Side Hustle City

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

September 20, 2023 Adam Koehler & Kyle Stevie with Doug Howarth Season 4 Episode 46
Exploring the Universe of Hypernomics: From Stock Market Strategies to Side Hustles With Doug Howarth
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Side Hustle City
Exploring the Universe of Hypernomics: From Stock Market Strategies to Side Hustles With Doug Howarth
Sep 20, 2023 Season 4 Episode 46
Adam Koehler & Kyle Stevie with Doug Howarth

Send us a Text Message.

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,

FranchiseU!
FranchiseU! is for those in, or considering, careers within the world of franchising.

Listen on: Apple Podcasts   Spotify

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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 Facebook

Show Notes Transcript Chapter Markers

Send us a Text Message.

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,

FranchiseU!
FranchiseU! is for those in, or considering, careers within the world of franchising.

Listen on: Apple Podcasts   Spotify

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 Facebook

Speaker 2:

Welcome to Side Hustle City and thanks for joining us. Our goal is to help you connect to real people who found success turning their side hustle into a main hustle, and we hope you can too. I'm Adam Kaler. I'm joined by Kyle Stevy, my co-host. Let's get started, all right? Welcome back to the Side Hustle City podcast. Everybody and Kyle Stevy once again, you're on like a streak here, kyle. It's kind of like Cal Rook and Bennett. I know Kyle's rocking and rolling man. He's here a lot now. So yeah, doug Haworth, we got you here today. Man, I really appreciate you being on the show. You've got a great background and we're going to talk about some economics stuff today.

Speaker 3:

Oh great. Well, thank you so much for having me Both of you, adam Kyle, this has really been quite an honor. I've been reading quite a bit about both of you, and you've done some tremendously inventive things early on in your career, so good on you.

Speaker 2:

Yeah, yeah, and we try to share whatever we figured out. I guess, or pretend we figured out, or maybe it's luck, I don't know but we got to make sure we don't lose our money due to economic macro events that are happening, and kind of be able to forecast things. And it's not just us or you know, not people on a personal level, but this is, you know, this is what governments are trying to figure out and big businesses are trying to figure out. And I mean you've got a very interesting background. I mean it sounds like you started out early and you kind of knew you wanted to be. You know you were interested in business. You were interested in a lot of things early on. You've had some health issues which you got over, and you were at Lockheed Martin's Skunkworks, which is wild to think about.

Speaker 3:

Yeah, 31 years, and I was running the F117A, the stealth fighter production line, for a while. It was the manufacturing program manager for it. So yeah, there's an interesting background. And then I ran their parametric analyst group so we would analyze what the markets were and the cost for things and what the market would bear for them, things like that.

Speaker 4:

Well, I would assume my friend does similar stuff, for it was a Johnson to Johnson subsidiary but they sold it off, but it was medical equipment. He was responsible for the implementation, well, the patenting and then the implementation of design at different warehouses across the world. Interesting, Does that sound somewhat similar?

Speaker 3:

It's the same idea, sure, yeah, it's just a different field. But the techniques what we do proves the techniques tend to be are virtually identical across every platform. So we've discovered this phenomenon we call hyper, meaning existing in more than three dimensions, inomics referring to a field of study. So hypernomics is a field of study that looks at things occurring in four more dimensions. And it sounds outrageous, but I actually got the idea of watching my wife buy a washing machine.

Speaker 2:

Oh.

Speaker 3:

Yes, we were buying this washing machine. And she said you know, I'd like to have more capacity than we have at home in this washing machine. So we're staring at one in this big box store and she says, yeah, I want more capacity. So I got the thinking capacity versus price and that was a little two-dimensional problem. And she says, you know, we only got one delicate cycle at home and I'd like to have more cycles there. And I got the thinking cycles against price and now she's up to three dimensions. And so we liked this one particular machine. And then there was the next one up 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, we can't afford it. And then I realized that we were part of the everybody that was buying the washing machine were part of the quantity and price relationship. So I realized that she was juggling four variables in her head at one time. And then I just I had this flash and that's where we went off to.

Speaker 4:

We bought speed queens, and I can guarantee you that none of that popped in my head. I was just like I heard 10 year warranty, get me the hell out of the store.

Speaker 2:

There, you go Give me that one. Well, this is interesting.

Speaker 3:

Well, that's what we call a feature. So, yeah, that's actually. You were actually doing part of that while you were doing that. And what's interesting is that everybody kind of works the same way, just like when you walk into a room, you don't expect to see any you know three foot males, you don't expect to see any eight foot males, everybody's kind of. You know human beings have kind of congregated to a an average height for men which is a little bit 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 in businesses and in products that people relate to how the products are, in the same way, they don't all focus on them one solid point, but they kind of have a clumping effect around what things are worth, and being able to see that lets you predict things. So I know, adam, you're particularly interested in real estate. So, for example, this thing would show you what the value of a commercial real estate property is based on the, the zip code in which you find yourself, which is to say the income there, then the square footage, of course, and then something that you might not think about, which is maybe not you're. You're both near in the Cincinnati area, is that true, yep, yep? Well, out here in LA, you're Los Angeles, I'm just north of it, the it's sometimes hard to get to other facilities that you might want to have from business, and so they this, this one firm, not us invented something called the walk score, and when you toss the walk score in on top of the, the income and the zip code and the square footage, you get a really nice relationship that says that in in, at least in LA, in this part of the town, for this particular timeframe, if you can make it twice as easy to walk to someplace, which is to say your, your walk score is doubled, your people pay more than twice as much for that particular property. Oh, wow, yeah, yeah. And that would be great to know. If you're in a position in which you're buying it or you're selling it, you, or if you want to put a new piece of property in that particular zip code, you would tell you how best to do that, based on on on these kinds of you know these phenomena that happened in the markets. So that's, that's part of what goes on in real estate. And then I know from reading about Chula that, kyle, you still work deeply in logistics, am I correct?

