Exploring the Universe of Hypernomics: From Stock Market Strategies to Side Hustles With Doug Howarth

Send us a text

Prepare for a captivating journey through the universe of Hypernomics and the groundbreaking world of Multidimensional Economics (ME). Our esteemed guest is none other than Doug Howarth, the visionary behind ME and a veteran of Lockheed Martin's Skunkworks. With 31 years under his belt, including managing the F117A stealth fighter production line, Doug offers unparalleled insights.

Doug's firm, Multidimensional Economic Evaluators (MEE) Inc., founded in 2011, brings the magic of ME to giants like NASA, Lockheed Martin, and Raytheon. His innovation in the field culminated in the pioneering software, awarded US Patent Number 10,402,838, designed to deconstruct markets into their 4D structures.

Beyond his ventures, Doug's academic prowess is evident in his 13 peer-reviewed publications spanning four continents. Institutes like IEEE, AIAA, and SAE have recognized his work. With multiple invitations from NASA and the Royal Aeronautical Society, Doug's expertise is sought after globally, from Amsterdam to Belo Horizonte and from Seattle to St. Petersburg.

Back to our discussion on hypernomics— this multifaceted approach has vast applications, be it in sharpening stock market tactics, amplifying restaurant revenues, or gauging product survival in fierce markets. We also join forces with Kyle Loomis, shedding light on the immense potential of AI in crypto trading and unveiling robust conservative trading strategies.

Navigating the tightrope between risk and reward is pivotal in trading. We aim to bridge the chasm between comprehension and application through a promising trading strategies course. As we conclude, we analyze product triumphs and fiascos, emphasizing market comprehension, touching upon topics from tax policies to the economics of homelessness.

Lastly, dive into our community haven—Side Hustle City on Facebook. Here, we ignite the spark for your side passion to flourish into a full-fledged profession. Come along, and let's harness the might of hypernomics and the innovations of Multidimensional Economics with Doug Howarth!

Learn more about Doug:
Websites: https://www.hypernomics.com
https://www.doughowarth.com/ 

Social media:
https://www.linkedin.com/in/doughowarth/
https://www.facebook.com/doug.howarth.37
https://www.instagram.com/hypernomicsinc/@dougkhowarth

YouTube: @hypernomics

As you're inspired to embark on your own side hustle journey after listening to this episode, you might wonder where to start or how to make your vision a reality. That's where our trusted partner, Reversed Out Creative comes in.

With a team of experienced professionals and a track record of helping clients achieve their dreams, they are ready to assist you in reaching your goals. To find out more, visit www.reversedout.com. We also recently launched our YouTube Cha

Buzzsprout - Let's get your podcast launched!
Start for FREE

Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.

Support the show

Subscribe to Side Hustle City and join our Community on
I'm joined by Kyle Stevy, myco-host.
Let's get started, all right?

(00:32):
Welcome back to the Side HustleCity podcast.
Everybody and Kyle Stevy onceagain, you're on like a streak
here, kyle.
It's kind of like Cal Rook andBennett.
I know Kyle's rocking androlling man.
He's here a lot now.
So yeah, doug Haworth, we gotyou here today.
Man, I really appreciate youbeing on the show.
You've got a great backgroundand we're going to talk about

(00:52):
some economics stuff today.

Speaker 3 (00:54):
Oh great.
Well, thank you so much forhaving me Both of you, adam Kyle
, this has really been quite anhonor.
I've been reading quite a bitabout both of you, and you've
done some tremendously inventivethings early on in your career,
so good on you.

Speaker 2 (01:08):
Yeah, yeah, and we try to share whatever we figured
out.
I guess, or pretend we figuredout, or maybe it's luck, I don't
know but we got to make sure wedon't lose our money due to
economic macro events that arehappening, and kind of be able
to forecast things.
And it's not just us or youknow, not people on a personal

(01:31):
level, but this is, you know,this is what governments are
trying to figure out and bigbusinesses are trying to figure
out.
And I mean you've got a veryinteresting background.
I mean it sounds like youstarted out early and you kind
of knew you wanted to be.
You know you were interested inbusiness.
You were interested in a lot ofthings early on.
You've had some health issueswhich you got over, and you were

(01:52):
at Lockheed Martin's Skunkworks, which is wild to think about.

Speaker 3 (01:56):
Yeah, 31 years, and I was running the F117A, the
stealth fighter production line,for a while.
It was the manufacturingprogram manager for it.
So yeah, there's an interestingbackground.
And then I ran their parametricanalyst group so we would
analyze what the markets wereand the cost for things and what
the market would bear for them,things like that.

Speaker 4 (02:20):
Well, I would assume my friend does similar stuff,
for it was a Johnson to Johnsonsubsidiary but they sold it off,
but it was medical equipment.
He was responsible for theimplementation, well, the
patenting and then theimplementation of design at
different warehouses across theworld.
Interesting, Does that soundsomewhat similar?

Speaker 3 (02:41):
It's the same idea, sure, yeah, it's just a
different field.
But the techniques what we doproves the techniques tend to be
are virtually identical acrossevery platform.
So we've discovered thisphenomenon we call hyper,
meaning existing in more thanthree dimensions, inomics

(03:01):
referring to a field of study.
So hypernomics is a field ofstudy that looks at things
occurring in four moredimensions.
And it sounds outrageous, but Iactually got the idea of
watching my wife buy a washingmachine.

Speaker 2 (03:17):
Oh.

Speaker 3 (03:18):
Yes, we were buying this washing machine.
And she said you know, I'd liketo have more capacity than we
have at home in this washingmachine.
So we're staring at one in thisbig box store and she says,
yeah, I want more capacity.
So I got the thinking capacityversus price and that was a
little two-dimensional problem.
And she says, you know, we onlygot one delicate cycle at home

(03:41):
and I'd like to have more cyclesthere.
And I got the thinking cyclesagainst price and now she's up
to three dimensions.
And so we liked this oneparticular machine.
And then there was the next oneup the line that I liked and I
said what about this one?
And it was.
You know, it cost more.
She said it's too expensive, wecan't afford it.
And then I realized that wewere part of the everybody that

(04:03):
was buying the washing machinewere part of the quantity and
price relationship.
So I realized that she wasjuggling four variables in her
head at one time.
And then I just I had thisflash and that's where we went
off to.

Speaker 4 (04:19):
We bought speed queens, and I can guarantee you
that none of that popped in myhead.
I was just like I heard 10 yearwarranty, get me the hell out
of the store.

Speaker 2 (04:30):
There, you go Give me that one.
Well, this is interesting.

