Ralph KeeneyRalph Keeney, a decision analyst at Duke University’s Fuqua School of Business, uses decision sciences to give “practical and usable advice” to help people make decisions, from lifestyle choices to management strategies.
Keeney claims that good decisions can even cheat death. A recent study of his, as reported in Wired, argued that 55 percent of U.S. deaths among people aged 15 to 64 were due to risky lifestyle choices, compared to just 5 percent a century ago. Why? Because, Keeney claims, most people are really bad at doing cost-benefit calculations. (Related: as Gary Becker once wrote, all deaths are, to some degree, suicides.)
Before coming to Duke, Keeney taught at M.I.T. and U.S.C., and was a research scholar at the International Institute for Applied Systems Analysis in Austria; he also founded a decision- and risk-analysis group at a geotechnical and environmental consulting firm. His most recent book, co-authored with John Hammond and Howard Raiffa, is Smart Choices: A Practical Guide to Making Better Life Decisions.
Keeney has agreed to take your questions about decision-making, so fire away in the comments section below. As with past Q&A’s, we’ll post Keeney’s answers here in short course.
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@ Eric – I think the 5% is based on total deaths, not just violent deaths. This larger set would include deaths from sickness, heart attack, old age, … the usual things that kill us today.
6 people died from baseball?
There’s a gap between making a decision and actually doing something about it. People can easily avoid following through on any decision that they make, and rationalize their lack of effort afterwards.
Given that, why is “decision making” relevant to the way people live their lives?
Is there a way to push other people make decisions quickly?
I’m often troubled by my friends who can’t make decisions on simple things like the date and time for a meet up or dinner. They often ask me to block off 3 to 4 possible days for them, making it impossible to optimize my schedule.
Q. My (very limited) understanding of game theory would tell me that when presented with a choice I should choose the “mini-max solution;” that is, choose the course of action for which the worst outcome is least bad.
First, have I correctly understood what game theory has to say about the mini-max solution? Second, does your research tend to support the wisdom of pursuing the mini-max solution, or does it turn out (as I suspect) that to do so ends up being overly conservative in many cases?
Dan – Not to make light of your predicament, but this seems to me to be a case of a negative feedback system. The classic negative feedback system is a thermostat; the driving state is the temperature, and the feedback signal is the difference between the desired temperature and the actual temperature. The closer you get to the target temperature, the less you need to run the furnace.
In your wife’s case, I suspect, sex is a means to achieving her ideal number of children. As she gets closer to that ideal number, sex becomes less important to her.
If, on the other hand, she is motivated by pleasing you, then the signal you want to sent her is that you are less than satisfied — together with an indication, perhaps, that you are willing to meet one of her felt needs (giving her time away from that brood, perhaps).
I often find myself paralyzed by a decision, because it always ends up being about something larger than the seeming issue at hand. For instance, choosing my first job out of graduate school became a decision more about the reactions of others (that firm isn’t prestigious versus what an awesome place; a life-partner’s pressure, etc) than about best fit, room for growth, or salary. What suggestions do you have to help me (and others) narrow the scope of their decision making?
“55 percent of U.S. deaths among people aged 15 to 64 were due to risky lifestyle choices, compared to just 5 percent a century ago. Why? Because, Keeney claims, most people are really bad at doing cost-benefit calculations.”
I would have thought this change would be, at least in part, due to a reduction in deaths not caused by risky lifestyle choices. That is, better hygiene, antibiotics, vaccines etc means that the things that killed 15-64 year olds 100 years ago don’t kill them now.
Also I’m really curious about how you dealt with the impact of risky lifestyle choices on deaths. For example, we all know that not wearing a seatbelt increases your risk of death in an accident. But if you’re looking at fatal accidents where occupants weren’t wearing seatbelts, how do you determine what percentage of them would have survived had they worn seatbelts? Surely some of the victims would have died anyway, seatbelt or none.
A more complicated question relates to health choices. Lack of exercise, poor diet, obesity and smoking all increase the risk of (amongst other things) heart attacks. But it’s also unfortunately common for fit, healthy, non-smoking people in their 50s or even 40s to have heart attacks. So if a 55 year old obese smoker who consumes little exercise or vegetables has a heart attack, how do you know he wouldn’t have had the heart attack if he had made less risky lifestyle decisions? How do you tease this out in a statistical sense?
Also (and I realise this is probably in your research, but there’s no links here to it in any detail) how do you define risky behaviour? I’m gathering that driving without a seatbelt and smoking are classified as risky in your research (hmmm, these wouldn’t have been considered risky behaviours 100 years ago). I’m curious as to how and where you draw the line of how much additional risk of death must be taken on for an activity to be described as ‘risky’. Driving a small car without airbags? Walking through long grass in the summer wearing shorts and thongs? Riding a motorcycle? Commuting on a bicycle (which increases your risk of death by car crash, but reduces your risk of death by heart attack)?