Originality, significance, clarity, and exactness ought to be key indicators in evaluating research. The assessment of scientific productivity and quality, however, is a difficult task: not only are the commonly used measures crude, but in many cases they are not even designed for this purpose. Further, metrics such as the Journal Impact Factor and the Hirsch Index are eagerly, universally, and uncritically used as performance predictors. They have a bearing on the filling and prolongation of academic positions, on the acceptance or rejection of grant proposals, and even on the evaluation of departments or individual institutes. In this presentation, I will introduce the most relevant metrics used in scientific publishing, demonstrate the risks of their inappropriate use, and signpost potential ways out of this dilemma.