Speaker 3 (04:34):
Well, that's what we call a feature.
So, yeah, that's actually.
You were actually doing part ofthat while you were doing that.
And what's interesting is thateverybody kind of works the same
way, just like when you walkinto a room, you don't expect to
see any you know three footmales, you don't expect to see
any eight foot males,everybody's kind of.
You know human beings have kindof congregated to a an average

(04:57):
height for men which is a littlebit higher than women, and then
if you get into specialty units, the average height for a NBA
center is higher still.
And so it works out that inbusinesses and in products that
people relate to how theproducts are, in the same way,
they don't all focus on them onesolid point, but they kind of

(05:18):
have a clumping effect aroundwhat things are worth, and being
able to see that lets youpredict things.
So I know, adam, you'reparticularly interested in real
estate.
So, for example, this thingwould show you what the value of
a commercial real estateproperty is based on the, the

(05:38):
zip code in which you findyourself, which is to say the
income there, then the squarefootage, of course, and then
something that you might notthink about, which is maybe not
you're.
You're both near in theCincinnati area, is that true,
yep, yep?
Well, out here in LA, you'reLos Angeles, I'm just north of
it, the it's sometimes hard toget to other facilities that you

(06:03):
might want to have frombusiness, and so they this, this
one firm, not us inventedsomething called the walk score,
and when you toss the walkscore in on top of the, the
income and the zip code and thesquare footage, you get a really
nice relationship that saysthat in in, at least in LA, in
this part of the town, for thisparticular timeframe, if you can

(06:25):
make it twice as easy to walkto someplace, which is to say
your, your walk score is doubled, your people pay more than
twice as much for thatparticular property.
Oh, wow, yeah, yeah.
And that would be great to know.
If you're in a position inwhich you're buying it or you're
selling it, you, or if you wantto put a new piece of property
in that particular zip code, youwould tell you how best to do

(06:51):
that, based on on on these kindsof you know these phenomena
that happened in the markets.
So that's, that's part of whatgoes on in real estate.
And then I know from readingabout Chula that, kyle, you
still work deeply in logistics,am I correct?

Speaker 4 (07:06):
Yeah.

Speaker 3 (07:07):
I'm still kicking.
Okay, well, in logistics, ofcourse, you're paying for the
weight and the speed and thedistance, and it works out that
you can model that in a way inwhich you can find out the what
something would be worth for anintermediate speed and distance,
and you can find out if your,your product is overvalued for

(07:27):
the the, the service that you'reoffering, or undervalued.
And if it's undervalued, ofcourse, you can raise the price.
If it's overvalued and you hadenough data for how many sales
you had, you could figure outwhat would happen if you were to
decrease the price.
You might make more sales andyou might actually make more,
more profit on that.
That.
This is what this is designedto do Just to be able to beat

(07:48):
out those kind of relationships.

Speaker 2 (07:50):
Yeah, so how do people use this?
And you know, and I know youwork with these larger companies
, but how do you know regularpeople take advantage of this
kind of data analysis thatyou've come up with in their
daily lives?
Like is there, is there, itlooks like you have classes and

(08:10):
things like that that you offer.

Speaker 3 (08:12):
Yeah, we're going.
We don't have them in placejust yet because I just finished
the book that we're going touse for their prime, their
primer on this thing, but we'regoing to be offering some
classes soon.
We have software but to yourquestion, how do average people
use it while there's arestaurant down the street that

(08:32):
I don't know what it's like inCincinnati during COVID, but
here during the initial monthsof COVID nobody could eat
indoors, and here in LA it'sit's warm enough in some of the
winter months for people to sitoutside.
So a lot of the restaurantsmove their serving to outdoors
and of course then they werelimited by the patio area that

(08:53):
they had.
And so this particularrestaurant that we had, that we
to, which we had beenfrequenting for a couple of
decades, at that point, well,the line started going out the
door and you know, it becamepretty apparent that what was
happening here is they.
They had a lot of seats, butthe seats were.
They had two or three, they hadthree tables of six, I think,

(09:16):
and three tables of four, andwhat happened there was the
parties didn't match the partysize didn't match the table size
, and so they were getting a lotof unoccupied.
All the tables were occupied,but not the, not the percentage
of seats that they would haveliked.
So what I did was I suggestedto the manager.

(09:37):
I said look, you need to takeout many of these big tables and
swap them in for tables of oneand two, because that was their
typical.
Clientele comes in and partiesof one and two, and they did,
and their revenue shot up 25% intwo months.
And I did a little moreresearch afterwards and I
discovered that the averageparty size of a restaurant, well

(10:01):
, there's 2.25 times as manypeople parties of two as there
are parties of four.
So you want to have at leasttwice as many tables of two as
you do tables of four, unlessyou're in a family style
restaurant, and that wouldactually max, tend to maximize
your throughput.
And then what the restaurantswant to do is they they don't

(10:21):
want to maximize capacity somuch as throughput, and I'm sure
that Kyle can tell you that,from a logistics standpoint,
that's exactly what you want todo.
You want to maximize how muchyou can carry one day.
You want to maximize how muchis going through hour by hour,
right, sure, yeah, so that thatthere's an example locally.
And then we were interviewed byinvestors business daily four

(10:46):
years ago now and I hadn'tapplied the techniques we had to
that point to the stock market.
So I decided to make a testfund which anybody could do my
own monies into what we call Icall the hypernomics fund and
we've just been drawing stocksonly out of the S&P 500.

(11:07):
And last week we had our threeand a half year anniversary and
we are doing 2.3 times as wellas the S&P 500.

Speaker 2 (11:18):
Oh, now we're talking yeah, so that's the average
person Took it with gas overthere.

Speaker 3 (11:23):
Undervalued stocks?
Yeah, so that's.

Speaker 4 (11:25):
It's not that Pelosi knows what's going to come off.
The soft-she's not working withDoug.

Speaker 3 (11:30):
She's been working with Doug he probably can't
disclose that your informationwas used here.

Speaker 2 (11:35):
yes, but yeah, that would be.

Speaker 3 (11:37):
That would be illegal .
You don't want to do that.

Speaker 2 (11:41):
You aren't getting any tips from her, are you?
I mean there's nothing?
No, I'm not.
Yeah, hey, we're going to.
We're going to buy a wholebunch of airplanes from GE
aircraft.

Speaker 4 (11:49):
You don't need to.
Yeah right, you don't need togo there.

Speaker 3 (11:51):
Well, yeah, Inside information gives you a leg up,
for sure.
But no, this is just.
This is what people would callretail investing.
You know, we don't have anyhigh speed ports or anything
like that, and the tradefrequency is pretty low, and we
could get more improvements ifwe added more manpower to it.

