Doug Howarth: Transforming Sales Strategies Through Hypernomics

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Let's make this happen together. Hey everyone, welcome back to Make It Happen Mondays, where we talk about sales, business, entrepreneurship, personal growth, mental health, and everything in between with guests who I truly respect and I think make a positive impact on the world around us. And oh boy, do I got a heady one here for you on this one. I have a feeling you're all going to want to go read the book on this because we get into some interesting stuff here that is next level. A little bit different than my typical podcast, but this week's guest is Doug Howarth. And Doug is the CEO of Hypernomics. And he's also the author of the book published by Wiley, Hyper Economics, using hidden dimensions to solve unseen problems.

And this guy's way smarter than I am. He's got his degrees. He's been around the block for more than a few years and he takes such an analytical approach. Now, this is mostly about product market fit in a lot of ways. So when you're entering a market and you're creating things, how do you go to market? What do you know the price is and everything else? And so for those of you who are in sales and have a future in entrepreneurship, this one is critical if you ever think you're going to come up with a product or service. Because he talks about how buyers self-organize their behaviors according to the law of value and demand in which, and these are the four dimensions, product features determine value.

Two, value drives price. Three, price limits quantity sold. And four, quantity sold is a feature. So it's full circle here. So we unpacked this quite a bit and I tried to boil it down towards the end of how we in sales can apply this to more complex sales and trying to connect the dots, if you will, for complex sales, multiple people involved in finding that sweet spot. You all hear me talk about the sell to the 20%, right? Well, we're trying to find that using this. So I hope you enjoy this as much as I did. Like I said, I think you're going to want to grab the book on after this one, at least read the cliff notes to get a better understanding. But super interesting conversation. Hope you enjoyed it as much as I did.

Let's make it happen. Doug Howarth, welcome to the Make It Happen Monday podcast, my friend. Thanks for coming on board. John, thank you so much for having me. It's a big pleasure to be here. Thanks. I appreciate it. And this is going to be an interesting conversation, man. I got to be honest and prepping for this. I was kind of reading through some of the book notes and there's some heavy stuff here, but I'm hoping we can boil this down to get people to thinking because this is a different way of thinking. I have a few analogies here on this one that we're going to get to that I want some clarity on. But before we get to all that and what's in the book, let's go back a little bit here and give us a little bit of how you got here.

But I'd love to not just talk about your work origin story. Talk to me a little bit about your origin story, if you will, like growing up and kind of what got you into this and made you where you are today. Because I always love to hear what, like from a grown up standpoint, parents, those type of things, did you kind of get a blog early in your career, those types. So give the audience a little bit of context here and then we'll dive into it. Well, sure, John. You know, I read that you wrote a book to your kid about why I wanted to get into sales. My dad wanted me to be an engineer and it turns out I didn't have very many mechanical skills, but he got me to thinking very critically very early on.

By the time I got to junior high, they started giving me some of the stuff that we get in junior high where you start getting into these plotting systems that were invented 400 years ago. You know, I believed it like everybody else did and still do that it works in two and three dimensions, but I always thought there was something else out there. So this idea was basically percolating from my mid-teens up until I was in my late 40s, early 50s, and I finally got a kidney transplant. I was sick with kidney disease for three decades and basically made it past that. Once I got the transplant from my best friend, my brain cleared up and all of a sudden I was able to think in different ways. And so one day when we went out shopping for a washing machine with my wife, I realized that she was buying the machine using four dimensions at the same time.

She was saying to herself, we came up to this machine. She says, you know, I like this machine. It's got a bigger drum than we have at home. And I thought capacity versus price, that's a 2D problem. And she said, we only have the one gentle cycle at home. I'd like to have more cycles. I thought cycles versus price. She's up to a 3D problem here. And then I saw the next machine up the line. I liked the one we saw, but the next machine up the line, of course, had more of everything and it costs more. And I said, what about this one? And she says, it's too expensive. We can't afford it. And I realized that our little purchase was going to add one to the quantity total for the total number of these units that have been sold over the course of the year.

So we're going to add a quantity of one to this entire quantity and price structure, which in classic economics is the demand curve. And so I realized then that she was solving for capacity, cycles, price, and quantity. And I looked around the store and I realized that everybody in the store was doing the same thing for whatever product they were looking at. And so it hit me in an instant and I eventually quit my job, worked out a way to plot 4D in an engineering plotting program, and then formed a little company around this and eventually patented some software that's the world's first 4D software that lets you look at how the markets behave in these four dimensions. And what's interesting about this, John, is that the reason it works is that people self-aggregate their behaviors.

So people form what we call a demand frontier. They have a certain price limit that they'll set for themselves. Often there'll be a quantity limit. And at the same time, what's happening on what we call the value side is people see things the same way. So when people buy, say, electric cars, they're buying a certain amount of horsepower and they're buying a certain amount of range. And nobody lets anybody get far away from that range at any one point in time. And so the trick is if you're trying to sell into this, which a lot of people like to do, if you want to make something new, what you need to do is find an open space in the market. Now, some people, some companies do this pretty well intuitively.

