Black Swans, Red Herrings, and Invisible Dragons: Overcoming Conceptual Obstacles to Improved Risk Management
In theory there is no difference between theory and practice. In practice, there is.
Even if every argument I made up to this point were accepted by all managers, there would still be some serious conceptual obstacles to overcome from some corners. Risk management may, for a number of reasons, not be considered feasible. Most of these objections to risk management boil down to some fundamentally different ideas about basic concepts like the nature of probability and predictability.
Here I need to give a bit more context for the eventual solution I propose. I’m proposing that quantitative risk modeling similar to what is used in engineering risks, insurance, nuclear power, and oil exploration is part of the solution. We need to modify the existing methods, but the ideal approach is a version of quantitative modeling of risks. In fact, the definitions I gave for risk and uncertainty in Chapter 5 were chosen in part because they lend themselves to quantitative modeling and are consistent with quantitative methods in decision science.
I propose that the probabilities and consequences of events can be measured in a meaningful way. In my previous book, How to Measure Anything, I argue that measurement is simply observation-based uncertainty reduction about a quantity. The objective of measurement is to improve (even just slightly) our current knowledge ...