Note: this is an excerpt from my book “Startup IP Strategy.”
As we all know, business is usually 10% idea and 90% execution. The successful companies rarely have the single best product on the market, but they do have successful execution.
Startup companies – and any business with a new product – spend more time doing product market fit than anything else. Figuring out what the market wants is the initial milestone of the startup, where nothing happens until they accomplish it. Once product market fit is validated, the business switches into an execution phase where the problems shift to marketing, supply chain, and delivery.
The early stage company has one mission: finding a solution for a customer need. This journey can be tortuous, constantly iterating on getting insights from customers, figuring out practical solutions, and testing your assumptions. All startups have “pivots” where the product morphs and grows. Rarely does a startup get to market without learning something significant through this process.
A patent on a brilliant but untested idea is only 1% of the way there. It is much harder to achieve product market fit than it is to come up with a random “cool idea.”
A data-driven patent is one where we have data to support an investment.
The most important data is whether a customer buys the product for the patented feature.
Because of the time restrictions on patents (you must file your patent application within one year of offering it for sale in the US), we usually do not have the full customer validation before investing in a patent. But we want to get as much of the validation as possible before doing a patent.
I evaluate patent portfolios for loans, and many of these are from startup companies who have been in business for a handful of years and may have a few patents. In almost every case, the patents that come later are much better than the original ones. The first couple patents filed early on are typically for ideas that never survived contact with the market. These first patents are almost laughable — capturing inventions that are crazy, especially with how the market has developed. The newer patents are simply much more informed. We have better data to tell us that the inventions are capturing something of value.
As an investor who finances new patents, my mantra is that I don’t want to finance the first patent. I want to learn what the market is telling us, then capture those lessons into patents.
What we really want is a patent that captures as much of the product market fit as possible. The missing data for most patents is the product market fit data.
There is an inherent tension in the patent system between the need to file early and my desire for product market fit data. A purely prophetic patent assumes that the market will want the invention as it is. However, we all know that there are many iterations that inevitably happen.
Prophetic patents have a huge problem. While these ideas can be very valuable, creating IP before its time can wipe out its value. Let’s say it takes 15 years for a science-fiction-style invention to make its way to the market. In that case, we wind up with a patent will only be in force for 5 years. 75% of the patent’s lifespan was wasted because the patent was filed too early. Where was the value of that prophetic patent? It was not worth the investment, no matter how monumental the idea.
I like the concept of data-driven patents because it removes the emotional component of wishing and hoping we are right about prophesying the future. As an investor in patents, I want to have as much market traction and customer feedback as possible before filing a patent application. At the same time, the one-year grace period limits how much data we have before we must file the patent application. This tension is always there and never goes away.
The implied message throughout this book is that, yes, patents can be incredibly valuable to your business, but, they should be done judiciously. Really valuable patents will come later in the business journey, so it is not necessary to gobble up as much IP space as possible early on. Most of that effort will be wasted, and you should default to skipping the patents until you have the business justification for them.