(12:12):
Right now, the manpower is medoing this every month or two,
but we get signals that saysomething is undervalued, and
then we cross-check it a varietyof ways.
So we'll test it multiple timesand, of course, before we
actually engaged this, we didthousands of back tests.
And we were back testing whenmarkets were going up, and we

(12:33):
were back testing when marketswent down.
And when markets went up, theback test suggested that we
would do better than the averagebear would be doing.
And then, when markets wentdown, the same kind of
phenomenon we would lose.
Unless you're Bernie Madoff, ifthe market's going down, you're
probably going to lose.
Yeah, that's right, unlessyou're going to cheat or have

(12:54):
insider information yeah,neither of which we did.
And so we lost when the marketwent down, but not as much as
other people.
So on net, we were doing betterthan other people.

Speaker 2 (13:04):
So are you able to factor things in like Fed rate
increases, the percentage atwhich they increase, and then be
able to apply that?
I mean because this sounds likeyou're taking a lot of factors
and helping that in yourdecision-making process, because
I mean, let's these macroevents that happen rate cuts,

(13:26):
things like that those are goingto affect so many different
aspects and they affectdifferent industries in
different ways, but everybodyhas access to that information
right, like that's the.
But they don't know how toapply it.

Speaker 3 (13:39):
That's what I'm saying.
Sorry, both of you are right.
Everybody has access to thatand not everybody knows how to
apply it.
So the trick is to figure outthe influencing factors.
And that's a statisticalproblem that we would coach
people to say figure out ifsomething is statistically
relevant or irrelevant.
But if it's relevant, then youstart to take the relevant

(14:01):
factors.
So, say, rate increases are arelevant factor or the speed
with which the rate factors havebeen increasing might be a
relevant factor.
One of the things we like withstocks is the MV term, the
momentum term.
So we take the factors that areimportant so we might get We've
had results that are based onup to six independent variables

(14:24):
at one time and what we do is weplug in those six independent
variables and then we'll spitout a list of Again, it's the
S&P 500.
We'll filter out the ones thatdon't have positive results in
some aspects, like earnings pershare or book value.
Everyone that's zero or belowwill exclude.

(14:45):
So you get the ones that arepositive and then you'll get
this list of 300 to 450 stocksthat are viable and then you
drive through this equation andthen you see the ones that are
undervalued and then you test itagain, using different
combinations of these equations,and you test it over and over
and over again.
You might have four or fivetests and then you see if

(15:05):
somebody keeps appearing on thesame list over and over again.
Yes, if they do, then you mightwant to check, say well, why is
this company showing up asundervalued?
Are they under a lawsuit?
Do they have?
Has the major brains of thecorporation left the building,

(15:26):
or are they in danger of beingon a shoreline and being washed
away?
I mean, what's going on withthis institution?
You try to do a little bit ofresearch there, which right now
is hard to automate, but here'swhere I know you've been.
Both of you are thinking aboutcrypto and AI.
So when you look at thepotential for AI that could
actually you could bring in datathat would say what's the?

(15:48):
In fact, there's actually AI insome of these trading platforms
, the retail platforms that giveyou sentiment.
You could actually plug insentiment on top of this.
We haven't done that yet.
In fact, as I'm seeing, I'dprobably be a good idea to do.

Speaker 2 (16:03):
Yeah, google Trends data or something like that you
could cross-reference.

Speaker 3 (16:06):
Yeah, yeah, so things like that.
And then again we back-testedour modeling technique and it
suggested it would work.
So it's doing pretty well andno shorts, no leverage, no fiat
or cryptocurrency trading.

(16:27):
It's all S&P 500 stocks and oh,Pretty conservative.
So we want to eventually not beclear.
This is not open to the public.
You've got to make thatdisclaimer.

Speaker 2 (16:37):
I was going to say because we got some traders.
We got some guys that want toside hustle, do some trading or
whatever.
Well, I mean, you probablypiqued their interest.
We're going to take the course.

Speaker 3 (16:46):
We're going to have the course up in a couple of
months here.
So yeah, the course would showyou what to do.

Speaker 4 (16:51):
What I like about this, and I would love to say
that I'm the resident skeptichere.
But I'm not because.
I think Adam's more skepticalthan I am about a lot of stuff,
even though he's moreopportunistic and happy than I
am.
I would say that I like thefact that you've sold this.

(17:12):
This is not a get rich quick.
This isn't like a bunch ofteenagers in front of Ferraris.

Speaker 2 (17:17):
Yeah, Sound.

Speaker 4 (17:18):
Dogecoin, I did hypernomics and now I'm suddenly
looking at my car.
But it seems like this isalmost excruciatingly
conservative, which is what Ilike about it is the fact that
you run it, you run it, you runit, you run it.
Then you do due diligence asquickly as you can.
Then you run some more and thenyou're not.
It doesn't sound like you'rebuying shares to sell them

(17:41):
within the next 10 days or so.

Speaker 3 (17:42):
No, you're buying a whole lot of them.
The trade frequency is very,very low on this and, to your
point, the returns are good butnot phenomenal.
It's 10.3% since inception.
Better my 401k, so that's notbad, that's pretty good.
Yeah, no, that's great, butwe're not trying to.
Well, I mean, there's thismovie coming out about the
GameStop phenomenon.

(18:04):
We're not trying to race up themarket and do try to game the
market or anything.
Well, yeah, and you're not.
Probably.
I mean, for a movie aboutGameStop is people are gaming
and then putting in all kinds oforders on that market.
But yeah, we're not doinganything like that.
This is something the averageguy me, you, anybody could do.

(18:28):
With a little bit of trainingand a little bit of background,
you'd be good to go.

Speaker 2 (18:33):
So you're probably not buying NVIDIA at 270 times
earnings or whatever they'retrading at right now.

Speaker 3 (18:39):
No, yeah, that's a good point.
We're a big fan of high P&Eratios, so we've looked for
things that are lower than that.
And yeah, I mean Boeing beforethey had the problem with their
737, the ones that went down acouple of times.
They were trading at a realhigh P&E ratio and, in fact,

(18:59):
when you do an analysis of stockmarket, they were way past
everybody else in terms of theirvaluation.

Speaker 2 (19:07):
Well, we got GE aircraft here in Cincinnati.
It's been here forever.
Right, now that GE is breakingup into several businesses, the
headquarters of GE Aviation isgoing to be here, which alone is
a Fortune 500 company by itself.
Oh yeah, right.
And Jeff Immelt, who ran GE foryears, was from Cincinnati, not

(19:27):
far from the GE, from GEAviation, right up on I-75 there
.
So we're excited that a such astable industry is located here.
I mean, we've already got youknow the proctoring gambles of
the world, which, if you're atrader, you know a bunch of
people have that just simply forthe dividend.
And then you've got you knowKroger, which is the largest you

(19:49):
know.
You've got the largest consumerpackage goods company in the
world here.
And then you've got the largestgrocery chain, which is about
to buy Albertsons here shortly.
As long as everything goesthrough, we'll see how that
works out with the SEC and allthose guys, but if that goes
through, that's going to be thelargest grocery chain in America
.
And then you've got, you know,ge Aviation.
You've got Sintos.
I mean there's a lot of verystable.