Elon Musk comes to mind. So in 2013, in the electric car market, Musk had a couple of interests. The early Model S, isn't there, was the Tesla and there was the Nissan Leaf. And there was this, you know, there were a few cars that had less than, you know, 100 horsepower or less and didn't have very much range. There were very capable Teslas and there wasn't very much in between. And what Musk did to his credit was he started to drive new models into those open spaces. And out here in California, his Model 3 is turned into the most popular car in the state right now. So it's really a matter of the technology is one that allows you to map what happens in a way in which you can use it to your own benefit.

So I love it. I mean, I get a lot to unpack here because this is almost like how I felt in college when I was studying art and Picasso and cubism, right, which is effectively four dimensions on a two-dimensional plane. And I could never wrap my head around it until well later in life and started, I got some perspective. But I'm going to ask, I'm going to ask a question I was going to ask later, but I want to ask it now and we'll go back into it. Does something like the challenge from a sales standpoint is obviously, right, if you're selling something of high value that people don't see, right, challenging it, getting people to spend more than, quote unquote, they're budgeted for. But it seems like sometimes there has to be a shift, like something happening in the market for to change the overall market's perception.

And I'll give you a quick example as it relates to me, right? For years up until COVID, everybody believed that for me, I do on-site training, right? So I always did remote training, but on-site, I'm sorry, I always did and offered remote training, but nobody ever wanted it because the perception was that on-site was better, right? So I would try to sell it and it would be cheaper, it'd be faster, it'd be better, you know, in my opinion, better. But yeah, no, no, no, no, John, we want you on-site. Now COVID hits, boom, everybody immediately adopts it. And now that's the preferred method versus on-site. Same thing with like SaaS, right? SaaS came along and for a while it was like, oh, no way am I going to spend that much money on something remote.

I need my on-prem stuff here. But then Salesforce kind of broke that mold with the SaaS. And they did it with a bunch of money and a bunch of marketing. So to break the perceived value curve and chain out there, does there have to be kind of an economic shift or can companies selectively make that shift in their buyers' minds themselves without having to have that monumental shift? Kind of like what you said with Elon. Well, what you're saying is, I would argue, probably rarer than the fact that people form these limits that you can discover. So what we try to do is we try to make sure that people don't overprice products or underprice products or suppose that the demand curve is way out there so that they can build a lot.

So just to give you some examples, take a couple from aerospace, we found a company up in Reno that was going to build a supersonic business jet. Now that was going to be a paradigm shift because nobody had a supersonic business jet. So we looked at the amount of money they had for cost and they had a development cost that seemed reasonable. And their price, even though it was $120 million, we could support that price by some analytics. It said, ah, looks like it's out with that. But then they supposed that they were going to sell 300 of these supersonic business jets in a decade and 500 overall. Well, it turns out that the world records how many business jets are sold. And you could go pull that data.

You could pull the prices and you'd find out that when they launched in 2014 with 20 orders, the world said that you can probably get about 47 plus or minus an air bar. And then five years later, it said you could maybe get 63. Well, five years later after they launched, they still had just the 20 orders. So I wrote a little bit on LinkedIn that said it was worth every penny, but there weren't enough pennies in the world for the world to buy this in sufficient quantities for this company. And they got kind of nasty and they wrote me a note back. So we got a big order. They didn't mention they were all options, which in an aerospace means if you build it and it works, then we'll buy it. But we're not going to give you the money up front, which is how everybody else works, like Boeing and Airbus.

And they went bankrupt in six months. So that was an example of overestimating demand. And then over in Albuquerque, a very smart individual, he was the seventh employee at Microsoft, a guy named Vern Rayburn. Well, Vern Rayburn had built computers because Microsoft built computers back in the day. And he said, well, you know what I'm going to do? I'm going to make a business jet, a very small one, and it's going to be very economical. It's going to have five seats. It's going to go 430 miles an hour. It's going to have its range. I'm going to sell this jet for $775,000. Well, if you did the analytics and we did it, you would have seen that the plane was worth about $2.2 million. And he's selling it for roughly a third of what it was worth.

And so you can imagine if you had 20 condos in your hometown that were worth $2 million, you were going to sell them for $775,000, you'd be flooded with orders. Well, he put this thing out. He was flooded with orders. And he couldn't build them fast enough. He couldn't get the margins. And he had some technical issues, too. And so he went bankrupt, too, on that. And the thing is, is that people have these behaviors that you can characterize. Now, what you're talking about is harder to figure. I mean, who would have figured before COVID? Like you were saying, how do you figure the change in training? Now, once you see it, you can react to it. But anticipating, it's pretty hard to do, you know?

