To install click the Add extension button. That's it.

The source code for the WIKI 2 extension is being checked by specialists of the Mozilla Foundation, Google, and Apple. You could also do it yourself at any point in time.

4,5
Kelly Slayton
Congratulations on this excellent venture… what a great idea!
Alexander Grigorievskiy
I use WIKI 2 every day and almost forgot how the original Wikipedia looks like.
Live Statistics
English Articles
Improved in 24 Hours
Languages
Recent
Show all languages
What we do. Every page goes through several hundred of perfecting techniques; in live mode. Quite the same Wikipedia. Just better.
.
Leo
Newton
Brights
Milds

# McNamara fallacy

The McNamara fallacy (also known as the quantitative fallacy[1]), named for Robert McNamara, the US Secretary of Defense from 1961 to 1968, involves making a decision based solely on quantitative observations (or metrics) and ignoring all others. The reason given is often that these other observations cannot be proven.

The first step is to measure whatever can be easily measured. This is OK as far as it goes. The second step is to disregard that which can't be easily measured or to give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can't be measured easily really isn't important. This is blindness. The fourth step is to say that what can't be easily measured really doesn't exist. This is suicide.

— Daniel Yankelovich, "Corporate Priorities: A continuing study of the new demands on business" (1972).

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 (e.g., in terms of enemy body count), ignoring other variables.[2]

## Examples in warfare

### The 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[who?] 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 reportedly told McNamara[3], who was trying to develop a list of metrics to allow him to scientifically follow the progress of the war, that he was not considering 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.

### The global war on terror

Donald Rumsfeld, US Secretary of Defense under George W. Bush, sought to prosecute wars with better data, clear objectives, and achievable goals. Writes Jon Krakauer,

... the sense of urgency attached to the mission came from little more than a bureaucratic fixation on meeting arbitrary deadlines so missions could be checked off a list and tallied as 'accomplished'. This emphasis on quantification has always been a hallmark of the military, but it was carried to new heights of fatuity during Donald Rumsfeld's tenure at The Pentagon. Rumsfeld was obsessed with achieving positive 'metrics' that could be wielded to demonstrate progress in the Global War on Terror.

— Jon Krakauer, Where Men Win Glory.[4]

## In modern clinical trials

There has been increasing discussion of the McNamara fallacy in medical literature.[5][6] In particular, the McNamara fallacy is invoked to describe the futility of using progression-free survival (PFS) 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 — such as those used for graduate medical education[7] — 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.