(20:10):
I mean what you're talkingabout like our city is
essentially what the stocks youwould probably trade.

Speaker 3 (20:18):
Yeah, yeah, they're in that.
They're in that bucket ofthings we would trade.
So to be, you know, to give acounterclaim against what we
won't find is you won't find aTesla hidden in the S&P 500, at
least at the beginning.
You won't be able to pick upSpaceX real readily.

(20:38):
Well, actually, we could havepicked up SpaceX.
I did some work for it.
It was funny.
I did some work for a spacecompany that'll be unnamed in
which I showed 10 years ago thatall the big rocket launchers of
the day again 10 years ago theBoeing's, the Lockheeds, the

(20:59):
Arians of the world they weregoing to sell maybe three or
four dozen launches over 10years.
And then I showed SpaceX with160, I think, launches over 10
years and they tried to laugh meout of the room.
And then here we are, 10 yearslater, we got within four.
So you know, if I paidattention to what I came up with

(21:20):
, I might have invested inSpaceX as soon as I hit the
market, because those guys wereextremely clever and you got to
really pay attention.
I mean to root out the stufflike a SpaceX, you'd have to go
deeper than the existing dataand see what people are the data
that's available on, say, aretail trading platform.
Back to the point you weremaking.

Speaker 4 (21:41):
Yeah, like government contracts to help with growth
in times of negative cash flowand things of that nature.

Speaker 3 (21:49):
Oh, yeah, yeah, yeah, yeah, yeah, exactly.
So what do?

Speaker 2 (21:53):
companies do to employ this hypernomics thing.
I mean because you got a patenton this too, yeah we have a
patent.

Speaker 3 (22:01):
I published 13 papers on it.
My book on the topic comes outand through Wiley in January.
That's a great public.
It's already available forpre-order at Amazon and Barnes
Noble and Wiley's own site.
So yeah, it's coming out.
January 29th, I believe, is thetarget date, and what's the
title of the?
Book.
It's called Hyponomics ColonUsing Hidden Dimensions to Solve

(22:28):
Unseen Problems.

Speaker 4 (22:30):
I hope you have much better success with your book
than I've had with mine, oh well.

Speaker 2 (22:35):
Kyle wrote a book on it.
Yeah, I see you have a book outthere looked interesting so.
Yeah, yeah, you would probablyunderstand it, but the majority
of America, he tried to kind of,you know, make it to where
people could understand it, likethe average person could
understand how tokenizationworks and how it applies to real
estate and other industries,and it failed.

Speaker 3 (22:56):
Well, it sounds complicated, but again, remember
, as I said, I got the idea fromwatching my wife buy a washing
machine.
She teaches elementary school,and so the basic core ideas of
this are actually pretty simple.
It's just a rearrangement ofthese things that you've already
seen into something you haven'tseen before.

(23:18):
But you can use it, and so itturns out, in principle, to be
quite a bit simpler than youthink it might be at first blush
.
So the book's written tobasically to the high school
level, early college level, andit's so how to answer your

(23:38):
original question how would youemploy it?
Well, we've employed it forNASA, lockheed Martin, virgin
Galactic most recently, and Ican't tell you specifically what
we do because of course it'sdefensive.
I told you I'd have to kill you, that kind of stuff.

Speaker 2 (23:52):
But we don't want that.

Speaker 3 (23:54):
Right.
But what it'll do is it'll fairit out how Marcus are
responding to launch vehicles,space tourism, and it tells you
if you play around with itenough, it'll tell you what the
value of a product is.
So what's the value of a launchto space?
Well, it's a function of howmuch force you can generate.

(24:16):
It's a matter of how much timethe rocket burns.
The longer it burns, the deeperit can get into space.
And it's a function of how safeit is.
And so if your rocket isn'tsafe enough, eventually the
people that want to throw asatellite out won't buy it
anymore.
So they happened to Lockheedback a couple of decades ago.

(24:38):
They tried to build somethingcalled the Athena and they set
it up seven times and it failedtwice, and the market couldn't
stand that failure rate.
So basically, that rocket wentaway.
So what it wants to do for acompany like the aerospace
companies is to figure out whatdo I need to do to be able to

(24:59):
get something to be successful,and then what's the limit on it?
So another thing it can do isit turns out that markets make
these.
This is all reflective ofcollective behavior, as I said
before.
So the markets set themselves alimit in every market of how
much they're going to buy, andso the market for business

(25:21):
aircraft has a limit to it.
And so there's a company upnorth of me, west of U, in Reno,
called Arianne.
Arianne was founded by RobertBass.
He's one of the Bass brothersout of Fort Worth, texas, all of
them billionaires, and it wastheir dream to build a
supersonic business jet.
And the supersonic business jetwas going to go over 900 miles

(25:47):
an hour and hold eight to 12people, and it was priced at
$120 million.
And so now you guys are prettyyoung.
Have you ever heard of thesinger called Meatloaf?
Yeah, I went to Meatloaf.
Yeah, okay, meat to his friends, mr Loaf to you and me.
So Meatloaf wrote a song backin the 80s, 90s and entitled Two

(26:13):
Out of Three Ain't Bad.
So one of the things that welike to look at is we look at
three important factors todetermine a fourth factor.
So the factor we want todetermine is profit.
We want to have the companieswant to make a profit.
That's the goal.
In order to figure that out,they have to work out the cost,
and there's a bunch oforganizations dedicated to cost

(26:33):
and what we call the value, whatit's worth, based on how the
market responds to it, based onwhat we call features.
And then the demand.
So cost, value and demand.
So we went out and the peopleat Arian actually posted what
their cost was to develop it andwe delivered the work and said,
hey, that looks pretty good.
So already they got the costright.

(26:55):
And then we worked out thevalue of the thing.
So the value is a function ofhow big is your tube that you're
carrying people in and how manypeople can get in the tube.
You know the volume per personin the tube and how fast is it
going.
So we worked that out and itwas actually worth at least $120
million.
So they got the cost right,they got the value right and

(27:16):
then they said they were goingto sell 300.
In a decade.
Well, there's a lot of datathat actually tracks this stuff,
model by model over decadesafter decades, and so we pull
this data in.
So they started this newconfiguration.
Then new configuration they hadin 2014.

