Disciplined Systematic Global Macro Views: Recognition-primed decision-making model

Monday, April 5, 2021

Recognition-primed decision-making model - A key approach to investing

One of the key concepts that separate good from great investors is better decision-making in an uncertain environment with limited information. Some refer to this special skill through the broad term of intuition, yet the concept of intuition is often fuzzy and imprecise. A negative view of intuition is a misconception. Intuition can and does have structure and can be well explained within the context of naturalistic decision-making.

Too often the focus of quick decision-making under uncertainty has been on biases and irrationality. In reality, there is much to learn from realistic approaches to decision-making that are based on practical rules or heuristics that cut time delays and focuses on the information available not what would be needed in a perfect world.

There has been significant work on modeling the idea of intuition through the pioneering with Gary Klein in his many studies of decision-makers under the stress of time and information constraints. One of the core approaches he developed was the recognition primed decision model (RPDM).

The recognition primed decision model starts with experience or base knowledge of the decision-maker. This experiential knowledge allows the decision-maker to assess many different situations and variation from core situations. The first question the decision-makers has to ask is whether the decision is typical. If the situation is typical, then the decision maker can focus on four by-products of recognition: expectancies, the relevant cues associated with a typical situation, plausible goals, and a set of possible actions.

From recognition, there needs to be an evaluation of the action plan. If the answer is that the plan will not work, the action has to be reassessed. If it can work, with some exceptions, then the plan has to be modified. Once a plan is accepted, the course of action should be implemented.

If the situation is not typical, the decision-maker will have to diagnose what makes this situation unique and look for more data. If the situation is recognized but has an anomaly, then there needs to be clarification with more data or a restructuring of the diagnosis. There is a feedback loop between recognition of similar situations and action against unique situations that require deeper thinking or more information and then an evaluation. Experience and intuition can be process driven.

The recognition primed analysis can follow fast or slow thinking. If the situation is well-known and defined, then the move from analysis to action can be quick. On the other hand, if the situation is not recognized, there will be required slower, more deliberate thinking. A recognition primed approach is used by most discretionary traders. A recognition primed approach can be applied to systematic modeling through specific rules of thumb, albeit there is limited room for modification or diagnosis.

Investment events create catalysts, and the investor exploits these events through recognition, diagnosis, and action.

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