Fantasy vs. Reality: Hypernomics & the End of Illusion

And yet it moves
Galileo

In 1633, the Roman Inquisition convicted Galileo of heresy. His offense? He pointed out that instead of the universe revolving around the Earth (A), Earth circled the Sun (B). For that, he spent the rest of his life under house arrest. In 1992, Pope John Paul II finally acknowledged that the Church had erred in condemning Galileo for saying the Earth revolved around the Sun.

The law of supply and demand tells us that markets have one equilibrium point where those lines intersect (C). Every introductory economics textbook has some version of it, an idea that has existed for over 130 years. And it works for commodities like iron ore.

But that’s where it ends.

It doesn’t work for business aircraft, where many models offer varying combinations of speed and cabin volumes command an equal number of prices, all upheld by variable quantities sold (D).

To understand economics, you need Hypernomics (E). It’s available for presale HERE.

Your competitors may be content waiting 359 years to see the world as it is.

But you shouldn’t be.

Dimensional Collapse

Perspective is a most subtle discovery in mathematical studies
Leonardo da Vinci (Attributed)

Collapsing dimensions sound like the premise of a creepy science fiction film.

But art, engineering, and architecture have used them for centuries.

The angles in (A’s) 12th-century painting do not truly represent what the eye sees. Art, up to the 1500s, suffered from this technique.

But with the advent of Brunelleschi’s drawings of Florentine buildings in the early 1400s, artists, engineers, and architects could offer visualizations that more closely mimicked reality. The trick was using a vanishing point where all dimensions necked down to a solitary spot. In (B), it’s in the sky between the central figures of Socrates and Plato.

In my upcoming book with Wiley, Hypernomics: Using Hidden Dimensions to Solve Unseen Problems, I show how simultaneously understanding multiple markets mandates dimensional collapse. Hypernomics has a five-market, 16D drawing representing 3% of world GDP. Hypernomics needs collapsing dimensions to solve hidden problems that artificially constrained approaches cannot see, let alone explain (C).

Modern business analysis mandates dimensional collapse, as does modern art.

Ants, Airbus, And Avoidance

Hit ’em where they ain’t.
Wee Willie Keeler

I finished a run the other day and stretched at the trail’s end. I looked down, and an ant caught my eye. Starting from position A1, it reached A2 and seemed to be going in a circle for a moment. But then, as its path widened to A3, A4, and A5, I realized it was doing reconnaissance! I raced home and found out that ants do that to “avoid hostile conspecific neighbours,” when considering where to set up camp, they use “a weighted additive strategy, the most comprehensive of consumer evaluations, to choose nests with the best combination of attributes.”*

People, of course, do the same thing.

In B, during 2009-2018, the business jet market had a lot of competitors offering various cabin and price combinations. Noticeably, though, there were a few prominent gaps in the market, akin to how the ants saw regions away from their neighbors. In Q1 of 2019, Airbus launched its A220-100 business jet in the most prominent open region (C). Along with the base airliner from which it came, this vehicle has several hundred orders, helping ensure its long-term viability.

When considering where to place your next product, work to avoid local opposition.

How to Lose €10B+

The race is not always to the swift, nor the battle to the strong, but that’s the way to bet.
Damon Runyon

According to Harvard professor Clayton Christensen, nearly 30,000 new products are introduced yearly, and 95% fail.

But there are ways that one can help increase the potential for product success. It involves determining the Value, Demand, and Cost of goods and services before they launch. Buyers reveal how they Value the product features and their Demand. It is up to producers to figure out those parameters, along with their Costs. Not looking at all those variables in advance is a recipe for financial disaster.

You’re bound to fail if you placed a heavy bet on a program with long odds against you– but you went ahead with it, got it into production, and rode it out until it ran out of steam after losing tens of billions of Euros. That is the conclusion I reached for the Airbus A380 in my paper, “CSI EU: Cost Scene Investigation,” for which I won the ICEEA 2023 Best Modeling and Case Studies Track Paper. This step-by-step analysis gives you the framework for creating models that enhance your chances of being that one in 20 product that succeeds. Below is the video of the presentation:

The Law of Value and Demand: Not Your Grandfather’s Economics

To reject one paradigm without simultaneously substituting another
is to reject science itself.

Thomas S. Kuhn

No rejection of science here. But we can dismiss an ineffective paradigm.

