
Any software project that's worth starting will be vulnerable to risk. Since greater risks bring greater rewards, a company that runs away from risk will soon find itself lagging behind its more adventurous competition. By ignoring the threat of negative outcomes---in the name of positive thinking or a Can-Do attitude---software managers drive their organizations into the ground. In Waltzing with Bears, Tom DeMarco and Timothy Lister---the best-selling authors of Peopleware---show readers how to identify and embrace worthwhile risks. Developers are then set free to push the limits. You'll find that risk management makes aggressive risk-taking possible; protects management from getting blindsided; provides minimum-cost downside protection; reveals invisible transfers of responsibility; isolates the failure of a subproject---readers are taught to identify the most common risks faced by software projects: schedule flaws; requirements inflation; turnover; specification breakdown; and under-performance. Packed with provocative insights, real-world examples, and project-saving tips, Waltzing with Bears is your guide to mitigating the risks---before they turn into problems.
I believe Barry boehm is on record stating that the biggest mistake he made in designing a software creation process was believing people who told him that you could get firm requirements up front.
So yes, if you're in that rare case where you can start out with clear and non-contradictory requirements, probably anything you do is going to succeed better than when you don't.
There's a good book on risk management that goes into this more, Waltzing With Bears, by Demarco and Lister
Mind you, these days Excel's got the distribution function formulae in it that you'd need to do it "properly" with a lognormal distribution, but I like the way the three estimation points have a direct and obvious link to the result with the triangle method.
Both books are worth reading; Hubbard's influence on FAIR is noticeable and positive. FAIR has the advantage that it comes with a fairly built-out ontology for assembling data or estimates. The OP touches on the top level (Loss Event Magnitude and Loss Event Frequency), but the ontology goes quite deep and can be used at multiple levels of detail.
The calculations are not difficult, I've implemented them twice in proofs-of-concept, including one that produces pretty charts.
The difficult part, to be honest, is that developing good estimates is difficult and frequently uncomfortable and the gains are not easily internalised.
Additionally, serious tool support is lacking in the places where it would make a difference -- issue trackers, for example.
[0] https://www.amazon.com/Measuring-Managing-Information-Risk-A...
edit -- Another good book in this area is Waltzing with Bears by DeMarco & Lister. A short, funny, insightful read, as you'd expect from the authors of PeopleWare: https://www.amazon.com/Waltzing-Bears-Managing-Software-Proj...
