When running a plan for chance of success, a certain percentage of “comfortable”/”almost made it”/and “failed in the middle” is acceptable, depending on the individual. It would be a neat and worthwhile feature to allow for the inclusion of potential stop-gap suggestions as a part of the output (and computation), which would inform the user of how much a few (user-selected) variables would need to change to close the gap on success between the rate obtained and their desired rate of success.

Given the wide number of variables and coding/computing power this would require, it may not be feasible. I could imagine a system where the user could select up to 3-5 variables for potential change that they would be willing to change (either in assumptions or behavioral) to meet their plan goal (with the given model).

Example: User wants to know their success rate in their plan, as-is. They select their “failure tolerance” of 10%. They also select the variables/assumption changes to see how these could be changed to increase the success rate to >=90%, if not already exceeding. They select: “Rate of return,” “Retirement Spending,” and “Annual savings pre-retirement” to allow feedback on the how much each variable would need to move to allow the plan to reach their target 90% success rate.

Output: 80% chance of success. -Increasing the assumption for rate of return from 6% to 6.5% increased the plan success to exceed 90%. -Lowering retirement spending from $100k to $95k increased the plan success to exceed 90%. -Increasing the annual retirement savings rate from 10,000 to 12,000 increased the plan success to exceed 90%.

The user can then look at those suggestions (which are really their own suggestions, based on their inputs, openness to change, and desired chance of success) and potentially make changes to one or more variables moving forward to optimize their plan and close their projected shortcomings to set themselves up for better chances of success.