Smart Choices
Page 9
Each time Alan makes an even swap, he changes the way the alternatives match up. With the office services objective eliminated, he finds that the Baranov alternative is now dominated by the Lombard alternative and can be eliminated. This highlights an important process consideration. In making even swaps, you should always seek to create dominance where it didn’t exist before, thus enabling you to eliminate an alternative. In your decision process, you will want to keep switching back and forth between examining your columns (alternatives) and your rows (objectives), between assessing dominance and making even swaps.
With Baranov out of the picture, only Lombard and Montana remain. They have equivalent scores in commuting time and services, leaving only three objectives to consider. Alan next makes an even swap between office size and monthly cost. Deciding that the 700-square-foot Lombard office will be cramped, he swaps an additional 250 square feet for a substantial cost increase—$250 per month. This swap cancels the office-size objective, revealing Montana to be the clearly preferable alternative, with advantages in both of the remaining objectives, cost and client access. Montana now dominates Lombard (see ‘‘Eliminate Office Size; Select Montana’’ table, page 98).
Alan signs the lease for space at Montana, confident that he has thought through the decision carefully, considered every alternative and objective, and made the smart choice.
Practical Advice for Making Even Swaps
Once you get the hang of it, the mechanical part of the even swap method becomes easy—almost a game. Determining the relative value of different consequences—the essence of any tradeoff process—is the hard part. By design, the even swap method allows you to concentrate on the value determinations one at a time, giving each careful thought. While there’s no easy recipe for deciding how much of one consequence to swap for some amount of another (every swap requires subjective judgment), you can help ensure that your tradeoffs are sound by keeping the following suggestions in mind.
Make the easier swaps first. Determining the value of some swaps will be more difficult for you than determining the value of others. In choosing among airlines, for example, you may be able to calculate, in fairly precise terms, the monetary value of a certain number of frequent flyer miles. After all, you know how many miles it would take to earn a free flight and what a flight would cost. Swapping between fares and miles will therefore be a straightforward process. On the other hand, swapping between airline safety records and flight departure times will be much less clear-cut. In this case, you should make the fare-mile swap—the easier swap—first. Often, you will be able to reach a decision (or at least eliminate a number of alternatives) by just making the easier swaps, saving you from having to wrestle with the harder ones at all.
Concentrate on the amount of the swap, not on the perceived importance of the objective. It doesn’t make sense to say that one objective is more important than another without considering the degree of variation among the consequences for the alternatives under consideration. Is salary more important than vacation? It depends. If the salaries of all the alternative jobs are similar but their vacation times vary widely, then the vacation objective may be more important than the salary objective.
Concentrating on an objective’s perceived importance can get in the way of making wise tradeoffs. Consider the debate that might occur in a town trying to decide whether public library hours should be cut to save money. The library advocate declares, ‘‘Preserving current library hours is much more important than cutting costs!’’ The fiscal watchdog counters, ‘‘No, we absolutely have to cut our budget deficit! Saving money is more important.’’ Were the two sides to focus on the actual amounts of time and money in question, they might find it easy to reach agreement. If cutting branch hours by just two hours one morning a week saves $250,000 annually, the library advocate might agree that the harm to the library would be small compared to the amount saved, especially considering other possible uses for the money. If, instead, the savings were a mere $25,000 annually, even the fiscal watchdog might agree that harm to the library wouldn’t be worth the savings. The point is this: when you make even swaps, concentrate not on the importance of the objectives but on the importance of the amounts in question.
Value an incremental change based on what you start with. When you swap a piece of a larger whole—for example, a portion of an office’s overall square footage—you need to think of its value in terms of the whole. For example, adding 300 square feet to a 700-square-foot office may make the difference between being cramped and being comfortable, whereas adding 300 square feet to a spacious 1,000-square-foot-office may not be nearly as valuable to you. The value of the 300 square feet, like the value of anything being swapped, is relative to what you start with. It’s not enough to look just at the size of the slice; you also need to look at the size of the pie.
Make consistent swaps. Although the value of what you swap is relative, the swaps themselves should be logically consistent. If you would swap A for B and B for C, you should be willing to swap A for C. Let’s say you manage an environmental protection program charged with preserving wilderness quality and expanding salmon spawning habitats for as low a cost as possible. In a cost-benefit analysis, you might calculate that both one square mile of wilderness and two miles of river spawning habitat have values equivalent to $400,000. In making your swaps, you should therefore equate one square mile of wilderness with two miles of river spawning habitat. From time to time, check your swaps for consistency.
Seek out information to make informed swaps. Swaps among consequences require judgments, but these judgments can be buttressed by facts and analysis. In making your environmental tradeoffs, for example, you might ask a fish biologist to provide information about how many salmon would use a mile of newly created spawning habitat, how many eggs might eventually hatch, how many fish would survive to swim downstream, and how many would return to spawn in the river years later. Whether a mile of spawning habitat would result in an increase in the annual salmon run of 20 or 2,000 adult salmon will likely make a big difference in the relative value you establish for that habitat.
