorrelate something like 0.98
with each other, meaning it'sjust shocking how much these two
ideas seem to track together.
And again, though, we see, Ireally thought this one would
bump up a little bit in thefirst quarter, but we, again, we

(11:17):
didn't see that.
And again, for perspective,we're not saying things are back
to 2014, 2015 levels.
They're not.
They're still runningsubstantially above where we saw
back in those days, but we'renot seeing anything like the
disruptions we saw in 2021,which, again, I receive a lot of
questions.
Well, ocean spot prices are sohigh.

(11:38):
What does this mean for inlandtransportation?
It's like.
Well, the answer right now isreally nothing, because it's a
very different dynamic of whathas caused the increase in
demand today, from a carrierstandpoint, versus what it was
in 2021.

Dr. Matt Waller (11:54):
So, Jason, here we have another graph, and this
is DAT dry van contract andspot rate with fuel surcharge
included.
And so the red line and this isover time, from 2013 to present
the red line spot and the blackline is brokerage contract, I

(12:19):
believe, and then the prices areon the vertical axis and then
the prices are on the verticalaxis.
So, first of all, would youtell us a little bit about DAT
data and then explain what we'reseeing here?

Jason Miller (12:34):
So DAT Freight and Analytics is a large data
provider in the trucking spaceand what they do is they have
data for spot pricing and sospot pricing in the trucking
sector and specifically truckload operations so a shipment
going from point A to point B,typically 30, 40,000 pounds of

(12:58):
freight.
On that A spot price is aone-time price negotiated
between a shipper and thecarrier for transportation on a
lane, and so spot rates make upsomewhere in between 10% and 20%
of how loads are priced.
But they shift very dynamicallybased on market conditions.

(13:20):
So we'll often say spottruckload rates are the canary
in the coal mine in terms ofwhere the market is going.
And this is specifically fordry van truckload operations,
which is moving essentiallygoods in a standard van type of
container.
And what we see here over timeis essentially multiple market
cycles.
That occurred is essentiallymultiple market cycles.

(13:42):
That occurred, and we saw abull market in really the back
half of 2013, first half andthen all through 2014, where a
bull market means conditions aregood.
From a carrier standpointthey're bad.
If you're a shipper, then youknow.
So spot rates go up during bullmarkets 2015 and 16, spot rates
go down.

(14:02):
It was a bear market.
We had then this very strongbull market, starting kind of in
the middle of 2017, lastedthrough most of 2018.
Then we had this bear market in2019.
You'd see spot rates go downCOVID hit.
We went from rates plungingbecause we had this massive drop
in freight demand to taking offon the other side, primarily

(14:26):
not so much because of totalfreight demand being so strong
like it was in 2017 and 2018,but a unique dynamic whereby,
once COVID hit, you saw somefirms have huge surges of demand
.
So canned food manufacturersmay see demand increase 50, 60%

(14:47):
and in truckload operations thatis actually very bad.
If I'm a carrier, so this isgoing to sound very different to
folks who may think aboutmanufacturing wanting to run
their plants as much as possible, because if you go from A to B,
you then need to go either Bback to A or you need to go B to
C, etc.
And so you plan to try to havesome type of balanced freight

(15:10):
network so you're not runningyour trucks empty and you're
making no money.
So all of a sudden, if I have asurge of 50% on that A to B
lane, that actually is achallenge because I now need to
have 50% more freight out of Bto get me elsewhere.
And so when COVID hit, freightnetworks got thrown completely

(15:33):
out of whack.
If Home Depot is selling 10%15% more goods than they were
before, whereas steel mills areproducing less at the same time
by 10%.
And so everything went out ofwhack.
And what this did is it put alot of freight on the spot
market because carriers withwhom shippers and contracts
would say I can't haul thisstuff because my network is

(15:53):
imbalanced, and so a lot offreight gets what we call
rejected.
At that point, a shipper has tofind capacity to move it, so
they go and get one off pricing.
Find capacity to move it, sothey go and get one-off pricing.
So spot rates went really highall through the rest of 2020.
And there was also demandincreasing.
Manufacturing turned back on.
We had very strong imports.
Then it actually felt like thespot market was normalizing a

(16:17):
little bit.
We had the February 2021 polarvortex.
But then the big thing was theMarch 2021 stimulus caused this
incredible surge of spending,and not only did that drive more
freight demand, we also saw acommodity market surge start to
take place, which increasesdemand for things like fracking.

(16:38):
We had housing activity 20%higher than it was before COVID.
At this point, that's moreloads of shingles and lumber and
washing machines and carpetsand everything that goes into a
house, and so just the freightmarket was incredibly strong in
21.
Not surprisingly, spot rateskept going up.

(16:58):
It's also important to remembertrucking saw a big drop in
payrolls at the onset of COVID,and so we were trying to serve
more freight demand in 2021 thanthere was before COVID with
less payroll, and so that isitself going to be challenging.
But then what happened was early2022, once we got past Omicron.

(17:18):
We essentially had had a largesurge of capacity enter the
market, just as we would expectfrom basic economics, and then
demand started to cool as theFed raised interest rates,
housing starts turning down, alot of manufacturers had ordered
too much raw materials, a lotof manufacturers had produced
too many goods, and so all of asudden, freight demand starts to

(17:42):
cool and then started todecline by the third quarter of
the year.
Supply kept coming into themarket.
These spot rates just startedplunging and they have been
plunging.
Essentially.
They reached sort of a bottomaround actually about a year ago
, almost in sort of May and Juneof 2023.
And we've just been movingalong essentially a trough since

(18:02):
then.
We saw a little bit of a surgein January of 2024 because of
the extreme cold.
Then we dipped down again.
Right now we're neutral yearover year, which what's funny is
I mean with inflation andeverything else.
This neutral year over year andconsidered to be very weak
market conditions is actuallynear where the highs were in

(18:24):
2018, believe it or not, we'rewell above where we were in 2019
, but it feels like very muchsort of a bear market.
And we've been in a bear marketnow for this extended period.
And what you'll see, looking atthat broker by contract rate,
and what a truckload broker doesis they'll go to a shipper and

(18:44):
say pay me X amount to and Iwill find you capacity to move
that load, and then the brokergoes out and finds capacity,
hopefully below X amount.
That way they make money for itand what we'll see is that
black series will track the redseries very well with a little
bit of a lag, but it's almostalways above it.