Yeah. And that's why I was kind of curious. Because, you know, a lot of what you're talking, you know, when it says, how do you find, describe, and capitalize on open spaces in your market, right? A lot of this comes with the blue ocean, right? That whole idea of like, hey, there's the red ocean and the blue ocean. Go to the blue ocean where there's not as many competitors, right? But I guess I'm trying to figure out, like, how do you identify it before the shift happens, right? So you're there early. Because a lot of every, my experience, at least in entrepreneurship and startups, is timing is everything. You could have the best product for the best market, whatever, the best price. But if the market isn't ready for it for whatever reason, then it doesn't matter.

And I've had, I've got 10 examples of myself, the things that I thought were fantastic, but I missed a fourth dimension here. So one of the things you said, you said, buyers self-organize their behaviors according to the law of value and demand in which one product features determined value, two value drives price, three price limits quantity sold, and four quantity sold is a feature. Seems to come full circle. I need some clarity on that. Yeah, people say, Doug, I need clarity on that. What's that? John, it's always been circular. That's my response. These are opposing forces. People, if you take away their cars again, if you have money, if you offer more horsepower, people will pay for it.

If you offer more rage and you can afford it, you'll buy it. But as the prices go up, the quality sold goes down, which is to say these things are always linked. So the added features add value and add price, and the added price reduces the amount of quantity sold. And so they form this four-dimensional system that you can actually plot using a 3D printer, which we've done before. And so back to your other question about blue ocean strategy. You know, I've read that book. I got it up here on my shelf. That's a kind of, you know, a heuristic way of going about it. They kind of talk about features in general, and they don't quantify them. And what we do is we quantify every feature that goes into a product and actually plot them as little points in space.

And those points in space show you where people are congregated. And if you have some openings, that'll show you where they're not congregated. Now, I can give you another example about something about how, why people do this. And I've done this for years. It's something I came up with very late, but it's actually very appropriate to this. He said, so roughly about three months ago, I got done with a trail run, and I was standing at the end of this trail, got off the dirt, got onto some asphalt where my car was. I was leaning over, breathing pretty heavily, and I looked down, and I saw a tiny little reddish black ant. And I thought to myself, well, Richard Feynman, the Nobel Prize-winning physicist, Richard Feynman used to watch ants.

I said, yeah, I'm going to just take a few minutes out of my life. I'm going to watch this ant work. And so, all I did, I see this ant starts to make a gradual counterclockwise turn. It kind of stops and fits and starts. And eventually, he goes 360 degrees, but he's a little bit wider out at the end of 360 degrees than he started. And then he does it again in little jumpy things like this. And he makes another 360 degrees. And then he does it again. And he's out further still. And I realized when he's stopping on these rocks, these little pebbles, you know, asphalt not being even, the higher asphalt pieces, he's just stopping there and he's taking a look. I said, and he's going out wider and wider.

And I realized this guy, this quarter inch long ant, he's doing reconnaissance. So, I went home, raced home and typed ant reconnaissance into a Google search bar. And sure enough, ants do recon. And what they do is they look for places, these are called rock ants out here. They look for places that are flat, dry, have the right amount of floor area, don't have too much headroom, but enough. And what they do, importantly, like what people should do in markets, is they look to avoid neighbors. They try to get away from people that can edge in on their territory. So, this specific species of ants has been around 140 million years to 180 million years ago, which tells us that since we're smarter than ants, we've been doing this since there have been humans doing recon.

And so, the recon, in this case, is actually looking for housing. And it has the same kind of salesy stuff that you do, which is you're figuring out, well, what's this worth? What's that worth? What am I going to pay for this? Why should I employ, if you're an ant colony, why should I employ somebody doing recon? Because that's part of what their output is, is they got some guys that are building the nest, and other guys are about there researching the nest. And so, they actually form a little economy for themselves where they have people doing recon that comes back and gets translated to the colony so that they can actually get a better life themselves by finding out where they need to go. And that's really what humans are trying to do, too.

So, then why do so many products are so over-feature oriented? And the context of this is in the SaaS world that I live in, right? I wrote a blog post a long time ago called Sell to the 20%. And it's my fundamental belief that if you pick any product or service you own, I guarantee you only use about 10% to 20% of the functionality of whatever that product or service is. And so, because of that, that's how I believe people buy, right? They don't care about the whole thing. They care about the part that's most relevant to them. But that's different for everybody. So, how do you, you know, how do you, and quite frankly, a lot of the companies that I work with are engineering founded and led companies.

And so, I always find a drastic difference between an engineering led company and a sales led company. An engineering led company thinks the product and the features should stand on its own and we're the best. Whereas a sales driven company thinks it's about how you sell, not matter, not what you sell. So, how can, how can, let's, let's talk about it from a corporate and then an individual standpoint. As a business, how do you start plotting the features, if you will, and let's just assume that we've already built the product and we're already go to market, that type of thing. But how do you plot the features that people are actually using to find the white spaces of what people don't care about?

And then how does that, and then what do you do with that information? And then I want to talk about the sales rep themselves, but how do, as an organization, how do you find those white spaces to, to avoid? Well, first of all, the, in an ideal situation, what we do is we, we don't build the product first and then try to find the, the, uh, the open space of the market. We, what we try to do is find the open space of the market and then figure out the specifications that would suit that. But if you've already got the product built, what does this tell you? You've got two or three options. Your price could be perfect, in which case you don't need to do anything. You just need to sell it, but what happens if the price is too high?

