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Dude, Where’s My Geometry?

Let me tell you how it will be/There’s one for you, nineteen for me
The Beatles, Taxman

Hypernomics loves geometry. It touches markets in many ways, including the Demand Frontiers, notably as they mature. Ignoring market geometry can lead to unwelcome multimillion-dollar surprises.

In 2014, CO and WA legalized recreational marijuana. CO taxed it 30%. Seeking vast riches from this new revenue source, WA taxed it about 108% (it varied by county). At years-end, WA, with a third more people than CO, made $51.7M in recreational pot tax monies. CO made $375.4M.

What WA didn’t understand because they didn’t study it was the cannabis demand curve slope. While we don’t have the WA pot data on hand (they do), we have a like curve for cars. If we apply another 100% tax on vehicles, the number sold, given the demand slope, falls by about 70%-80%. As steep as these reductions are, they still don’t match the WA experience in 2014, suggesting the actual slope for recreational cannabis in that year was even flatter than that for automobiles.

But there is no need to guess about this. If you study it, within statistical bounds, market geometry will “tell you how it will be.”

#innovation #hypernomics #business #technology #management

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Two Trillion Dollars; One Hard Edge

If you inquire what the people are like here, I must answer, “The same as everywhere!”
Wolfgang Goethe

How did $2T in the 2018 new car market worldwide behave?

When it comes to market limits, it was in much the same way.

Figure A studies all 36 electric car models in 2018 for which there were sales quantities and prices, depicted by green dots. Added to them are 43 like figures for selected gasoline-powered models in the same year, shown by blue points. Note that while several models of each type do not sell well, those that make the most sales form a wall extending from the upper left to the lower right. The line described by the overlaid small red points is the 2018 Car Demand Frontier. Of all the similar curves we’ve studied, this one is the sharpest, with a minuscule Mean Absolute Percentage Error of 6.0%.

We see the differences between each sub-market in Figure B, where the prices paid for horsepower change between types and as sales grow.

Taking only 43 of the 100s of models of gas-powered cars, trucks, and SUVs offered represents a short cut. But, if we take the most popular (Toyota Corrolla) and expensive of them (Bugatti Chiron), it’s likely viable.

#innovation #market #future #economy #startups #management

Worth Every Penny – Not Enough Pennies

There are several ways to sink a new project.  A common method is to ask potential customers about their willingness to buy an offering and then suppose some fraction of the resulting sum is viable.  In the 1960s, surveys indicated there was a market for 200-300 supersonic Concorde airliners.

They built 20.

Decades later, multiple companies are entering this market again. One of them, Aerion, is building its AS2 bizjet (A), selling for $120M.  Suppose we compile and analyze a dataset of all business aircraft that cruise at 400 MPH or more.  We’ll then find a production possibility curve for planes worth $120M as shown in B (that curve has an adjusted R^2 of 97.5%, a standard error of $10.1M, and P-values of 6.11E-43 and 1.02E-19 for Cabin Volume and Max MPH, respectively).  By this measure, the AS2, over ten standard deviations above the line, is worth every penny.

However, in C, we find that the market only supported 55 business aircraft worth $80M or more for a decade, up only slightly from a like study done for the same duration done five years earlier (with 46 planes over $80M).

Five years ago, Aerion announced an order for 20 units. They have the same number today.

#innovation #markets #future #economics

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Introducing Hypernomics

“Everything should be made as simple as possible, but not simpler.”
Albert Einstein

The world oversimplifies.

Want more government revenue? Raise taxes. That’ll work. But why did Nevada make more cannabis tax revenue in 2019 than California with a tax rate of less than half of CA’s?

You’d like the safest helicopter in the world for the president? Put all the widgets on it. Oops, too many, it’s too expensive, Obama cancels it.

Do you like cool? I give you the DeLorean. But it’s under-powered. It won’t sell. The company goes bankrupt.

These are but a few cases where thin study led to bad outcomes. The solution for them and many more is to expand the analysis.

Don’t suppose you can get by with two dimensions when the problem begins with four.

Earlier, I called the field I found Multidimensional Economics. The research revealed that the forces within it exist beyond markets.

Thus, its new name: HYPERNOMICS.

Hyper-: Existing in more than three dimensions: hyperspace

-nomy-: A system of laws governing or a body of knowledge about a specified field: agronomy

-nomic: adj combining form

HYPERNOMICS studies forces working with and against each other in four or more dimensions.

#entrepreneurship #innovation #strategy #success #design

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Problem? What Problem?

A mathematical problem should be difficult to entice us, yet not completely inaccessible. It should be a guidepost on the mazy paths to hidden truths. – David Hilbert

In a space-limited outdoor diner we visited a while ago, we observed the seating arrangement in A. They had two tables for two and ten for four. Seven of the four-place tables had parties of two. So, I wondered – is the setup they had the best for the crowd they faced?

A report I found (see below) noted that restaurant parties of two outnumber four-person parties by over two to one. On average, there should be more tables set up for couples than for larger groups.

But the average condition may not be the usual one. Or the one they faced.

What to do?

Suppose the four left-most tables were modular. The establishment could separate them into eight two-place setups. Then they could seat all seven of their two-person parties and put a two-top in storage. Their capacity would go down by two (at least temporarily), but, in the case shown, occupancy could go up by 30%, as we see in B.

Restaurants make money through occupancy, not capacity. It’s important to know what problem you need to solve.