Speaker 4:

Yeah.

Speaker 3:

I'm still kicking. Okay, well, in logistics, of course, you're paying for the weight and the speed and the distance, and it works out that you can model that in a way in which you can find out the what something would be worth for an intermediate speed and distance, and you can find out if your, your product is overvalued for the the, the service that you're offering, or undervalued. And if it's undervalued, of course, you can raise the price. If it's overvalued and you had enough data for how many sales you had, you could figure out what would happen if you were to decrease the price. You might make more sales and you might actually make more, more profit on that. That. This is what this is designed to do Just to be able to beat out those kind of relationships.

Speaker 2:

Yeah, so how do people use this? And you know, and I know you work with these larger companies, but how do you know regular people take advantage of this kind of data analysis that you've come up with in their daily lives? Like is there, is there, it looks like you have classes and things like that that you offer.

Speaker 3:

Yeah, we're going. We don't have them in place just yet because I just finished the book that we're going to use for their prime, their primer on this thing, but we're going to be offering some classes soon. We have software but to your question, how do average people use it while there's a restaurant down the street that I don't know what it's like in Cincinnati during COVID, but here during the initial months of COVID nobody could eat indoors, and here in LA it's it's warm enough in some of the winter months for people to sit outside. So a lot of the restaurants move their serving to outdoors and of course then they were limited by the patio area that they had. And so this particular restaurant that we had, that we to, which we had been frequenting for a couple of decades, at that point, well, the line started going out the door and you know, it became pretty apparent that what was happening here is they. They had a lot of seats, but the seats were. They had two or three, they had three tables of six, I think, and three tables of four, and what happened there was the parties didn't match the party size didn't match the table size, and so they were getting a lot of unoccupied. All the tables were occupied, but not the, not the percentage of seats that they would have liked. So what I did was I suggested to the manager. I said look, you need to take out many of these big tables and swap them in for tables of one and two, because that was their typical. Clientele comes in and parties of one and two, and they did, and their revenue shot up 25% in two months. And I did a little more research afterwards and I discovered that the average party size of a restaurant, well, there's 2.25 times as many people parties of two as there are parties of four. So you want to have at least twice as many tables of two as you do tables of four, unless you're in a family style restaurant, and that would actually max, tend to maximize your throughput. And then what the restaurants want to do is they they don't want to maximize capacity so much as throughput, and I'm sure that Kyle can tell you that, from a logistics standpoint, that's exactly what you want to do. You want to maximize how much you can carry one day. You want to maximize how much is going through hour by hour, right, sure, yeah, so that that there's an example locally. And then we were interviewed by investors business daily four years ago now and I hadn't applied the techniques we had to that point to the stock market. So I decided to make a test fund which anybody could do my own monies into what we call I call the hypernomics fund and we've just been drawing stocks only out of the S&P 500. And last week we had our three and a half year anniversary and we are doing 2.3 times as well as the S&P 500.

Speaker 2:

Oh, now we're talking yeah, so that's the average person Took it with gas over there.

Speaker 3:

Undervalued stocks? Yeah, so that's.

Speaker 4:

It's not that Pelosi knows what's going to come off. The soft-she's not working with Doug.

Speaker 3:

She's been working with Doug he probably can't disclose that your information was used here.

Speaker 2:

yes, but yeah, that would be.

Speaker 3:

That would be illegal. You don't want to do that.

Speaker 2:

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 whole bunch of airplanes from GE aircraft.

Speaker 4:

You don't need to. Yeah right, you don't need to go there.

Speaker 3:

Well, yeah, Inside information gives you a leg up, for sure. But no, this is just. This is what people would call retail investing. You know, we don't have any high speed ports or anything like that, and the trade frequency is pretty low, and we could get more improvements if we added more manpower to it. Right now, the manpower is me doing this every month or two, but we get signals that say something is undervalued, and then we cross-check it a variety of ways. So we'll test it multiple times and, of course, before we actually engaged this, we did thousands of back tests. And we were back testing when markets were going up, and we were back testing when markets went down. And when markets went up, the back test suggested that we would do better than the average bear would be doing. And then, when markets went down, the same kind of phenomenon we would lose. Unless you're Bernie Madoff, if the market's going down, you're probably going to lose. Yeah, that's right, unless you're going to cheat or have insider information yeah, neither of which we did. And so we lost when the market went down, but not as much as other people. So on net, we were doing better than other people.

Speaker 2:

So are you able to factor things in like Fed rate increases, the percentage at which they increase, and then be able to apply that? I mean because this sounds like you're taking a lot of factors and helping that in your decision-making process, because I mean, let's these macro events that happen rate cuts, things like that those are going to affect so many different aspects and they affect different industries in different ways, but everybody has access to that information right, like that's the. But they don't know how to apply it.