Now, if you can do the analysis, you can figure out what would happen if, if you were to sell this thing, what happens if you drop the price? Well, you're going to sell more, but your margin goes down. So you have to be able to figure out what the difference is in how your margin is going to go down versus your costs to produce that. On the other side, if the, if it were priced too low, much like that business jet, what happens if your price goes up? Well, in that case, the guy couldn't keep up. So if the price had gone up, his margin would have increased and he still would have had sufficient cap capability to build the number that he needed to do. And so it comes down to, and when you're, your point about engineering companies is great because, you know, I worked as an engineering firm for 31 years.

And as you know, with the engineers, if you get something that was bright and shiny, like that supersonic business jet, well, the engineers get really excited about it. And then you say to yourself, okay, I'm a, I'm a sales guy, but how excited is the market going to be about this? And so in a blog post I just did about a night, a really fast, shiny thing by my ex company, Lockheed Martin, they decided to build something called the AGM 183. Maybe some of your listeners heard of hypersonic missiles. Hypersonic means that it goes faster than Mach 3. And so Lockheed was going to make this hypersonic missile that was going to go Mach 7, which is fine, but they wanted the range to be a thousand miles, which I figured out was not fine.

And I'll tell you why. Because at a thousand miles range, that means this thing became as big as a good, you know, a small jet plane by itself. And so along with the, the, the, the, the size of this thing being big, it was as costly as a midsize, as a midsize Gulfstream aircraft. It was $42 million for the first one. And the congressional budget office in their infinite wisdom said, well, I wouldn't offer him to buy this, this version, but we think whatever version we buy, they'll start at 42 million. By the time we get to a hundred, they'll be down to 14 million. We can buy a hundred at that point. But what we do is we go out and say, well, let's go look at the points that you actually have purchased.

You being the U S government, which you have purchased over 20 years and start to plot those things. And you come up with a little line and that line says that, oh, you're down here. You can sell a hundred. Sure. But there has to be three and a half million, not 14 million. And so what's the chance of that happening? Well, it's less than one in a trillion. That will not happen. And all these brilliant engineers at Lockheed didn't take the time to do this job that you can do this for, you know, most guys after, you know, it takes a few weeks to retrieve the data. And once you jam it through the software, the software takes care of it pretty quickly. Mostly it's data retrieval that we spend our time on.

But that engineering firm didn't bother to do the sales analysis back to your point there, John. And the sales is everything. I mean, just because you make something cool to make your company profitable, you got to sell it. Do you believe that in the old adage here, everybody, people buy on emotion and back it up with fact? Oh, God, yeah. And they build with emotion, back it up with fact. That's the same thing we just saw here. Right. Yeah. We've seen this in droves. And so back to your point about a lot of products failing, one of the books that I've read that I consider myself a competitor against by Clayton Christensen. Now, he's got some points I really like, one of which is, he says that 95% of new product ideas fail, like the ones I just mentioned.

Well, why is that? Well, in many, many cases, they haven't bothered to do the analytics. And so what we're hoping will happen is that people start picking up these ideas and start to percolate through industry and academia, government, and people will start to say, you know, if we do this and we apply this every time, instead of having only 5% of the programs that we're launching, products launching that are successful, what if we made it 6? Go from 5 to 6. Well, you know, you could look at it the other side. Oh, you're going to just drop your failure rate from 95% to 94%. Well, the other way to look at it is, no, I'm increasing my success rate by 20%, going from 5% to 6%, or maybe even 7%. Well, what would happen to the world if we get more and more products that launch successfully because people took the time to figure out what would work successfully?

Now, having said that we've done the analytics, just because you've done the analytics, no guarantee you're going to get the product to work. I mean, there's a million ways you can fail. Let's take a couple off the table before you start. Let's take away the, you know, I'm going to over, I'm going to overprice it. I'm going to, you know, suppose the quantity is too great. I'm going to suppose people like this feature. When they really test out, they like that. You got to take a few of these, these things that you could know in advance and take them off the table. So what we like to talk about, John, is that we like to take the distant past, take a good look at the distant past, the near past, and the present to predict the near future.

So the distant past, near past, and the present can predict the near future. If you can think of it like a soccer ball. If somebody kicked a soccer ball to you from 20 yards away. So at 20 yards away, that's a distant past. Gives 10 yards to you. That's the near past. It comes up to you. That's the present. Well, you've got a pretty good idea where that ball is going to go the next three to five yards. And that's kind of what we're trying to do with the analytics is to show people what people have done over time and then work out what we would call the economic trajectory analysis or the ETA of where the market's moving. And so that turns out to be a pretty useful concept as you go forward in this.