#sales #demand #restaurants #business #success #management #problemsolving

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Restaurant Math – Thin Odds

You spend your life waiting for a moment that just don’t come/Well, don’t waste your time waiting – Bruce Springsteen, Badlands

You know the feeling you get when you walk up to a roulette wheel in a casino, place a $100 on 00, it comes up, you win $3,500, and then you let it ride on 00, hit it again, and walk out with $122,500? No? Me either.

The reason I don’t is that while it’s possible to come up with that combination, the chance of that happening on a 38-pocket wheel is 1/38 * 1/38 = 1/1,444 = 0.00069, about 7 times in 10,000 tries.

But that is more than twice as likely as the probability of a restaurant result I recently witnessed.

As we left a brewery, it had four open tables; each sat eight, B. Four parties waited, C, held in place by their policy not to seat parties of four or fewer in tables for eight. But, the chance of filling them up according to their plan and the data, A, is 0.13^4 = 0.00028, less than half that of our roulette gambit.

Meanwhile, those people stayed hungry. They and the restaurant both suffered.

We are, all of us, always playing games of chance. It pays to know the odds. Anybody up for blackjack?

#business #success #management #probability #sales #restaurant

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Restaurant Math

“I was at this restaurant. The sign said ‘Breakfast Anytime.’ So I ordered French Toast in the Renaissance.”
Steven Wright

Forget about ordering off the menu; first, you have to get a seat. That’s not a given anymore.

It was never a slam dunk to get into our preferred local eatery. Once COVID-19 forced all patrons outside with social distancing, it was harder still. As we sat waiting for some seats for the third weekend in a row, we began to fidget. What to do? In an era where restrictions abound, sometimes it’s hard to see the options.

Happily, we knew the owner and every boss in the place. I pulled our most-beloved manager aside and asked her if she would be willing to rearrange the furniture and make more money. I explained to her that smaller parties were crowding out larger ones. Why not go from the arrangement you have (which was A) to one with several smaller tables (which became B), I asked? If you track the revenue changes, you’ll be pleasantly surprised.

As shown below, she did just that. Revenue went up by over 25%. Unlike A, Setup B recognizes they face a Demand Curve, with more parties of one or two people than groups of five or more.

#demand #demandanalysis #restaurant #restaurantmath #profits #revenue

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A Sufficient Condition

For a successful technology, reality must take precedence over public relations, for Nature cannot be fooled
Richard P. Feynman

Feynman’s observation about truth is one that can move past physics, where he won the Nobel prize.

It happens that in all markets, we collectively form relationships about how we respond to product features and prices. It is our Nature.

As we build, say, a helicopter for the President of the United States (A), we might be inclined to keep adding to it: unprecedented speed, a larger cabin, extra defensive systems. After all, we might tell ourselves; there won’t be a more important thing in the sky. It is a necessary condition to protect it and everyone inside.

The bonus features drive an increase in Value – and Price.
But at a group-induced limit we call the Demand Frontier, sales stop. We do not have any more monies to buy more of the product in question past the points on that line. Trying to exceed the Demand Frontier is a sufficient condition to stop any program.

In the case of the VH-71, USG requirements creep let it become untenable. All of that could have been avoided by analyzing the market as in B.

Doing a market analysis is hard.

Losing $4.2 billion is harder.

#innovation #demand #marketanalysis #business

 

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Finding Your Niche

Wee Willie Keeler knew a thing or two about baseball. The Hall of Famer still holds the National League hitting streak record, 45 games over two seasons. He summed up his approach with “Hit ‘em where they ain’t.” It turns out that’s sound advice for entering a market, too.

In the early 1970s, the airline industry embraced the then-new Boeing 747 wide-body. Lockheed and McDonnell Douglas both wanted some twin-aisle profits as well. They came up with the L-1011 and DC-10, respectively. While they had obvious design differences, from the standpoint of their customer airlines, they were virtually identical, with highly similar specifications and prices. Neither had a corner in the market – they shared the same spot, and would have to split the sales.

Lockheed only sold 250 L-1011s; its break-even point was 500 units. With a lower target, McDonnell-Douglas managed to squeak past its break-even value of 438 planes, as it sold 446 DC-10s, eventually offering engine options and added range to distinguish it from the L-1011.

But neither model was a financial triumph.

Nothing guarantees success in the market.

But mimicking the competition reduces your chances.

#innovation #newproduct #business #success #branding #competition #entrepreneurship

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Steep Learning Curves

A 2016 EPA paper called “Cost Reduction through Learning in Manufacturing Industries and the Manufacture of Mobile Sources” estimated automobile learning curves at 84% to 88%.

Some think “steep learning curves” are a bad thing. Used in their first sense, i.e., how quickly someone learns, it’s the opposite. Learning or experience curves measure time reductions to do a task as repetitions of it double, as percentages. If it took you 10 hours to do a job the 1st time you did it, 8.4 hours the 2nd and 84% of 8.4 hours or 7.1 hours the 4th time, you’re on an 84% learning curve. If you took 10 hours for the 1st job and 8.8 hours for the 2nd one, and 88% of 8.8 hours or 7.7 hours for the 4th, an 88% curve described your experience.

Our 1981 auto industry work found that Product Demand fell at the equivalent of an 87.2% curve. As shown below, eventually, a flatter 88% learning curve for a car could intersect its Product Demand Curve. Then, production ceases, as its cost exceeds its sustainable price.

A steeper cost curve of 84% never approaches the Product Demand Curve; instead, it diverges from it. In such cases, Demand Frontiers limit sales.

Moral of the story: Steep learning curves are good.

#innovation #learningcurve #sales #steeplearningcurve