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Pure Importance Says Nothing

26/5/2015

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”Content of the job is more important than wage”

“Debt reduction trumps financial growth”

“Life is more important than money”

All three above statements are sentenced I could well imagine someone utter in an intelligent discussion. All the statements have one other thing in common: they’re pretty much meaningless.

It’s clear that we can – and often do – make such statements. In itself, there’s nothing wrong about saying that A is more important than B. For example, “the math exam is more important than the history exam” is a perfectly legit way of relating your lack of interest in what happened in the 30 Years’ War. But when it comes to talking about what you want, and how you should distribute your resources, importance statements are meaningless without numbers.

The third case is perhaps the most common one. Presumably the idea is to say that we should never sacrifice human life to gain financially. Of course, that’s flat out wrong. Even if you agreed with that in principle, in practice you’re trading off human life for welfare all the time. When you go to work, you risk getting killed in an accident on the way, but have a chance of getting paid. Buying things from the grocery means someone has risked themselves picking, packing and producing the items – if you really valued their health, you’d grow your own potatoes. In healthcare, we recognize that some treatments are too expensive to offer – the money is better used for other welfare-increasing things, like building roads for instance. Life can be traded for welfare, ie. money.
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The first case also seems clear in intent: you want to have a meaningful job, instead of a becoming a cubicle hamster for a faceless corporation, no matter the wage differential. However, it’s surely not true that meaning of the job is infinitely more important. Would you rather help the homeless for free, or be a hamster for 10 million per hour?

The problem with importance without numbers is that they are hinting at tradeoffs, but grossly misrepresenting what we’re willing to accept. The choice examples involve tradeoffs, and tradeoffs are impossible if one goal is always more important than another. This causes an infinite tradeoff rate, causing you to favor a teeny-tiny probability of loss of life over the GDP of the whole world. Doesn’t sound too reasonable, does it? In fact, Keeney (1992, p.147) calls the lack of attention to range “the most common critical mistake”.

Naturally, we can always say that the examples are ridiculous, surely no one is thinking about such tradeoffs when they say life is more important than money, surely they’re thinking in terms of “sensible situations”. In a sense, I agree. Unfortunately, one’s ridiculous example is another’s plausible one. If you don’t say anything about the range of life and money that you’re talking about, I can’t know what you’re trying to say. It’s just much easier to say it explicitly: life is more important than money, for amounts smaller than 1000 euros, say.

Even this gets us into problems, because now if I originally have a choice problem involving 3000 euros and chance of death, you’d be willing to make some kind of tradeoff. But if I subdivide the issue into three problems, now suddenly human life always wins. If you think about utility functions, you can see how this can quickly become a problem. But the situation is still better than not having any ranges at all. Even better would be to assign a tradeoff ration that’s high but not infinite. 
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Two Keys for Better Decisions: Criteria and Alternatives

23/9/2014

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Thomas came to see the new flat, climbing to the fifth floor in the cramped hallway – and no elevator. Ugh. What a trek. But as the estate agent showed him around the place, he was engulfed by light and the smell of fresh baked bread came from the kitchen. No matter that this was 20 minutes further from work. Thomas was sold.
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Hell, I'd get this kitchen, too!
What’s wrong with this decision case? Well, it looks like Thomas is making his decision to buy an apartment based on criteria that only seem noteworthy at the apartment, not beforehand. Even worse, he ends up being carried away by the fresh smells – surely a trick from the estate agent’s sleeve. I’d venture to say that Thomas hasn’t made an exemplar decision here. What could he have done better?

An old adage works also in decision analysis: Think before you act. In the context of decisions, it refers to thinking about the problem itself first. In decisions, two key parameters largely define your success: the criteria, and the alternatives.

The criteria mean dimensions along which you compare and evaluate the alternatives. For example, for the apartment common ones are size, price, location, and so on. What’s the key is defining those criteria yourself. You don’t have to be constrained by what other people think. Your criteria are anything you care about. For example, one of Thomas’ criteria could be the amount of ambient light in the apartment, if he had thought about it beforehand. Thinking about the criteria before the decision helps to stay on the premeditated path, and not be drawn away by other enticing things. If you’ve given thought to criteria in advance of seeing the alternatives, you’re less likely to focus on salient, but ultimately irrelevant ones (like the fresh smell above). It’s like when you’re going to work: you decide to walk straight there, and don’t go into shops even when you see that shiny new guitar in the window (also, your boss might not value your musical enthusiasm to make it a good idea).

Another thing about criteria: they don’t necessary have to be numeric. Sure, there are benefits to using numerical values, especially when they are objective, like size. But inherently there’s nothing wrong with subjective criteria like a “feel” of an apartment, the comfort of a chair or the taste of a wine. After all, it’s your decision we’re talking about. The only thing that matters is that you can be consistent with the criteria, ie. you can rate equally tasty wines as equal on the taste. This is crucial, because otherwise you might be tempted to reevaluate some criteria to end up with the “best alternative”. The point of evaluation is to determine the best option, not to “prove” the choice ex post facto. 
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An example of a consistent evaluation - with two hands, no less!
There’s one other trick that’s useful to remember: thinking about the alternatives. This might sound like an obvious thing, and often it is, too. For example, when buying a flat, most of us tend to spend countless hours on websites and with estate agents, looking at alternatives. However, that’s not exactly what I’m referring to. What’s important as well is conceptual alternative-generating before actual data gathering phase. In concrete terms: thinking about conceptually possible alternatives that you would like. In my case, as we’re thinking about apartments just now, it means the following. I enjoy living with a bike distance to the center, so I’ll mentally think of all neighborhoods that fill that criterion.

The point with this is that your decision quality is driven by the alternatives you’ve come up with. If you don’t find good alternatives, you might consider them nonexistent and fall for the status quo bias. Enlarging the conceptual alternative space will help to see what’s possible. An alternative you didn’t think of won’t get picked.

The major point being: you can improve decisions heavily by structured, reflective thinking. This is an idea that Ralph Keeney, an emeritus professor from Duke University, has championed for decades now (for example, in this paper, or this book). Most decisions are not important enough to require a huge decision analysis trade-off analysis. But thinking is almost free, and has the potential to help a lot.
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