How does this compare to or relate to design thinking in a lot of ways, right? Because when it comes to sales, right? I mean, design thinking is usually a lot of product, right? Where they watch the consumer and then they create the product based on the consumer. What you're doing to a certain degree is looking at the market and creating market pricing and products that fit to where the market is. Because I see a lot right now of design thinking being applied to sales where they walk into a customer and instead of going top down to the CEO and trying to sell them on this big vision, they work the floor. Or they understand the workflow, you know, the flow throughs and the logistics of things.

And then they come up with a solution that fits their needs, right? So are you basically taking that approach to a market as opposed to a sales scenario? Well, I'd say we're taking the approach that if you had given enough market, the market will tell you through the analytics. It tells you what it wants, doesn't have and can afford. What it wants, doesn't have any kind of form. So basically, it's giving you some sense in these responses about how it responds to getting back to electric cars, how it responds to horsepower and range. It's giving you some looks about the open spaces relative to price. So if your cars, back in the early, in the mid-10s, there weren't any cars that were between 300 and 500 horsepower.

I mean, we remember the big Tesla, the Model Ss had, you know, started at 700 horsepower and went up. And nobody had built anything that was in 300 to 500 horsepower range. So if you know what people have spent for this amount and you know what they've spent for this amount, then you can interpolate in between to do that. And then back to your other point about the, try to work out the design. Now, it's not all the physical features. We had an outfit come to us, can't mention the company, but it was a general aviation company that was building a new plane and they had a certain range and seats and speed and all that kind of stuff, the things that you know you should pay for. And so we're starting to work all that stuff out.

We give them an answer and they said to us, great question too, by the way. I said, Doug, we think our plane is prettier. It's better looking than the average plane. Can you figure out what our plane was worth for the added cosmetic features of it? I never looked at that, but let's try that. So what we did was we took three view drawings of every plane that was in our database. And then we passed them out to people in a survey mode. They said, rate these planes from zero to 10 based on how attractive you find the lines. And it turned out that one of the best selling planes in the industry was the most attractive. And her client's plane was close to being the most attractive and it added value to the plane.

So you can use these quantitative measures for qualitative features. I'd venture to say that that was actually Tesla's, my ignorance of the data and the analytics side of this, where I, because my wife's an environmental scientist. We actually had, you know, the movie Who Killed the Electric Car by General Motors, like how they had the original electric car and we killed it. So we actually had one of those, right? And then we went to the Prius, which I hated, you know, because it just looked like it just looked dumb. You know, I had this little bullet that we like kind of looked dumb, even though the thing screamed and I was like shut my mouth when I got into the thing. Then we had the Prius and I literally, I felt like an idiot, you know, no disrespectful people who drive Priuses, but I just felt like an idiot driving the thing.

It's probably my ego over anything else. But then Tesla came out and the Tesla looked awesome. It looked like a badass car and all the other stuff. Yeah, range was better and all this other stuff. But to me, the biggest thing that hit was, holy shit, finally a car that looks cool and is electric. And I think that was the premium. I don't know what their economics are as far as how much that thing costs to make and if it's better or worse or whatever. I don't know, but I do know that that perception of the cool factor was what I think shot Tesla through the roof. Yeah, yeah. That can be a big adder to our car. Now, having said that, what's also interesting too is, you know, some of your listeners probably don't remember the DeLorean automobile, except maybe they saw it in Back to the Future.

Back to the Future? You know, if you don't know Back to the Future, then you don't know you haven't been listening to this podcast. Back to the Future is awesome. Yeah, it is. It is awesome. And, you know, there's a line in there when, you know, the Doc Brown wheels in the DeLorean and Marty says, in shock, he says to Doc Brown, he says, you build a time machine out of a DeLorean? And he says, the way I feel, the way I look at it, you got to do something that's kind of cool. Yeah. And so, DeLorean was selling cool with his car because, for those of you who don't remember, it had gull wings, that was a big feature of it, and it had stainless steel construction. So, he was selling this car, and it turned out to be about as much as a Porsche 911 back in the day.

But the Porsche 911 and cars of that type had roughly double the horsepower that the original DeLorean did. And so, what happened then was that, yeah, people like the style. Some people bought the car based on the style, but, you know, people like sports cars like horsepower, too. And so, there wasn't enough horsepower to be built. So, he missed the value proposition. So, he tried to sell it for $25,000. Our analysis said it was worth closer at $15,500. There was a demand limit out there. It said that he could probably sell $6,000 or $7,000. He built $10,000. He ended up holding a lot of those. And, in fact, he didn't hit the limit because the car wasn't worth everything that he wanted it to be worth because he priced it too high.

So, yeah, it kind of cuts both ways. The appearance is huge. You know, the Tesla is a testament to that. But you've got to integrate all these things together at the same time to try to make a good product. Did Henry Ford do that? So, let's go back to the early days, right? Like, the whole adage, everybody's heard the quote, you know, if I listened to what the market wanted, I would have built a faster horse, right? And so, he built something, right? He built something that, like, the market wasn't asking for, right? So, and again, let's just make sure we're clear. He didn't invent the automobile, right? The Germans did. But he operationalized it. And he created the assembly line. So, what was that analysis like?

