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Making Complex Decisions: A Scientific Method, with Lawrence Summers, Former Director, White House United States National Economic Council
When you make decisions you are much more likely to make good decisions if you think in terms of alternatives than if you just assume there’s only one choice to be made. And so I always require of myself and others who work with me that there be a description of some alternative broad strategies that we could pursue: We could stay home for the holidays, we could go to someplace cold and ski, we should go to someplace warm and enjoy the beach.
And then having articulated the broad strategies you think about how each one of them could be done as effectively as possible: So if we decided to go skiing, where would we decide to go skiing? If we decided to go to the beach, where would we decide to go to the beach? If we decided to stay home, what kind of special celebration would we have?
So one begins by articulating a number of different approaches and if it seems like there’s only one approach then one needs to be rather careful that one’s not thinking about the problem widely enough.
Once you’ve thought about how you would optimize each of the approaches then you seek to analyze what their consequences would be and come to a judgment about which is the best among the feasible approaches. Obviously part of analyzing any approach is figuring out whether it’s feasible. It’s all very good to say that we’ve decided we’d like to go to Caribbean island X over the holiday, but if we made this decision on December 18 and there are no hotel rooms available then it’s not a feasible decision. If we’ve decided in government that there’s something we would like to do but it requires congressional authorization and Congress won’t vote for it, then that’s not really a feasible choice.
So the analysis is articulating broad strategies, figuring out what’s feasible on the trajectory of each of the strategies and then figuring out what’s most desirable on each of the strategies among what is feasible.