Funnel plots are an increasingly common graphical tool which are widely used in the literature. They were first introduced by Light and Pillemer in 1984 . In scientific literature, funnel plots are used to identify the probability of bias in meta-analyses and compare institutional performance. The ability to identify variation is better with graphical than tabular display. In addition, the way data are presented can directly influence the interpretation of results. This was demonstrated by Marshall et al (2004) , who presented institutional mortality data in both a league table and control chart format. This study illustrated that when displayed as a league table, a greater number of units were identified for investigation than were actually required. The use of control charts or funnel plots may therefore show benefit in reducing the number of inappropriately labelled outliers. This article explains how clinicians should read and interpret funnel plots, and discusses their considerations and limitations.