Speaker 3:

That's what I'm saying. Sorry, both of you are right. Everybody has access to that and not everybody knows how to apply it. So the trick is to figure out the influencing factors. And that's a statistical problem that we would coach people to say figure out if something is statistically relevant or irrelevant. But if it's relevant, then you start to take the relevant factors. So, say, rate increases are a relevant factor or the speed with which the rate factors have been increasing might be a relevant factor. One of the things we like with stocks is the MV term, the momentum term. So we take the factors that are important so we might get We've had results that are based on up to six independent variables at one time and what we do is we plug in those six independent variables and then we'll spit out a list of Again, it's the S&P 500. We'll filter out the ones that don't have positive results in some aspects, like earnings per share or book value. Everyone that's zero or below will exclude. So you get the ones that are positive and then you'll get this list of 300 to 450 stocks that are viable and then you drive through this equation and then you see the ones that are undervalued and then you test it again, using different combinations of these equations, and you test it over and over and over again. You might have four or five tests and then you see if somebody keeps appearing on the same list over and over again. Yes, if they do, then you might want to check, say well, why is this company showing up as undervalued? Are they under a lawsuit? Do they have? Has the major brains of the corporation left the building, or are they in danger of being on a shoreline and being washed away? I mean, what's going on with this institution? You try to do a little bit of research there, which right now is hard to automate, but here's where I know you've been. Both of you are thinking about crypto and AI. So when you look at the potential for AI that could actually you could bring in data that would say what's the? In fact, there's actually AI in some of these trading platforms, the retail platforms that give you sentiment. You could actually plug in sentiment on top of this. We haven't done that yet. In fact, as I'm seeing, I'd probably be a good idea to do.

Speaker 2:

Yeah, google Trends data or something like that you could cross-reference.

Speaker 3:

Yeah, yeah, so things like that. And then again we back-tested our modeling technique and it suggested it would work. So it's doing pretty well and no shorts, no leverage, no fiat or cryptocurrency trading. It's all S&P 500 stocks and oh, Pretty conservative. So we want to eventually not be clear. This is not open to the public. You've got to make that disclaimer.

Speaker 2:

I was going to say because we got some traders. We got some guys that want to side hustle, do some trading or whatever. Well, I mean, you probably piqued their interest. We're going to take the course.

Speaker 3:

We're going to have the course up in a couple of months here. So yeah, the course would show you what to do.

Speaker 4:

What I like about this, and I would love to say that I'm the resident skeptic here. But I'm not because. I think Adam's more skeptical than I am about a lot of stuff, even though he's more opportunistic and happy than I am. I would say that I like the fact that you've sold this. This is not a get rich quick. This isn't like a bunch of teenagers in front of Ferraris.

Speaker 2:

Yeah, Sound.

Speaker 4:

Dogecoin, I did hypernomics and now I'm suddenly looking at my car. But it seems like this is almost excruciatingly conservative, which is what I like about it is the fact that you run it, you run it, you run it, you run it. Then you do due diligence as quickly as you can. Then you run some more and then you're not. It doesn't sound like you're buying shares to sell them within the next 10 days or so.

Speaker 3:

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 but not phenomenal. It's 10.3% since inception. Better my 401k, so that's not bad, that's pretty good. Yeah, no, that's great, but we're not trying to. Well, I mean, there's this movie coming out about the GameStop phenomenon. We're not trying to race up the market and do try to game the market or anything. Well, yeah, and you're not. Probably. I mean, for a movie about GameStop is people are gaming and then putting in all kinds of orders on that market. But yeah, we're not doing anything like that. This is something the average guy me, you, anybody could do. With a little bit of training and a little bit of background, you'd be good to go.

Speaker 2:

So you're probably not buying NVIDIA at 270 times earnings or whatever they're trading at right now.

Speaker 3:

No, yeah, that's a good point. We're a big fan of high P&E ratios, so we've looked for things that are lower than that. And yeah, I mean Boeing before they had the problem with their 737, the ones that went down a couple of times. They were trading at a real high P&E ratio and, in fact, when you do an analysis of stock market, they were way past everybody else in terms of their valuation.

Speaker 2:

Well, we got GE aircraft here in Cincinnati. It's been here forever. Right, now that GE is breaking up into several businesses, the headquarters of GE Aviation is going to be here, which alone is a Fortune 500 company by itself. Oh yeah, right. And Jeff Immelt, who ran GE for years, was from Cincinnati, not far from the GE, from GE Aviation, right up on I-75 there. So we're excited that a such a stable industry is located here. I mean, we've already got you know the proctoring gambles of the world, which, if you're a trader, you know a bunch of people have that just simply for the dividend. And then you've got you know Kroger, which is the largest you know. You've got the largest consumer package goods company in the world here. And then you've got the largest grocery chain, which is about to buy Albertsons here shortly. As long as everything goes through, we'll see how that works out with the SEC and all those guys, but if that goes through, that's going to be the largest grocery chain in America. And then you've got, you know, ge Aviation. You've got Sintos. I mean there's a lot of very stable. I mean what you're talking about like our city is essentially what the stocks you would probably trade.

