Why does recurring decision types fail?

The most common reason recurring decision types fails: Treating every decision as unique. When you fail to recognize recurring types, you approach each decision from scratch — re-gathering information, re-weighing criteria, re-deliberating tradeoffs that you have already resolved in structurally identical situations. This is not thoroughness. It is cognitive waste. The failure is perceptual, not analytical: you see surface differences (different people, different stakes, different context) and miss structural similarity (same decision type, same relevant variables, same optimal process). The antidote is classification — training yourself to look past the skin of a decision to its skeleton.

The fix: Over the next five days, keep a decision log. Every time you face a decision — large or small — write down what it is, then classify it by type. Do not invent categories in advance. Let them emerge from the data. By the end of five days, count how many distinct types you have logged and how many decisions fell into each type. Most people discover that 80-90% of their decisions cluster into fewer than ten recurring types. For your top three most frequent types, write a one-sentence description of the pattern: what varies between instances, and what stays the same. This is the beginning of your decision type inventory — the raw material for building dedicated frameworks in L-0443.

The underlying principle is straightforward: Most decisions you face are variations of types you have encountered before.