Veteran Security Practitioner Rick Howard shares how Alan Turing’s ideas and Thomas Bayes' Theorem hold the key to how organizations should forecast risk. Most organizations default to heat maps relying on a low, medium, and high model. But they aren’t reliable. What if we said you’re better off providing risk metrics, that offer ballpark answers and not so much precision? Is it possible to forecast complex things without a lot of data?