“• If it’s really that important, it’s something you can define. If it’s something you think exists at all, it’s something you’ve already observed somehow. • If it’s something important and something uncertain, you have a cost of being wrong and a chance of being wrong. • You can quantify your current uncertainty with calibrated estimates. • You can compute the value of additional information by knowing the “threshold” of the measurement where it begins to make a difference compared to your existing uncertainty. • Once you know what it’s worth to measure something, you can put the measurement effort in context and decide on the effort it should take. • Knowing just a few methods for random sampling, controlled experiments, or even merely improving on the judgments of experts can lead to a significant reduction in uncertainty.”