Speaker 3:

Yeah, yeah, they're in that. They're in that bucket of things we would trade. So to be, you know, to give a counterclaim against what we won't find is you won't find a Tesla hidden in the S&P 500, at least at the beginning. You won't be able to pick up SpaceX real readily. Well, actually, we could have picked up SpaceX. I did some work for it. It was funny. I did some work for a space company that'll be unnamed in which I showed 10 years ago that all the big rocket launchers of the day again 10 years ago the Boeing's, the Lockheeds, the Arians of the world they were going to sell maybe three or four dozen launches over 10 years. And then I showed SpaceX with 160, I think, launches over 10 years and they tried to laugh me out of the room. And then here we are, 10 years later, we got within four. So you know, if I paid attention to what I came up with, I might have invested in SpaceX as soon as I hit the market, because those guys were extremely clever and you got to really pay attention. I mean to root out the stuff like a SpaceX, you'd have to go deeper than the existing data and see what people are the data that's available on, say, a retail trading platform. Back to the point you were making.

Speaker 4:

Yeah, like government contracts to help with growth in times of negative cash flow and things of that nature.

Speaker 3:

Oh, yeah, yeah, yeah, yeah, yeah, exactly. So what do?

Speaker 2:

companies do to employ this hypernomics thing. I mean because you got a patent on this too, yeah we have a patent.

Speaker 3:

I published 13 papers on it. My book on the topic comes out and through Wiley in January. That's a great public. It's already available for pre-order at Amazon and Barnes Noble and Wiley's own site. So yeah, it's coming out. January 29th, I believe, is the target date, and what's the title of the? Book. It's called Hyponomics Colon Using Hidden Dimensions to Solve Unseen Problems.

Speaker 4:

I hope you have much better success with your book than I've had with mine, oh well.

Speaker 2:

Kyle wrote a book on it. Yeah, I see you have a book out there looked interesting so. Yeah, yeah, you would probably understand it, but the majority of America, he tried to kind of, you know, make it to where people could understand it, like the average person could understand how tokenization works and how it applies to real estate and other industries, and it failed.

Speaker 3:

Well, it sounds complicated, but again, remember, as I said, I got the idea from watching 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 of these things that you've already seen into something you haven't seen before. But you can use it, and so it turns out, in principle, to be quite a bit simpler than you think it might be at first blush. So the book's written to basically to the high school level, early college level, and it's so how to answer your original question how would you employ it? Well, we've employed it for NASA, lockheed Martin, virgin Galactic most recently, and I can't tell you specifically what we do because of course it's defensive. I told you I'd have to kill you, that kind of stuff.

Speaker 2:

But we don't want that.

Speaker 3:

Right. But what it'll do is it'll fair it out how Marcus are responding to launch vehicles, space tourism, and it tells you if you play around with it enough, it'll tell you what the value of a product is. So what's the value of a launch to space? Well, it's a function of how much force you can generate. It's a matter of how much time the rocket burns. The longer it burns, the deeper it can get into space. And it's a function of how safe it is. And so if your rocket isn't safe enough, eventually the people that want to throw a satellite out won't buy it anymore. So they happened to Lockheed back a couple of decades ago. They tried to build something called the Athena and they set it up seven times and it failed twice, and the market couldn't stand that failure rate. So basically, that rocket went away. So what it wants to do for a company like the aerospace companies is to figure out what do I need to do to be able to get something to be successful, and then what's the limit on it? So another thing it can do is it turns out that markets make these. This is all reflective of collective behavior, as I said before. So the markets set themselves a limit in every market of how much they're going to buy, and so the market for business aircraft has a limit to it. And so there's a company up north of me, west of U, in Reno, called Arianne. Arianne was founded by Robert Bass. He's one of the Bass brothers out of Fort Worth, texas, all of them billionaires, and it was their dream to build a supersonic business jet. And the supersonic business jet was going to go over 900 miles an hour and hold eight to 12 people, and it was priced at $120 million. And so now you guys are pretty young. Have you ever heard of the singer called Meatloaf? Yeah, I went to Meatloaf. Yeah, okay, meat to his friends, mr Loaf to you and me. So Meatloaf wrote a song back in the 80s, 90s and entitled Two Out of Three Ain't Bad. So one of the things that we like to look at is we look at three important factors to determine a fourth factor. So the factor we want to determine is profit. We want to have the companies want 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 of organizations dedicated to cost and what we call the value, what it's worth, based on how the market responds to it, based on what we call features. And then the demand. So cost, value and demand. So we went out and the people at Arian actually posted what their cost was to develop it and we delivered the work and said, hey, that looks pretty good. So already they got the cost right. And then we worked out the value of the thing. So the value is a function of how big is your tube that you're carrying people in and how many people can get in the tube. You know the volume per person in the tube and how fast is it going. So we worked that out and it was actually worth at least $120 million. So they got the cost right, they got the value right and then they said they were going to sell 300. In a decade. Well, there's a lot of data that actually tracks this stuff, model by model over decades after decades, and so we pull this data in. So they started this new configuration. Then new configuration they had in 2014. And in 2015, they made their first sale pre-sale. They had 20 firm orders. Then, five years later, the thing still had the 20 firm orders. So I wrote it in December 2020, after the analysis that the company had a thin chance of making their 300 units sales in a decade. Then I got a very angry response. After I made this post, one of the VPs a guy actually knew from Lockheed, by the way writes me back and says you're all wet, we just got a huge order. You don't know what you're talking about. And I looked at their order and again they wanted to sell 300 in a decade and the order was for 93, but they're all options, which in aerospace means maybe I'll buy it. And I said, well, good for you, you're still not going to make it. And then six months later they went bankrupt. And the reason they went bankrupt I don't want to gloat about this but they didn't do the analytics going in. If they had done the analytics going in, they would have seen that it's not possible to sell 300 units, or very thin chance 300 units at the price that they posted. It just wasn't possible. There wasn't enough money in the world for them to sell it at that price.

