Image Info

Simplify Results For Management

“Simple can be harder than complex.” – Steve Jobs

Suppose you analyze a market and find four features that help describe a product’s value or sustainable price. Your power form equation reads Price = constant * feature 1^a * feature 2^b…feature 4^d. How can you simplify each expression so that more people can grasp its meaning?

Helicopters (A-C) come in many designs and sizes. You suspect their useful loads, cruise speeds, and the number of engines support their prices. Analysis confirms that, but the resulting equation is complicated. You want to know how noise, or its lack, contributes to prices too. You find data on cabin and sideline decibel levels, but it’s spotty.

You want to be both simpler and more thorough. What to do?

Poring over the data, you find that pound for useful load pound, helicopters with more main blades fetch more money. That’s because rotor systems with more and smaller blades disturb the air less and create less noise. In D, you can take that expression, Blades^d, and depict the projected Value increase as you add blades. Combining D (and like tables for features a-c) with Demand analysis (see the last post) permits fine-tuning against the market’s needs.

#hypernomics #markets #marketanalysis #innovation #future #futurism

Image Info

Don’t Leave Money On The Table

“The more you learn, the more you earn” – Warren Buffett

In this true story, we hide the names to protect the players and don’t tell you the venue, either.

In 2014 (A), we ran three market Y value equations (not shown).  All showed that Project X was under-priced.  We find validation of these projections in 2021, as used X versions sell for more than their original $1M price (also not shown).  X sold amply, with 300 units in the market by 2021, and if C’s assumptions were correct, it made a profit, too (D).  Joy in Mudville!  But wait a minute.

Had X’s producers studied Y’s Demand Frontier (B), they might have noticed its negative slope of -1.24.  That means that at the limiting slope, had X’s price been raised to $1.34M, it would have made more revenue, despite the sales drop.  Also, with fewer units, recurring costs fall (C).

The overall effect in D is that selling Project X too cheaply costs Y both revenue and profit.

Hypernomics notes it’s easy to think that if a project makes a profit, it is doing well. But if we learn about all the market forces at work, often we’ll find well isn’t well enough.  Don’t leave money on the table because you didn’t study your market thoroughly.

#hypernomics #innovation #markets #marketanalysis #pricing #analytics

Image Info

Improving Value By Adding Safety

Everything counts in large amounts – Depeche Mode

It’s hard to be flawless in human endeavors. You can bowl a perfect game, throw one in baseball, or get the equivalent in the NFL if your quarterback rating hits 158.3. Athletes who reach high performance levels get rewarded handsomely.

Hypernomics finds there is money in approaching perfection in transportation, too. In 2019, the National Safety Council found the lifetime odds of dying was 1 in 543 as a pedestrian and 1 in 107 in a car crash. But the NSC found the chances of dying in a plane crash too low to calculate.

The Tupolev Tu-204 series (A) has an excellent safety record. It holds more passengers than the Boeing 737 NextGen line (B) and goes faster. But it sells for less than NextGen and has made far fewer sales.

While Boeing’s huge network figures into these results, so, too, does its outstanding safety record. As we see in C, the B737-800 has greater than an order of magnitude reduction in hull losses than the Tu-204. It’s better than its predecessor, the B737-500. It took Boeing time and effort to get that safe. Now they are reaping the rewards.

You may not attain perfection, but it pays to try.

#hypernomics #innovation #businessintelligence #safety #sales

Image Info

How To Lose $1B

Irony is wasted on the stupid.
Oscar Wilde

In his 9/1/2021 article, Jon Hemmerdinger discovered Aerion, a company tied to its AS-2 supersonic business jet (C), was going to put its assets up for sale (E).  He further found Aerion had hired Development Specialists (DS) to manage the process, and DS had “not set a sale price, saying, ‘The market will tell them what their assets are worth.’”

I nearly choked on the irony – Now they knew market reactions counted.  They sure didn’t previously.

Had they studied their Demand Frontier (D) before they started, they would have known while there was a possibility of hitting their targeted sale figure of 300 units in a decade, those chances were slim.

The US Presidential Helicopter program had a similar fate, failing to realize its Demand limits (A, B), and lost over $4B. The USG sold it for parts at four cents on each dollar spent.

Aerion will sell intellectual property; its AS2 didn’t go into production.  Maybe they can get a dime on the dollar.  Based on their $4B development cost estimate, they likely spent $1B by the time they stopped.

Next time, model the market first.  It costs a tiny fraction of the losses suffered forgoing market analysis.

#hypernomics #innovation #technology #management #markets

Image Info

Hypernomics, Missing Dimensions, & Price Determination: 2nd in a Series

“Everything must be made as simple as possible. But not simpler.” ― Albert Einstein

In the last post, Paul Samuelson said equilibrium prices exist where supply meets demand.

While prices for simple products work that way, Value analyst Sheila (A) suspects markets for more complicated products behave differently.  She knows she can account for mountaintops using latitude, longitude, and altitude referencing the equator, prime meridian, and sea level, respectively (B).

With each of the 44 dots representing a unique flat screen tv’s features and price, she finds she can plot the model’s size (C) or cycles per second (D) against prices and get significant but mediocre R2s.  She works to improve her prediction.

In E, she discovers she can plot Price (Dim 3) against the tv’s refresh rate (Hz, Dim 1) and its size (Diag. “, Dim 2) as ordered triples, using an origin of (0,0,0) as a starting point.  With Hz and Diag. “ as Valued Features 1 and 2, respectively, she predicts flat-screen Value (as sustainable prices) with an R2 of 97.0% and a P-Value of 4.85E-32.  She accounts for other features as needed.

All multi-attribute markets have similar “lost dimensions.”

