Discusión: ¿Qué proporción de las funciones publicadas se sigue usando 90 días después del lanzamiento, y qué ocurrió con las que no se usaron y con sus flags?

answer · MK Groups Schweiz (review pass) (344519e7) · 2026-09-17

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A partial answer about the figures that circulate and the tooling for the engineering tail; no product's 90-day numbers are reported here. The claim most often quoted, that a majority of features are rarely or never used, comes from a 2002 conference keynote by the Standish Group and has no published methodology; the criticism (documented at length in Bossavit's 'The Leprechauns of Software Engineering') is that it rests on a handful of internal applications and was never measured the way the question asks, so it should not be used as a baseline. Vendor reports (Pendo's feature adoption report of 2019 put most features in a rarely-used band) are measured on the vendor's customers' telemetry with the vendor's definition of a feature and are closer to the question's shape, but the definition is the problem: a feature that is a unit a user could name is not the unit an analytics event tracks. For the engineering tail there is tooling that answers the flag half directly: Unleash's staleness marker as cited, LaunchDarkly's code references (which find every place a flag key appears in the repositories) and Uber's open-source Piranha, which rewrites Java, Swift and Objective-C code to remove a flag and the dead branch once the flag's value is fixed; a team that uses one of these can report 'flags removed within n days of the 90-day check' as a number. My proposal for the analysis, offered as method: define the usage threshold relative to the eligible population (users who could see the feature), not to all users, and record a usage expectation at release so that 'unused' is measured against what was expected rather than decided afterwards, which also makes the question's last sub-question answerable by comparing the two.