Post 2: What If Expensive Things Aren’t Actually Expensive?

I recently came across a meme on Facebook and an idea associated with Elon Musk’s engineering philosophy has stuck with me. I am paraphrasing the concept rather than quoting him: if something remains expensive after it has been properly designed and produced at enormous scale, perhaps it really is expensive. But if its cost collapses at scale, much of what looked like intrinsic cost was actually inefficiency in the system. This post explores more in depth this concept.

Suppose a product sells for $10,000. It is tempting to think, “That is a $10,000 object.” But why does it cost $10,000?

Sometimes the answer is justified: engineering, certification, warranty risk, intellectual property, regulation, capital requirements and low production volume can all be expensive.

But sometimes the system itself is expensive.

Scale changes more than manufacturing

Scale affects manufacturing, but also purchasing, shipping, utilization, insurance, data, negotiating power, reliability and coordination.

Imagine 10,000 small businesses each paying $2,000 annually for the same kind of service. Individually, none has much negotiating power. Collectively, they represent $20 million of demand.

An organization aggregating that demand would not have manufactured the underlying service. It would have manufactured scale.

Utilization changes cost

Consider a $500,000 machine used four hours per week. The service it provides may appear extraordinarily expensive. If utilization rises to 60 hours per week, the machine did not become cheaper; its capability became cheaper.

People do not really want drills; they want holes, they want to turn screws. Sure a screwdriver manually can do the job to turn a screw but they want speed and efficiency too. Businesses do not necessarily want servers; they want reliable computing. A company may not fundamentally want a warehouse; it wants protected storage and distribution capability.

Ownership is often simply a mechanism for guaranteeing availability.

Tiny improvements can become enormous

Suppose a corporation performs an activity 400 million times per year and someone reduces the cost by three cents.

400,000,000 × $0.03 = $12,000,000.

A three-cent improvement becomes a $12 million annual improvement.

The inverse matters too

Something individually worthless can become valuable at scale.

One database record may be worth almost nothing. Ten million correctly linked records may answer questions no partial dataset can answer.

This gives us two transformations:

Expensive → cheap through scale

Worthless → valuable through scale

Sometimes the important economic properties do not appear until the pieces are combined.

As we continue through this project, I will use several anecdotes and recall situations from some of my past experiences. This is deliberate and I am attempting to incorporate my knowledge, experiences and past to try to make this project unique and relevant.

Please continue to Post 3 if you’d like to continue following along.

Post 1: The $100,000 to $10 Million Thought Experiment

I started with a deliberately unreasonable question: If I had $100,000, how could I turn it into $10 million legally, ethically, and without gambling?

I did not want a scam, a get-rich-quick scheme, or a strategy dependent on reckless financial risk. I also was not particularly interested in the usual answers: buy rental properties, start an e-commerce company, trade stocks, build SaaS, or invest in somebody else’s startup. Those can all be legitimate paths. They just were not the question I wanted to answer.

I wanted the kind of idea that makes someone stop and say,

“How in the world did you figure that out?”

Turning $100,000 directly into $10 million is a 100x return. If I insist that the investment itself produce that return while remaining low risk, I am probably asking for something that does not exist.

But what if the $100,000 is not investment capital? What if it is discovery capital?

Instead of asking what I can buy for $100,000, I can ask what $100,000 might allow me to discover, model, validate, prototype, or gain some form of control over.

A company might spend $30 million acquiring something that cost $100,000 to develop if it saves $20 million every year. A corporation values an asset according to what ownership allows it to gain, save, avoid, accelerate, or prevent a competitor from obtaining.

That leads to a different equation:

$100,000 → discovery → proof → strategic asset → potentially $10 million+ of value

I do not necessarily want to run the company

I am not dreaming about managing 400 employees. I do not particularly want fleets, warehouses, a huge customer-service department, complicated physical operations, or a product where something breaking at 2:00 a.m. becomes my emergency. I like the freedom of flexibility so taking on a project that would consume me or my time was not of interest.

I love spreadsheets and data. I’m overly analytical and I enjoy the freedom that comes with research and development as inspiration happens. That being said, the ideal opportunity would rely heavily on information, research, software, AI, intellectual property, contracts, data, or transaction architecture.

Maybe I become an owner, originator, deal architect, or owner of the data/IP while experienced operators run the actual company. At this stage I do not know. That is intentional.

The asset should have teeth and should provide a benefit to all involved.

I do not want an idea whose only defense is secrecy. If explaining it allows a corporation to reproduce it next Tuesday, it is not what I am looking for.

The eventual advantage should have layers: historical data, classifications, verified outcomes, rights, relationships, accumulated observations, and perhaps proprietary models. Additionally, this project should be put together in unconventional ways and use unimaginable connections at first glance. Ideally, this would be something that although simple, may not be obvious.

The ideal response from a competitor would not be “I don’t understand it.” It would be: “I understand exactly what they built. Reproducing it would take us years.” This project should stand on its own without fear of competition. In fact, this should be something that should inspire competition and challenge the status quo to think in different manners to provide solutions to problems that no one knew existed.

There is an even stronger test. Imagine Company A sees the asset and immediately asks, “What happens if Company B buys this?”

That is the Corporate Fear Test.

Perhaps Company A decides its best use case is to prohibit Company B from acquiring the tech, data or IP. While this is not ideal, this could be a possibility that I am open to.

What are we actually trying to build?

I don’t know yet.

The objective of this first phase is not to invent a product. It is to develop a better way of noticing opportunities.

What is abundant but treated as scarce? What is valuable but classified as waste? What capability does a company possess without realizing it? What does one industry throw away that another buys? What information becomes visible only when unrelated datasets are combined? What should be happening in a company but isn’t? What two ordinary companies would become extraordinary if combined?

Those questions became more interesting than “What business should I start?”

This series documents that search as it happens. There is no hidden business at the end that I already know about.

And if this works, perhaps the most valuable thing we discover will not be one opportunity. Maybe it will be a machine for finding opportunities nobody else thought to look for.

The origins of this thought came to me as I was reading “The Science of Getting Rich” by Wallace D. Wattles. In Chapter 3, he mentions an abundance of opportunity and abundance of supplies. Although this book was written in the early 1900s, I’ve expanded this view to incorporate how it applies today and have noticed that there is still an abundance of supply. If you’d like additional context, his book can be bought on Amazon.

If you are interested in continuing the journey with me, please continue to Part 2.