The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty

CHAPTER 13

Mindle 5: Interrelated Uncertainties

Michael Kubica had boxed himself into a corner. Because he was math-phobic, he had put off taking any quantitative courses in college as long as possible. In his last term, with a perfect 4.0 grade point average that he wanted to keep, the only way out was to learn math. The converted make the best proselytizers, and today Michael is president of Applied Quantitative Sciences, Inc., a consultancy he founded to help firms model risk and uncertainty for a number of business problems.¹

Recently Michael had a client that manufactured a line of surgical instruments, with several product development teams working on new product lines. The problem was to value the portfolio of existing and new products over an uncertain future. Historically, each new product team was responsible for developing their own forecasts of future demand, whereas the marketing department created the demand forecast for all currently commercialized products.

To their credit, some of these teams were not blindly churning out single average estimates of demand but were actually running simulations to produce distributions. This is one of those cases where each team was shaking its own ladder. But the full portfolio of current and future products was like a bunch of ladders connected by planks, which meant that they could not be simply added up.

Consider, for example, just one new product, as forecast by its development team, and one existing product, which might ...