(27:38):
And in 2015, they made theirfirst sale pre-sale.
They had 20 firm orders.
Then, five years later, thething still had the 20 firm
orders.
So I wrote it in December 2020,after the analysis that the

(27:59):
company had a thin chance ofmaking their 300 units sales in
a decade.
Then I got a very angryresponse.
After I made this post, one ofthe VPs a guy actually knew from
Lockheed, by the way writes meback and says you're all wet, we
just got a huge order.
You don't know what you'retalking about.
And I looked at their order andagain they wanted to sell 300

(28:21):
in a decade and the order wasfor 93, but they're all options,
which in aerospace means maybeI'll buy it.
And I said, well, good for you,you're still not going to make
it.
And then six months later theywent bankrupt.
And the reason they wentbankrupt I don't want to gloat
about this but they didn't dothe analytics going in.
If they had done the analyticsgoing in, they would have seen

(28:44):
that it's not possible to sell300 units, or very thin chance
300 units at the price that theyposted.
It just wasn't possible.
There wasn't enough money inthe world for them to sell it at
that price.

Speaker 2 (28:57):
When the demand probably for that many business
jets and this is like a Concordestyle jet, I'm guessing.

Speaker 3 (29:04):
Exactly.
Yes, it was the same problem.
Good call there.
Yeah, that's exactly what itwas.
It was the Concorde issuerevisited.
The Concorde only sold 20 unitsand they were expecting to sell
300 too.

Speaker 2 (29:18):
Which is a shame, because I would have loved to
fly on the.

Speaker 3 (29:21):
Concorde Right, I know.

Speaker 2 (29:23):
Let me see what a thousand miles an hour looks
like.
Let's get it, let's get there.

Speaker 3 (29:27):
Yeah.
And why this happens is thepeople.
Well, what they do in thesebusinesses typically is they
will say well, let's go askpeople, if I build a jet for
$120 million and it went nearlya thousand miles an hour, would
you buy it?
And they go off to all theserich people and they go yes, yes
, yes, yes, no, yes, yes, yes.

(29:49):
So they totally tell all thesepeople up and they'll say, well,
we got a thousand people thatsaid they'd do it.
We'll discount it by 50%,that's 500.
We're good, well, but do peoplealways do what they say they're
going to do?
No, well, not really.
And what this type of study isdoing is looking at past

(30:15):
behaviors to predict futurebehaviors.
So when I was looking at thattrend for the sales, what you
like to do is you take thedistant past data and the recent
past data and then you take thepresent data so, distant past,
recent past, present and thenyou can predict the near future.

Speaker 2 (30:38):
This is what I say about oh, go ahead, Go ahead.

Speaker 3 (30:41):
I was just going to say.
We call it going from thedistant past to the recent past,
to the present, to the future.
We call that economictrajectory analysis to see where
the market's headed ETA.

Speaker 2 (30:52):
I always tell people in crypto.
They said, well, how do youknow Bitcoin's going to keep
going?
How do you know it's not goingto go to zero?
I said, well, tell me, whenpeople stop being greedy and
thinking they can get rich quick, that's when Bitcoin goes away.
Right, right, yeah.
When an entire generation thatdidn't get burned on the last
bull run and dip, they thinkthat they're going to get rich,

(31:17):
that next generation, the nextwave of investors they got money
, they want to get rich quick.
They don't want to work forever.
So I mean, it's just going tobe a cycle and you got more and
more people.

Speaker 4 (31:27):
I got a question, Absolutely.
I got a question, though.
Go ahead, yes, when you'redoing your analysis.
When they were doing theanalysis of this, did they take
into account okay, this planeflies 900 miles an hour.
We've got to do these salesover a decade.
Did they take into accountcompetition coming up with like
jets that could potentially flymore clientele and get up to

(31:48):
like 700 miles an hour or 650miles an hour to where the value
of going 900 miles an hour wasjust six people Just wasn't
there compared to?
I mean, was that hour or twohours less fly time worth?
You know, not bringing the CEOand the COO and their wives or
whatever it?

Speaker 2 (32:08):
costs the fuel.
Because you're going faster,it's going to burn fuel faster.

Speaker 3 (32:12):
I'm assuming that, yeah, there are people that done
like studies to your pointthere.
Kyle Boeing was trying to makesomething they called the sonic
cruiser.
That was going to go in factmight have had a GE engine, by
the way that was going to gomuch closer to the speed of
sounded altitude.
The speed of sounded highaltitude is about 661 miles an

(32:34):
hour.
They wanted to go about 630miles per hour.
What they discovered was backto your other point that Adam I
think made is that as you startto approach what they call the
sonic barrier, you're actuallypushing the, compressing the air
more and actually shoots yourfuel consumption way up.

(32:57):
Back to your original questionit's actually more efficient to
go just past the speed of soundto be able to get that.
No, I don't think anybodylooked at anybody else entering
the market.
I know when I was tracking itnobody else had entered the
market at least as well.
There's a couple othercompanies that are trying to,
but I think Arianne was furthestalong.

(33:18):
So there's about three or fourwould-be competitors in that
what they call market spaceright now and all of them have
to make sure that they get theirprice down to a point at which
people can afford the jet andthe quantities that they need to
build them.
And I don't think any of that.
My understanding is noteverybody understands that, so

(33:39):
that becomes a problem.
What can also happen on theother end is, interestingly,
back in the early 2000s, a guynamed Vern Rayburn who was, I
think, the seventh employee atMicrosoft.
Well, vern Rayburn made afortune at Microsoft and he goes

(33:59):
down to Albert Kirk and he saysI'm going to build a business
jet and I'm going to crank themout like computers.
Well, he built this businessjet.
He called it the Eclipse 500,eclipse Aviation, and his
original price for the thing was, I think, $775,000.
And our analysis said the thingwas worth $2 million.

(34:22):
Now I guess I could ask Adam aquestion If you had a house that
was worth $2 million and youpriced it at $800,000, you're
probably going to have more thanthe average number of bids on
that right.

Speaker 2 (34:35):
Oh yeah.

Speaker 3 (34:36):
Okay, well, see now Vern Rayburn was saying well,
he's going to make a whole bunchof these planes, so it's not
just one house or one plane,he's going to make a whole bunch
.
So he got orders for about2,000 of these things, and what
he discovered pretty quickly was, well, he made the first
attempt and he underpowered itbecause he didn't know how to
build airplanes, so he had to doit all over again.