Speaker 2:

When the demand probably for that many business jets and this is like a Concorde style jet, I'm guessing.

Speaker 3:

Exactly. Yes, it was the same problem. Good call there. Yeah, that's exactly what it was. It was the Concorde issue revisited. The Concorde only sold 20 units and they were expecting to sell 300 too.

Speaker 2:

Which is a shame, because I would have loved to fly on the.

Speaker 3:

Concorde Right, I know.

Speaker 2:

Let me see what a thousand miles an hour looks like. Let's get it, let's get there.

Speaker 3:

Yeah. And why this happens is the people. Well, what they do in these businesses typically is they will say well, let's go ask people, if I build a jet for $120 million and it went nearly a thousand miles an hour, would you buy it? And they go off to all these rich people and they go yes, yes, yes, yes, no, yes, yes, yes. So they totally tell all these people up and they'll say, well, we got a thousand people that said they'd do it. We'll discount it by 50%, that's 500. We're good, well, but do people always do what they say they're going to do? No, well, not really. And what this type of study is doing is looking at past behaviors to predict future behaviors. So when I was looking at that trend for the sales, what you like to do is you take the distant past data and the recent past data and then you take the present data so, distant past, recent past, present and then you can predict the near future.

Speaker 2:

This is what I say about oh, go ahead, Go ahead.

Speaker 3:

I was just going to say. We call it going from the distant past to the recent past, to the present, to the future. We call that economic trajectory analysis to see where the market's headed ETA.

Speaker 2:

I always tell people in crypto. They said, well, how do you know Bitcoin's going to keep going? How do you know it's not going to go to zero? I said, well, tell me, when people stop being greedy and thinking they can get rich quick, that's when Bitcoin goes away. Right, right, yeah. When an entire generation that didn't get burned on the last bull run and dip, they think that they're going to get rich, that next generation, the next wave 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 to be a cycle and you got more and more people.

Speaker 4:

I got a question, Absolutely. I got a question, though. Go ahead, yes, when you're doing your analysis. When they were doing the analysis of this, did they take into account okay, this plane flies 900 miles an hour. We've got to do these sales over a decade. Did they take into account competition coming up with like jets that could potentially fly more clientele and get up to like 700 miles an hour or 650 miles an hour to where the value of going 900 miles an hour was just six people Just wasn't there compared to? I mean, was that hour or two hours less fly time worth? You know, not bringing the CEO and the COO and their wives or whatever it?

Speaker 2:

costs the fuel. Because you're going faster, it's going to burn fuel faster.

Speaker 3:

I'm assuming that, yeah, there are people that done like studies to your point there. Kyle Boeing was trying to make something they called the sonic cruiser. That was going to go in fact might have had a GE engine, by the way that was going to go much closer to the speed of sounded altitude. The speed of sounded high altitude is about 661 miles an hour. They wanted to go about 630 miles per hour. What they discovered was back to your other point that Adam I think made is that as you start to approach what they call the sonic barrier, you're actually pushing the, compressing the air more and actually shoots your fuel consumption way up. Back to your original question it's actually more efficient to go just past the speed of sound to be able to get that. No, I don't think anybody looked at anybody else entering the market. I know when I was tracking it nobody else had entered the market at least as well. There's a couple other companies that are trying to, but I think Arianne was furthest along. So there's about three or four would-be competitors in that what they call market space right now and all of them have to make sure that they get their price down to a point at which people can afford the jet and the quantities that they need to build them. And I don't think any of that. My understanding is not everybody understands that, so that becomes a problem. What can also happen on the other end is, interestingly, back in the early 2000s, a guy named Vern Rayburn who was, I think, the seventh employee at Microsoft. Well, vern Rayburn made a fortune at Microsoft and he goes down to Albert Kirk and he says I'm going to build a business jet and I'm going to crank them out like computers. Well, he built this business jet. 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 thing was worth $2 million. Now I guess I could ask Adam a question If you had a house that was worth $2 million and you priced it at $800,000, you're probably going to have more than the average number of bids on that right.

Speaker 2:

Oh yeah.

Speaker 3:

Okay, well, see now Vern Rayburn was saying well, he's going to make a whole bunch of 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 about 2,000 of these things, and what he discovered pretty quickly was, well, he made the first attempt and he underpowered it because he didn't know how to build airplanes, so he had to do it all over again. But by the time he got around to building it, he didn't have a positive margin. The thing was costing him more than he was selling it for, and so what he should have done is he should have priced it at the price that it was worth, which was $2 million. It has some additional problems, like the construction of a wasn't sound in some way. You could read about that I'll say that on air but there were some other technical issues with it. But that program also went under. So that went under because they valued it too low. The Arian AS2 collapsed because they projected the demand to be too high. So there's a real balancing act that people have to do when it comes to figuring out what should I build and what should be the price, and how many can I expect to sell, and that's kind of what we try to address. Are those kind of issues.

