Monday, 27 October 2008

The fallacy of the tipping point

A few years ago I had my own epiphany when debating with someone the value of the concept of the "tipping point" when applied to social change processes.

Most of the research literature as well as the populist books subscribe to the notion that when you get the write idea and it tweaks opinion leaders and the target population, then it will spread automatically once it has reached its tipping point which can be anywhere from 15 - 30% of the total population.

All well and good though this research is descriptive; namely it describes something that has happened. It is not inherently predictive. Many people have written books and articles with their ideas on how to take the descriptive lessons and apply then predictively. However, there are very few longitudinal studies which chekc these implemented efforts with what actually happens.

If you do want a predictive method then there have been a number of formula around for 70 or so years all of which can be used to guide you in your implementation efforts.

Another fundamental issue is the tipping point usually refers to transformational innovation. It is when something quite new and novel gets adopted by others. It has little or no relevance for communities where incremental improvement is underway. Some studies make a point of assuming that innovation is the same as improvement, and they can thus include all innovation spread and adoption research into their models and theories. However, I beg to differ. Anyone who has a strategy of incremental improvement I suggests avoids using the tipping point as a planning tool.

I've written before about the concept of opinion leadership and my ambivalence about it (see earlier blog posts). The tipping point is fairly well predicated on the theory of opinion leaders yet there is much research to demonstrate the wekness in this model.

Yes, you may see many charts showing what looks like an S-curve in the adoption of an idea. However, my first question is to ask what was the total population, namely to how many peopel did you intend this idea to spread? ONce you have the total population you will most likely notice that what you are seeing as an S-curve may not be much mroe than the variation you might get in the early phases of adoption.

Next time I read a strategy and implementation plan that says something like "Once 25% of the population has adopted the change the rest will pick it up" I will continue to be sceptical.

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