When you talk of the diffusion of innovation, I’m sure most people have come across the life cycle diagram proposed by Everett Rogers.
It’s so well known that it doesn’t really require any explanation. Of course, his diagram was part of a much wider work into how and why we adopt particular innovations.
Whilst the diagram provides a nice heuristic for the lifecycle of an innovation, it doesn’t really provide any insight into why people adopt an innovation (or not).
Alas, Rogers did cover that topic, although strangely his insights on that don’t appear to be anywhere near as well known as his diffusion model above.
Five variables behind the rate of innovation adoption
- How visible is the innovation? For the innovation to ‘cross the chasm’, the mainstream need to be able to see the early adopters using the innovation.
- How easy is it to try? Is it possible for people to try out the innovation without sacrificing a great deal of time, money or effort.
- How much better is it? I wrote previously about quality trumping first mover advantage, and if you’re to persuade people to shift, the new innovation has to be markedly better than what people currently use. Bare in mind that to begin with, the gains will probably need to be large as the cost and performance benefits of greater scale probably won’t be available yet.
- How compatible is it? Does the innovation work well with things that people are already using?
- How simple is it? If both the advantages plus the usability aren’t rapidly apparent, then it will always be a struggle to gain adoption of your innovation.
It’s a useful list of attributes to consider with your own innovations to see if they have what it takes to make it.