(34:57):
But by the time he got aroundto building it, he didn't have a
positive margin.
The thing was costing him morethan he was selling it for, and
so what he should have done ishe should have priced it at the
price that it was worth, whichwas $2 million.
It has some additional problems, like the construction of a

(35:18):
wasn't sound in some way.
You could read about that I'llsay that on air but there were
some other technical issues withit.
But that program also wentunder.
So that went under because theyvalued it too low.
The Arian AS2 collapsed becausethey projected the demand to be

(35:40):
too high.
So there's a real balancing actthat people have to do when it
comes to figuring out whatshould I build and what should
be the price, and how many can Iexpect to sell, and that's kind
of what we try to address.
Are those kind of issues.

Speaker 2 (35:56):
Well, to your point there about being able to
project things and what should Isell it at all?
That stuff comes into play evenwith smaller businesses.

Speaker 4 (36:05):
Oh yes, you sent out some data about this.

Speaker 2 (36:07):
I mean 20% of small businesses fail within the first
year, 30% within a couple ofyears.
By the end of the fifth year,you've got like a 70% failure
rate in most businesses.
And then 30,000 new productsare introduced every year.
I had no idea about this andwe're in the CPG capital of the
world right now, but 95% of themfail and I know this for a fact

(36:31):
because I'm in marketing and wedid a lot of work with Procter
and Gamble.
I mean they will test and testand test and market test and I
mean the things like the Swifferthat came out, like the amount
of testing that they did withthe market and adjustments that
they made to that product islike mind numbing.
So if you're not a Procter andGamble with a huge budget and
think about all the productsthey just throw away every year.

Speaker 3 (36:53):
Sure, sure, sure yeah .

Speaker 2 (36:55):
I mean, remember, olin, remember that thing and
then people started gettingstomach aches or something from
it.

Speaker 4 (36:59):
I was just thinking about Olin.
The other day, were you?
Yeah, I've been listening to anew podcast called A Whole New
Level about metabolic health andthey're talking about the 80s
and the trend of pretty muchpushing fat out of every food
they're possibly could push itout.

Speaker 2 (37:12):
Yeah, they thought it was bad, they thought that was
like a meat fat Right Like arotting meat fat.
Yeah, but I mean things fail.
I mean it's just the way it is.
Even for companies withbillions of dollars to throw at
stuff, you know it still fails.
But you know, talk a little bitabout that and how.
Maybe what people miss out onAre they not?

Speaker 3 (37:31):
Yeah, well, yeah, what are they doing wrong?
It's my big hope that, goingforward, when people start to
understand that these there'smore forces at work than you've
been led to believe in your econcourses and once the people
start to get this by the way,why is it going to market this
as a textbook right from the getgo?
Oh, nice, but once people startto understand this, what's
going to happen, in my view, is,instead of 95% of the products

(37:54):
failing excuse me, maybe acouple of years in, it's 93%,
maybe 92%, and while it doesn'tsound like a lot, you're going
to go from a 5% success rate toa 6% success rate, to a 7% to
maybe a 10% success rate, andwhat's that do to the economy?
That just would start to shootit up.
Yes, and so it's my hope thatthis will become widely adopted

(38:20):
and people stop making sillydecisions based on a lack of
information.
Now, this also works forgovernments too, by the way.
We hope.

Speaker 2 (38:29):
Yeah, you hope, if they actually listen to you.
If they listen to you, Doug.

Speaker 3 (38:33):
Well, they were to listen to me, so I'll give you a
for instance.
In 2014, Washington State andColorado both legalized
recreational marijuana.
Colorado's got three quartersof the population that
Washington does.
At the end of the year,Colorado had $350 million of
recreational marijuana taxrevenue.

(38:55):
At the end of the year,Washington State had 50.
The reason they had that wasthat Colorado had a 30% tax rate
and Washington State had 108%tax rate.
What How's that even possible?

Speaker 4 (39:08):
Yeah, this is like.
Why would you leave the blackmarket for that Like?

Speaker 3 (39:13):
I bingo Speaking yes, exactly.
So what happened was thateverybody just went to the black
market and said, well, I cansmoke illegally now when do I
care where it comes from?
I'm sorry, good.
What happened then was thatWashington State people finally
woke up and they figured theycould drop the taxes and make
more money.
And that's exactly whathappened.

(39:34):
So they dropped the tax rate.
I don't forget what it was, butthey took the revenue up by, I
think, almost 10X in a couple ofyears.
But it turns out that there'syou may have heard the Laffer
curve from Arthur Laffer stillaround.
Sure, yeah, working for ReaganTurns out there's a Laffer curve
for marijuana, and if you don'toptimize to your best point on

(39:59):
the Laffer curve, you'reactually just taking tax dollars
and just lighting them on fire.
And so here in Californiathey've managed to do that.
We've legalized marijuana hererecreationally, but they've
taxed it too high and they madeit hard to get distributorship,
and so there's a big legalmarket.
Now People still smoke itbecause, well, I got marijuana,

(40:21):
who knows if it's legal or not?
So the answer is to drop thetax rate.
A Also, by the way, they'respending lots of money and
trying to do drug enforcement.
Now you should be dropping thetax rate A and then do what you
do for alcohol or tobacco.
Is you regulate it in a waylike you make it?

(40:41):
So it turns out in themarijuana market that you can
have one strain of marijuanacould have the potency from one
store that's listed at 5%.
Another store could list thesame strain at 25%.
So obviously the strains aren'tthe same, and so if the
government were to homogenizethis stuff like they do with the
FDA, and people got the sameyou know, I don't buy this stuff

(41:06):
, but if people wanted to buy itand it was exactly the same
every time if you buy from thegovernment, then the government
would have a draw that wouldbring the recreational marijuana
market to it rather than pushit away.

Speaker 4 (41:20):
Another element that they don't think about, too, is
that California's got theEmerald Triangle.
I know way more about marijuanathan I probably should, so
they've got the Emerald Triangle.
Supply is never going to be anissue.
Supply is never going to be anissue.
So you've got that and you know, if you tax it at a stupid rate

(41:44):
, even if you tax it at theColorado's rate, they can find
it without just going wherever.
Everybody's got friends thathave it.
If you're in South Dakota,where they may grow it but the
supply is nowhere near as high,then your taxes can be a little
bit higher.
That's what I don't understand.
I mean, I know Washington's gotkind of similar places the

(42:07):
Emerald Triangle, where it's upin the mountains a little bit.
You've got kind of the sameclimate, not so much, but kind
of.
Yeah, oregon, but likeKentucky's got their own climate
.
But if you want to get thestrand that California has,
you've got to ship that acrossstate lines.
You've got transportation costsand the taxes are going to be

(42:30):
higher so you can levy highertaxes because the supply is
going to be less.
You're going to have a higherdemand.
That's basic economics, that'schile-nomics, that's not
hyper-nomics, but he's talkingabout California.

