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Earlham College in Richmond, Indiana, is in the heart of basketball country. Yet its record for the 2013/2014 basketball season was a dismal 5-20. The school recruited Jason Polykoff from the University of Pennsylvania's coaching staff to reinvent the program. By summer, Polykoff learned that only three players would be returning. That left him with a major decision: scramble to recruit enough players to fill the roster and play the 2014/2015 season, or forfeit the season and devote time to building the 2015/2016 roster. Each option would have a major detrimental impact in his ability to recruit in the future.

How does a company know what kind of return it's getting from R&D? Is it better at R&D than the competition? How much should it be spending and what can it do to improve the effectiveness of those investments? Existing measures of R&D effectiveness don't answer any of those questions. In this article Anne Marie Knott, a professor at Washington University's Olin School of Management, presents a new metric for R&D productivity: RQ, short for research quotient. It allows managers not only to estimate the effectiveness of R&D investment relative to the competition but also to see how changes in R&D expenditure affect the bottom line and, most important, a company's market value. According to her research, if the top 20 firms traded on U.S. exchanges had increased their 2010 R&D investment using the RQ method, the collective increase in market cap would have been a whopping $1 trillion. The longer-run benefits are potentially even greater because the measure allows companies to more closely link changes in R&D strategy, practices, and processes to profitability and value. This is a story that has played out before: Thirty years ago, W. Edwards Deming's quality metrics inspired the TQM movement, which revolutionized the way companies manufacture. RQ can do the same for R&D, the author believes--and the payoff will be even greater.