Like, if you were to plot this, did he just hit because it was a gap in the marketplace that people didn't even know they needed and he figured that out? Like, help me understand how this plotted against that, allowed for that to happen. Well, I think there's a couple things going on here, John. One is what you just said. There was a gap in the market. If all things being equal, if you wanted to go someplace at 20 or 30 miles an hour versus six with a horse, people are going to go faster if they can. And they don't have the smell that it comes out of the horse that you get with a car. So, that's part of it. But Henry Ford's great contribution was the assembly line. And he figured out how to keep dropping costs out.

So, one of the things, in fact, it's an example in my book, is that as you continue to build stuff, in order to keep selling it, it's like big screen TVs. Big screen TVs now cost 3% of what they cost 20 years ago. Now, how do I know that? The Bureau of Labor Statistics actually captures that data. So, if you were to buy a 720 DPI screen, I don't know if they make them anymore, but this is as a couple years ago. Well, back in the day, that was HD back then. And you were to buy a 36-inch screen. Well, you could buy a 36-inch screen that has 720 DPI. You could buy that for 3% of what it cost 20 years before. So, how did that happen? Well, the TV manufacturers got really smart and they figured out how to drop the cost.

As long as they could continue to drop the cost and they could sell it for more than it was costing them, they can keep making this wedge, this profit wedge. And that's what Henry Ford did. He figured out that he could keep dropping out the costs and he could keep dropping the price. Now, you know, he was inventing mass-produced cars and he built, I think, 16 or 17 Model Ts, to your point. You know, held the record for the most models built for the longest time. But what he was slow to recognize was that people wanted more at a certain point. And back to the other point is they wanted a better suspension. They wanted to be, you know, wanted heaters, colors. Yeah, they didn't want it to all be black, you know, new styles.

And to him, that was kind of foreign because he'd done so well with what he had. But the point here is that you're trying to listen to what people want and what they're telling you. So you try to keep your finger on the pulse of the market to see how things change. Because the one thing that's constant about the world is change, is people change. Things aren't the same now as they were just a few years ago. I mean, COVID made us all realize that. So, I mean, it sounds like Elon has definitely done this with the Tesla. And the examples are in multiple areas. Because when I first bought, when the X first came out, right, like the one with the Falcon doors and the whole thing, I was able to go online and I was able to configure mine, right?

I could have the heated seats. I could do this. And it wasn't a lot of options, but there were options. And then when I got, then, you know, a couple of years went by and then the lease ran up and I got the Y because I just liked it a little bit better, you know, whatever. And then when I went on, there was no options. It was, here it is, right? This is what you get. And you can get, you know, and it didn't, you could, before you could even buy the battery length, right? Like this one got you this far. This one got you that far. This one got you this far. Now, the only thing you can do is buy like the, the hyper fast, you know, ultra version with plaid or whatever it is. And then the baseline version, but the baseline version, the only option you have is basically the wheels and the color.

That's it. So did he plot? Do you think? And also, I mean, again, let's keep using the Tesla as an example. You go into the Tesla. The first Tesla had the dashboard that everybody was used to, had the normal steering wheel that everybody is used to. The new Y that I have, there's just an iPad. There's no front dash. It's the iPad. And even the newest one has this weird ass, you know, joystick handle thing that I couldn't stand instead of the round wheel. So he's purposely taking away what seemingly are features that people are very used to in a normal car, but he seems to be doing it in a way that is graduating us to a different world, if you will. Is he doing this plot matrix? Like, how, how do you think they are looking at this?

Are they constantly looking at the features that people are using and not, and then just getting rid of the ones that are not high value? Yeah, I think that's, that's probably exactly spot on, John. I think what he's got a team of statisticians that keep testing, you know, they would bring people in the focus groups. What do you like this or this? Do you like this or this? Do you like this or that? And you keep testing this over and over again with a bunch of people, much like we did with the, uh, the shape of those, it was general aviation planes that were out there. You just keep testing until you refine it to the point where more people like this more often than any other option that we've got.

And then the whole thing about necking down the number of options that you have. I mean, one of the problems that Ford and GM had in the early 2000s, I think they still have this problem is that unlike some of their Japanese competitors, they might have 40 different chassis or 50 different chassis. And they're putting a whole bunch of bodies on top of these things. And so if you look at something like Toyota, they've got two or three chassis. They've got the Corolla chassis, which can go be moved into a, an SUV. They've got the Camry chassis and they've got the extended Camry chassis. And then they make the SUVs off of that. So they've necked down the number of options. So they don't have the, what basically happens in a, in a, in a productionalized, you have what's known as learning, learning curve.

And if you get, if you learn over 5,000 units, the cost will fall more than if you only learn over say 1500 units. So if you gave somebody three options and you've got 1500 of one, 1500 of another, and 2000 of another, you're not going to get as much learning as you would if you could get 5,000 of one. So they probably figured out, well, we'll just get by with two or three options here and then we'll, we'll reduce their options, but it keeps us learning at a, at a really high rate. And that's, that's kind of what we want to be able to do is, is to, is to be able to learn at the, at the longest possible rate for the longest possible time. And that, that's kind of what I think behind what Tesla is doing.

