Chapter 6. Measuring Risk through Modeling
It is better to be approximately right than to be precisely wrong.
We've defined the difference between uncertainty and risk. Initially, measuring uncertainty is just a matter of putting our calibrated ranges or probabilities on unknown variables. Subsequent measurements reduce uncertainty about the quantity and, in addition, quantify the new state of uncertainty. As discussed in Chapter 4, risk is simply a state of uncertainty where some possible outcomes involve a loss of some kind. Generally, the implication is that the loss is something dramatic, not minor. But for our purposes, any loss will do.
Risk is itself a measurement that has a lot of relevance on its own. But it is also a foundation of any other important measurement. As we will see in Chapter 7, risk reduction is the basis of computing the value of a measurement, which is in turn the basis of selecting what to measure and how to measure it. Remember, if a measurement matters to you at all, it is because it must inform some decision that is uncertain and has negative consequences if it turns out wrong.
This chapter will discuss a basic tool for almost any kind of risk analysis and some surprising observations you might make when you start using this tool. But first, we need to separate from this some popular schemes that are often used to measure risk but really offer no insight.
How Not to Measure Risk
What many organizations do to "measure" risk is not very enlightening. ...