Innovation and the formula for change -3
“Technological change (TC) is a term that is used to describe the overall process of invention, innovation and diffusion of technology or processes (…) TC is often modeled using a learning curve.”
Quick recap from previous posts on this subject:
- innovating is about delivering something new, “a first” that makes a difference
- innovating involves change
- Gleicher’s change formula
- Pip Coburn’s change function
- Cost-benefit ratio and opportunity cost analysis
- Diffusion of innovation theory
I am now adding Bass Diffusion Model to the above listing:
- Nt is the number of adopters at a given point in time
- m is the market size in terms of total number of potential adopters
- p is the coefficient of innovation, which is defined as the impact of the “external influence,” advertising being a key example
- q is the coefficient of imitation that relates to the so-called “internal influence,” such as word of mouth
The model accounts for market saturation and differentiates between innovators and imitators with regards to new adopters of the technology. Other variations account for variables such as changes in pricing.
In Crossing the Chasm, Geoffrey A. Moore talks about a “chasm” between technology enthusiasts and visionaries and the early majority who would require addressing additional proof points and a higher trade-off level between the cost of switching and the benefits that it would entail.
While the above are well known models that have become must know references for the high-tech industry, the fact is that there are other considerations worth taking into account when working on technology roadmaping. Here are some examples:
- “The speed with which new technologies are coming to the market has increased dramatically. All these technologies are aimed at the early adopters. And they love it and they try it. But the question is what happens when your early adopters run off to play with a new great thing before you have a chance to take your technology mainstream? Rethinking Crossing The Chasm by Alex Iskold.
- “Technologies of the first sort sustained the industry’s rate of improvement in product performance and ranged in difficulty from incremental to radical. The industry’s dominant firms always led in developing and adopting these technologies. By contrast, innovations of the second sort disrupted or redefined performance trajectories–and consistently resulted in the failure of the industry’s leading firms.” The Innovator’s Dilemma. When New Technologies Cause Great Firms to Fail” by Clayton M. Christensen.
- “When superior technologies emerge, old ones usually don’t simply fade away. To the contrary, their performance often leaps suddenly, thereby extending their lives and slowing the adoption of the new technologies.” Beware of Old Technologies’ Last Gasps by Daniel C. Snow.
Related posts:
- Innovation and the formula for change –3 (this post)
- Innovation and the formula for change –2
- Innovation and the formula for change –1\
- Demonstrating and introducing new technologies –1
- Demonstrating and introducing new technologies –2
- Demonstrating and introducing new technologies –3
- The product growth matrix: a XXI century update
- Innovator dilemmas: modeling real options
- Innovation’s accidental enemies: logical fallacies
- Increasing innovation capacity
- About innovation (slides)
J. de Francisco blogging from Chicago on June 18, 2010