And, um, that's, uh, yeah, it's just, it's, it's commendable what he does there. And two, and then the other thing that hasn't caused the attention of most people is to the, the same degree as what he's doing with satellite service. His star link system, he's putting up these, these satellites that just weigh a few hundred pounds instead of tens of thousands of pounds. And he's taking, setting up 60 at a time and he's working, trying to get a network of, I think about 18,000 of these guys now. So there's an interesting map that shows up, that shows star link coverage and it shows all the satellites that he has floating around the planet. And when you talk about trying to fill open spaces, well, there's nothing so graphic as, as satellites filling open spaces in the sky.

That's an exact, you know, just a one for one translation of the, the, the, what we're trying to do with hypernomics in terms of trying to figure out how to, where to go as we go forward in our, uh, building things. So let's, let's finish up with the application to sales, right? So I think this go-to-market strategy, you know, trying to find that blue ocean to a certain degree using plots and data, plot the dots, I think is, is how you described, you know, if there was one sentence to describe the book, um, as a sales rep, right, we're dealing with a fixed product, if you will, you know, a solution that somebody else has dictated, uh, the price and all those other stuff. But the key is obviously finding the clients, right?

Like where is the, where's the white space with the client and, and what did they value versus what everybody else values, right? Let's go back to that sell to the 20%. How would a sales rep using kind of the, the, the theory or the practice around this, be able to apply it to find where the value and price, you know, and the four dimensions intersect, if you will, for the client for what they're trying to sell. Is there a practical application for a sales rep to be asking questions, to be plotting certain information that they can use to then determine this client doesn't value these things. Um, therefore I need to focus on this or my pricing. I can hold it because they see the value of that versus I got to discount this because the price, the client just fundamentally doesn't seem the value in this.

Even though my company's telling me it's fantastic. Well, that's an interesting question, John. I hadn't thought that through, but what we've discovered in the, in the past, just to do a little end around on this is that we, we've discovered that the, the technique of hypernomics works in different fields. So for example, in, with respect to COVID, COVID, instead of trying, COVID not selling for, it's not trying to solve for money, it's trying to solve for cases. And so COVID goes, and these might be sales, COVID, COVID, uh, looks at two primary factors, or at least in 2020, early on when the, in the epidemic, COVID was looking for the population density of a country. So if you were to plot the cases per capita against population density, you'd find that the COVID was pretty highly correlated to the population density.

And, and that was expected. But what wasn't expected was that COVID was also pretty highly correlated with high income countries where the per capita income was higher. Now, I think as time went by, people said, oh, well, the reason is, is because high income people at the beginning of an epidemic are the ones that are traveling and they get a chance to spread the disease. And that's what COVID liked that a lot. And so the, the sales application is something like that is to try to figure out your, you know, your target, you know, the number of sales and you'd have to try to figure out, well, what do these people like, as opposed to, you know, they're making this product. I got to make the sale.

What are these people like in salespeople? Do they, I mean, they like the, the approach that you have, because you might say, well, you know, you're going to be affable with them. You're going to be accommodating. You're going to be able to give them discounts if they want it. And you measure your discounts against what you need to do for your goals. But you'd have to have a lot of that stuff kind of pre-programmed in your head. I said, well, if they say this, I'm going to say that. I know you had Chris Voss on your program, whom I've met before. He's a member of the same men's group I met. Chris Voss talks about, you know, negotiations and never splitting the difference, but he does want to try to figure out what the other person wants and tactical empathy.

And so what you need to do, what COVID was doing, COVID was figuring out what it wanted. It wanted people that could infect and it just needed targets. And how did it get targets? It got targets from density and travel. You need to be able to get people that are amenable to your sales. And you need to figure out what it is that pushes that line up for you versus what, what would push the line down for you. Yeah. Yeah. And I think that's the, the, uh, the never ending challenge of sales professionals is to find like, especially in complex sales, you got three, four, five, 10 buyers, sometimes in finding what they value versus others and therefore, and who values it on the, on the value chain or the decision chain as well.

Right. Cause there's some people below non-decision makers, if you will, that value certain features really, really high. Whereas the ultimate buyer doesn't necessarily care about those features. They care about some other stuff. So plotting that, you know, it'd be interesting almost to do a 3d map of every conversation that you have in a complex sale and seeing where those dots, if you will, intersect, right? Cause that's what I, I try to help as reps figure out what's the Venn diagram here, right? So if I'm talking to the technical buyer and the economic buyer and this buyer, you know, that type of thing, they're all going to have their own priorities and challenges, but what's the Venn diagram where we can all kind of agree that this is the problem, this is what we're trying to solve.

