A new report takes stock of how metrics are being used and abused in research management across UK universities
In his 2003 bestseller Moneyball, the writer Michael Lewis describes how the fortunes of the Oakland Athletics baseball team were transformed by the rigorous use of predictive data and modelling to identify undervalued talent. These approaches soon spread through baseball and into other sports, and are now widely used in the financial sector, recruitment industry and elsewhere, to inform hiring and promotion decisions.
A recent study by researchers at the MIT Sloan School of Management suggests that universities are ripe for their own Moneyball moment. Its authors argue: “Ironically, one of the places where predictive analytics hasn’t yet made substantial inroads is in the place of its birth: the halls of academia.” By analysing publication, citation and co-authorship metrics at an early stage in a researcher’s career, the MIT team suggests that it is possible to predict future performance with greater reliability than by subjective judgements alone.