The inspiration for today's blog post is a chapter from Daniel Kahneman's "Thinking, Fast and Slow" where he explored how our brains often figure out how to solve difficult questions by – sometimes unwittingly – substituting an easier question, and answering that instead.
For instance, if someone asks us “How popular will the
president be six months from now” most of us don’t actually go through the
detailed analysis to project how changing trends will impact the president’s popularity
down the road. Instead, our brains will tend to take a shortcut, like looking
at how popular the president is now, and simply projecting that into the future
(perhaps with some very small adjustments). Similarly, if someone asks you how
happy you are with your overall life right now, you’re more likely to simply
reflect what your current mood is right now – it’s an easier, more readily
available question your brain knows how to answer. If your mood is good, you'll probably say life is pretty good; if your mood is bad, you'll answer accordingly, too.
The research shows that for some types of questions, the
easier question we substitute may simply be one that reflects the current
situation or environment, such as our mood for our overall life or the current
popularity of the president for an estimate in the future. With some kinds of
abstract questions, however, we have to go a step further.
Relating to Intensity
It turns out that one thing our brains are especially good
at is thinking in terms of intensity, and relating things on different scales
to a similar one based on intensity. For example, Kahneman’s book gives the
example of a situation: “Julie read fluently when she was four years old.” If a
researcher were then to ask you a relative question, such as “How tall is a man
who is as tall as Julie was precocious” it turns out that most people give a
fairly consistent response – in this context, we relate it to some height that
is as remarkable as a four-year-old who can read is also remarkable.
In fact, within a consistent cultural environment – where we
all tend to relate to the context similarly – we could also answer questions
like “What level of income in your profession matches Julie’s reading
achievement?” or “Which crime is as severe as Julie is precocious?” or “Which
graduating GPA in an Ivy League college matches Julie’s reading?” The point,
simply put – we’re quite good at relating comparative intensities on different
scales and translating between the two.
Combining Substitution and Intensity Questions
In some situations, our brains will attempt to answer
difficult questions by using a combination of substitution, for an easier
question, along with intensity to answer that question. For instance, Kahneman's book notes that when we are asked a question like “How much would you contribute to save an endangered
species?” what most people really answer is the question “How much emotion do I
feel when I think of dying dolphins?” We grade the answer on our emotional
intensity scale, relate it to an associated dollar amount, and answer the
In fact, in one experiment (which has since been confirmed repeatedly) first conducted not long after the Exxon Valdez spill, researchers asked various groups of participants about
their willingness to pay for nets to cover oil ponds in which migratory birds
often drowned. The participants were asked to state how much they would pay to
save either 2,000, 20,000, or 200,000 birds. Logically, saving 200,000 birds
should be worth radically more than saving just 2,000 birds, but the
researchers found in fact that the average contributions of the three groups
were $80, $78, and $88 respectively. The number of birds made remarkably little
different at all. In this case, it was because the participants first
substituted the question “how much would you pay to save XXX birds” for the
easier question “how intensely do you feel about the image of a helpless bird
drowning because its feathers are soaked in thick oil” and then related the
intensity of their thoughts about a single bird into a dollar amount. While our
brains are good at relating intensities, the substitution effect meant that the
participants had virtually entirely disregarded the part of the question about
the number of birds (without even
realizing it) and the magnitude of the project and its success or failure.
Substitution and Intensity Questions in Financial Planning
Reading through this discussion on how our brains evaluate
difficult questions was striking to me, because we often ask similarly
challenging questions of clients as a part of the financial planning process.
And given the research on how our brains think, it’s almost certain our clients
engage in a similar process – which is somewhat concerning, as the consequences
can lead to very distorted conclusions, such as the study participants who were
only willing to pay 10% more to save 100 times as many birds.
For instance, imagine the situation where the client is
asked to decide what probability of success is acceptable for his/her
retirement plan. As the conversation often goes, the client is asked which plan
is preferable: one that has an 85% probability of success, a 95% probability,
or if the client would like to save more/spend less/retire later so that the
plan can have a 99% probability.