(19:06):
When it's not above it or thetwo series are close.
That actually is a veryinformative piece of information
that we'll talk about here in asecond.

Dr. Matt Waller (19:16):
I'll go to the next slide so we can talk about
that and here the metric is thedifference between the spot and
contract price divided by theaverage of the two, so it's kind
of like the percentagedifference between the two in a

(19:37):
way.

Jason Miller (19:39):
Exactly, and this metric has been very, very, very
effective at sort of predictingwhen the market's going to turn
, and the magic threshold seemsto be 10 percent.
I've got that drawn in here.
I don't know why it's 10percent, so this is one of those
that there's an underlying.
I don't can't really tell youwhy it's this magical 10 percent

(20:01):
threshold.
It's this magical 10% threshold.
But once we see this ratio getaround 10%, that tends to be
indicative of the market eitherturning really strong for
carriers or, conversely, turningweak.
And what I've done is justhighlighted some key dates to
think about.
Okay, when would a freight bullmarket start?
Those are in black.

(20:22):
So, for example, june 2017feels like we enter a bull
market.
It's the last you know.
After that, we drop down tothat 10% threshold by January
2019, we're above 15%.
We're in a bear market.
June of 2020, market flips overApril 22,.
It flips back.
The key thing is right now iswe're nowhere near, apparently,

(20:45):
flipping back yet, and this hasbeen one.
I've been probably one of themost bearish individuals on the
prospects for the dry vantruckload sector over the past
six to eight months.
A lot of that is.
There's been this historicalbeliefs that market cycles
completely change withintypically two, at most three

(21:07):
years, and so this idea that wecould have a two plus year
freight recession was not reallyregistering in for folks who
believe, well, the cycle willonly last X, y, z as long,
whereas I take a little bit moreof a what's the underlying
fundamentals of supply anddemand?
And right now, the underlyingdemand fundamentals are not such

(21:28):
that I would see some type ofsurge of freight happening soon.
That would get us out of wherewe are.
So my general view is you knowthis is an election year.
It's a highly consequentialelection policy uncertainty out

(21:48):
there right now that I don't seefirms making the major capital
investment decisions through therest of the year.
We're not seeing the Fed cutinterest rates, which would help
spur home building activity andresidential fixed investment
activity.
That generates a lot of freight, and we're never going to see
fracking activity in the UnitedStates like we did, let's say,
back in 2014, not because ofgovernment policies, but just

(22:10):
because the underlying economicsare completely different and no
one is willing to essentiallyfund fracking companies just
going out and drilling likethere's no tomorrow, like they
did in 2013 and 2014.
We're never going to do thatagain today.
And so there's just not thosedemand drivers right now, from
my standpoint, that really areset to turn the market anytime

(22:34):
soon, and certainly not quickly.

Dr. Matt Waller (22:36):
You know I'm going to back up a second here
and just make a note forlisteners.
I've already mentioned that youmake posts every day on
LinkedIn that include thesekinds of analyses, but many
times you talk about rules ofthumb or fallacies that people

(22:57):
believe and you demonstrate howthey are fallacies or folklore,
and the data really is what theyshould be looking at and you
show how to do that.
The other thing I noticed thatwas interesting on the previous
graph we were talking about thisbig increase that we saw after

(23:22):
2020.
You know you mentioned a lot ofthe increase was the result of
the stimulus right and I totallyagree, but it's interesting.
I have watched the news andread articles over and over
where, jason, they don't sayanything about that.

(23:45):
They just say the supply chainbroke.
It's like I don't understand.
Either they're not trying tounderstand it or they have an
agenda, I don't know which it is.

Jason Miller (23:58):
That has been for me such a frustrating thing
because there is no doubt thatsupply chain glitches that we
had in 21,.
It created, I think, amentality among buyers to
essentially want to obtainwhatever they could obtain.
We certainly saw things likemotor vehicle prices that

(24:19):
consumers paid went through therough and a lot of that was
because the dealers were able tocharge more because demand was
really strong and supply was lowbecause of chip shortages.
But the thing is is basiceconomics.
Why was demand strong?
And it was because we gave,effectively, most adults in the
United States $1,400 checks.

(24:41):
We still had expandedunemployment that individuals
were on.
We did stimulus like we'venever given before and folks
were not conservative and savingmost of it.
They went out and they spentmost of it and they were
spending it heavily on goods,not on services.

(25:02):
Because you couldn't go to aTaylor Swift concert Right now.
I mean, if you think about thisright now Taylor Swift tickets
you're lucky if you're payinganything less than $3,000 per
ticket right now to go see therest of the Aris tour.
Think about how many goods$3,000 buys.
And so you had folks spendingmore on goods during this time

(25:26):
period.
You had freight networksdiscombobulated.
I've heard stories in 21 ofcompanies making food products
that have regional networks.
So you'll have a plant herethat ships to this region plant
here they're out of stock and sothey're sending a truckload of
crackers, as an example, fromWashington State down to Atlanta

(25:47):
, georgia, because they can'tstock out a key customer.
And you know, that's one whereI put on my freight end and say
you send a truckload of crackers2,500 miles at $3.25 per mile
spot rates, yikes, wowza.
And so that was happening.
But to me the ultimate issue ishow much money did we give out?

(26:13):
And that's where Dean Croke atDAT Freight and Analytics I
remember he and I talking inJanuary of 21, so before the big
March stimulus, and we bothkept saying you know, maybe the
market is about to get around tonormalize, because things were
starting to cool a little bit.
And then we had these two bigrounds of stimulus and that sort

(26:34):
of set everything off, and soat the end of the day it was
really a demand story, and youcan always think about it that
if demand doesn't go through theroof, then you're not going to
have all of these supply chainglitches occur, because if
demand isn't high, companies canwork through disruptions a lot

(26:55):
easier.
Demand isn't high.
Companies can work throughdisruptions a lot easier.
That's what we're seeing today,why issues like the Red Sea
crisis are not causing rampantshortages on retailer shelves.