Paul Samuelson wrote that the law of supply and demand, the root paradigm of economics, meant that “the equilibrium price, i.e., the only price that can last…must be at this intersection point of supply and demand curves.” That model works for commodities such as gold, silver, or iron.

But what about jets and jet engines? They use iron. You’ll only gain deep insight into these markets by substituting economics with Hypernomics.

Its fundamental principle, The Law of Value and Demand, states that:

  1. Features define Value,
  2. Value determines Price,
  3. Price limits Quantity Sold, and
  4. Quantity Sold is a Feature.

You can study this new field in my upcoming book with Wiley, entitled Hypernomics: Using Hidden Dimensions to Solve Unseen Problems, in January 2024. In the meantime, have a look at my paper called “8D Cost Trades with Entanglement,” published in the April 2023 edition of the Journal of Cost Analysis and Parametrics,” to see how markets work.

My Book Is Coming: What’s In It For You

It’s not what you look at that matters; it’s what you see
Henry David Thoreau

Many of you asked about it; now I can tell you: I’ve signed a deal with Wiley to publish my book, Using Hidden Dimensions to Solve Unseen Problems: Hypernomics and Markets.

It studies market phenomena we haven’t been able to examine previously, mainly because no one invented the techniques to do so.

Until now.

The book’s theme of finding the location and direction of market competitors mirrors the development of radar and has a like effect.
In the years between WWI and WWII, many countries sought to discover opposing planes’ positions and headings. Several had acoustic detectors like that in (A) but found they could only provide broad direction of incoming aircraft. It took the development of the Chain Home Radar (B) to reveal the value of having a much finer granularity of approaching enemy warplanes.

Modern economics gives us simple 2D charts such as (C), showing the intersection of iron supply and demand curves. But planes use iron, and to characterize them thoroughly, we need the 4D arrangements the book offers, as (D). The book’s readers will gain ways to see more clearly for themselves, improving bottom lines.

Proper Production Possibility Curves

There are no solutions; there are only trade-offs
Thomas Sowell

Forget the “classic” choice model between guns and butter with its single imaginary frontier. Such notions offer no basis for action. Never settle for heuristics when you can have analytics. To reveal true alternatives, we’ll need to do some heavy lifting.

In 4D.

No, really.

In A, we find an aircraft Demand Frontier in yellow. If we want to make 100 units (Quantity – Dimension (Dim) 1), we find our price limited to $393M (Price – Dim 2). For 55 copies, our price could rise to $610M (purple lines). In A’s Value Space, the sustainable price goes up with range (Dim 3) and velocity (Dim 4) but down with added units; thus, the angled Value Response Surface for 55 units is higher than that for 100 units. They form straight lines in log space where they intersect their respective price ceilings (the horizontal yellow and purple planes in Value Space). In B’s linear space, those intersections form multiple curves revealing the proper trade-offs. The yellow line shows us we could build a plane with 10K in range, with a max V of just over 1400 KPH.

It takes work to find Demand and Value, but in the end, we get insight available nowhere else.

Markets Across Seven Dimensions

One should concentrate on getting interesting mathematics.
Paul Dirac

Let’s examine how markets work together across 7 dimensions.

Far from being some exotic mathematical anomaly, such arrangements occur daily across many markets. Please feel free to offer some feedback.

To make a pencil, given wood, you’ll need graphite.  Making a bike takes a frame and tires.  These markets are bonded—you can’t make a final product without some key pieces.  How do bonded markets such as jets and their engines interact across 7 dimensions?

Let’s look.

In the 7D diagram below (with log scaling in all directions), turbofan engines use Dimensions (Dims) 1-4.  As Specific Fuel Consumption (SFC, Dim 1) goes down and Max Thrust goes up (Dim 2), turbofan prices, reflecting their Value, moves up as well (Dim 3), with Quantities sold (Dim 4) limited by the market’s demand frontier (yellow line on the red, right-hand Demand Plane).  Making a new engine with a specified level of SFC and Max Thrust yields a value of the large green sphere, marked by “T,” at left.

That engine supports a new business aircraft model and accounts for a portion of the plane’s cost, marked by the large green sphere labeled “B.”  Aircraft Value goes up (Dim 3, shared with the engines) with Max MPH (Dim 5) and Cabin Volume (Dim 6), as limited by their Demand Frontier (Dim 7).  Such entanglements exist in all bonded markets.  They must be studied thoroughly to be optimized.