Speaker 3 (42:44):
I'm sure you're aware , the feds also have you know
regulations that they can't usethe banking system the way you
and I do.

Speaker 4 (42:52):
Oh no, they have all the stuff.

Speaker 3 (42:53):
They've created this whole sub-market within the
market there to have all thecash moved around in armored
cars and kept in storagefacilities because they don't
allow banking For the now legalthing.
They don't let regular bankingapply to this, and so it's just
ridiculous.
There's such a disconnectbetween what they wanted to do

(43:15):
and what they're doing that theydon't understand these kind of
techniques.
Kind of just flesh all thatstuff out so you don't have to
figure out what you're doingwrong.

Speaker 2 (43:24):
So Yet regional banks are still failing for other
reasons.

Speaker 3 (43:28):
Yeah, and the same thing happens to the overall
income tax.
So here again, here inCalifornia the income tax is
really high, along with theproperty tax and everything else
, and so California has had anet decrease in population.
And the way to address that isyou don't.
When you want to get a lot oftax revenue in, it doesn't mean,

(43:50):
based on what we just saw withWashington, you don't want to
raise the tax rate.
If you raise the tax rate,you're assuming that the demand
is very the tax demand, or theycall it.
You know elasticity.
We call this called steep orflat.
You have a really steep demandcurve for taxpayers, but that's
not the way the taxpayer marketis.
It's really flat.
There's a lot more people atthe bottom end of the market.

(44:11):
If you want to get more taxrevenue, you should drop your
tax rate, make it a draw.

Speaker 4 (44:18):
Yeah.

Speaker 3 (44:19):
Make the state a draw for more people and you'll get
more tax dollars.

Speaker 2 (44:22):
So Florida's doing right now.
I mean, florida's got Miami,which we're going to.
We got a place getting builtdown there.
I talk about it sometimes onthe show here, but we got a
place getting built in Januarydowntown Miami, and they
actually have people leaving thecity of Miami.
But the crazy thing is is, ifyou look deeper into the numbers
and this is what we're talkingabout right, people are like you

(44:44):
know, oh well, people, you knowCalifornia.
People might say, yeah, peopleare leaving California, but
they're also leaving Miami.
And you're like, the peoplethat are leaving Miami are the
people that can't afford to livein Miami.
But they're staying in Florida,but for every, say, five people
that can't afford to live inMiami, you have one
ultra-wealthy person move in, oryou've got, you know, a

(45:04):
wealthier person moving in, sothose people are going to pay
more taxes than the five peoplethat just left.

Speaker 4 (45:11):
Well, look at, okay, so everybody wants to live in
California because of theweather, everybody wants to live
in Florida because of theweather.
But look at Tennessee.

Speaker 2 (45:18):
Tennessee Rock, now Nashville's.

Speaker 4 (45:20):
I was just there.
And the same deal with thestate income tax.
And you know they have lowertaxes Nevada, arizona.
I mean, you've got peoplemoving to those places, yeah,
right, and I mean Nevada makessense because of Las Vegas and
Reno, but Tennessee's gotNashville.
I mean Knoxville's okay,they've got Nashville, you don't
want to go to Memphis.

(45:40):
So like, even with that they've.
They're the amount ofpopulation that that state's
captured in the last,particularly the last three
years, but last five, 10 yearshas just been astronomical.
I agree.

Speaker 3 (45:52):
Oh yeah, well, I mean , they made it.
It's a draw compared to otherstates now, and it doesn't need
to be that way if you justchange the policy.
That's.
That's what's so astonishinglyfrustrating about the way the
policy is set up now.
It's just, it doesn't take into.
Nobody's looking at what'spushing the people in or drawing
them out.
Pushing them in or pushing themout.

(46:13):
You know they don't look atthat.

Speaker 4 (46:15):
There's no money.
There's no money in solvingproblems, that's.
I've come to that conclusion.

Speaker 2 (46:20):
Well, I mean yeah, yeah.
Well, I saw that.
I don't know if you've everread the book San Francisco by
Shelen.

Speaker 3 (46:26):
That sounds great, though I had to pick that one up
.

Speaker 2 (46:28):
Yeah, Schellenberger.
I mean, he's a liberal, he grewup in, you know, he lived in
San Francisco for many years andhe's mostly critical of these
nonprofits, especially ones thatare supposed to be supporting
the homeless.
When you know you've got thedirectors making you know, a
quarter million to a halfmillion dollars a year, why
would they want to solvehomelessness?

Speaker 4 (46:49):
LA County had.
La County has some like 15people that are on the whatever,
whatever agencies overseeingthe homeless problem there,
making over 200K.

Speaker 2 (46:59):
We got people here making two of them.

Speaker 4 (47:01):
200k is like not 200K here obviously Right, Right,
but 200K is still a prettydecent living for screwing up.

Speaker 2 (47:08):
I was like make it 200K being a meteorologist, yeah
.

Speaker 3 (47:11):
You never write Well yeah, and then out here they had
the additional problem thatthey tried to solve the
homelessness by building houses,and they had one house that was
going for for one person wasover $400,000 for one person,
geez, yeah.
So I mean, you want to buildmassive, cheap housing?

(47:33):
They should put up a big,massive complex and invite
people in and, you know, policeit, give them food, give them
shelter.
Of course, part of the problemis a lot of these people don't
want to be indoors.

Speaker 2 (47:46):
No, they don't, they don't want rules and they want
to have pets and they want yeah,it's, they want the freedom.
I mean the reasons some of themare homeless.
I mean I would, I would ventureto guess and this is just my
opinion and you know, what Iread from the book is that a lot
of them just they don't wantresponsibility, they don't want
the responsibility of having tobe anywhere and they kind of

(48:06):
want to live outside of therules of society really, and
that's just their lifestyle.
And do we want to support that?
Like it's great that that'swhat you want.
I mean, we all kind of want thefreedom to be able to do what
we want all day, but do my taxdollars have to support that?

Speaker 3 (48:23):
Well, if you're out here in California, the answer
is yeah, that's what's going tohave to.
We like it.
Yeah, it's, yeah, and you knowthe.
We have all these camps andthey're, you know, trashed the
trash several blocks downtownand in certain you know areas
around it.
It's, it's really quiteremarkably bad.
There's a few tens of thousandsthat are outside, right now all

(48:47):
the time I think we need.

Speaker 4 (48:48):
We need a crowd fund of hypernomics, like during the
GOP debates and have you haveyou have you go like a little
Ross Perot and just rent, rent30 minutes on NBC, cbs and Fox
and just spout this Well.