Dr. Matt Waller (27:06):
Absolutely, ed.
You mentioned Taylor Swift, andI know you've said before that
your daughter is a big TaylorSwift fan, and I've always
wanted to ask you is she aChiefs fan too, though?

Jason Miller (27:26):
Not really.
She's still figuring outfootball.
She's much more.
You know ballet and things ofthat sort.
So I'll admit I'm not a bigsports fan, so I'll watch.
I'm not a big sports fan soI'll watch maybe the Super Bowl
when it comes to football, butthat's pretty much like the one
game a year that I'll actuallyturn on the TV.

Dr. Matt Waller (27:45):
Let's go to the next set of graphs, and here we
have quarterly containerizedexports of US manufactured goods
to the world, not includingCanada and Mexico, and it goes
from 2002 to present.
So this is a lot of data andit's pretty interesting.

(28:06):
And then down below, you'vebroken it out into the sectors,
which is really nice, and theinteresting thing you put in the
far right-hand column, titled2023 minus 2018, is the

(28:26):
difference between the two, soyou can tell which ones have
increased the most, which oneshave decreased the most, which
ones have stayed the same.
But, going back to the originalgraph, what's the story you get
from this?

Jason Miller (28:44):
Yeah.
So a couple aspects of thestory to me, and that is sort of
one just a strong secularincrease up until really 2018
and 2019.
We did have the COVIDdisruption, but we also had the
tariff war start to take place,so we can't overlook that.
So the strong secular increasein exports, of course, barring

(29:07):
the crash that was the globalfinancial crisis, and then just
the dip in 21, 22, and 23.
Now, part of 21 was demand wasso strong in the US.
Everything was going to thedomestic market, so a good
example of this was plasticresins, so some of the things
like Dow Chemical makes as anexample.

(29:28):
Because of the polar vortex andbecause of incredibly strong
domestic demand, everything wasstaying domestic and what
happened was exports plunged.
The only stuff that gotexported was charged,
essentially a very, very, veryhigh rate.
So part of it was strongdomestic demand.
But then 22, 23, justessentially just weak demand in

(29:53):
general from around the globe,especially in 23, kind of the
bottom of that, and we have seena little bit of an uptick now.
But I mean, when you're talkingthese numbers, 20 million
metric tons is an incrediblylarge number when you start to
think about that.

(30:13):
When you start to think aboutthat, and even though we don't
talk about the US as a you know,a manufacturing you know
manufacturing export powerhouse,we still are the world's second
largest manufacturing country.
China is larger, but it's thatus is a very clear number too,
and so you start thinking aboutthese numbers like 2 million
metric ton difference.
That's thousands and thousandsand thousands of fewer

(30:37):
containers of exports, and thisis just what's going in a
container.
This isn't the bulk stuff thatwe send, and so it's to me the
story of it's an additionalheadwind on domestic
manufacturing.
But just to put numbers inperspective, from the Commodity
Flow Survey, 97% of what isshipped out of US manufacturing

(31:03):
plants that moves by for hiretruck is domestic destination.
Only 3% is exported, and you'restill getting numbers here that
are in 20 million metric tons,I mean.
So it just it puts the size ofthe US economy and what we make

(31:24):
here in perspective.
But you know the dollar'sstrong right now.
Still, demand in Europe remainsweak, and that's, I think,
what's setting things sodifferent from, let's say, 2016,
which was a weak year, but thenwe have this really strong 17
and 18.
It was essentially the globaleconomy was very strong, and

(31:47):
we're just not seeing that rightnow we have China manufacturing
so much, trying to essentiallyprop up the economy because
they're having such issues onthe real estate side, but Europe
is in general in a weakeconomic condition right now.
You have the United Kingdomhamstrung with Brexit, you have

(32:07):
Germany that is still nowherenear recovered from the energy
shock that they experienced onceRussia invaded Ukraine, and you
know the European economy isnot doing that strong right now.
The Wall Street Journal justhad an article today talking
about the one bright spot forSouthern Europe.
Is funny enough Americantourists going over there and

(32:28):
spending money, which I can'thelp but start thinking, hey,
could that have just an ever soslightly small hit on domestic
demand for goods here in theUnited States.
But that's, I guess, adifferent story and would take a
lot more data analysis, but avery interesting one.
Yeah, it's.
You know the US.
We have been really kind of theshining light in terms of the

(32:52):
developed countries since COVIDand I think a lot of it is due
to how much we stimulated.
So this is this pro and con.
Right of intense demandcertainly caused some inflation,
but that intense demand was dueto stimulus that has helped
elsewhere.

Dr. Matt Waller (33:10):
Would you like to say anything about these
differences Like, for example,food and Kindred products took a
huge hit there and it's thesecond largest containerized
product.

Jason Miller (33:25):
Yeah, no, it is.
So.
You know, food prices in the UShave went up tremendously, but
some of this, as well asretaliatory tariffs.
We've always been a major foodmanufacturer.
The one really on a percentagebasis to emphasize is paper, and
that is an industry that peoplejust don't think about as the
average American in the UnitedStates.
But paper manufacturing is ahuge generator of freight and

(33:50):
it's a huge export category.
It bats so much above andbeyond what you would think
about as a manufacturing sector.
This piece that's, I don't evenbelieve, 1% of GDP.
I think paper manufacturing islike half a percent of GDP, but
it is one of the biggest exportsectors that we have, on a

(34:15):
weight basis, or a volume basis,if you want to think about it
that way.
And in general, we've seen ahuge global downturn in paper
production, not only in theUnited States, but in Europe.
In Germany, it's a big paperproducer.
Their production's down 20%from where it was in 2018, kind
of akin to where the US is at.

(34:35):
And you know some of theseother sectors too.
You know wood products.
No real explanation for thatspecifically, for why we would
be down as much as we are, otherthan one of my thoughts would
be wood, that especially thingslike chips and whatnot that go
overseas to China as an example.

(34:55):
But just in general you can seethe story of just exports down
really across the board acrossmost major manufacturing sectors
.
The one that is up slightly ischemicals and a good chunk of
that is plastic resins and ifyou take a look at let's say

(35:20):
Europe's energy cost surge makesUS exports more attractive,
even with a strong dollar.

