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Triple Limited Demand

And he writhed inside at what seemed the cruelty and unfairness of the demand – C.L. Lewis.

Many products sink due to scarce sales. Uninspected, market boundaries seem murky.

Hypernomics can project at least three demand limits before entry, reducing the chance of overreach.

Pilatus makes the PC-12. It’s the best-selling business aircraft model (1st limit). Part of its appeal is that, by some measures (not shown), it sells for less than what it could command. The relatively low price boosts sales and shapes the statistically significant (P-value 1.5%) Outer Demand Frontier, a saturation limit the market collectively creates.

In 1981 car buyers revealed a Product Demand Curve (P-value 2.00E-05), a term applied to all models (2nd limit). If a given model were popular enough (as the Porsche 911C and BMW 528i), it would eventually find itself limited by the Upper Demand Frontier (P-value 0.01%), as it helps form a communal price limitation.

If a Product Demand (Price) Curve is steeper (more negative) than its related Unit (Recurring) Cost Curve, they may eventually intersect. If cost >= price, a line stops, as it is no longer be profitable, as was the case for the Ford Model T (3rd limit).

#hypernomics #markets #innovation #sales #demand

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Interactive Redundancy

Redundancy is ambiguous because it seems like a waste if nothing unusual happens. Except that something unusual happens-usually. – Nassim Nicholas Taleb

Life assures little.

Recognizing that, many create contingency plans. Backup aircraft flight controls systems and duplicative car safety features save lives. Emergency generators keep hospital lights on.

As history shows judges favor local athletes, many sports force even-handed results through mandated redundancy. In A, only three of the seven scores will count for the diver (B).

Rather than rely on a single Value estimate, Hypernomics takes redundant cuts at market reactions. In C, the general aviation aircraft market values horsepower and speed. However, those features correlate with one another. We can use that to our advantage. Equations 1 and 2 use horsepower to drive Value. The 3rd equation uses speed. Equation 4 combines them. Various groupings of valued traits should be tested, with outlying results discarded as in diving.

Excel has many handy controls in its Developer menu. In C, Scroll Bars drive inputs for Equations 1-4, letting users place products in market gaps interactively, in the manner of my most recent post.

#hypernomics #markets #innovation #sales #technology

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Gap Maps

If everybody else is doing it one way, there’s a good chance you can find your niche by going in exactly the opposite direction – Sam Walton.

Lots of people will tell you to discover your niche. What if you could map it?

Hypernomics shows you how.

On September 16, 1893, tens of thousands sought such openings in the 4th Oklahoma Land Rush as guns went off at noon, signaling the crowd the game was on. Those who waited for the cannons were “Boomers” (A), but many “Sooners” jumped the gun and got some of the best plots in the Cherokee Outlet’s eastern part. As many would discover, its western end was prone to drought and later formed part of the Dust Bowl with a moving Frontier (B). Figuring which tracts were viable was tricky.

But in C & D, market maps reveal several flourishing models (blue dots) bounding spaces without competitors. If a new model enters a region in C (red circle) and offers the indicated and other features that create value (through analysis not shown), it may by design enter a price gap (D). By interpolation, we know buyers will accept its specifications and price. It then has open market space for both, thereby not so much finding as creating its niche.

#hypernomics #markets #innovation #sales #technology

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Chasing the 8th Dimension

“May I pass along my congratulations for your great interdimensional breakthrough? I am sure, in the miserable annals of the Earth, you will be duly enshrined.”
Lord John Whorfin, The Adventures of Buckaroo Banzai

In the film named for him, rockstar, brain surgeon, and test pilot Buckaroo Banzai drives a pickup through a mountain and enters the 8th Dimension. That geometry seems impossible to imagine.

Or is it?

Hypernomics studies nonnegative market and mathematical dimensions. Without needing to navigate negative regions or physics, new coordinate systems open up for us.

As we see in A, we can portray missiles in a 4D system like the one we used for general aviation planes in the last post. Separately we can do the same in B for bombers. But, are they separate? The 4 dimensions portraying the missile market match the number needed for bombers. But since both share price as a nominally vertical axis that links them (Dimension 3), we can reuse that line, as in C. Here 4 + 4 = 7 dimensions.

How do we get to 8 dimensions? Figure C represents a snapshot in time. If we trace a path through several such views at different intervals, we add time to the mix, reaching the 8th Dimension.

#innovation #hypernomics #economics #markets

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3 + 2 = 4

No one is so brave that he is not disturbed by something unexpected
Julius Caesar

It’s disturbing to think that 3+2 won’t equal 5. Or that markets are unlike space and begin with four dimensions. Or that we might discover images that disagree with paradigms held for over 100 years. But what happens if we use Hypernomics to take a new look at an old problem?

Let’s see.