And this is what's important. And then hyper-focusing on leaning in on that to get everybody to agree. And it'd be interesting to apply this to a kind of almost like a sales process to see where those dots on that graph get plotted from a 4d standpoint. Well, yeah, and as you were saying that I realized that I, I, I realized an application of hypernomics that would be critical to you would be, you know, to the salespeople that you're working to, do they make more money with fewer, more expensive sales or do they make their money with many more, less expensive sales? And that's what's known in, in economics, well, they call it the elasticity of demand because they like to have a lot of syllables.

I call it the demand slope because I don't like that a lot of syllables and it basically is asking, well, what happens? Am I going to make more money making two sales at a million or can I, am I more likely to get six sales at 300,000 or 500,000? And so what you need to do over time, I would argue, is you need to start to try to plot that for your people and say, well, the, the, the data is suggesting that we're actually doing down here, we should be up here or we're up here and we should be down here. Now we're not going to give away the people that are at the top that we've, to whom we've already sold, but it works out in some markets that there's more money at the, at the lower price part of the market.

So back in aerospace, for those people that know airplanes that the government has, there's, there are 21 B2s that the government bought for about 1.2 billion, but there's about 4,800 F-16s they bought for 30 million, which means there's five, more over five times the amount of money in the F-16 as there is in the B2. Now you can contrast that with what it costs for reconnaissance. So there's a, there are $10 billion satellites that are out there and they might sell one or two or three and they make a lot more than the little drones that you see that they might sell. They might sell 19,000 Raven drones, but they're, they only cost 10,000 bucks a piece. And so there's a lot more money in the top of the recon market than there is the bottom, but the converse is true when it comes out to a military fighter and bomber aircraft.

And so it would be very useful for your sales team to actually plot that for themselves and say, well, what, you know, where should we lean, you know, because we only, we only have so many resources. Should we go to the top? Should we go to the bottom? Should we go to the middle? Do we have, is the middle underpopulated? Is the edge not populated enough? That would, that would be a very useful question to be answered. In fact, the first thing we do in any market is we try to plot the demand because that's only a 2D, 2D issue there. So we try to plot the, you know, again, the plot is, you know, the quantity sold versus the price, those little dots, plot the dots. If you just plot quantity versus the price, you're going to see that over time that you're going to have this upper boundary that's going to form.

That upper boundary is your demand slope, your upper frontier. And you'd like to be able to know that. Awesome. Well, I got to read this book. So I, I skimmed through it. I picked out some of the highlights, but I definitely have to go deeper now. And I, and I'm going to suggest the rest of my audience do the same thing. Well, I appreciate that. So absolutely, Doug. So where can people find out more about you, about the book, about what you're working on right now? So they can, they can follow some of this stuff. And because I, and the reason I, you know, context here, and I'll, I'll set the stage for this when we kick this thing off or the preface to it. But a lot of sales reps are entrepreneurs.

A lot of sales reps are just inherently like looking for that next step. And I think sales is an entree to that world. And so understanding, oh, a great idea. Good for you. But if you don't have this plotted out, as far as price and all that other stuff, you could be failing to your point. Sure. 95%, 97% of the time. So where can people find out more information about this very important topic? Well, again, my full name is Doug Howarth. So I've got a website that's cleverly enough, DougHowarth.com. That's D-O-U-G-H-O-W-A-R-T-H.com. That's my personal website. We do all of our work on our company website, which is Hypernomics.com. H-Y-P-E-R-N-O-M-I-C-S.com. And the title of my book is Hypernomics Using Hidden Dimensions to Solve Unseen Problems.

And that's not a stretch. That's actually what happens. There are dimensions that you can't see unless you figure out how to plot them. And there are problems that you won't see unless you take time to work that out. So that book, again, Hypernomics Using Unseen Dimensions to Solve Unseen Problems, is available at Amazon, Walmart, Barnes & Noble, and the Wiley sites. And in some Barnes & Noble stores. Perfect. Awesome, Doug. Well, thank you again for coming on, man. John, thank you so much for having me. It's been a great pleasure here. I really appreciate your time. Thanks. It's been a fun conversation. So, everybody, I hope you enjoy the conversation as much as I did here. And piqued your interest in this topic because, again, it's all about leveling up here.

And whatever your future holds, this could be a part of it. So, like I say at the end of all my podcasts here, go out there and make somebody smile today. Because no matter how bad your day is going or how bad you think it went, you make somebody smile today and you know you had a good day. And the world needs a lot more of that right now. So, thank you all very much. And I will see you on the other side. I hope you enjoyed that conversation as much as I did. With your support and our incredible guests, we're one of the top sales podcasts out there right now. And I can't thank you enough. Now, to keep the momentum going, it would mean the world to me if you could go and leave a five-star review on your favorite podcast platform and share some of your favorite episodes with your network.

Also, check out my new website, jbarrows.com, where you'll find even more ways to engage. There's a ton of free content and you can also get trained from me directly as an individual or for your team. Look, I'm out there selling every day just like you are. And I'm doing my best to stay on top of all the latest trends in sales and technology. So, if you're looking to level up and you give a shit about this profession of sales, let's connect and make it happen together.