Sources of Power: How People Make Decisions

by Gary Klein

the RPD model posits a two-stage process, starting with intuition, as decision makers recognize how they need to respond, followed by deliberate evaluation as they mentally simulate a possible response to see if it will work. A blend of intuition and analysis, not just gut feelings.

The power of intuition enables us to size up a situation quickly. The power of mental simulation lets us imagine how a course of action might be carried out. The power of metaphor lets us draw on our experience by suggesting parallels between the current situation and something else we have come across. The power of storytelling helps us consolidate our experiences to make them available in the future, either to ourselves or to others.

The commanders’ secret was that their experience let them see a situation, even a nonroutine one, as an example of a prototype, so they knew the typical course of action right away. Their experience let them identify a reasonable reaction as the first one they considered, so they did not bother thinking of others. They were not being perverse. They were being skillful. We now call this strategy recognition-primed decision making.

We can call this strategy a singular evaluation approach, to distinguish it from comparative evaluation. Singular evaluation means evaluating each option on its own merits, even if we cycle through several possibilities.

Simon (1957) identified a decision strategy he calls satisficing: selecting the first option that works. Satisficing is different from optimizing, which means trying to come up with the best strategy. Optimizing is hard, and it takes a long time. Satisficing is more efficient. The singular evaluation strategy is based on satisficing.

Before we did this study, we believed that novices impulsively jumped at the first option they could think of, whereas experts carefully deliberated about the merits of different courses of action. Now it seemed that it was the experts who could generate a single course of action, while novices needed to compare different approaches.

The recognition-primed decision (RPD) model fuses two processes: the way decision makers size up the situation to recognize which course of action makes sense, and the way they evaluate that course of action by imagining it.

Intuition depends on the use of experience to recognize key patterns that indicate the dynamics of the situation.

This is one basis for what we call intuition: recognizing things without knowing how we do the recognizing.

The part of intuition that involves pattern matching and recognition of familiar and typical cases can be trained. If you want people to size up situations quickly and accurately, you need to expand their experience base. One way is to arrange for a person to receive more difficult cases.

Another approach is to develop a training program, perhaps with exercises and realistic scenarios, so the person has a chance to size up numerous situations very quickly. A good simulation can sometimes provide more training value than direct experience. A good simulation lets you stop the action, back up to see what went on, and cram many trials together so a person can develop a sense of typicality. Another training strategy is to compile stories of difficult cases and make these the training materials.

He was using the term fantasy to refer to a heuristic strategy decision researchers call mental simulation, that is, the ability to imagine people and objects consciously and to transform those people and objects through several transitions, finally picturing them in a different way than at the start.

This is the “parts requirement“ for building a mental simulation: a maximum of three moving parts. The design specification is that the mental simulation has to do its job in six steps. Those are the constraints we work under when we construct mental simulations for solving problems and making decisions. We have to assemble the simulation within these constraints.

The biggest danger of using mental simulation is that you can imagine any contradictory evidence away.

One reason for problems such as de minimus explanations that discard disconfirming evidence is that once we have built a mental simulation, we tend to fall in love with it.

A final shortcoming is that we have trouble constructing mental simulations when the pieces of the puzzle get too complicated—there are too many parts, and these parts interact with each other.

Cohen believes that until we have an alternate mental simulation, we will keep patching the original one. We will not be motivated to assemble an alternate simulation until there is too much to be explained away.

premortem strategy.

Our exercise is to ask planners to imagine that it is months into the future and that their plan has been carried out. And it has failed. That is all they know; they have to explain why they think it failed.

The experts placed a greater emphasis on situation assessment, while the majority of the novices emphasized deciding on the course of action. … This finding is consistent with the RPD model which proposed that experts based their decisions on situation assessment.

The standard advice for making better decisions is to identify all the relevant options, define all the important evaluation criteria, weight the importance of each evaluation criterion, evaluate each option on each criterion, tabulate the results, and select the winner.

