Quantitative vs Qualitative
also Amounts vs Binaries · Quantity vs Quality
The distinction between differences of degree (more or less of the same thing) and differences of kind (different types, categories or dimensions).
A quantitative difference is a matter of degree: more or less of the same thing, measured in shared units along one dimension (an apples-to-apples comparison). A qualitative difference is a difference of kind: distinct types, categories, or dimensions, such as price versus deliciousness (apples-to-oranges). The two are not interchangeable. Addition only works across like terms, because adding means combining amounts of the same thing; you cannot meaningfully sum dollars, kilograms, and deliciousness.
CF treats this distinction as decisive for how decisions should be made. Weighted-factor schemes and Bayesian credences try to force qualitatively different factors onto one numeric scale of “goodness,” then add them. CF argues this fails: there is no correct way to pick the weights or the conversion, and after converting you often still face multiple dimensions of goodness.
CF’s alternative converts quantities into qualities rather than the reverse. The tool is the breakpoint: a difference in quantity that produces a qualitative change, typically the threshold between good enough and not good enough (success versus failure). Instead of scoring a factor, you ask which breakpoints it passes, leaving a margin of error. Most factors have plenty of excess capacity and sit far from any breakpoint, so changes in them should not move the result at all — a point CF imports from Theory of Constraints’ focus on the constraint. Genuinely quantitative information matters only near a breakpoint; elsewhere, qualitative pass/fail judgment is both less work and more reliable.