Suppose we want to see how customers value products. Specifically, let’s consider the three aircraft models in Figure A. We’ll want to examine features that might be important to customers, here, Max MPH and Seats. Those features mandate a pair of horizontal axes; their combined effects drive a third vertical axis, that for Price, making three ordered triples.

At the same time, we may want to plot each model’s quantity sold as a horizontal dimension and couple it with its associated Price on the vertical dimension for three ordered pairs, as we see in Figure B.

But the three dimensions of Value Space are not straight additions to the two dimensions of the Demand Plane. Instead, as C reveals, 3D Value Spaces and 2D Demand Planes share the Price Axis, forming 4D structures, thus 3+2=4. Four dimensions offer more insight. Time adds a fifth dimension.

#innovation #hypernomics #economics #markets

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Lost In Place

Danger Will Robinson!
Lost In Space TV series

Hypernomics wants to know: Where are we?

Concerning geolocation, it’s an easy question today. Google can map your global spot within a couple of feet. Thanks to modern navigation techniques, going through the western end of the English Channel is trivial now. But it wasn’t always so.

On October 22, 1707, Sir Cloudesley Shovell led a British fleet to that opening, hove-to, and tried to get his bearings. It was about 4:00 PM. Clouds obscured the sky as the seas rolled in a heavy storm, making latitude readings from an astrolabe inaccurate. Most of his compasses didn’t work. The chronometers eventually used to help fix longitude were years away. Not recognizing his true position was far from his calculated one, he ordered the fleet to sail at about 6:00 PM. Two hours later, the Scilly disaster took his life and 1400 to 1800 others. It led to a series of Longitude Acts, which developed sea-worthy timepieces to avoid such fiascos in the future.

When your life depends on it, you need to know where you are.

When your product is at stake, you need to find what promises clear sailing. Hypernomics helps you find your proper heading and bearings.

#hypernomics #innovation #position #markets #location

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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Bounding Problems

In countless games, the parameters, once set, never vary. There are only a given number of spaces on the chessboard. American football always uses an elliptical spheroid built to strict specifications. All NBA basketball rims are the same diameter, ten feet in the air.

Markets seem different. They don’t have instruction manuals. At first glance, it would seem you could do anything you want in them.

Still, they have rules. Not understanding them can sink a project.

In addition to DeLorean not understanding the value of horsepower (see the last post), they also failed to appreciate the Demand Frontier they faced in 1981. As A shows us, DeLorean thought they could exceed that limit by nearly two standard deviations, despite no one else beating it by half that much.

In this and many other markets, Product Market Demand Curves form. Always flatter than the overall Demand Frontier they build, they describe the product price limits as quantities sold increase. These curves set boundaries producers must consider before they enter any market. Ignoring them can have disastrous consequences.

How do Product Market Demand Curves compare to their Learning Curves? Look to the next post for answers.

#markets #demand #pricing #boundary #innovation #business

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Demand By Proxy

You can’t always get what you want…

Finding data can be hard. Say you needed to model demand for Japanese bullet train travel, or the London to Paris run. Ideally, both firms would post these figures, and you could reduce that to insight. While you can locate that information for NYC cab data (see one of my previous posts), you won’t for The Shinkansen or the Chunnel. What to do?

Let’s suppose train operators match the number of seats offered by class to their demand. Why wouldn’t they? If they had too many high-priced seats open, they’d either drop the price or change the seating arrangement. Eventually, they would come to a configuration that works most of the time.

Below, we see the number of seats by price for Japanese (A) and European (B) high-speed rail services. By themselves, neither has enough data to form a viable study. Together, in (C), they reveal collective thinking from different sides of the planet – and it’s much the same. Yes, that’s only two routes. More would be better. But this shows us we can gain an understanding of a market using the files we have instead of the ones we want.

…If you try sometimes, you just might find…you get what you need (Mick Jagger/Keith Richards).

#innovation #demand #markets #marketanalysis #strategy

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Solve Profit First

Suppliers make products and see what markets will bear for them.  That’s precisely backward.

Instead, we can solve for profit potential first and discover product specifications second.

Suppose a market has products for which there are particular quantities, and prices demanded, as shown by the red dots.  We want to avoid competition, so we choose a Target Price, 1, that exploits a price gap.  Given a Demand Frontier, this sets a quantity limit, 2.

With some work (not shown), we find the market supports Features A & B with a green Value Surface (supportable prices based on those features), and that there’s an area of interest with no competition.  Linked to that region are the costs for 1 and 200 units of our new product.  If we constrain the problem (orange planes), we form an enclosure.

We then run Financial Catscans through this region.  Much like brain scans, they are virtual market section cuts.  At the optimum, we solve for the specs of Features A (3) and B (4), and the per-unit profit (5).  Per unit profit (5) times the demand limit quantity (2) yields max potential profit.

In the process, we’ve solved a 4D problem (Feature A, Feature B, Price, Quantity) from a 1D goal (profit).

#innovation #price #value #markets #profit #sales #manangement