Dr. Matt Waller (35:22):
Well and petroleum and coal.
While it's not one of thebiggest, percentage-wise, the
decrease is quite remarkable.

Jason Miller (35:29):
Yeah, it is, and this is just so everybody
understands.
When we say, manufacturepetroleum and coal products,
this isn't crude oil, this isstuff that is even going into a
shipping container.
So this could be things likegreases and things of that sort,
and we had seen a huge surge in2018, 2019, part of 2020, and

(35:52):
then we kind of dropped back.
That would be one.
Somebody who really knows thatspecific part of the world would
have to really dive in and beable to say, like this is what
was going on over that periodthat was spurring this demand.

Dr. Matt Waller (36:07):
Well, if anyone knows, please put your.
You can make a comment in theshow notes and.

Jason Miller (36:16):
I'll share it, please.
I am very curious to know thatone too.
I just don't have time to digin.

Dr. Matt Waller (36:23):
Well, and so this next graph is seasonally
adjusted trucking 10 miles.
Seasonally adjusted index towhere 100 is equal to 2017.
It goes from 2017 to presentand, of course, it also has this
huge change around to 2020.

(36:46):
So could you explain this?

Jason Miller (36:48):
Yeah.
So this index and this is notjust my product, this is also
something I co-authored withYamboy Molle, who's the writer,
endowed professor at theUniversity of Tennessee and
great friend to both of us.
Academia is a very small worldfor anybody listening,
especially in the supply chainspace.
But what we do with this indexis we know from the Census

(37:09):
Bureau doing this thing calledthe Commodity Flow Survey.
We know essentially whatindustries account for the most
demand that for hire truckingcompanies move and in declining
order of sectors, it is foodmanufacturing is about 15
percent, chemical production isabout 8 percent, 9 percent,

(37:33):
believe it or not, quarryingactivity and hydraulic fracking
is about six percent.
So you see all those dumptrucks on the road.
It's like six percent of whattrucks move is just literally
bulk aggregates and things forfracking sites and whatnot.
About another than five percentis this non-metallic mineral
product category which is likebricks and clay refractories and

(37:57):
glass and cement and concreteblocks and things of that sort.
And then, believe it or not,it's paper is up next and you're
probably saying but wait aminute, what about stuff I buy
from Amazon that's way down onthe list, stuff even Walmart
shipping from their warehouses.
We got to go down a couple moremarks to get to that, and so

(38:17):
trucking is really veryindustrial oriented, as you're
kind of picking up on this.
And so just with thatbackground 2017 through mid 2018
, we have a very strong growthin trucking output.
From a historical standpoint, wesee demand increase by about 5%
, but we're in the middle of acommodity market boom, so a lot
more fracking activity.

(38:38):
Construction activity wasreally strong, food production
was going up.
Basically everything was firingreally well and the global
economy is doing there's a bigdrop in January of 18.
That's the polar vortex ofJanuary of 18.
It was like zero degrees.
Up here is a high in Michigan,which we're used to cold, but
even that for us this is cold.

(39:00):
But then by the end of 2018, westart to dip down.
A lot of this was retaliationdue to the Trump tariffs.
There's just overwhelmingevidence that those tariffs have
been very counterproductive tothe US economy.
So we go down into a freightrecession kind of sort of move
along a trough.

(39:20):
It looked like we were climbingout in the middle of 19, but
then we had an auto strike.
So that's when you can blamethe state of Michigan
predominantly and GM.
It put us back into a deeperfreight recession, moving along
again.
This trough COVID hits.
I have to truncate the graph,otherwise we lose all the detail
, because freight demandplummets almost 15% with the

(39:43):
April lockdowns.
Then we come roaring backthough, and actually by the end
of 2020, freight volumes wereback to where they were in 2019,
believe it or not.
Then that huge drop, you see, isFebruary 2021.
That's a polar vortex.
That's like 3% of freightdemand gets wiped out.
And then you just see we comeabsolutely roaring out of that

(40:08):
Some of the strongest growth offreight we've ever seen.
It was actually almost doublethe pace of the growth we saw in
17 and 18.
So back half of 21 into thefirst part of 22 is just this
incredible period for freightdemand.
Then we kind of hit a peak.
That highest point is March of2022.
And that corresponds to whenthe Fed starts raising interest

(40:29):
rates, and then we have stillpretty high activity.
And then that first drop, yousee, is September of 2022.
We start to go down.
We have a deep polar vortex inDecember 2022.
You're starting to see a themehere about extreme weather
events and demand for truckingfreight, which is really because
manufacturing gets hit andreally since then we have just

(40:52):
been going down, then we havejust been going down and we've
been basically in a trough andmoving along a trough really.
Since about the I'd say, latethird quarter of 23, we had
another dip, that's january 24again polar vortex a little bit
of a bump up in february andmarch down in april, um, kind of

(41:12):
though, I'd say just in general, moving flat.
This is just because, bluntly,manufacturing activity in this
country is not doing that great.
Wholesaling activity is notdoing that great relative to 22.
But again, it's worthemphasizing, freight demand is
above where it was in 2019.
So it's not like we're in thisdeep recession, but we're down
from those highs and especiallythat torrid growth that we saw

(41:36):
in the back half of 2021, whichwas, to be very clear, not a
sustainable trajectory to be on.
The only other time we were onthat trajectory was actually
2004 through 2006, in the midstof our housing boom, and we all
know how that ended two yearslater.
Very interesting.

Dr. Matt Waller (41:52):
That ended two years later Very interesting.
So this next graph looks at icecream and frozen dessert.

Jason Miller (42:06):
This is one of my favorites because I love ice
cream.
Mine too, mine too.

Dr. Matt Waller (42:12):
But you know, this is more.
You really see the seasonalityin this, I think.

Jason Miller (42:20):
Yeah, no, exactly, and this is one of those ones.
So some of the content I try toput up is, you know, sort of
very serious Where's the marketat?
Other of it's just kind of likerandom things that I see.
Looking at the data that I maythink would be interesting.
And one of the things we talkabout is almost all of the data

(42:41):
presented to us by the CensusBureau Bureau of Economic
Analysis and gets reported bythe media is what's called
seasonally adjusted.
So we try to take out thatregular temporal fluctuation
that we know happens each year.
But when you think about being asupply chain manager, you don't
move seasonally adjustedfreight.
You move not seasonallyadjusted freight, and so this is
just to give folks aperspective.

