Predicting if a new innovation will be adopted and the time it will take, would be of course, valuable information a company could use to take the risk out of innovation. Unfortunately, it’s not so easy to predict how something inherently new and different, will be perceived by the market. There are lots of factors that come into play. Some of these factors are hard to control.
But what if you could understand the perceptions new users have of the innovation? Perhaps you could better plan your product launch and marketing strategy over the adoption curve and achieve your time to profit goals quicker with less risk.
The Five Attributes of Innovation
It turns out, there are five fundamental attributes that determine the likelihood of an innovation being adopted. According to Everett Rogers, “49 to 87 percent of the variance in the rate of adoption are explained by five attributes.” The attributes are:
Relative Advantage
The degree to which an innovation is perceived as being better than the idea it supersedes. The degree of relative advantage is often expressed as economical profitability, social prestige or other benefits.
For example, the hybrid car delivers a perceived attribute as being economically beneficially with the added value of being socially responsible for protecting the environment. It’s also very hip in many circles.
Whereas Segway, as innovative as it was, never provided a real advantage over existing personal transportation alternatives. Be it by foot, or a bicycle, or a scooter – or a less sophisticated and inexpensive 3 wheel version of the Segway. There was very little advantage in helping people getting their “personal transportation job done,” that they couldn’t already do with existing alternative solutions.
Compatibility
The degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters. Compatibility also has an infrastructure component where the new innovation is compatible with existing technologies (i.e. it interoperates and complements existing technologies).
For example, the cell phone while certainly technically radical, wasn’t that great of a stretch in terms of users understanding how to use the innovation (a telephone without wires). And because it could interoperate with existing phone networks, the value or utility of a limited number of phones was not constrained (i.e. Metcalf’e’s law of the value of the network wasn’t an issue).
Whereas cloud computing/software-as-a-service was a radical departure from the then industry practice of owning and maintaining enterprise software on internal servers. Perhaps the biggest incompatibility was the thought of losing control of a company’s data. This simply was not compatible with IT’s security practices.
Complexity
The degree to which an innovation is perceived as relatively difficult to understand and use.
Again the cell phone provides a good example where the complexity of the innovation was relatively small for the target user to adopt. Making phone calls on a cell phone was not much more complicated than using the good old land line phone – though reliability was a different issue.
Whereas high speed rail, while simple enough to understand from the passenger’s perspective (i.e. get on a train to go from point A to B in shortest amount of time as possible), it is extremely complex to understand form a societal perspective. “Creating a new rail infrastructure will be too complicated – just getting the land grants alone will be complex and expensive. The payback argument is just too complicated”…. Etc.
Trialability
The degree to which an innovation may be experienced with on a limited basis. Stated another way: the easier it is to try and quicker the benefit is understood and to dispel uncertainty about the new idea.
For example it is easy to go test drive a new hybrid car. Just go down to the auto dealer, and test drive it. Getting behind the wheel for a test drive would remove any doubt about the driving experience. You might even find it quite enjoyable and ready to make the switch.
Whereas LASIK eye surgery isn’t something you can simply just try. Sure you can try out one eye and see if you like it – but who really wants to bet an eye on an unknown and seemingly risky procedure? Thank you I’ll keep my glasses for now.
Which segues nicely to the last attribute:
Observability
The degree to which the results of an innovation are visible to others.
While LASIK surgery is difficult to “try out,” it’s quite easy to observe the results of other people who had LASIK. Seeing a bunch of friends enjoying life without glasses would likely lead you to thinking “I want to be able to see without my glasses.”
Whereas software-as-a-service is less observable (compatibility issues on behavior and infrastructure also come into play) and therefore had a relatively slow rate of adoption compared to smart phones which were easy to observe in action.
Final words: perceptions count!
49 to 87 percent of the variance in the rate of adoption are explained by five attributes. As Rogers states “The receivers’ perception of the attributes of innovation, not the attributes as classified by experts or change agents, affect its rate of adoption.”
Perception is everything when it comes to early adoption. Be aware of the five perceptions of innovation and use them to increase your likelihood of success.
Kevin