Over the past decade, Monte Carlo analysis has been slowly replacing its retirement planning predecessor - the straight-line projection - which was overly reliant on a single distant outcome, with no acknowledgement of the potential impact of volatility on the final results and the success of the plan. By contrast, the virtue of Monte Carlo analysis is that it shows a range of possible outcomes, and quantifies results not with a single and inevitably inaccurate estimate of final wealth decades from now, but instead a probability of success/failure that captures how many of a wide range of outcomes are projected to be successful or not.
However, as Monte Carlo analysis has become increasingly popular, the focus has unfortunately shifted once again towards a single projected outcome - the probability of success/failure - without fully acknowledging the range of outcomes and their nuances, such as the fact that a plan with a higher probability of failure may actually be the more appealing option if it's accompanied by a less severe magnitude of failure. Perhaps most significant, though, is simply that the labels "success" and "failure" do little to connote the true reality - that "success" actually means an excess left over, and that failure merely means that some kind of mid-course adjustment may need to occur.
Yet the reality is that while these differences are arguably mere semantics and nuance, how results are framed matters, and can significant impact real world client behaviors, given the difficulty our brains have in trying to interpret Monte Carlo's probabilistic results. Which means if the truth is that "failures" merely require mid-course adjustments and that "successes" actually leave over excesses, perhaps it's time to relabel Monte Carlo results accordingly as "probability of adjustment" and "probability of excess" to ensure clients are making the proper decisions!