(43:02):
Of course the summer months,but there's these big gaps
throughout the year.
So you may have production up25%, 30% in June from the yearly
average, but it's down 25% inJanuary, and it's just to

(43:26):
highlight just how seasonalthings are.
And what I tend to find is thatwe don't think about
seasonality to the degree thatwe should.
Is that we don't think aboutseasonality to the degree that
we should is you start thinkinglike okay, and of course ice
cream is going to requirerefrigerated trailers so it may
not fit as well in a context ofa carrier only doing that.

(43:47):
But if you're a fleet and youhave a mix of, you do have some
refrigerated and you haul icecream, you may have fruit and
vegetable preserving.
Peak season there is a littlebit later.
It's kind of this July, august,september, a little bit into
October peak, and so it sort ofcounterbalances.
So you start thinking abouttargeting shippers and saying,
hey, I want a little bit of thisbecause right as this season

(44:11):
maybe starts to cool down, thisseason is going to pick up a
little bit and again it helpswith your planning.
I used to work at a picklefactory and I was seasonal.
Labor started working themoment baseball was done in the
summer, which baseball ended inJune.
We typically weren't goodenough to make it on far enough
in tournament.
I needed to worry about July.
Guess what?

(44:31):
I worked July and August upuntil when school started in
high school, and then I was done.
But that was peak months inthat sector, working in
Northeast Indiana.
And the one thing that has beeninteresting is a lot of sectors
in manufacturing haven't beenas seasonal as normal since
COVID hit.
I do wonder to what extent thatis lack of seasonal labor and

(44:53):
we may start to see them returna little bit, what extent that
is lack of seasonal labor and wemay start to see that return a
little bit.
But you can see that in thissector that the normal big
seasonal fluctuations that wehad happen, they've been absent
since the COVID pandemic hit,certainly in 21 and 23.

Dr. Matt Waller (45:09):
So this graph is the number of non-employer
businesses and general freighttrucking long distance, and
we've heard you've shownsomething like this a few times
over the past year.
What do we gather from this?

Jason Miller (45:29):
Yeah, so kind of to take a step back.
One of the challenges withtrucking is the vast majority of
industries in the economy whatwe call employer firms, so firms
with employees make up the 98plus percent of activity.
So take motor vehiclemanufacturing there's nobody out

(45:51):
there building cars in theirshop by themselves.
That matters from an economicstandpoint, and the reason I say
this is when you think abouthow the Census Bureau and Bureau
Labor Statistics have to devotetheir resources.
There are approximately 12million locations in the United
States, so what we callestablishments that have at

(46:14):
least one employee.
In the United States, so what wecall establishments that have
at least one employee, there'sanother 30 million non-employer
businesses.
So this would be literallysomebody operates a sewing
operation out of their housejust them.
Sewing together pillows rightJust them.
They buy the material, they doit themselves, they sell it on
Etsy and whatnot.

(46:34):
The reality is, the CensusBureau doesn't care very much
about non-employer firms.
They're a very small share ofeconomic activity, but that's
not the case in every industryConstruction and especially
trucking non-employer firmsmatter, and they matter a lot,
and so we get a lot of confusionabout how do we think in

(46:58):
trucking, about what the maingovernment data sources
essentially officially track andwe get on a high frequency
because we only get employmentdata from firms with employees
and so the non-employerstatistics is a program the
Census Bureau does through theIRS, so this essentially the IRS

(47:20):
just hands the Census.
Bureau data is how this programworks, but this actually lets us
get a sense of how many firmsare there out there where it is
me myself operating.
I'm not an employee.
I am effectively some type ofowner operator and trucking that
could typically be leased to acarrier or it could be.

(47:41):
I have my own operatingauthority, I run my own company,
etc.
And this data here is justshowing the growth of these
non-employer businesses overtime and in essentially the
over-the-road driving andtruckload space is what we're
focusing on here.
Not that many folks are goingto be doing LTL operations by
themselves, but there will besome, believe it or not.

(48:03):
There's far more firms outthere that operate on a.
Hey, I got one or two trucks, Iconsolidate some small loads
from some shippers here inLansing and I run them over to
Detroit.
There's a lot more people to dothat than just Old Dominion and
SIA and whatnot.
But, to not digress, the vastmajority of this is folks doing

(48:24):
truckload operations.
This is just showing thatnumber has almost doubled since
2012.
And this gets back in part tothe conversations routinely
about a shortage of truckdrivers and saying well, you
know, it's fascinating that ifthere's this massive shortage
and people unwilling to enterthis market.
We've got 300,000 individualsinvolved doing this as their own

(48:46):
non-employer business back in2012.
Man, a steady upward trend toover 525,000 by 2021.
And I guarantee you that numberin 2022 is going to be at least
575.
I wouldn't be surprised if it'snot 600,000, just given lags
that exist.
And so part of this is sayingwell, look, if there's a chronic

(49:06):
driver shortage boy that's notshowing up in that data right
there, that people are unwillingto enter a sector.
They clearly are.
But also, too, the non-employerstatistics.
We do get a sense from arevenue standpoint of roughly
what percentage of truckingrevenue does go to non-employer
establishments and non-employerfirms.

(49:28):
It's roughly 20%, and the goodnews, though, about that number
is it doesn't change over time.
No, that's not what's shownhere, but it just helps us
understand things.
But this chart that you'reputting up here right now, this
is basically saying okay, if weadjust the revenue that we have
for these farms because the IRSagain has revenue data Is it

(49:50):
100% accurate?
Probably not, but it's closeenough.
100% accurate?
Probably not, but it's closeenough.
This is saying okay, we knowthe total revenue.
We know the number of firms.
That gets us a sense forrevenue per firm.
Let's adjust that forsector-specific price changes to
basically get a proxy for realrevenue per firm.