For some decisions, you yourself will be the source of much of the relevant information. If you are trading off vacation time and salary in choosing among job offers, only you know how you would spend a two-week versus a four-week vacation and the value of the difference to you. You should be as rigorous in thinking through your own judgments as you are in assessing objective data from outside sources. No matter how subjective a tradeoff, you never want to be guided by whim—think carefully about the value of each consequence to you.
Practice makes perfect. Like any new approach to an old problem, the even swap method will take some getting used to. The first few times you make swaps, you may struggle with the overall process as well as with each assessment of relative value. Fortunately, the process itself is relatively simple, and it always works the same way. Once you get the hang of it, you’ll never have to think about it again. Deciding on appropriate swaps, on the other hand, will never be easy—each swap will require careful judgment. As you gain experience, though, you’ll also gain understanding. You’ll become more and more skilled at zeroing in on and expressing the real sources of value. You’ll know what’s important and what’s not. Perhaps the greatest benefit of the even swap method is that it forces you to think through the value of every tradeoff in a rational, measured way. In the end, that’s the secret of making smart choices.
APPLICATION
To Renovate or Move?
Still unsure of their decision after reviewing their consequences table, Drew and Darlene decide to try to rank the alternatives by objective. For each of their main objectives, they compare the houses in terms of the relevant subobjectives. Regarding house quality, they easily determine a ranking that places Amherst first, followed by Wade, Eaton, West Boulevard, and finally School Street. Although based on the information about house quality pulled together by Darlene, the ranking derives not from
a formula but from judgments the couple made. Satisfied and encouraged by their first stab at rankings, they move on to the other objectives, drawing up the table below after much further thought and discussion.
Darlene begins drawing some conclusions. ‘‘These rankings make some things pretty clear. For instance, they confirm our earlier conclusion that Eaton should be eliminated—Wade is better on every main objective.’’ It doesn’t matter that Eaton is better than Wade on some subobjectives, as this is accounted for in the ranking on the main objectives.
Drew adds further assessments. ‘‘I think that West Boulevard could go, too. Wade is better on five main objectives and inferior by only a small difference in cost. In addition, look at West Boulevard and School Street. They are even on location: School Street is in a better neighborhood, but its schools are worse. West Boulevard beats School Street on house quality and yard, but School Street is slightly less expensive. All in all, School Street seems about equal to West Boulevard, so if West Boulevard goes, School Street should, too. Do you agree?’’
Ranking the Alternatives for Each Main Objective for the Mathers’ New House
* * *
‘‘Yes, I do! So we’re down to the crux: do we want to try for Wade or Amherst?’’
‘‘Daddy, I think we should move to Wade Street.’’
‘‘Why do you think so?’’
‘‘Well, the scores on your table add up to 12 points for Wade and 15 for Amherst, and the fewer the points the better.’’
Drew and Darlene mull this over. Is it right to just add the ranking scores? No, they finally decide; both Wade and Amherst are better on three objectives. The rankings capture neither the degree of superiority of one over the other nor the nature of the differences, and both are important for their decision.
To better compare the pros and cons of Wade and Amherst, the Mathers return to the consequences table (page 78). After a while, Drew says, ‘‘I’ve been agonizing over this table, and it’s hard to see which is better. One thing I realize now is that I don’t really understand the cost implications of either alternative very well. Let me work on that for an hour or so.’’
Drew goes to work on the monthly costs of ownership. In other words, he digs deeper into the cost portion of the consequences table. He considers mortgage, upkeep, insurance, and real estate taxes. He reduces the mortgage interest and real estate taxes figures by the amount the Mathers would save in deductions on their income tax. He also estimates the equity buildup after 10 years resulting from the appreciation of each house and the paying down of the mortgages. After completing his financial analysis, he summarizes his conclusions to Darlene. ‘‘It all boils down to Amherst’s being about $150 per month more expensive than Wade. However, that added expense per month buys us something financially. We’d have more equity building up at Amherst than at Wade—about $24,000 more in 10 years, I estimate. That has to be taken into account. These numbers surprise me. I thought that Amherst would be much more expensive than Wade, but it really isn’t. With Amherst, we’d have a sort of forced savings plan.’’
‘‘So are you tilting toward Amherst?’’
‘‘No, no, no. I’m just saying that as far as cost is concerned, it’s not much of a difference. We have to look at all the other factors, too.’’
Darlene says, ‘‘I’ve been trying to think systematically about this. It seems to me that the choice boils down to this: Wade is way better on location, somewhat better on cost, slightly better on school quality, a little worse on neighborhood quality, a little worse on house quality, and not quite as good on yard quality.’’
‘‘That’s still apples and oranges—evaluations across categories. How can we compare less commuting time with better house quality?’’
‘‘Well, for me the answer seems clear now. And it was John who helped me decide. Do you want to know my reasoning, or do you want to struggle more yourself? I don’t want to bias you.’’
