I recently read and finished taking notes on a book called: Smart Choices: A Practical Guide to Making Better Life Decisions (4.5 stars, 63 reviews on Amazon, affiliate link)
Making good decisions and executing well on those decisions are basically the only things that matter in life. I recently shared my book notes on Good Strategy / Bad Strategy, which explains how organizations can develop better strategies. This book is similar but focuses on how individuals can make better decisions, especially for the important aspects of their personal life. The approach is simple and the examples are relatable: buying a house, changing careers, planning an event, etc
The Acronym to Remember
The authors coined this somewhat helpful acronym: PrOACT, which stands for Problem, Objectives, Alternatives, Consequences, Tradeoffs.
The Biggest Mistake
The most common (and most easily avoided) mistake people make when deciding things is that they just don’t think about it. They just go with the gut. For smaller decisions, this isn’t always a big deal, but for bigger decisions, just taking a few minutes or a few hours to carefully think through a decision can make a big difference, especially given how bad our brains sometimes are at making decisions.
It’s useful to start off by asking yourself what problem you are trying to solve exactly. Their example is of a family that’s out growing their current home. One problem definition might be “What new house should we move to?” but perhaps a better one is “How can we find a home that fits our family’s needs?” which includes the possibility of renovating the current home.
Thinking about problem definitions is a fuzzy thing but a few other tips include:
- ask what trigger caused you to consider the problem in the first place
- question the constraints contained in your problem statement
- recognize what other decisions hinge on this one
- develop a workable scope for your problem definition
Objectives are what really matter to you in your decision. Before you look at your options, you should first think about what success looks like. What would constitute a best case scenario for your decision? For example, if you’re choosing a new office, your list of objectives might be minimal commute time, low cost, lots of space and fully staffed administrative services.
It’s important to try and list all possibly relevant objectives to help you guide your decision. Include both quantitative and qualitative objectives. If you have other stakeholders, involve them in the objective finding process. Ask other people who have made this decision if there are other objectives you should consider. Do your best to refine your objectives, asking “why?” until they are an accurate reflection of what you truly care about in this decision.
This is where you review your options. The key is to ask “How?”. How can you fulfill your objectives for this particular problem definition? Don’t try to evaluate the alternatives just yet, focus on generating as many as possible.
Question your constraints – most of the time, we put assumed barriers around our options. For instance, if you were thinking about what laptop to buy, you’d open up a lot more alternatives if you considered refurbished options or other solutions like using an iPad with a keyboard.
Do your own thinking first, but then consider asking others for their suggestions. Consider alternatives that give you more time and or more information. Sometimes the best alternative is a process one (voting, arbitration, random draw). Of course, after thinking hard about your alternatives and finding at least a few that you might be happy with, move on to the next stage.
While we focused before on quantity for both objectives and alternatives, if you have a ton of items, it’s worth condensing a bit as this next section will otherwise be rather time consuming.
Here is where you look at how your alternatives will play out. Put yourself into the future and imagine you are now living with one of your alternatives. Write down a free form description about the consequences of this particular alternative. If in this process you think of new objectives, consider whether or not you’d like to add that to your objective list. Do this free-form thinking for all alternatives, then weed out any clearly bad ones via “King of the Hill” comparison (where one alternative starts off as the ‘champion’ and is pitted against another alternative, the winner takes on the next alternative, etc).
Take your remaining alternatives and create a consequences table that displays how well each alternative stacks up against all the objectives you’ve specified. Try to quantify how well the alternative fulfills the objective and if that’s not possible, create a ranking system that reflects the range of outcomes. Here’s a (fictional) example with a job hunting decision
To get the most accurate consequences, use these techniques:
- carefully imagine your life in each alternative – note how you feel, what matters to you
- find ways to try before you buy (allowing you to experience some of the consequences first hand)
- talk to experts who can help you understand potential consequences for complex areas
- recognize that some consequences are uncertain / imprecise / can vary (see Uncertainty section later)
Dealing with Constraints
Decisions with multiple objectives cannot be resolved by focusing on any one objective – there are always tradeoffs. The key is figuring out what those tradeoffs are in a thoughtful way.
Look at your consequence table and eliminate dominated alternatives – if alternative A is equal or better than alternative B in every way, then you can say alternative A dominates alternative B and thus eliminate B because it has no chance of being the best option.
Make tradeoffs using even swaps – a technique suggested back in 1772 by Ben Franklin. Figure out what you’d trade on one objective to get more of another and use this knowledge to clarify your consequences.