(50:11):
So, in other words, how big isthe average firm?
And what we can see here isthat's interestingly enough,
these are non-employer firms,these are people with firms
without employees.
That number still went downactually 15%, from where it was
a decade ago.
What that's telling you isthere's a lot more people
involved in trucking today atleast on the other side of the

(50:32):
COVID bull market that got in aspart-time folks.
Okay, I'm going to run someloads here, but I may work some
construction here, and that'sjust something that, to me, is
not really appreciated, as thevastness of this sector is
something that we almost cannotwrap our heads around, and
you'll have folks who may runjust a few loads here and there

(50:52):
and they've got another job.
I already mentioned the namebefore, but Dean Croke at DAT.
Dean and our friends Dean's gothis own trucking company.
Dean drives an absolutelygorgeous rig and Dean will go
haul some loads from time totime just because he can.
He was a driver in Australiafor years, but Dean's primary
job is with DAT, and so I don'tthink we appreciate how diverse

(51:14):
trucking is and that some ofthese firms are a farmer who,
hey, they do their farming fromMarch through early November.
You got some time off inDecember, there ain't much to do
.
Hey, I got my operatingauthority, I got my truck.
I'll go move a couple ofholiday loads for the local
warehouse.
And those are folks who areinvolved in trucking, believe it

(51:36):
or not.

Dr. Matt Waller (51:36):
So Jason has.
This is I mean trucking,especially long distance
trucking, and others, even intrucking, have been noted as
being very low concentration,having low concentration.
So is it?

Jason Miller (51:59):
dropping over time .
Yeah, so we'll get data fromthe 2022 Economic Census on
industry concentration next year, because it takes the Census
Bureau a while to processessentially the entire US
economy, which is what wecollect every five years.
But I have no doubt that wewill have less concentration in

(52:19):
that over-the-road truckloadspace than what we did in 2017.
And this is just a sector ingeneral that is very low for
economic concentration andbecause of the economics of this
, there never will be muchconcentration in over-the-road
dry-van truckload operations.
The economics of the sectordon't favor that Versus less

(52:45):
than truckload where there is alot of concentration.
Though, interestingly enough,the failure of Yellow Corp
actually caused the sector tobecome less concentrated,
because Yellow was the thirdlargest player prior to its
failure and how their freightgot reallocated, a lot of it
actually went to the smallerplayers, because FedEx Freight

(53:07):
and Old Dominion Freight Lines,the two biggest players didn't
want a lot of this stuff and soFedEx didn't really pick up much
of Yellow's freight.
So actually that sector thefailure of that company actually
has led to less industryconcentration.
Unfortunately, we won't knowthat till the 2027 economic
census, because Yellow failed in2023.

Dr. Matt Waller (53:30):
So the truckload trucking industry has
always been used as an exampleof an industry that's highly
competitive, close to perfectcompetition, and it seems like
it's going even more in thatdirection.
And I wonder, jason, to whatdegree does just information,

(53:53):
availability and tools that areout there allow this to happen?

Jason Miller (54:00):
So I love the way you framed that, because I view
the over-the-road truckloadspace as almost two distinct
markets.
And I'm going to simplify offof some fascinating work by
Holmes and Stevens and economicswhere they talk about industry

(54:20):
structures, kind of havingtypically a small number of very
large generalists that play tothe big market.
And you have that.
You've got your JB Hans andyour Knight Swiss and your
Warners, those firms.
I view that's not perfectcompetition at this point.
This is monopolisticcompetition with a high
substitutability factor.
I mean, if Knight Swift decides, hey, we're going to charge 30%

(54:44):
more, they're going to lose alot of market share really
quickly.
But those firms are serving thelargest shippers, they're
providing asset-based capacity,they're competing really only
with each other, they're notcompeting with the mom and pops.
So we then have this tertiaryor the secondary market of the
smaller players and I mean again, this is a continuum I'm really

(55:06):
oversimplifying but just sayingbig boys and girls and really
small players, and obviouslythere's a lot of firms in
between.
So it's really a continuum, butI'm thinking about it from that
sort of two extremes.
You then have the small players.
I think a unique dynamic thattends to be missed is there's
this assumption that these smallplayers are primarily spot

(55:28):
market based, and they're reallynot Most of them.
If you've got four or fivetrucks, you still have
contractual relations withshippers to get most of your
freight and some colleagues ofmine and I we've published
research using industry datashowing this.
But you're not serving ProcterGamble.
Not to be mean, p&g don't careif you got five trucks, but some

(55:48):
small manufacturer in Sydney,ohio that is a one plant
operation that ships out 10truckloads of freight a week.
They care to have a smallcarrier who probably has got an
operation in the Sydney Ohioarea.
The managers and owners knoweach other and you've got some
type of in a lot of caseshandshake agreement for what

(56:11):
you're doing for these rates,right, and so these small
carriers will have a decentportion of contract freight,
typically with small shippers,and then they'll go to the spot
market to get their backhauls.
Now what has changed over thelast 30 years was 30 years ago
that spot market was not thatrobust.

(56:31):
Brokers essentially almost werea bad terminology, like I mean
brokerage versus now shipperssay I strategically need brokers
in my routing guide to get mecapacity on low volume lanes, on
inconsistent lanes, et cetera,and so what's happened is that
these small players are betterable to find those back calls

(56:53):
than before and they're not sotied to that set of anchor
shippers that they used to be.
And we see this show up,actually, in a paper that was
just accepted in Journal ofBusiness Logistics with one of
the alums from your wonderfuluniversity, jonathan Ferris, as
a matter of fact, where one ofthe things we picked up and it

(57:14):
was almost as an aside was therate that trucking companies die
is much lower today, and it wasmuch lower by 2018, 2019, and a
downward secular trend than itwas in the 1990s.
And so it sounds weird to saylike trucking companies don't
die as rapidly as they used to.
But this really showed up andthis was secondary to the paper,

(57:37):
but it's like wait a minuteinformation availability, the
ability to have essentially tofind those backhauls, and not
being as tied to that localmanufacturer that if that
company goes out of business,we're done.
But you still see that all thetime in trucking is when you
hear these announcements ofcarrier failures.

(57:58):
Oftentimes it'll be a statement, especially a little bit larger
carriers.
It's going to be we lost ourtwo key customers or we lost
this key account and we can'tallocate 40 trucks elsewhere.
And so while the informationside helps, we can't overcome

(58:18):
again those huge economies ofscope.
That exists that if I lose 30%of my business and I now have
30% of my trucks idle, findingenough freight to make a
sensible network, especially ifI'm regional, can be very
difficult.
So it certainly has helped.
I think it helps the smalloperators start up and maybe,
hey, I'm one or two trucks, I doplay more spot market.