Speaker 2:

Well, to your point there about being able to project things and what should I sell it at all? That stuff comes into play even with smaller businesses.

Speaker 4:

Oh yes, you sent out some data about this.

Speaker 2:

I mean 20% of small businesses fail within the first year, 30% within a couple of years. By the end of the fifth year, you've got like a 70% failure rate in most businesses. And then 30,000 new products are introduced every year. I had no idea about this and we're in the CPG capital of the world right now, but 95% of them fail and I know this for a fact because I'm in marketing and we did a lot of work with Procter and Gamble. I mean they will test and test and test and market test and I mean the things like the Swiffer that came out, like the amount of testing that they did with the market and adjustments that they made to that product is like mind numbing. So if you're not a Procter and Gamble with a huge budget and think about all the products they just throw away every year.

Speaker 3:

Sure, sure, sure yeah.

Speaker 2:

I mean, remember, olin, remember that thing and then people started getting stomach aches or something from it.

Speaker 4:

I was just thinking about Olin. The other day, were you? Yeah, I've been listening to a new podcast called A Whole New Level about metabolic health and they're talking about the 80s and the trend of pretty much pushing fat out of every food they're possibly could push it out.

Speaker 2:

Yeah, they thought it was bad, they thought that was like a meat fat Right Like a rotting meat fat. Yeah, but I mean things fail. I mean it's just the way it is. Even for companies with billions of dollars to throw at stuff, you know it still fails. But you know, talk a little bit about that and how. Maybe what people miss out on Are they not?

Speaker 3:

Yeah, well, yeah, what are they doing wrong? It's my big hope that, going forward, when people start to understand that these there's more forces at work than you've been led to believe in your econ courses and once the people start to get this by the way, why is it going to market this as a textbook right from the get go? Oh, nice, but once people start to understand this, what's going to happen, in my view, is, instead of 95% of the products failing excuse me, maybe a couple of years in, it's 93%, maybe 92%, and while it doesn't sound like a lot, you're going to go from a 5% success rate to a 6% success rate, to a 7% to maybe a 10% success rate, and what's that do to the economy? That just would start to shoot it up. Yes, and so it's my hope that this will become widely adopted and people stop making silly decisions based on a lack of information. Now, this also works for governments too, by the way. We hope.

Speaker 2:

Yeah, you hope, if they actually listen to you. If they listen to you, Doug.

Speaker 3:

Well, they were to listen to me, so I'll give you a for instance. In 2014, Washington State and Colorado both legalized recreational marijuana. Colorado's got three quarters of the population that Washington does. At the end of the year, Colorado had $350 million of recreational marijuana tax revenue. At the end of the year, Washington State had 50. The reason they had that was that Colorado had a 30% tax rate and Washington State had 108% tax rate. What How's that even possible?

Speaker 4:

Yeah, this is like. Why would you leave the black market for that Like?

Speaker 3:

I bingo Speaking yes, exactly. So what happened was that everybody just went to the black market and said, well, I can smoke illegally now when do I care where it comes from? I'm sorry, good. What happened then was that Washington State people finally woke up and they figured they could drop the taxes and make more money. And that's exactly what happened. So they dropped the tax rate. I don't forget what it was, but they took the revenue up by, I think, almost 10X in a couple of years. But it turns out that there's you may have heard the Laffer curve from Arthur Laffer still around. Sure, yeah, working for Reagan Turns out there's a Laffer curve for marijuana, and if you don't optimize to your best point on the Laffer curve, you're actually just taking tax dollars and just lighting them on fire. And so here in California they've managed to do that. We've legalized marijuana here recreationally, but they've taxed it too high and they made it hard to get distributorship, and so there's a big legal market. Now People still smoke it because, well, I got marijuana, who knows if it's legal or not? So the answer is to drop the tax rate. A Also, by the way, they're spending lots of money and trying to do drug enforcement. Now you should be dropping the tax rate A and then do what you do for alcohol or tobacco. Is you regulate it in a way like you make it? So it turns out in the marijuana market that you can have one strain of marijuana could have the potency from one store that's listed at 5%. Another store could list the same strain at 25%. So obviously the strains aren't the same, and so if the government were to homogenize this stuff like they do with the FDA, and people got the same you know, I don't buy this stuff, but if people wanted to buy it and it was exactly the same every time if you buy from the government, then the government would have a draw that would bring the recreational marijuana market to it rather than push it away.

Speaker 4:

Another element that they don't think about, too, is that California's got the Emerald Triangle. I know way more about marijuana than I probably should, so they've got the Emerald Triangle. Supply is never going to be an issue. Supply is never going to be an issue. So you've got that and you know, if you tax it at a stupid rate, even if you tax it at the Colorado's rate, they can find it without just going wherever. Everybody's got friends that have 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 got kind of similar places the Emerald Triangle, where it's up in the mountains a little bit. You've got kind of the same climate, not so much, but kind of. Yeah, oregon, but like Kentucky's got their own climate. But if you want to get the strand that California has, you've got to ship that across state lines. You've got transportation costs and the taxes are going to be higher so you can levy higher taxes because the supply is going to be less. You're going to have a higher demand. That's basic economics, that's chile-nomics, that's not hyper-nomics, but he's talking about California.

Speaker 3:

I'm sure you're aware, the feds also have you know regulations that they can't use the banking system the way you and I do.

Speaker 4:

Oh no, they have all the stuff.

