Simon Wardley was in a quandary. medium 
> Having described the three states of war, Wonder and peace then I found myself in the unusual position of finding them everywhere.
By 2010, the signals were suggesting that this was happening and in early 2011, I had exactly the opportunity I needed. Being a geneticist, I was quite well versed in population characteristics and so as part of a Leading Edge Forum project (published in the same year) we decided to use such techniques to examine populations of companies, specifically a hundred companies in Silicon Valley. We were looking for whether a statistically different population of companies had emerged and their characteristics (phenotypes) were starting to diffuse. It was a hit or miss project, we’d either find a budding population or it was back to the drawing board.
[…]
Simon Wardley interviewed a dozen companies that
> I thought would be reasonable examples of traditional and web 2.0 and where I hoped a couple of highly tentative next generation companies might be hiding.
I developed a survey from those companies, removed them from the sample population to be examined and then interviewed over 100 companies divided roughly equally among those that described themselves as web 2.0 and those who called themselves more traditional. The populations all contained a mix of medium and huge companies. I examined over 90 characteristics giving a reasonable volume of data. From the cycle of change and our earlier interviews, we had guessed that our next generation was likely to be found in the self describing “web 2.0” group and in terms of strategic play they would tend to be focused on disruption (the war phase) rather than profitability (the peace phase). From our earlier interviews I had developed a tentative method of separating out into candidate populations. So, I divided the population sample out into these categories and looked at population characteristics — means and standard deviations. Were there any significant differences? Were the differences so significant that we could describe them as a different population i.e. in a sample of mice and elephants then there exist significant characteristics that can be used to separate out the two populations.
I ran our analysis and waited. It was an edgy moment. Had we found something or as per many attempts before had we found nothing? I tend to assume nothing and when there is something, I tend to doubt it. Within our data set we found statistically significant population differences across a wide number of the characteristics but also significant similarities. I re-examined, looked through my work, tested, sought the advice of others and tested again — but the differences and similarities remained. For example, I examined each company’s view on open source and whether it was primarily something that means relatively little to them, a mechanism for cost reduction, something they relied upon, something they were engaged in or whether open source was viewed as a tactical weapon to be used against competitors. The result is provided in figure 120 with the subdivision by population type.
Figure 120 — Views on open source