(58:41):
I do well enough, I add thatthird, fourth truck.
Maybe now I can give some localshipper enough capacity.
They'll give me somecontractual business.
But this is an area we need atremendous amount more research
for it to really get a sense andunderstand this.
Because we know from the CensusBureau there's about 155,000

(59:01):
trucking firms across all partsof the sector that have at least
one employee.
That's a really big ocean tostart to figure out some of
these nuances responses.

Dr. Matt Waller (59:20):
Jason, before we go to the next slide, I want
to talk just a little bit aboutan article I read that just came
to mind that you had written.
You were the sole author on it.
It was published I don'tremember the date, but it was
published in a journal calledForecast and I thought it was
really interesting.

(59:41):
You were talking aboutbasically how ARIMA models can
forecast the prices rates prettywell.
Prices rates pretty well, andyou know, I wonder a couple

(01:00:02):
things.
I wonder, first of all couldyou give a little overview of
that?
But also one question I had andI forgot to think about this
before the podcast was do verymany firms use ARIMA models to
make these predictions?

Jason Miller (01:00:20):
Yeah, so, boy, that is an article that was an
interesting one to write, man, along time ago I wrote that back
.
Oh man, I think it was 2018, Iwrote it and it came out in 2019
.
Yeah, so, basically the ideabeing, if you want to forecast
both spot and contract rates,your best prediction is

(01:00:40):
essentially what was going onthe exact month previously, and
so a lot of people.
One of the critiques I'll getis people say well, you're only
using backward-looking data.
Now, no offense to everybody,All data is backward-looking
because data from the past.
There's no magical.
Oh well, the market'sprojecting this out forward.
Let's set that aside.

(01:01:01):
But essentially, it's the ideaof you can use prior values of a
series to get a pretty accurateforecast moving forward.
But the thing that wasinteresting was, just as you
would expect, spot market ratesshould be much more transient
than contract rates, and that'sexactly what showed up in the
data and putting some parameterson it, and I'd be curious to

(01:01:26):
actually go back, take thosemodels, parameters, and just see
how they performed in 2020,2021.
They would have a little bit oftrouble, but I think in general
, it would catch up reallyquickly, like it would be off.
You know, we'd be trailing.
What's that, ned?
So one of those like, maybe ifI get some time and you know is

(01:01:48):
a department head, you've been adepartment head and indeed
getting some time to do anythingis a challenge, but yeah, it
was interesting to see.
In terms of using ARIMA inpractice, I don't really get a
sense that it's probably usedthat much because it is fairly
technical.
But what I always joke withpeople is, on a scheme of

(01:02:08):
technicality, arima dates from1970 is when George Box and some
of his colleagues startdeveloping this statistical
approach.
So this is something that'swhat.
50 some years old now and it'sstill viewed as technical.
I use ARIMA forecasting forJournal of Commerce's Intermodal

(01:02:31):
Savings Index, both thecontract and spot index, and
I'll tell you what a reallysimple model works really really
really well with like a 1% mean, absolute percent error, which
is you know for data.
I'll take that every day of theweek and that's an out of
sample mate prediction for threemonths ahead and it's just

(01:02:52):
again.
A lot of series and supplychain are just typically, in
normal conditions, really darnstable and that really darn
stable piece makes themforecastable, which is then
helps explain why did things goso chaotic in 2020 and 2021.
It was because sort of thesmooth behavior got completely

(01:03:12):
demolished by the shocks that wecouldn't really parameterize
statistically.

Dr. Matt Waller (01:03:17):
Thank you, that's really interesting.
Now we're going to shift gearsjust a little bit here and we're
going to talk about anotherfallacy that people believe.
But before we get into that, Iwant to talk about something
else that you brought up that Iwas not aware of and, I might

(01:03:44):
add, I really like how you useeconomic theory and economic
research and apply it in thisfield.
But so everyone knows about thebullwhip effect and the
bullwhip effect essentially justsays that uncertainty gets
magnified as it goes up theechelons of the supply chain.

(01:04:07):
So uncertainty at the retaillevel gets amplified as it moves
up in the supply chain to theDC level, to the factory level,
et cetera, et cetera.
And there was an article inJournal of Operations Management
a long time ago by Rich Meadors, who's now at Texas A&M, but he

(01:04:28):
was at Vanderbilt at the timewhere he got his PhD.
I think he was at Vanderbiltwhen it was published or it was
from his dissertation, and heshowed yeah, this exists, but if
there's capacity constraintsit's not as extreme as you might
expect.
But you brought up a point.

(01:04:50):
And so when COVID happened andthere was the stimulus, a lot of
people were talking about thebullwhip effect.
But you brought up in a post,also in a paper.
You wrote a paper saying, hey,there's this other effect that's
kind of similar.
That probably is a bigger issueand I think it was called the

(01:05:13):
inventory acceleration effectand you discovered it in an
economics journal, I believe.

Jason Miller (01:05:21):
Yeah, so it's funny.
So the inventory acceleratoractually predates the bullwhip
effect by a long time at least,and this is being conservative.
The concept you can trace itback to 1917 for capital
investment, and as economistswere talking in 1917, they were
viewing inventory as capitalinvestment as well.