‘‘I’m all ears. How did John help? I suspect he prefers Wade because there are loads of kids on the block.’’
‘‘When I considered the longer commuting time for Amherst, I had in mind your frustration and the time you’d waste stuck in traffic. But John had a different twist. He said, ‘If Daddy has to travel more, he won’t have time to play with me before dinner.’ And this got me thinking about the real downside of a longer commute. As it is, you only have about two hours between the time you get home and the time John goes to bed. A longer commute will just cut into the time you have to spend with John and the baby. That’s serious! So . . . I think the advantages in location for Wade outweigh its other slight deficiencies.’’
‘‘Boy, am I glad you think so. I didn’t want to make too much of more travel time, because it falls mostly on my shoulders, but I agree with John. I would miss not having time to play with him after work.’’
‘‘And there’s another reason I’d like you home earlier. You’re sweeter when you’re not frustrated with traffic.’’
So the Mathers call Anne and ask her to put in a bid of $190,000 for the Wade Street house. It is accepted the next day.
Lessons from the Application
The Mathers organized their information wisely to help them evaluate their alternatives. The ranking on each main objective allowed them to see that the Eaton house was dominated and that West Boulevard and School Street were practically dominated. It then boiled down to a decision between Amherst and Wade. As is often the case, when it gets down to decision time, there was an aspect of consequences—in this case, cost—that needed further exploration before they were comfortable making a decision.
What would we have suggested the Mathers do to better appraise the suitability of the remaining two houses?
•In specifying their original objectives and subobjectives, the Mathers did not ask ‘‘Why?’’ often enough. Why, for example, did they want to reduce commute time? If they had, perhaps they would have identified earlier the objectives of increasing Drew’s play time with John and reducing his grumpiness.
•The Mathers could have used the even swap method to compare the relative pros and cons of the final two contending houses. This would help identify the Wade house as the smart choice and clarify the basis for this choice.
•When only Amherst and Wade remained as contenders, the Mathers could have listed the pros and cons of one house versus the other and applied Benjamin Franklin’s method for balancing the pros and cons to help make a choice.
After thinking very carefully about which house to try to buy, the Mathers spent too little time deciding how much to offer. Deciding on a bid is a separate decision from which house to purchase, and it’s a decision worthy of careful thought. Maybe an offer of $172,000 would have been accepted, saving the Mathers $18,000. The decision of what to offer comes with significant uncertainties: Are there other bids from other potential buyers? What might they be? What offer will the seller accept? How might the seller counter? In the next chapter, we’ll discuss how to systematically address such uncertainties to help make a smart choice.
CHAPTER 7
Uncertainty
IN THE PRECEDING CHAPTERS, we’ve laid out a comprehensive approach to making smart choices when, for practical purposes, you can know the consequences of each alternative before deciding. We now turn to situations in which—no matter how much time and thought you expend—you won’t know what the consequences will be until after deciding. They’re uncertain. When you choose, you may know what might happen, but you won’t know what will happen.
Because life is full of uncertainties, many of the decisions you make will involve calculated risks: investing in a mutual fund, accepting a blind date, deciding to have a child, asking for a raise or promotion, starting a business, launching a new product. You can’t snap your fingers and make the uncertainties go away. But you can raise the odds of making a good decision in uncertain situations. How? The first step is to acknowledge the existence of the uncertainties. Then you need to t
hink them through systematically, understanding the various outcomes that might unfold, their likelihoods, and their impacts.
Distinguish Smart Choices from Good Consequences
Whenever uncertainty exists, there can be no guarantee that a smart choice will lead to good consequences. Although many people judge the quality of their own and others’ decisions by the quality of the consequences—by how things turn out—this is an erroneous view, as these two examples illustrate:
A smart choice, a bad consequence. Eager to build a long-delayed addition to his home in North Carolina, Lee Huang carefully weighs the risks and benefits of starting work in December. Construction in the region, with its usually mild winters and light snowfall, typically goes on year round, and the current long-range weather forecasts predict normal conditions. Because the chances of serious weather-related problems are small, Lee decides to proceed. The winter, however, turns out to be the worst in 40 years. The project takes an extra month and costs $6,000 more than planned. Was this a stupid choice? No! The choice was fine; only the consequence was bad. Lee might say, ‘‘If I had only known the weather would be so bad, I’d have waited until spring!’’ But how could he have known?
A poor choice, a good consequence. Roberta Giles, an inexperienced investor, acts on a tip from an acquaintance and, without doing any research, invests in a venture to build a large apartment building. For the first few years after construction, the building reaches only 75 percent occupancy and runs deep in the red. But, just as bankruptcy seems inevitable, a large business unexpectedly moves into a nearby office park. Soon, the apartment building is full, with a waiting list for vacancies. Rents skyrocket. Three years later, Roberta sells out for four times her initial investment. Was the investment a smart choice? No! The decision making was terrible, even though the consequence was good. Would other decisions made the same way turn out as well? Extremely doubtful.