The Black Swan is a book that was published a few years ago and generated much publicity and at least some controversy. It occurred to me that there are lessons market researchers can learn from that book, particularly about the relationship between qualitative and quantitative data obtained from a survey format. The idea is that the framework used to analyze such data is different from that used for directly obtained qualitative data through methods such as IDIs and focus groups. Understanding the difference between quantitative and qualitative frameworks for data analysis (and in particular, the difference between statistical and managerial outliers) can help derive more value when the qualitative data are collected in a regular survey. But first, let's take a detour.
A Brief Tour of The Black Swan
In his informative (and entertaining) book, Nassim Nicholas Taleb argues that real data are either distributed normally (from "mediocristan") or not (from "extremistan"). The former are characterized by data that follow the traditional normal distribution (or bell curve). The majority of the distribution is near the middle surrounding the average and as we venture further out the number of observations becomes increasingly scarce. It is a distribution that defines many phenomena in the natural world. In fact, basic statistics shows that with a reasonable number of observations most distributions start approximating the normal.