(01:05:42):
But for sure 1941, we start tosee the mentioning of this
concept.
And what the inventoryaccelerator is is it's
essentially the idea that whendemand goes up, your absolute
level of inventory will alsoincrease.
And the reason for that isbecause we typically have sort
of target inventory to salesratios or target days to turn

(01:06:06):
inventory ratios, because wedon't want to be turning
inventory too fast, because ifwe are, we're probably stocking
out a lot, we're not providingthe associated service level.
Ask because if we are, we'reprobably stocking out a lot,
we're not providing theassociated service level.
But we also don't want to beturning inventory too slow and
be getting a poor return oninvestment.
So what you'll see is if demandgoes up and if demand goes up

(01:06:27):
very suddenly.
So take what happened againwith COVID.
Think about what happened here.
We've got data for generalmerchandisers up in this chart
and this is inflation-adjustedinventory.
So this data here isessentially controlling for
inflation.
The baseline of 100 is thefirst quarter of 2019, because

(01:06:50):
as of today we have data throughthe first quarter of 2024.
Covid hits and you get sort oftwo effects.
First everybody goes to theWalmart, target, costco and
liquidates pretty mucheverything on the store shelves
in March, and then everythingstops in April and the

(01:07:12):
department stores are all shutdown at this point so they're
included in generalmerchandisers.
So because of this, essentiallythe department stores
practically stopped orderingstuff in the second quarter of
2020.
And I mean you can see this intheir financial data.
Like they just have nothinghardly arriving, so they're

(01:07:33):
liquidating like crazy.
They're just trying to getstuff out.
Like they are convinced thatlike demand is just gone, so
inventories dip suddenly andthey really get drawn down.
Well, demand then gets reallystrong.
Come about June again, whenpeople can go out and start
shopping, and so I don't have onthis chart real sales, but real

(01:07:54):
sales for general merchandisersare going up then at this point
in time.
So you've got inventory reallylow and sales going up to just
get back to where you werebefore you burnt down all of

(01:08:14):
this.
But you also need to getinventories even higher than
before to essentially keepinventory balanced relative to
demand.
And boy do generalmerchandisers do this, and you
can see this ininflation-adjusted inventory
skyrocket Through 21 into 22,.
They go up over 25%.
So this is physical unit stockson hand increased by 25%.

(01:08:39):
Well, the problem is thendemand starts cooling with
inflation and with consumersrunning out of stimulus.
So inflation adjusted salesflatline by early 2022.
And inventories went up way toomuch.
So now we are in a situationwhere we've got a glut and you

(01:09:01):
can see on this chart then thedrawdown of inventories and
we're still almost 12% abovepre-COVID levels.
But that's also because demandis also decently above pre-COVID
levels.
You can see that Walmart,target, costco are selling more
today, even adjusted forinflation, than what they were

(01:09:22):
back in 2019.
No-transcript without realizing, like, wait a minute, that

(01:09:58):
actually isn't what that means.
And so I've always said thatreally, as we think about what's
happened since COVID, thebullwhip really isn't the story.
It's much more this inventoryaccelerator idea, which is
actually the initial idea thatpredated Forrester discovering
the Bullwhip effect in the 50sand 60s at MIT, and then how Lee

(01:10:19):
and folks essentially I'm goingto say, rediscovering it but
popularizing it in the late1990s.

Dr. Matt Waller (01:10:29):
Yeah, that's excellent, you know, and it's
interesting, jason.
So something that happened tome fairly recently and I've
talked to you a little bit aboutthis.
Of course, living in NorthwestArkansas, I'm around tons of
suppliers, because we've gotsuppliers to Walmart.

(01:10:49):
There's like over 1,500 officeshere and the big CPG companies
here have huge offices, some ashigh as 300 people, and they're
not just sales teams, they'retruly cross-functional teams.
You've got all the differentfunctions represented and a lot

(01:11:09):
of them are alumni, and so Iknow tons of them and many of
them live in my neighborhood andso I see them all the time and
I'm always talking to them aboutthese kind of things.
I'll tell you a theme that cameout.
It was really interesting we'renot doing a good enough job of

(01:11:34):
selling, you know, because theretailers aren't ordering as
much, right, not just Walmart,but all of them, okay.
So that's a backdrop.
I was at another event wherethere were a lot of senior
retail executives from manydifferent retailers.

(01:11:57):
It wasn't a big group, but,let's say, 10.
And one of the themes wasmanaging inventory is one of the
most critical success factorswe have and we need to do a
better job of it, and soretailers right now in general

(01:12:20):
are really trying to figure outhow to manage retail, manage
inventory more effectively.
So on the one hand you've gotsuppliers thinking we just need
to sell harder.
You've got the reality of theinventory environment on the
other.
Would you mind speaking to thata little bit?

Jason Miller (01:12:40):
Yeah, I mean, you know it's fascinating.
You mentioned that because youknow we're now in a you know I'm
going to say 2021, it was youordered whatever you could,
probably inflated it a littlebit because you were worried
about shortages and we were veryloose on, essentially,
inventory control because youjust wanted stuff to sell,
because, typically, if you hadit, you were going to sell it.

(01:13:02):
Now we're essentially crankeddown the other way as we start
to think about things, and thatfolks are being quite
conservative.
We are seeinginflation-adjusted retail sales
have rebounded.
They are moving back up again,which is a good sign.
Now, the key thing, though, isthey're not growing at the same

(01:13:24):
rate they were growing in, let'ssay, 2014 through 2019.
They're growing at a less of apace now, but that's again
because we just so goosedeverything up in the back half
of 2020, all through the firsthalf of 22, that you're not
going to have the same growthrate, cause we're again
regressing back to the power ofthe long-term trend line.

(01:13:46):
Um cannot be ignored with thisUm, but no, it makes it's
fascinating.
You hear that Cause I thinkthat you know, and it's
fascinating you hear thatbecause I think that a lot of
CPG companies want to go back towhere demand was in 2021.
And it's like we're not rightnow.
That was a unique period inhistory, and that's why I think

(01:14:18):
one of the challenges is how dowe teach everything that
happened with COVID, but alsoexplain to people?
Here's the lessons you reallyshouldn't take from this.
Here's the mechanisms that wereso distinct in this time period,
and I mean that chart that youhave right there, matt just
shows you.
I mean that literally vertical.
I mean that looks like a rockettaking off in terms of how we
build up inventories and thatjust screams right off the bat,
we clearly overordered, whichnow, when you think back to what

(01:14:39):
the suppliers are saying,they're remembering in 21 and 22
, watching all those orderscoming in and saying, well, we
have to go back to that.
Well, if you're drawing downinventory, you're ordering
inherently less than what yourdemand is.
That's the only way,mathematically, to make this
work, and so it's interestingthat what you're describing is

(01:15:03):
exactly what the Census Bureau'sdata would say.
The narrative would likely be,if you're finding value in this
podcast.

Dr. Matt Waller (01:15:10):
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