Studying even the right tail of a distribution doesn’t tell you how to break free of the distribution. In short, if you want to use inferential methods to get outside the box, you have to look at someone who is outside the box!
To see the importance of this step in the analysis, ask yourself this question: If two firms in the same industry had differences in shareholder returns (or sales growth or return on assets […] it doesn’t really matter) of 0.1 percent over one year, would you think they were behaving in fundamentally different ways? What about 1 percent? 5 percent? 10 percent? Over two years? Or ten? How much of a difference do you need, and for how long, before the performance differences are marked enough that you’re willing to believe that the two firms behaved differently? In every success study we’ve reviewed, what constitutes great performance is simply asserted. Wouldn’t it be useful instead to know – really know – which companies have delivered truly great performances?
Authors: Andrew D. Henderson, Michael E. Raynor, Mumtaz Ahmed
Source: Ivey Business Journal
Subjects: Best Practices, Statistics
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