In practice, our brains have little framework to really
evaluate such probabilities; in the end, we don’t really know how to evaluate a retirement that has a 90% probability
of succeeding. Instead, the research suggests that we probably substitute an
easier question, such as “how intensely bad would you feel about running out of
money in retirement?” Given our ease of converting intensity questions on
different scales, the brain can easily answer this question, evaluating the
intensity of negative feelings about the potential adverse outcome, and then
converting them to a 1% - 100% scale. Clients who have intensely bad feelings
about a potential retirement “failure” will give higher required probabilities
of success, while clients who are less emotionally distressed at the thought
will answer lower probabilities. Thus, notwithstanding the original question,
clients who suggest a preferred probability of success are probably not
actually indicating how much risk (of
failure) they wish to expose themselves to, but instead are indicating how
distressing in their minds that failure would be.
Framing the Consequences
The reason that this substitution effect matters – where
clients answer the question “how much risk would you like to take” with the
easier “how intensely bad would you feel if the adverse risky event happened”
is that as planners, we often do a poor job of effectively defining exactly
what the risky outcome would be.
For instance, think again about the scenario where a client
is asked what probability of success would be preferable for a retirement plan:
85%, 95%, or 99%. In asking this question, we generally leave it up to the client
to imagine what failure would look like. Without any other information, the
logical conclusion – and in fact, the one sometimes implied by the planner – is
that failure means a total loss of assets. Lifestyle and enjoyment ends. The
family home is sold. From now on dinner is dog food, and you can never afford to see the grandchildren again.
Yet when we look at the realities of a retirement plan and
how the financial planning process is executed, this is really a gross mis-statement.
As discussed previously on this blog, the reality is that the probability of
“failure” would be more actually characterized as a probability of adjustment instead. It represents the
odds that the client would be heading down an adverse path that, through
monitoring, might require a mid-course correction to get back on track. As
research by Guyton in the Journal of Financial Planning has shown, “mere” spending
cuts of 10% in difficult times can be effective to get clients back on track,
and in fact they generally can make up the spending cuts and more in the future
when the good returns come back.
So imagine a world where two clients are asked a similar but
Client A: “What probability of success would be preferable
for your retirement plan, 85%, 95%, or 99%?”
Client B: “What probability of success would be preferable
for your retirement plan, 85%, 95%, or 99%, where a ‘failure’ means you would
have to engage in a 1-5 year spending where your spending is cut by 10% until
the market recovers?”
In reality, both scenarios describe the same situation, at
least how it would likely play out with a planner engaging in an ongoing
monitoring process with a typical client (who could intervene with a mid-course
correction if the client was heading towards a danger zone). Except the reality
is that because the scenarios have a very different implied outcome – client B
faces “just” a potential 10% spending cut for a few years, while client A is
left to his/her own imagination about how catastrophic the failure must be
(given no other information) – the clients may convey very different comfort
levels and risk preferences, even though it’s actually the same planning
scenario, because they're expressing different intensities around what they think are different outcomes!
Which means the bottom line is that in situations where
clients are invited to make a decision about how much risk to take, it is crucial to define what a risky event
or an adverse outcome really means. Is it a retirement plan that requires some
mid-course corrections with moderate spending cuts, or total destitution? Is it
a portfolio that could experience a 20% pullback, or a 100% total loss? If the
consequences aren’t defined clearly, the client at best will simply infer
whatever consequence he/she thinks would be the result, judge the intensity
accordingly, and make a decision about risk taking. At worst, the client
infers the wrong risky outcome, leading to an
entirely inappropriate conclusion about risk taking. Because like it or not,
the research – as discussed in Kahneman’s book – clearly shows that this is how
our brains operate.
So what do you think? Do you always clearly define the
consequences of a potential risk decision? Do you frame for clients that
probabilities of success are about success versus total failure? Or success
versus moderate mid-course corrections? Do you think it would change their
decisions about which retirement plan they choose?