- Retirement planning metrics, such as the probability of success, are flawed and do not provide a comprehensive view of a client’s retirement income situation.
- Monte Carlo projections, commonly used by financial advisors, demonstrate the uncertainty associated with funding retirement income and goals.
- Success-related metrics, like the probability of success, treat retirement goals as binary outcomes and do not consider the magnitude of failure or how close the individual came to achieving the goal.
- Goal completion percentages offer a more nuanced perspective on the results of Monte Carlo simulations and can provide context about the degree of potential failure.
- Diminishing marginal utility should be considered when assessing goal completion, as the pain associated with missing a goal may vary depending on the essential or discretionary nature of the expense.
- Financial advisors should use better outcomes metrics that consider goal completion and incorporate utility theory to provide more accurate information to clients.
- The probability of success as the primary outcomes metric ignores the magnitude of failure and may not accurately reflect the retirement income situation for individuals with guaranteed income or spending flexibility.
Retirement planning metrics, such as the probability of success, are flawed and do not provide a comprehensive view of a client’s retirement income situation. Monte Carlo projections, commonly used by financial advisors, demonstrate the uncertainty associated with funding retirement income and goals. They show the likelihood that a goal may not be achieved and the array of potential scenarios.
However, success-related metrics, like the probability of success, treat retirement goals as binary outcomes and do not consider the magnitude of failure or how close the individual came to achieving the goal. These metrics do not provide a clear picture of the safety of the target level spending.
Goal completion percentages offer a more nuanced perspective on the results of Monte Carlo simulations. They indicate the percentage of the goal that is completed and provide context about the degree of potential failure. For example, a goal may be partially met in some simulations, but each run constitutes a “failure” based on success-related metrics. The goal completion score gives a more positive picture of the progress towards the goal.
Diminishing marginal utility should be considered when assessing goal completion. The pain associated with missing a goal may vary depending on the essential or discretionary nature of the expense. For example, not funding essential expenses like housing or health care will likely lead to more dissatisfaction than cutting back on travel or other flexible items. Adjustments can be made to goal-completion percentages to incorporate this concept.
Financial advisors should use better outcomes metrics that consider goal completion and incorporate utility theory. Currently, few instruments accomplish this, so advisors may have to offer improved guidance using the current toolset. Success rates should be dialed down to around 80% as a target. This reflects the fact that “failure” in retirement situations is rarely cataclysmic. Providing context about bad outcomes and the income generated in unsuccessful trials can give clients a better understanding of the potential risks.
In conclusion, the probability of success as the primary outcomes metric for retirement planning is flawed. It does not consider the magnitude of failure and may not accurately reflect the retirement income situation for individuals with guaranteed income or spending flexibility. Alternative outcomes metrics, such as goal completion percentages, can provide a more comprehensive view and enable better financial decision-making.