Speaker 3:

They've created this whole sub-market within the market there to have all the cash moved around in armored cars and kept in storage facilities because they don't allow banking For the now legal thing. They don't let regular banking apply to this, and so it's just ridiculous. There's such a disconnect between what they wanted to do and what they're doing that they don't understand these kind of techniques. Kind of just flesh all that stuff out so you don't have to figure out what you're doing wrong.

Speaker 2:

So Yet regional banks are still failing for other reasons.

Speaker 3:

Yeah, and the same thing happens to the overall income tax. So here again, here in California the income tax is really high, along with the property tax and everything else, and so California has had a net decrease in population. And the way to address that is you don't. When you want to get a lot of tax revenue in, it doesn't mean, based on what we just saw with Washington, 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 they call it. You know elasticity. We call this called steep or flat. You have a really steep demand curve for taxpayers, but that's not the way the taxpayer market is. It's really flat. There's a lot more people at the bottom end of the market. If you want to get more tax revenue, you should drop your tax rate, make it a draw.

Speaker 4:

Yeah.

Speaker 3:

Make the state a draw for more people and you'll get more tax dollars.

Speaker 2:

So Florida's doing right now. I mean, florida's got Miami, which we're going to. We got a place getting built down there. I talk about it sometimes on the show here, but we got a place getting built in January downtown Miami, and they actually have people leaving the city of Miami. But the crazy thing is is, if you look deeper into the numbers and this is what we're talking about right, people are like you know, oh well, people, you know California. People might say, yeah, people are leaving California, but they're also leaving Miami. And you're like, the people that are leaving Miami are the people that can't afford to live in Miami. But they're staying in Florida, but for every, say, five people that can't afford to live in Miami, you have one ultra-wealthy person move in, or you've got, you know, a wealthier person moving in, so those people are going to pay more taxes than the five people that just left.

Speaker 4:

Well, look at, okay, so everybody wants to live in California because of the weather, everybody wants to live in Florida because of the weather. But look at Tennessee.

Speaker 2:

Tennessee Rock, now Nashville's.

Speaker 4:

I was just there. And the same deal with the state income tax. And you know they have lower taxes Nevada, arizona. I mean, you've got people moving to those places, yeah, right, and I mean Nevada makes sense because of Las Vegas and Reno, but Tennessee's got Nashville. I mean Knoxville's okay, they've got Nashville, you don't want to go to Memphis. So like, even with that they've. They're the amount of population that that state's captured in the last, particularly the last three years, but last five, 10 years has just been astronomical. I agree.

Speaker 3:

Oh yeah, well, I mean, they made it. It's a draw compared to other states now, and it doesn't need to be that way if you just change the policy. That's. That's what's so astonishingly frustrating about the way the policy is set up now. It's just, it doesn't take into. Nobody's looking at what's pushing the people in or drawing them out. Pushing them in or pushing them out. You know they don't look at that.

Speaker 4:

There's no money. There's no money in solving problems, that's. I've come to that conclusion.

Speaker 2:

Well, I mean yeah, yeah. Well, I saw that. I don't know if you've ever read the book San Francisco by Shelen.

Speaker 3:

That sounds great, though I had to pick that one up.

Speaker 2:

Yeah, Schellenberger. I mean, he's a liberal, he grew up in, you know, he lived in San Francisco for many years and he's mostly critical of these nonprofits, especially ones that are supposed to be supporting the homeless. When you know you've got the directors making you know, a quarter million to a half million dollars a year, why would they want to solve homelessness?

Speaker 4:

LA County had. La County has some like 15 people that are on the whatever, whatever agencies overseeing the homeless problem there, making over 200K.

Speaker 2:

We got people here making two of them.

Speaker 4:

200k is like not 200K here obviously Right, Right, but 200K is still a pretty decent living for screwing up.

Speaker 2:

I was like make it 200K being a meteorologist, yeah.

Speaker 3:

You never write Well yeah, and then out here they had the additional problem that they tried to solve the homelessness by building houses, and they had one house that was going for for one person was over $400,000 for one person, geez, yeah. So I mean, you want to build massive, cheap housing? They should put up a big, massive complex and invite people in and, you know, police it, give them food, give them shelter. Of course, part of the problem is a lot of these people don't want to be indoors.

Speaker 2:

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 them are homeless. I mean I would, I would venture to guess and this is just my opinion and you know, what I read from the book is that a lot of them just they don't want responsibility, they don't want the responsibility of having to be anywhere and they kind of want to live outside of the rules of society really, and that's just their lifestyle. And do we want to support that? Like it's great that that's what you want. I mean, we all kind of want the freedom to be able to do what we want all day, but do my tax dollars have to support that?

Speaker 3:

Well, if you're out here in California, the answer is yeah, that's what's going to have to. We like it. Yeah, it's, yeah, and you know the. We have all these camps and they're, you know, trashed the trash several blocks downtown and in certain you know areas around it. It's, it's really quite remarkably bad. There's a few tens of thousands that are outside, right now all the time I think we need.

Speaker 4:

We need a crowd fund of hypernomics, like during the GOP debates and have you have you have you go like a little Ross Perot and just rent, rent 30 minutes on NBC, cbs and Fox and just spout this Well.

