Why Decisions Based on the Results of Worst-Case, Most Realistic, and Best-Case Scenarios Work Well?

Often, to make an appropriate decision, people try three scenarios: the worst case, the most realistic case, and the best case. This three-scenarios approach often leads to reasonable decisions. A natural question is: why worst case and best case? These extreme cases mean that all numerous independent random factors work in the same direction: either are all stacked for or are all stacked against. Such stacking of random factors is highly improbable. So, at first glance, it would be more beneficial to use more realistic scenarios than the worst case and the best case. However, empirically, decisions based on the worst-case and the best-case scenarios work well -- better than other three-scenarios alternatives. In this paper, we provide a theoretical explanation for this empirical phenomenon.