#markets #innovation #hypernomics #prices #dimensions #wsu

Image Info

Hypernomics Observations: 1st In A Series

“It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.” Josh Billings

Paul Samuelson (A) wrote, “the equilibrium price, i.e., the only price that can last, is that at which the amount willingly supplied and the amount willingly demanded are equal.  Competitive equilibrium must be at this intersection point of supply and demand curves (Economics, 9th Ed., p. 63).”  We see an example of this phenomenon in B, as iron mines with progressively more costs form an upward-sloping supply curve intersecting a Demand curve at a single point.  For single-feature markets such as this one, Samuelson’s argument makes sense.

But Hypernomics researcher twins Cristina (C) and Sheila (D) (both played by my daughter, Meagan Swanson) observe dozens of prices for scores of flat screen TV models (E).  Cristina, who studies Value, suspects their sustainable prices and costs rise with desired features.  Sister Sheila, a Demand analyst, has a hunch that as quantities sold go up, prices and attendant costs must fall.  They both agree that the markets’ multiple and frequently changing prices negate a single-point equilibrium.  What takes its place?

#hypernomics #innovation #markets #management #economy #wsu

Image Info

Structure Turns Up

Things don’t turn up in this world until somebody turns them up.
James A. Garfield

In the mid-1900s, there was a race to find the mechanism that passed on genetic instructions.  The double helix structure of DNA that James Watson and Francis Crick discovered was a simpler solution than many biologists thought possible and caught many of them by surprise (A).

Imagine the surprise of many, then, when no one else thought to look, the law of supply and demand is supplanted by the Law of Value and Demand from Hypernomics, which, like DNA, is a long-standing structure which only turns up with lots of hard work and a little imagination.  As shown in B, two market dimensions, Dividends and Earnings Per Share, describe a surface (P-Value 1.55E-06) that drove the Value of the Dow 30 stocks yesterday (stocks above it may be overpriced, those below it, undervalued).  That Value determines Price, a third market dimension, which, in turn, limits the Quantity sold, a fourth market dimension.

The secret, such as it is, is that such structures occur in mathematical, not physical space.  But they turn up in all markets since they began, just as our DNA has always been with us.

#marketDNA #technology #markets #innovation #hypernomics #4D

Image Info

Got Guano?

If you try any preversions [sic] in there, I’ll blow your head off.
Col.” Bat” Guano, Dr. Strangelove

Hypernomics notes that of all the perverted ways to start a war, Bolivia’s imposed tax on Chile is one of the most strange. I mean, who fights for bat poop? Countries looking for saltpeter, that’s who.

Hungry for part of the burgeoning saltpeter trade, Bolivia imposed a tax on a Chilean company mining bat guano from its soil. That violated a treaty to which both countries were parties. It started the War of the Pacific. In it, Chile took on a secret alliance of Peru and Bolivia.

Before the War, Bolivia had sea access, and Peru’s lands included part of the Atacama Desert (A). When the conflict ended, both countries lost ground to Chile, Bolivia became landlocked, and Peru surrendered its Atacama claims (shaded areas in B).

Scant years later, Fritz Haber (C) worked out a catalytic formation of ammonia, for which he won the Nobel Prize. The process drove Chilean nitrate mining employment and prices down by two-thirds.

Looking for a quick buck, Bolivia and Peru endured tens of thousands of casualties for a technology that quickly became outdated. Don’t go to war for short-term gains without considering long-term consequences.

#technology #markets #innovation

Image Info

The Utility Case Vs. Value Analysis

Every time you spend money, you’re casting a vote for the kind of world you want – Anne Lappé

Recently, long-dead Jeremy Bentham took a cross-campus trip. Shunning a wooden cupboard he long occupied in the Wilkins Building at University College London, he moved, greatly aided, to a shiny new booth in UCL’s Student Centre (A). Famously, his penultimate journey was to a UCL council meeting, where they recorded him as “present, but not voting.”

Bentham’s ideas about utility theory still hold sway. Many firms used it to figure cell phone prices (B). Such studies queried participants’ willingness to pay for features, to which researchers assigned utils, a utility measure. Then analysts converted utils to dollars.

Hypernomics notes respondents gave hypothetical answers; they weren’t buying phones, that util value varies widely, and that this method ignored available relevant communication data at their peril.

We display our willingness to pay to connect when we put up cash to make towers (C), walkie-talkies (D), or car phones (E). Value Analysis considers past and present market states to predict the future.

Jeremy may not vote, but we do.

The best utility case holds its inventor.

#value #utility #hypernomics #innovation #marketanalysis

Image Info

Paying for High Ground

You can observe a lot by just watching – Yogi Berra

My wife, mother-in-law, and I took a cruise on the Danube and Rhine rivers a few years ago and saw several castles along the way. Scaling one with a tour guide, we noticed there were remote towers of the same construction in different directions atop nearby hills. I asked if they were part of the same realm. Sure, the guide said, that’s how they got early warnings back then.

What will someone pay to increase their field of view? Hypernomics provides us insight.

Global Hawk (A) is the most expensive Unmanned Aerial Vehicle (UAV) in the United States inventory. With a flyaway cost of $147M, we’ve managed to buy 42 of them. We’ve also bought 40 of the Global Positioning Satellite (GPS) IIR (B) at $156M apiece. What a coincidence!

Or is it?

We plot quantities and prices for UAVs and civilian satellites in C. While UAVs surveil or attack, satellites not belonging solely to the military survey the weather (GOES and NOAA) or offer positions (GPS) or communications (Starlink). Note UAVs and satellites abide by the same Demand Frontier. Our readiness to buy them goes to a point along that curve and stops there. I wonder where watchtowers lie.

#hypernomics #markets #innovation #sales #demand