Nearly everyone involved in a technology business that sells to a wide array of customers has seen the depiction of the standard “adoption curve” first theorized by Everett Rogers in the 1960s. (Here’s a picture of it from Wikipedia). Modern re-interpretations have included Geoffrey Moore’s “Crossing the Chasm”, where the ‘early adopter’ and the ‘early majority’ stages are difficult to bridge, and other sociological and game-theory models that collectively strain the brain.
To me, the weirdest aspect of the adoption curve was that is was based on a previous study of, get this, a diffusion of farming practices into rural America. That study was written in 1957 by two agricultural researchers named George Beal and Joe Bohlen (available here). It defines the various stages of adoption of ideas into a marketplace or culture as discrete and linear in their progression: awareness, interest, evaluation, trial, and adoption.
Here’s where it gets interesting. Beal and Bohlen designate the first three stages above (awareness, interest and evaluation) as purely mental. As in, the potential customer or user is thinking about the possible idea, solution or product. No actions yet, just the thought process of how the idea could work in the user’s environment. This activity of getting through the first three stages takes quite a while. To quote from the study,
“Apparently individuals need to test a new idea even though they have thought about it for a long time and have gathered information concerning it.”
Assuming the process Beal and Bohlen describe is true, the first stage in which a possible idea is actually tried out, and even that only in a controlled, small-scale manner, is the fourth out of five. That’s it. After that, if it works, it’s adopted. The mental work is all up front in this model; the thinking about “What is this?” “How can it help me?” “Does it hold promise?” and finally “Is this the right thing to do?” occupies the brain for at least 60% of the process. Sixty.
Demographically, Beal and Bohlen break down the adopters into various classes that correspond roughly to Rogers’ curve. But it’s the mental, thinking aspect that really got me as I read the paper. Almost two-thirds of the time, we’re mulling things over, balancing and measuring things in our head. It’s only that last third in which we act.
As a technologist, I’ve always been fascinated with the uptake of new products and ideas into companies, their adoption into the mainstream, and their eventual demise. All concepts have a lifecycle, if you will. NetApp creates some of the most innovative, far-reaching data management products in the world for handling the various new conceptual approaches to business practices. How are companies adopting these innovations, and at what rate? Even better, what exactly are the characteristics of those businesses who do? Can we be aware of their adoption path? What’s the process they’re going through?
What Beal and Bohlen (and Rogers and Moore, etc.) proved conclusively was that up front, the adoption process is mostly in the mind. It has to do with how much time and effort has been exerted in consideration of the possible solutions and pathways. The adoption curve is back-end loaded toward the implementation, but front-end loaded toward thought, reason, consideration and gathering of knowledge.
Contrast this “think first” model with other ones based on hype. I think we can all agree that Beal and Bohlen’s process is antithetical to a “quick decision” or “throwaway” adoption strategy. Business decisions made on a cheap price, for example, or on ‘fast fashion’ and ‘what’s hot’ in the marketplace collectively weaken the diffusion process. They short-change and short-circuit it. Beal and Bohlen had it right from the beginning – most of the real work comes in what they called “a mental trial of the idea.”
Ultimately, we at NetApp want our customers to understand the new world of cloud migration, containers, storage virtualization, and seamless data placement. The future will be filled with it. Start at http://cloud.netapp.com . Talk to us about where we see the technology and the data directions going. Because we see the various technological adoption processes as being necessarily thoughtful, and not just based on a snap judgment.
And don’t you want a partner like that?