Speaker 2:

I mean he mentioned this is for governments, like, why aren't they using what you've got here? I mean, could you go to them? I mean, is this is there? Is there a possibility that what you've come up with and the way you analyze information and I know some things are subjective and it's hard to you know to quantify some of the things that are happening out there? I mean, there's qualitative data, there's quantitative data, but is it possible for them to use some of these things to solve some of these arguments, these debates between the left and the right?

Speaker 3:

Absolutely. I can't give you his name because he can't be seen to endorse this, but there is an Air Force Colonel that I was talking to. He actually invited me out to his base and I met with his people and I was showing him that it works out that these principles could help out the Air Force. So, within the Air Force, they have these, that the B2 bomber that you may know, the stealth bomber, 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 F16s at $31 million a piece. That means that there's over six times the amount of revenue for F16s as there is, as ours, for B2s, which means that if you want to solve defense problems, you need to make cheaper and more of the less expensive items than to be driving up the curve. Up this demand curve, try to get the really expensive things, and so this kind of technique applies to every government's purchasing division is facing these kind of limits and they need to understand what the alternatives are to what it is that they're doing. So right now, the government is making a B21 bomber and they want to build 100 to 200 of these, and I actually went to Northrop Grumman and told them there's a chance you could do that. It's less than one in a million, but you can do that. You can go ahead and try to do that. And so what happens is is that this demand frontier is pretty solid In fact, if you can imagine a barrier in this, just like land, it's moved 2% in 25 years. I mean, we're here in California. The ground moves more than 2% in 25 years. Yeah, but it's the same thing. In fact, the book likens the hypernomics phenomenon to geographic phenomena. So if you don't understand that, you've got a limit. So, for example, there's an example I give from 1707, there was an admiral shovel from the British Navy that was sailing out of the Mediterranean going home, 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 thought he was here. But he was really here and he set sail at night in a storm and he basically blasted into these what'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 know physically in the world if you're sailing, water is great for sailing Rocks. You don't want to rock in the middle of the ocean. He ran into the rocks and he died. So it's the same phenomena in business 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 to year, maybe even month to month. It's changing, it's moving out, but you need to know where it is, where it's been, where it's going, in order to properly assess what you're going to do with that information. And so it turns out that it's much easier to characterize this than you can imagine, and so the name may throw a few people off, but I mean it's at least accurate hyper, more than you know four or more dimensions, but it's actually not any more complicated than looking at a two-room house. So Elvis Presley grew up in a two-room house that was basically a rectangle, split in the middle, with a partition between the two rooms that looked like two square rooms glued together, and so it's really the hypernomics. In fact, we actually use that metaphor, we use what we call the house of Elvis as a point of departure for our analytics, and so if you can understand a rectangular house with two square rooms, you can understand hypernomics. That's what it's about. It's looking at these two adjacent structures that meet in the middle. They have a common wall. They meet at the intersection of this. When the common wall hits the back wall, there's a common point, a common line that separates both forces here. That's what we talk about. So the book will march you through 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 advanced portions of this thing, but the book would actually march you through all this stuff step by step, so that you would have a pretty good handle on what's going on by the time you get to some of the more technical stuff that we're talking about right now and you can make your. You can draw your own conclusions using the techniques that you're going to learn. That's the idea behind it.

Speaker 2:

I was just at Dollywood this weekend and I did walk through her a recreation of the house she grew up in and it was pretty much pretty much the same house Elvis grew up in, I think, and then had a lot of kids in it too. So very similar. But, doug man, I could talk to you all day about this stuff, but I think people need to get on Amazon and pre-order this book. Hypernomics Thank you yes. Yeah, colon, using hidden dimensions to solve unseen problems, it is going to be awesome. I mean your background, you know Northrop, nasa, lockheed Martin, raytheon I mean the client list goes on and on. Some of the people in your group are impressive. I mean you've got a guy who's the what's CEO of CNET on here and some other media companies. I mean it was. It's pretty wild, but you guys know your stuff and you've proven it. And I think there's a lot people could learn from this book to educate themselves, and not just for you know a side hustle of their business, but just to understand economics and the complexities of it and all the factors that go into making decisions, even for your own personal budget. So, doug, we appreciate it. Thanks so much for being on the show. If there's anything else you want to, you want to mention to people, go for it.

Speaker 3:

Well, I want to say from my Kyle and thank you so much for having me on. I've really impressed with your program and you both of you personally. So I thank you for having me on and it's been my great pleasure to be able to talk to you for the, you know, this hour here. I appreciate it.

Speaker 2:

Yes sir, yes sir, and good luck with the book and good luck with everything you guys are doing and hopefully you can open some eyes.

Speaker 3:

All right, appreciate it. Thank you again so much. I really appreciate it.

Speaker 2:

All right, thank you have a great afternoon, bye-bye. Thanks for joining us on this week's episode of Side Hustle City. Well, you've heard from our guests, Now let's hear from you. Join our community on Facebook, Side Hustle City. It's a group where people share ideas, share their inspirational stories and motivate each other to be successful and turn their side hustle into their main hustle. We'll see you there and we'll see you next week on the show. Thank you.

Discovering the Power of Hypernomics
Seating Optimization and Stock Market Investing
Trading Strategies and Stable Stocks
(Cont.) Trading Strategies and Stable Stocks
Analyzing the Feasibility of Jet Sales
Product Failures and Tax Policies Simplified
Insights on Homelessness and Government Spending
Side Hustles and Next Episode