The McNamara fallacy, named for Robert McNamara, the US Secretary of Defense from 1961 to 1968, involves making a decision based solely on quantitative observations and ignoring all others. The reason given is often that these other observations cannot be proven. The fallacy refers to McNamara's belief as to what led the United States to defeat in the Vietnam War—specifically, his quantification of success in the war, ignoring other variables.
Examples in warfare
Vietnam war
The McNamara fallacy originates from the Vietnam War, in which enemy body counts were taken to be a precise and objective measure of success. War was reduced to a mathematical model: By increasing enemy deaths and minimizing one's own, victory was assured. Critics note that guerrilla warfare and widespread resistance can thwart this formula. McNamara's interest in quantitative figures is seen in Project 100,000: By lowering admission standards to the military, enlistment was increased. Key to this decision was the idea that one soldier is, in the abstract, more or less equal to another, and that with the right training and superior equipment, he would factor positively in the mathematics of warfare. US Air Force Brigadier-General Edward Lansdale gave McNamara a lesson he was not able to process in 1962, when the war was in its infancy. McNamara was trying to develop a list of metrics to allow him to scientifically follow the progress of the war. He asked Lansdale if the list was complete. Lansdale replied that it was missing "factor X", the feelings of the common rural Vietnamese people. McNamara wrote it down on his list in pencil, then erased it and told Lansdale that he could not measure it, so it must not be important.
There has been increasing discussion of the McNamara fallacy in medical literature. In particular, the McNamara fallacy is invoked to describe the futility of using progression-free survival as a primary endpoint in clinical trials for agents treating metastatic solid tumors simply because PFS is an endpoint which is merely measurable, while failing to capture outcomes which are more meaningful such as overall quality of life or overall survival.
In competitive admissions processes
In competitive admissions processes — such as those used for graduate medical education — evaluating candidates using only numeric metrics results in ignoring non-quantifiable factors and attributes that may ultimately be more relevant to the applicant's success in the position.
