I'm currently working on a range of techniques to identify and respond to future changes in an oncoming ‘Age of Wonder’. The title is somewhat of a conceit as there is nothing unique about the changes that are occurring. In fact, throughout history we’ve experienced many 'Ages of Wonder' and a more apt term would therefore be stage because it is a repeating pattern caused by general economic forces.
Behind the work is a question and like all good questions it starts a journey of discovery. The question was "How do we navigate through a future of change?"
In order to properly explore this subject then I need to lay out some ground work on the general forces that drive our society. To begin with, we need to ask ourselves the question of "What is change?"
In the 1962 book Diffusion of Innovation[1], Everett Rogers defined a model for how an innovation is adopted over time among the members of a social system. In this case, an innovation is defined as an idea, practice or object that is perceived as new. The idea of diffusion itself however wasn’t new but instead pioneered first by Gabriel Tarde in 1903. However, Rogers developed this work demonstrating how most changes showed a common S-Curve shape with adoption being through common groups (from innovators to early adopters to early majority to late majority to laggards). The only significant difference between innovations being the variance of the slope of the curve (see figure 1)
Figure 1 - A diffusion curve.
This pattern occurs both for the diffusion of an object (e.g. a specific product example of a phone such as Ericsson’s Bakelite Telephone introduced in the 1930s) and the diffusion of the activity that the object relates to (e.g. use of a phone). Whilst incredibly useful, there are a number of key considerations with the idea of diffusion which make it problematic for exploring the future. These are: -
1) The rate of diffusion is not constant: comparisons over time provide a wide range of adoption curves and a general observation that the diffusion of innovations is accelerating.
2) Not all innovation spreads: even where an innovation has utility (usefulness), a number of factors can influence its adoption. As Geoffrey Moore noted[2] there is a chasm between the early adopters of an innovation and the early majority.
3) Diffusion is not continuous: highlighted by Christensen’s work[3] on disruptive innovation, the diffusion of one innovation can be disrupted by the introduction of a new technology that offers different performance attributes from those established in existing value networks.
4) Diffusion of an activity consists of multiple waves: innovations tend to spread through multiple waves of improved objects such as products. In the early stages of a technological change, this rate of improvement tends to be slow and then accelerates until reaching a more mature and slow improving stage[4]. One consequence of the diffusion and maturing of a technological innovation is that increased information about the technology reduces uncertainty[5] about the change. Each improved version increasingly adds definition, eventually providing a system that can be considered feature complete, mature and generally well understood.
Hence whilst diffusion is a powerful concept, it unfortunately doesn’t provide us with a means of understanding future change i.e. we cannot say how something will mature, we can only say that multiple waves of diffusion over an unspecified length of time is involved in something maturing.
Of course, this leads to our next question "Does maturity matter?"
I'll examine this in the next post.
References
[1] Everett Rogers, Diffusion of Innovations, 4th Edition, Free Press, 1995
[2] Geoffrey A. Moore, Crossing the Chasm, Harper, 1991.
[3] Clayton M. Christensen, The innovator's dilemma. Harvard Business Press, 1997
[4] D.Sahal, Patterns of Technology Innovation, AddisonWesley, 1981
[5] Rogers and Kincaid, Towards a new Paradigm of Research, 1981