For instance, with the job hunting example, how much of a salary hit would you take to the Twitter job to raise “Like the Team” to awesome? Same for the Pepsi gig. Now you can cancel out the “Like the Team” objective because they are all the same.
Continue doing this for all objectives until you are left with only one. This system sounds complex, but our brains are actually pretty good at making these types of swaps so with a little practice it shouldn’t be too bad.
Since most decisions involve consequences that are not totally knowable upfront, it’s important to create a risk profile:
- What are the key uncertainties?
- What are the possible outcomes of these uncertainties?
- What are the chances of each outcome?
- What are the consequences of each outcome?
The key here is to capture the most critical uncertainties (as there are potentially an infinite number to choose from) and provide best-guesses on chances of each outcome (which should be mutually exclusive). Yes, it’s impossible to capture all the uncertainty, but doing this exercise will take you to a better end result then just “winging it” or going by gut alone.
A great way to visualize the uncertainty is with a decision tree. Here’s one from the book about a woman’s decision on whether or not to go to court for a personal injury lawsuit (or take the settlement)
Given the same uncertainties, different people would prefer different outcomes. Most people are moderately loss averse and would prefer to avoid bad outcomes, even if they have a shot at really great outcomes.
Sometimes you can just think about the chances and decide whether you want to go for it (e.g. high upside / low downside or high chance of success / low chance of failure). But in cases where that’s not enough, you can use desirability scoring:
- Assign desirability scores to all consequences (0-100)
- Calculate each consequences contribution to the overall desirability of the alternative (chance * score)
- Calculate each alternative’s overall desirability score (sum of all chance * score)
- Compare the overall desirability score associated with the alternatives and choose (compare sums)
In the original consequence table, you were comparing options that were not clearly better than the other. In this case, you have to score each alternative (the assumption being that some alternatives have potentially better and worse outcomes that overlap in desirability with another alternative’s potential outcomes.)
Example: Job hunter comparing two offers that have uncertainty around where they’ll be located:
- New York
- 90% chance
- 80 on Desirability Score (based on salary, projects, location)
- 10% chance
- 0 on Desirability Score (worst option)
- Buenos Aires
- 75% chance
- 50 on D score
- 25% chance
- 100 on D score (best option)
Then, do the math. This works best when each outcome is relatively comparable (i.e. it’s not like of the consequences is “Death” because it kind of throws everything else off)
- Accounting Firm total score: 72 (NYC’s 80 * 0.9 + Santiago’s 0 * .1)
- Consulting Firm overall score: 62.5 (50 * .75 + 100 * .25)
Final decision: take the accounting firm because its score (72) is higher than the consulting firm’s (62.5)
The book also discusses creating utility curves for evaluating specifically quantitative risk decisions (like investing money) which I’m going to skip over.
There are many ways where you can change the risk profile (usually making the worst case scenario less bad) and the authors offer a few suggestions:
- Share the risk with others (less upside, but also less downside)
- Seek risk-reducing information
- Diversify the risk (similar to sharing risk)
- Hedge the risk (create ways where you might benefit a bit from the “bad thing” happening)
- Insure against risk (spend a small amount to prepare against big bad stuff)
The book discusses linked decisions – which I think is relatively straightforward: certain decisions open and close doors for other decisions. Keep this in mind especially when you’re formulating your problem definition – it’s probably better to choose a smaller decision that can be made quickly, especially if it results in more information and options for future decisions.
The book ends with a number of well-documented biases/mistakes that people make when thinking and reminding readers to watch out for them:
- Anchoring – first thoughts/ideas often become the “set point” for later thinking
- Status Quo – people tend to want to keep things the same
- Sunk Cost – people often keep going down a certain path because they feel too invested to change course
- Confirmation – be careful not to seek evidence that merely supports your desired choice
- Framing – thinking about things from a different angle or perspective often changes the decision
- Overconfidence – people are often too sure of their intuitions/judgements (and underestimate the chances they may be wrong)
- Recallability trap – it’s easier to remember uncommon but dramatic things than common but mundane things
- Base-rate – don’t extrapolate based on less relevant features
- Prudence – people sometimes slant their estimates “just to be safe”
- Pattern matching – we sometimes find patterns where none exist, especially in random phenomena (dice)
- Surprised by Surprises – some coincidences are not actually that uncommon (2 ppl with same birthday in group of 30)
Overall – a really great book and worth reading in its entirety. Find it on Amazon here (affiliate link).
Jason Shen | Cultivating Resilience Newsletter
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