When we say a technology develops, we tend to mean is that the performance of said technology on certain tasks improves over time. If you zoom out far enough, this often resembles an s-curve. At some point, the performance increases are so incremental it’s hardly noticeable. Some say this currently is happening at petrol cars and their fuel efficiency, that we are close to the physical limit.
What metric is measured for gaging the performance varies per technology and very often it can be a myriad of metrics combined. If we take the example of the steam engine, we can think of the force it can generate, but also the downtime due to mechanical errors. However, for now, having a more abstract performance metric is sufficient.
The first steam engines were not as powerful as the latest. Its first applications were in the mines of England. This is not coincidental. The very first steam engines were highly inefficient in converting coal to kinetic energy, a lot of coal was required for its use. As the first steam engines required a lot of coal, the only place the coal was cheap enough was close to the source: in the mines themselves. This allowed the steam engine to get some early adoption in this use case (pumping water). The steam engine was not ready yet for being used in other use cases, for example for trains. Nonetheless, this early adopter allowed the steam engine to be developed as the market had this demand.
While the mine-use case was growing, the train use case had a performance threshold. To make it interesting to deploy a steam engine powered train, it should be feasible to transport more than what appears was 5 tons for 10 miles. For this, a certain amount of force for a certain duration was required.
Over years, the steam engine was able to be improved continuously by its use in the mines. At some point, the performance crossed the threshold for performance on a distance that made it feasible to be used as a train. Let alone the time of modifying a steam engine to fit a train. The first train track was 9 miles long and deployed in 1804 by Richard Trevithick. We see that technologies undergo adoption at different timespans due to the requirements set by the use case.
What we very often see in the media is when a certain technology has displayed some kind of performance. “First self driving car hits the road” or “V-shape airplane finished maiden flight”. These are performance milestones. However performance is not what drives adoption. Value, or perceived value, is what drives adoption. The key point in this article is that in media we tend to see to a much lesser extent the proof of value than proof of performance. This is not intentional, we believe that technological performance can be measured more objectively than value. You can see something function, you can use a scale to measure weight if that’s a key metric for the solution.
What is value, precisely? Value is attributed by the users of the technology. We use a certain technology for a certain goal, hence it creates the value for attaining that goal. Sometimes value can be measured in monetary value, but this is not everything. The fact that we pay €10 euro per month for my Spotify subscription, does it mean that its value is just €10 per month? It arguable generates more value in my life than €10. It helps me focus, work out, and so on. Value is an intangible concept. In order to make sense of it, as it is socially constructed, the best proxy we discovered is the adoption of solutions. In this way, at least we can see how many people value the solution as a worthy one for a specific goal.
The second key point of this article is the following. Value is discovered or found using existing technologies. Based on the hundreds of emerging technologies we’ve scouted, we see a pattern that value creation comes after performance development. First, the technology shows it can do the trick, then people start applying it in various contexts to check whether it generates value.
In the case of Richard Trevithick’s first steam-powered locomotive, the performance was there. However, the value creation was not imminent. This was because the performance was created at extremely high costs. A source tells us this was not commercially viable at that time. However, this motivated Richard to keep developing its steam engine to making operational costs lucrative over existing solutions. Multiple years later, the steam engine became a viable mode of transport.
In the case of blockchain, many startups started experimenting with applications of the technology. However, massive adoption of this technology apart from cryptocurrencies is still a long way out, if it ever arrives. This shows the same principle. The technology performance, but we do not know where to apply this where it generates more value than existing solutions. In most use cases this is a ‘traditional’ database that still is the prefered solution.
What we see in the case of the steam locomotive and blockchain is that the development of the technology preceded the value creation. Technology often is developed agnostic to value. Technologies can exist without the generation of value and this is what we see is not everyone seems to get. Therefore, when you see new technologies in the media, try to see if there are signs of proof of value. Is this solution getting massively adopted and generating value? If not so, it might take multiple years for it to hit mainstream adoption.
This is a working theory from us at Bit. Do you have an example that undermines this theory? Please let us know.
If you want to understand better how long it takes for technologies to hit the mainstream, I suggest reading this article on the Bit maturity wave containing some rules of thumb. In this maturity wave, value creation is to be discovered in the wave ‘First applicants’ and clear value creation is found in ‘Potential unlocked’.