When individuals make decisions, they rarely weigh all possible outcomes to make their choice. Instead, while we may like to think that this is how we make decisions, the reality is that our brains simply don’t have the capacity to consider all of the possible variables and outcomes involved in most decisions. Further, sometimes our decisions are based on fleeting recollections of how we felt while experiencing something, which often has little to do with how much we are actually enjoying what it was we were experiencing (e.g., remembering that a movie was good because of the fun experience we shared with friends, as opposed to the movie actually being good). While neoclassical economics has examined theoretical models of effective decision-making involving what we should do and how we should calculate whether to make one choice or another, behavioral economics suggests that what we actually do is quite different because we generally can’t really make calculated decisions in an unbiased manner, given the (strong) influence of our feelings and emotions.

Researchers have developed a decision-making framework based on three ways that individuals can make use of “Utility”, which describes the potential happiness that can be brought about by a particular choice. Expected Utility considers whether an individual thinks they will be satisfied by a potential future outcome, and decisions are essentially made based on pure conjecture and subjective opinion (e.g., I want the vanilla ice cream because I think it sounds good right now). Experienced Utility, on the other hand, is based on how an individual remembers the feelings when they experienced the decision being considered in the past, though it does not generally involve the actual experience itself (e.g., I want the vanilla ice cream because I remember how I had so much fun with my friends when we went out for vanilla ice cream last week). Thus, Experienced Utility is not often a useful tool to make important, objective decisions. On the other hand, with Remembered Utility, we remember the choice itself when we made it in the past, and its specific aspects that actually brought us pleasure or displeasure (e.g., I want vanilla ice cream because I remember how delicious it was and how much more I enjoyed it over the chocolate ice cream), which makes it particularly effective as a decision-making framework.

Researchers have also established that when we use Remembered Utility, we tend to remember experiences in three discrete phases (the starting event, the ‘peak’ positive or negative event, and the end event), and our decisions are generally only influenced by the peak and end events. This phenomenon, called the “Peak-End” Rule, has shown that the way an experience associated with an unpleasant ‘peak’ is recalled is more positive when the end event can be perceived more positively relative to the peak (i.e., “it was bad for a while, but it turned out better in the end”). This difference in how these two events are perceived (the end relative to the peak) can have a significant impact on how we later feel about the event and our willingness to do it again. For example, even though the peak event of giving birth can be excruciatingly painful, the end event of holding the baby after it is born is so positive for most new mothers that they would be willing to have a second child.

In financial planning, the Peak-End Rule can be used to help clients overcome challenging tasks that they imagine will have negative outcomes (potentially due to their irrational use of Expected Utility) by helping them identify similar challenges that were resolved positively and comparing the peak and end events to the current situation, which helps clients realize that positive outcomes are possible. Additionally, clients who aren’t sure whether they are choosing realistic goals for their future plans might consider testing out their options to have an appropriate basis for using Remembered Utility (e.g., suggesting that a client who wants to budget for an annual 3-month European vacation during retirement try it out now, to see if the location and length of time is something that they will actually enjoy before they create a long-term plan committing to such a large budget item).

Ultimately, by understanding how individuals tend to make decisions, financial advisors can help clients plan their futures by using the Peak-End Rule and Remembered Utility not just to help their clients to formulate suitable financial goals that will be most likely to bring them happiness, but also to find workable solutions to attain those goals!

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When preparing a financial plan, advisors often tend to break down the key issues of a client’s situation into smaller parts in order to ‘zoom in’ and separately analyze each problem. While this analytical approach aligns very well with the education and technical training many advisors have, a ‘synthesis-based’ approach, where the aim is to generate insight from ‘zooming out’ and to garner a more comprehensive understanding of the client’s finances and lifestyle concerns, can be a valuable complementary perspective in the financial planning process. For example, synthesizing a big-picture view of a client’s long-term goals and financial concerns can help an advisor create a long-range tax plan that is likely to be more effective in reducing tax burdens than a “rearview mirror” attempt to plan taxes based on what has already happened within the tax year.

Operating at the analytical level can work well when considering questions that have little behavioral or lifestyle implications (e.g., choosing which tax lot to sell when raising cash); however, synthesis can be particularly useful when thinking about significant choices that do impact the client’s lifestyle or behavior. Furthermore, while synthetic thinking may have a bad reputation as being sloppy or uninterested with the details, sometimes a detailed (and labor-intensive) analysis is simply not necessary to make good decisions. Other times, a synthetically derived reason might be compelling enough to override a decision based on analysis. For example, an advisor operating on an analytical level might eschew a ‘no-consumer-debt’ constraint if expected investment returns would be greater than the interest on the debt. However, this approach could backfire for a client who may not be able to manage credit responsibly and who may be prone to developing reckless spending patterns. A more synthetic approach would consider such big-picture behavioral factors when developing client recommendations.

When it comes to famous financial ‘gurus’, advisors often disagree with their synthetically focused popular recommendations. This is because advisors tend to optimize at a more technical and granular level, while gurus tend to optimize at a more generalized behavioral level. For example, financial personality Dave Ramsey advocates the ‘Debt Snowball’ method, where a borrower pays off the smallest debts first rather than those with the highest interest rates. This approach might not seem optimal to an advisor, but at a behavioral level the momentum (and sense of achievement) built from paying off debts could encourage the client to pay off the remaining debts faster than if they were to use what may seem to some advisors as the more ‘sensible’ approach of tackling high-interest-rate debt first.

Ultimately, the key point is that advisors can use both analysis and synthesis as complementary approaches to help create better financial plans for clients, and that neither approach should be neglected. Advisors can be mindful of their potential biases as they look for solutions through a ‘zoomed-in’ analytic lens and consider when a more ‘zoomed-out’ synthetic approach may be more appropriate. Because understanding the ‘zoomed out’ perspective of a client’s situation and identifying the details that warrant a ‘zoomed in’ analysis can only lead to better recommendations for clients who stand to benefit from both approaches!

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