Who’s Who on the Adoption Curve

For me, the Adoption Curve of the Internet of Things is fascinating to observe. Take the PoloTech shirt from Ralph Lauren, for example. It’s a “smart shirt”. The skintight shirt measures your heart rate, how deeply you’re breathing, how stable you are and a host of other key biometrics. All this is sent to your smart phone. One will set you back a cool 300 bucks. But it’s probably not the price that will separate the adopters from the laggards in this case. In the case of the PoloTech shirt, as with many of the new pieces of wearable tech, it’s likely to be your level of fitness that determines which slope of the adoption curve you’ll end up on.

polotechIf you look at the advertising of the PoloTech, it’s clear who the target is: dudes with 0.3% body fat and ridiculously sculpted torsos who live on protein drinks and 4 hour workouts. Me? Not so much. The same is true, I suspect, for the vast majority of us. Unless we’re looking for a high tech girdle to both hold back and monitor the rate of expansion of our guts, I don’t think this particular smart shirt is in the immediate future for me.

As I said, much of the current generation of wearable technology is designed to tell us just how fit we are. Logic predicts that these devices should offer the greatest benefits to those who are the least fit. They, after all, have the most to gain. But that’s not who’s jumping the adoption curve. In my world, which is recreational cycling, the ones who are religiously tracking a zillion metrics are the ones who are already on top of the statistical heap. The reason? Technology has created an open market of bragging rights. Humans are naturally competitive. We like to know how we stack up against others. But we don’t bother keeping track until we’re reasonably sure we’re well above average. So, if you log onto Strava, where many cyclists upload their tech-tracked rides, you can find out just who is the “King of the Mountain” at your local version of the Alpe d’Huez.

This brings about an interesting variation on Roger’s Technology Adoption Curve. Wearable technology often means the generation of personal data. Therefore, an appetite for that data will accelerate the adoption of those respective technologies. We don’t mind being quantified, as long as that quantification paints us in a good light. We want to live in Lake Wobegon, where all the women are strong, all the men are good-looking and all the children are above average.

Adoption of new technologies, according to Rogers, depends on 5 factors: Relative Advantage, Compatibility, Complexity, Trialability and Observability. To this, Rogers added a sixth factor – the status conferring potential of a new innovation. Physical fitness, by its nature, begs to be quantified. Athletic ability and rankings go hand in hand. Status is literally the name of the game. Therefore, there is a natural affinity between wearable technologies that tracks physical performance and fitness.

This introduces some interesting patterns of adoption for new additions to the Internet of Things. Adoption will rapidly saturate certain niches of the population, but may take much longer to cross the chasm to the general masses. And the defining characteristics of the early adopters could be completely different in each case. As more and more things become “smart” the factors of adoption will become more fragmented and diverse. Early adopters of Coke’s Freestyle vending machine will have little in common with early adopters of the PoloTech shirt.

The absorption rate of technology into our lives has been increasing exponentially, seemingly in lock step with Moore’s Law. Every day, we are introduced to more and more things that have technology embedded in them. The advantages that this technology offers will depend on who is judging it. For some, a given technology will be a perfect fit. For others, it will be like trying to squeeze into a high tech shirt that makes us look like an overstuffed sausage.

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