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sions. The answer is not to replace intuition with computer programs you can t. Instead, Schoemaker and Russo suggest basing computer programs on the modern science of expert intuition. They highlight three methods for doing this: rules, bootstrapping, and value analysis. For rules, you just ask managers what the rules are. For example, they might say that they grant a loan if the borrower has no record of payment defaults, has debt less than 50% of current income, has not moved or changed jobs in at least a year, and has a job as at least a skilled laborer. Given these rules, it s easy for a computer program to accept or reject applications. But this method has a key weakness: It reflects what managers say they do, not what they actually do. Typically, good managers make exceptions all the time. They accept loans that violate these rules, and they reject loans that fit the rules but fail some other rule of thumb that they use without really knowing that they use it. Bootstrapping tries to capture what good managers really do. You study the decisions they make, write a computer program to do the same thing, and then hand it back to the managers. Research shows that managers do better with such a program than without it. They pulled themselves up by their own bootstraps. 11 Schoemaker and Russo offer a real-live case. A gifted claims handler had an excellent nose for sniffing out fraudulent cases. It was a clear case of expert intuition: She had that rare ability to make good intuitive decisions decisions based on automated expertise. Before she retired, her company wanted to find out how she did it, so that others could learn it too. But, of course, she didn t know:
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All she could say was that she looked at such factors as lack of adequate support data, valuable property that did not fit the insured s income level, evasiveness in the police report, financial difficulty such as loss of a job, personal problems like divorce, and frequent or suspicious past claims.
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But how did she weigh all these factors and combine them with the more ordinary data on debt, employment, and income To find out, the company turned to bootstrapping. They took a
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wide cross section of applications and asked the expert to rate them for fraud potential. Then they took her results and plotted them out across the various factors she listed. That gave the weights she used. For example, the data might show that she counted an evasive police report twice as much as divorce. It was not something she knew she did. She just did it. Bootstrapping is quite a compliment to experts: It enshrines what they do. But very often, experts don t like it. On this score, Schoemaker and Russo give the example of Harris Investment Management. It used a bootstrapping program for investment strategy that gave analysts and portfolio experts the power to override it. The program improved the company s bottom-line results. Even so, several intuitive experts left the bank because they perceived their role as having been diminished by the new process. Schoemaker and Russo s third method of computerizing expertise is value analysis. It applies complex rules to complex decisions by asking what decision makers want, or value, and what characteristics they think they should look at. For example, a large oil and gas multinational used value analysis to make an important strategic investment decision : Where should it build a $500 million pilot plant The company considered more than 10 countries, each of which had dozens of advantages and disadvantages. Senior executives and technical experts first laid out the criteria they thought were important, then rated each country on how well it met those criteria. Thanks to a complete, careful, and generally honest analysis, the company agreed on the rankings quickly and picked the country that came out on top. As we see from this example, value analysis does not draw on the actual results of experts; instead, it draws on their judgments. For this reason, it is weaker than bootstrapping. But value analysis has the added advantage of drawing in some way on all the experts involved through a method that seems fair to all. It is no small achievement that the company came to a quick decision on such a complex question. We imagine everyone pitching in after the decision in order to make it work, rather than second-guessing a decision made by someone else.
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