Rapidly Diffusing Technology

on January 2, 2017
Reading Time: 4 minutes

With the mass proliferation of smartphones and a rapidly maturing consumer base making their smartphones their primary computing devices, there is a fascinating new dynamic emerging. Our company, Creative Strategies, spent a lot of time in the late 80s modeling adoption cycles of new technologies. Using the market data in hand, along with discussions with academics and people like Geoffrey Moore who published a seminal book on the subject called Crossing the Chasm, models were built to understand the conditions that drove technologies into the mainstream. In those days, decades were used in models to predict how technologies went from the early innovators into the hands of average consumers.

Then, much of the effort was built around adoption cycles for personal computers that fit on desks and, eventually, ones that fit on your lap. It took decades just to get to the point where it was common for a single household to have a personal computer in their house. Now, around 3 billion humans across the globe have a computer that fits in their hands and goes with them everywhere. We are in uncharted territory and at a unique point in technology history with this many people owning such a powerful pocket computer, continually connected to the internet and other people, with instant access to buying and selling, and a wealth of information and data accessible at all times. Put all this together and we are watching technology diffuse and become adopted into the mass mainstream at unprecedented rates. This is happening with both hardware and software.

I first started thinking about this trend several years after Apple released the iPad. As that product launched, we were still using traditional models to predict and anticipate adoption cycles of new technology. We shortened the time span some, due to more mature market dynamics, but we did not expect the iPad to become the fastest adopted new technology product of all time and forecasts were well under what iPads sales rates were. So, we focused our research and analysis on why this happened and what we can learn. This was the first time we needed to step back and honestly look at how much has changed in the market to rethink how technology will diffuse in the modern age.

The iPad was a useful case study in adoption cycles for more than just how quickly it went mainstream but also how quickly it seemed to hit its addressable market. Once the iPad’s S-curve was on a steep incline, forecasters began to modify their underestimated forecasts but then began to overestimate. Some people were predicting a potential market size north of one billion tablets. Sales started to slow and it quickly became a replacement market with a total active installed base of around 350-400 million units, well short of the billion plus forecasts and well short of the PC installed base of ~1.5 billion and smartphone installed base of ~3 billion. While the iPad went mainstream faster than any tech hardware product in history, it also hit its max total addressable market extremely quickly. This is the new dynamic I think we are to expect as we move into a cycle of rapidly diffusing technology.

We can make some of the same observations about the wearable market. Specifically, things like smart watches and fitness wearables. This market shot off like a rocket but then slowed very quickly. This dynamic made predicting its exact market size difficult. The slowing year over year growth of the category came quickly and, while the market size for wearables may still be larger than it appears it is today, it also diffused quickly in certain developed markets.

We also see this trend in software. Perhaps one of recent example was the fascinating phenomena of Pokemon Go. There has never been software which went from zero to 500 million as fast as Pokemon Go. While not all of those 500 million people are still using the app, we saw a fascinating phenomenon of diffusion of software in the form of hoards of people walking around public spaces hunting for digital creatures hiding in the physical world.

The groundwork has been laid for technology, both hardware and software, to diffuse rapidly in short periods of time. Which again, makes it very difficult to predict their market size. A product, app, or service may appear to be addressing a larger market than it is in its early stages. This means metrics around hardware sales, app downloads, service subscriptions, etc., may be extremely misleading. The problem is, we have no idea the degree to which they are misleading or not.

Twitter, Fitbit, and GoPro are just recent examples of things that grew quick but also hit their max market opportunity just as quickly. As these companies went public, it was on the basis of a much larger market opportunity than it appears is the case. It’s possible Snapchat may fall into this category, but we don’t know, which is the new challenge of our modern era.

One last point. There are clearly things which will not diffuse as quickly because they are truly new and groundbreaking types of technologies (AR and VR for example) and may spread more slowly since consumers have less familiarity or context with the new technology. In those cases, I believe, we can still assume some type of longer than usual adoption metrics. I’m also not saying the mentioned companies or categories can not still grow their market opportunity with innovations. Only that the “easy” growth was over and over quicker than anticipated.

All in all, I’m convinced those of us who study these markets are in for new challenges in our approach as we try to size market potential for consumer technology. It means we need to address research with new methodologies, ask different sets of questions, understand deeper nuances of each consumer segment and, overall, be willing to abandon old practices and assumptions to create new ones for the modern era.