Jorion (2007) wrote that “Western Europe conquered the world because of a technological revolution that started from the attempts to measure the world.” In the same way, attempts to measure risk - (and its related project performance impacts) - more definitively, realistically, and accurately will surely lead to better project management. - thanks to: "Here, There Be Dragons: Considering the Right Tail in Risk Management," Christan B. Smart, Missile Defense Agency, Redstone Arsenal, Alabama, Journal of Cost Analysis and Parametrics, 5:65–86, 2012.
Making estimates of cost, schedule, and technical performance outcomes and their impacts to programmatic and technical risk in the absence of long tails is venturing into waters where Dragons live.
In the insurance business - and other financial domains - conditional tail expectations is applied to mitigate risk.
When questioning to perform or not perform some method of managing a project, select from a variety of features, or make any decision involving cost, schedule, or performance, ask first what's the value at risk? The answer is the basis of your decision. And making decisions without estimating these impacts creates even more food for the Dragon.
- My value at risk is $27,000. I should spend some amount of time making sure I'm on the right track to produce benefit from my 6 week 2 person, database integration project. But that time should be quick and provide some sense that my efforts will work. Maybe 30 minutes looking at the possible margin I need to raise the confidence in completing inside that 6 week period.
- My value at risk is in excess of $2B for a nation wide health care enrollment systems used indirectly by all 50 states and directly by a large number of states. I'd better have a deep understanding of the long tail aspects of estimates for cost, schedule, and technical performance. So some type is modeling (Monte Carlo) connected with the Reference Classes I'm going to use to drive the Probability Distribution Functions for the model, a Risk Register containing the reducible and irreducible risks connected to my model, and a probabilistic critical path analysis of all the blocking factors for this project. With this I can start to understand the probabilities of success, but will need to do the analysis again every time we have a deliverable to make sure we're in track
And for all projects in between, ask what am I willing to lose if I'm seriously wrong about the cost and schedule? What should I invest to decrease the probability to an acceptable level that I'm wrong about my estimates? That's one of the basis of Value at Risk.
When you hear we can make decisions about future outcomes in the absence of estimates - think how tasty you'll be to that Dragon when he eats you alive.