#hypernomics #markets #innovation #economics

Financial Cat Scans

Cost, Price, and The Space Between

I sing my heart out to the wide open spaces
Pet Townshend

This month, we’ll study the difference between cost and price, why it matters, and how knowing how both behave in tandem is the key to success.

I know from our analytics that most of you are in the business of working out costs and prices. For many, it is hard to separate the two, especially if you work in or with the government. Today’s analysis directs itself to commercial operations. In a future newsletter, we’ll look at how to adapt this framework to the public sector.

All too often in business, someone comes up with a seemingly great idea and gets fellow workers excited about it. It gets pushed into production. Producers then wait to see what the market will bear for it, often falling short of projections.

What if you could change the paradigm?

Suppose you could see market openings and limits and test sample specifications and sales targets before you commit resources to a configuration. That would improve your chances of success.

You’ll have to work to enable this vision, but you will find it worthwhile.

When we at Hypernomics look at a market, we begin with Demand. As shown below as the red plane, that means finding the ordered pairs for Quantity and Price. We create a series of price bins (either equally spaced or binned by geometric or Fibonacci methods) and determine the ordered pairs (as the purple hexagons) representing each bin’s average price and total Quantity. Then we run a regression curve through them, which represents Aggregate Market Demand.

To the left of that curve, we find the Demand Frontier, a regression through the outermost points on the Demand Plane. This curve shows the limit of the products this market can absorb over time. As markets mature, the Aggregate Market Demand and Demand Frontier slopes often approximate one another.

If we examine the points closely, we’ll notice a price gap. Using its midpoint, we would find the 1) Quantity limit the market will support at that price (the vertical red line coming down from the Demand Frontier) and our 2) Target Price (the horizontal red line originating from the Demand Frontier).

To support that price, we’ll need to offer our customers something they like, here as Features A and B, which show up as the green Value Space at left, with the target Price as the horizontal red plane. We’ll need to figure out the Value Surface that the combinations of Features A and B command (the points for which we excluded from this view, for clarity). As seen on the left, there are Cost Surfaces for one or 500 units below the Value Surface. If we further bound our potential offering with Constraints (the vertical orange planes), we now have a region restricted on all sides. Conceptually, this expanse is not different than a like delimited region, such as your head.

Now, if you suspected that you had a deviated septum, your ear, nose, and throat doctor might order a CT scan, in which the doctor would develop section cut views of your head.

We can do the same thing in markets, using Financial CAT scans. Thus, after carefully setting up a 4D arrangement and taking cuts in both the Sections A and B directions, we can predict the 1) maximum Quantity Sold (reducing the 4D problem to one in 3D). Then we selected 2) the Price (dropping the remainder of undetermined dimensions to 2), 3) Feature A (the distance of the black plane from the origin, reducing the problem to 1 dimension), and 4) Feature B (the Vertical Profit Line, the final dimension). The per-unit profit line on the left times the number of units on the Demand Plane gives the projected profit.

In the process, we reduced a 4D problem to a single objective of maximum potential profit.

To complete the analysis, we’d examine all open price points and all viable combinations of the Features considering risk as well, searching for the best potential configuration.

Watch this video to see the analytical steps in action:

Help Your Partner; Help Yourself

Together we stand, divided we fall;
come on now, people, let’s get on the ball and work together.
Canned Heat, Let’s Work Together

Upper Demand Frontiers form in every market outside of commodities. You can prove this by plotting shares for all S&P 500 companies on the horizontal axis against their sales prices on the vertical (best seen in log-log space). For any given day, you’ll find an Upper Demand Frontier takes shape.

Frontiers limit sales. How do you work around them?

Hypernomics enables us to see how interconnected markets work. In (A), the Boeing 787 Business Jet was, for a period, pushed up against its Demand Frontier (the dashed blue line). One of its compatible engines, the GE Genx-1B, found itself in a like condition, hard up against its Demand Frontier (in B, the dashed orange line). What to do?

If GE, whose engines make up about a quarter of the B787 cost, finds their Learning Curve (recurring costs, as the solid orange line) below their price limit, they could drop their prices and make more profits. That would enable Boeing to lower their B787 business jet price and do the same. Knowing your partner’s place in the market is key to making them and you more profits.

#hypernomics #profits #markets #partner