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Such efforts haven’t always been executed with finesse. Texas A&M University, for example, issued a report in 2011 that listed faculty members’ names in red or black — like a corporate balance sheet — depending on whether the research and tuition dollars they generated covered their salary and expenses. Such heavy-handed efforts usually crumble under faculty opposition. Texas A&M abandoned its plan amid faculty objections to the perceived corporatization of the university as well as the accuracy of the data.

Mr. Usher says the metrics aren’t meaningful without context and often aren’t even accurate. He echoes faculty members on many campuses who have complained that reports based on metrics often show deflated grant awards and incorrect journal citations, and omit publications that should be included (and vice versa).

Peer-reviewed publications may be an effective productivity metric for some departments. For others, like computer science, which produce fewer papers, the metrics might be citations per publication, or conferences per faculty member, or honors and awards. Federal grants could be a productivity metric for a department like chemistry, but not for engineering, since engineering faculty members at MIT receive a large share of grants from private sources that aren’t captured by Academic Analytics’ data.