In the 1960s, researcher Everett Rogers published a work called Diffusion of Innovations that aimed to explain how, why, and at what rate new ideas and technology spread through cultures. Nearly half a century later, his research is still the guiding rule across various industries—including the technology space—for predicting and driving technology adoption strategy. Since standard-setting organizations and technology-focused consortia are largely in the business of developing and promoting the adoption of new technologies, Rogers’ work has some very strong relevance.
At the core of Rogers’ theory is a bell curve, which illustrates the different stages of innovation adoption. The ideology behind that curve is two-fold:
First, it highlights the very real influence that different types of audiences or customers have on one another. For instance, early adopters want to get their hands on new inventions quite soon after they are introduced. They do not, however, want to be first, and thus rely on the so-called “innovators” to take the proverbial test drive and work out some initial kinks. This progression of influencer-to-influenced behavior flows through the curve.
Second, the curve demonstrates that a successful innovation should progress through the entire curve and not get stuck at any particular stage. In other words, a technology that does not diffuse through all of the stages is most likely one that will die.
There is much scholarship that points to a particular place in the curve where innovations tend to hit the greatest point of resistance—the intersection between “early adopters” and the “early majority.” That is, if the “early adopters” haven’t convinced the “early majority” that the technology is worth adopting, it simply won’t diffuse further through the curve. This inflection point is often known as the “innovation cliff” or the “tipping point.”
This cliff, then, is exactly what technical consortia and standards-setting organizations should focus on in their strategic planning. How is the organization going to make sure that its specifications/technology diffuses through the entire target ecosystem? Here are some points to consider in answering that question:
- Know the players. Which players inside or outside the organization are the “innovators” or “early adopters? Don’t just identify them; figure out a way to get them deeply embedded into your organization and its work.
- Set the cadence. How long do you have to get over the cliff or the tipping point? You may have the right parties involved to get past the cliff, but you may have the wrong level of urgency behind your work and deliverables.
- Consider backward design. What might help the “late adopters” or the “laggards” consider your work sooner? By doing advanced planning for the later stages of diffusion you can avoid having to create solutions in real-time when you get at or near the tipping point.
- Get feedback early and often. Learning what the “innovators” and “early adopters” like and don’t like can help ensure you make critical adjustments before the “early majority” gets turned away. Also ensure your organization stays nimble enough to implement change against such feedback.
- Be data-driven. Data and metrics can (and should) tell you where you are within the diffusion model. These metrics should be something the organization studies often. The alternative, of course, is to have no such metrics only to realize too late that your organization is already hanging on the edge of the proverbial cliff.
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