Before the metaverse there was Second Life. It has been a decade and a half since Second Life was heralded as the next big thing: virtual worlds. Second Life still is around, but did not really become the next big thing. In fact, significant new technologies often take decades to become commercially relevant or ubiquitous.
Advanced technology often does not get adopted as rapidly as the hype would have you believe. In fact, most useful advanced technologies tend not to go mainstream until adoption reaches about 10 percent. That is where the inflection point tends to occur. That essentially represents adoption by innovators and early adopters.
Consider mobile phone use, among the most-ubiquitous products used globally. On a global basis, it took more than 20 years for usage to reach close to 10 percent of people. The point is that even a truly useful or transformative new product or technology can take a decade or more to reach the early adopter stage, which is when 10 percent of people or households use an innovation.
That is why Sigmoid curves are the rule for product or technology diffusion. The S curve has proven to be among the most-significant analytical concepts I have encountered over the years.
It describes product life cycles, suggests how business strategy changes depending on where on any single S curve a product happens to be, and has implications for innovation and start-up strategy as well.
Some say S curves explain overall market development, customer adoption, product usage by individual customers, sales productivity, developer productivity and sometimes investor interest. It often is used to describe adoption rates of new services and technologies, including the notion of non-linear change rates and inflection points in the adoption of consumer products and technologies.
In mathematics, the S curve is a sigmoid function. It is the basis for the Gompertz function which can be used to predict new technology adoption and is related to the Bass Model.
I’ve seen Gompertz used to describe the adoption of internet access, fiber to the home or mobile phone usage. It is often used in economic modeling and management consulting as well.
The next big thing will have first been talked about roughly 30 years ago, says technologist Greg Satell. IBM coined the term machine learning in 1959, for example.
The S curve describes the way new technologies are adopted. It is related to the product life cycle. Many times, reaping the full benefits of a major new technology can take 20 to 30 years. Alexander Fleming discovered penicillin in 1928, it didn’t arrive on the market until 1945, nearly 20 years later.
Electricity did not have a measurable impact on the economy until the early 1920s, 40 years after Edison’s plant, it can be argued.
It wasn’t until the late 1990’s, or about 30 years after 1968, that computers had a measurable effect on the US economy, many would note.
The point is that the next big thing will turn out to be an idea first broached decades ago, even if it has not been possible to commercialize that idea.
Metaverse seems to follow the pattern.
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