Speaker 2 (49:01):
I mean he mentioned this is for governments, like,
why aren't they using whatyou've got here?
I mean, could you go to them?
I mean, is this is there?
Is there a possibility thatwhat you've come up with and the
way you analyze information andI know some things are
subjective and it's hard to youknow to quantify some of the
things that are happening outthere?

(49:22):
I mean, there's qualitativedata, there's quantitative data,
but is it possible for them touse some of these things to
solve some of these arguments,these debates between the left
and the right?

Speaker 3 (49:32):
Absolutely.
I can't give you his namebecause he can't be seen to
endorse this, but there is anAir Force Colonel that I was
talking to.
He actually invited me out tohis base and I met with his
people and I was showing himthat it works out that these
principles could help out theAir Force.
So, within the Air Force, theyhave these, that the B2 bomber

(49:57):
that you may know, the stealthbomber, sure, and they've got 21
of them at $1.2 billion a piece, and meanwhile they've got F16s
, and there's about 4,600 F16sat $31 million a piece.
That means that there's oversix times the amount of revenue
for F16s as there is, as ours,for B2s, which means that if you

(50:21):
want to solve defense problems,you need to make cheaper and
more of the less expensive itemsthan to be driving up the curve
.
Up this demand curve, try toget the really expensive things,
and so this kind of techniqueapplies to every government's

(50:44):
purchasing division is facingthese kind of limits and they
need to understand what thealternatives are to what it is
that they're doing.
So right now, the government ismaking a B21 bomber and they
want to build 100 to 200 ofthese, and I actually went to
Northrop Grumman and told themthere's a chance you could do

(51:05):
that.
It's less than one in a million, but you can do that.
You can go ahead and try to dothat.
And so what happens is is thatthis demand frontier is pretty
solid In fact, if you canimagine a barrier in this, just
like land, it's moved 2% in 25years.
I mean, we're here inCalifornia.

(51:26):
The ground moves more than 2%in 25 years.
Yeah, but it's the same thing.
In fact, the book likens thehypernomics phenomenon to
geographic phenomena.
So if you don't understand that, you've got a limit.
So, for example, there's anexample I give from 1707, there

(51:48):
was an admiral shovel from theBritish Navy that was sailing
out of the Mediterranean goinghome, and he wanted to go up
through the English Channel.
Of course, getting back home,he was off to the west of the
English Channel and he thoughthe was here.
But he was really here and heset sail at night in a storm and

(52:12):
he basically blasted into thesewhat's known as the Silly
S-C-I-L-L-Y, the Silly Islands,killing himself from 1400 to
1800 of his fellow sailors.
So what you don't knowphysically in the world if
you're sailing, water is greatfor sailing Rocks.

(52:34):
You don't want to rock in themiddle of the ocean.
He ran into the rocks and hedied.
So it's the same phenomena inbusiness there is a limit out
there to what you can sell.
Now that limit can change.
In fact, you take electric cars.
That limit is changing year toyear, maybe even month to month.
It's changing, it's moving out,but you need to know where it

(52:57):
is, where it's been, where it'sgoing, in order to properly
assess what you're going to dowith that information.
And so it turns out that it'smuch easier to characterize this
than you can imagine, and sothe name may throw a few people
off, but I mean it's at leastaccurate hyper, more than you

(53:17):
know four or more dimensions,but it's actually not any more
complicated than looking at atwo-room house.
So Elvis Presley grew up in atwo-room house that was
basically a rectangle, split inthe middle, with a partition
between the two rooms thatlooked like two square rooms
glued together, and so it'sreally the hypernomics.

(53:39):
In fact, we actually use thatmetaphor, we use what we call
the house of Elvis as a point ofdeparture for our analytics,
and so if you can understand arectangular house with two
square rooms, you can understandhypernomics.
That's what it's about.
It's looking at these twoadjacent structures that meet in

(54:00):
the middle.
They have a common wall.
They meet at the intersectionof this.
When the common wall hits theback wall, there's a common
point, a common line thatseparates both forces here.
That's what we talk about.
So the book will march youthrough this over several
chapters.
So it's you know we don't get.
You know, I'm sorry you guys,I'm just kind of diving into the

(54:23):
advanced portions of this thing, but the book would actually
march you through all this stuffstep by step, so that you would
have a pretty good handle onwhat's going on by the time you
get to some of the moretechnical stuff that we're
talking about right now and youcan make your.
You can draw your ownconclusions using the techniques
that you're going to learn.
That's the idea behind it.

Speaker 2 (54:44):
I was just at Dollywood this weekend and I did
walk through her a recreationof the house she grew up in and
it was pretty much pretty muchthe same house Elvis grew up in,
I think, and then had a lot ofkids in it too.
So very similar.
But, doug man, I could talk toyou all day about this stuff,
but I think people need to geton Amazon and pre-order this
book.
Hypernomics Thank you yes.
Yeah, colon, using hiddendimensions to solve unseen

(55:08):
problems, it is going to beawesome.
I mean your background, youknow Northrop, nasa, lockheed
Martin, raytheon I mean theclient list goes on and on.
Some of the people in yourgroup are impressive.
I mean you've got a guy who'sthe what's CEO of CNET on here
and some other media companies.
I mean it was.
It's pretty wild, but you guysknow your stuff and you've

(55:30):
proven it.
And I think there's a lotpeople could learn from this
book to educate themselves, andnot just for you know a side
hustle of their business, butjust to understand economics and
the complexities of it and allthe factors that go into making
decisions, even for your ownpersonal budget.
So, doug, we appreciate it.

(55:51):
Thanks so much for being on theshow.
If there's anything else youwant to, you want to mention to
people, go for it.

Speaker 3 (55:57):
Well, I want to say from my Kyle and thank you so
much for having me on.
I've really impressed with yourprogram and you both of you
personally.
So I thank you for having me onand it's been my great pleasure
to be able to talk to you forthe, you know, this hour here.
I appreciate it.

Speaker 2 (56:11):
Yes sir, yes sir, and good luck with the book and
good luck with everything youguys are doing and hopefully you
can open some eyes.

Speaker 3 (56:18):
All right, appreciate it.
Thank you again so much.
I really appreciate it.

Speaker 2 (56:21):
All right, thank you have a great afternoon, bye-bye.
Thanks for joining us on thisweek's episode of Side Hustle
City.
Well, you've heard from ourguests, Now let's hear from you.
Join our community on Facebook,Side Hustle City.
It's a group where people shareideas, share their
inspirational stories andmotivate each other to be
successful and turn their sidehustle into their main hustle.

(56:43):
We'll see you there and we'llsee you next week on the show.
Thank you.