Again and again, the message is repeated: careful analysis is good, incomplete analysis is bad. And again and again, the message is ignored; trainees listen dutifully, then go out of the classes and act on the first option they think of.

First, the rigorous, analytical approach cannot be used in most natural settings. Second, the recognitional strategies that take advantage of experience are generally successful, not as a substitute for...

The analytical methods are not the ideal; they are the fallback for those without enough exp...

analytical methods may be helpful for people who lack experience.

When options are very close together in value, we can call this a zone of indifference: the closer together the advantages and disadvantages of competing options, the harder it will be to make a decision but the less it will matter.

difficulty is created by the lack of information rather than the closeness of the two outcomes. We can think of this as a zone of ignorance: the squad leader will have to choose one route, primarily by chance.

a number of ways that experts in different fields learn

They engage in deliberate practice, so that each opportunity for practice has a goal and evaluation criteria.

They compile an extensive expe...

They obtain feedback that is accurate, diagnostic, and ...

They enrich their experiences by reviewing prior experiences to derive new insights a...

leverage points—a small difference that makes a large difference, a small change that can turn a situation around

Leverage points are just possibilities—pressure points that might lead to something useful, or might go nowhere. Expertise may be valuable in noticing these leverage points.

In interpreting situations, experts seem attuned to the leverage points—both the opportunities and the threats facing them—rather than just being aware of the physical and spatial arrangement of objects.

We also need to spot leverage points that can work against us, in order to learn the weaknesses in our plans. These are sometimes called choke points.

we need to tie the leverage points together into a path in which we can feel confidence. Once we see how to move from hold to hold, we have a plan. We also know we will be changing the plan during the climb as we notice new features. We may have gaps in the plan where we do not see the connection but trust that we will find it when we get that far.

The concept of leverage points opens the way to think about problem solving as a constructive process. It is constructive in the sense that solutions can be built up from the leverage points and that the very nature of the goal can be clarified while the problem solver is trying to develop a solution.

To solve ill-defined problems, we need to add to our understanding of the goal at the same time we generate and evaluate courses of action to accomplish it.

When we use mental simulation to evaluate the course of action and find it inadequate, we learn more about the goal we are pursuing. Failures, when properly analyzed, are sources of new understanding about the goal.

We can think of problem solving as consisting of four processes: problem detection, problem representation, option generation, and evaluation

The problem representation function covers the way a person identifies and represents the problem.

Not all gaps or opportunities lead to problem solving. They must be important enough, and the problem solver must judge that the gap or opportunity will not be resolved without special effort. Then comes a difficult judgment: the solvability of the problem.4 Somehow we use our experience to make this judgment even before we start working to come up with a solution.

the function of problem representation includes goal setting because the problem solver must judge whether to try to come up with a solution or turn to other needs. For ill-defined goals, we can expect to see a lot of goal modification during the problem-solving effort.

When a gap or opportunity is identified, often we will try to diagnose it.6 This is the mental simulation function in which we try to weave together the causes that might have led to the current situation.

The problem representation and diagnosis processes are linked to forecasting, which usually requires mental simulation.

The next function is directed at generating a new course of action, in many cases, a straightforward process: we recognize what to do, and do it. At other times, we do not recognize what to do and must rely on leverage points in order to construct a new course of action.

We also have to be careful not to pursue opportunities too enthusiastically since they might distract us from our more important goals. We have to balance between looking for ways to reach goals and looking for opportunities that will reshape the goals.

The fourth function is to evaluate plans and actions, to play out a scenario to see what will happen. If the evaluation is favorable, we carry out the action. We also can learn from the evaluation, perhaps discovering new gaps or opportunities, resulting in problem detection or in a new way to represent the problem, as when we would modify our goals.

De Groot (1945) and Isenberg (1984) have suggested that what triggers active problem solving is the ability to recognize when a goal is reachable.