Multi-dimensional indices currently employed in the social sciences, such as indices of democracy (e.g. Freedom House, Polity, Vanhanen) or the “Human Development Index” (HDI) , use aggregation procedures based on simple arithmetic means of the various dimensions (FH, Polity) or, at best, multiplication (Vanhanen). As has been rightly criticized by many authors (Munck/Verkuilen 2002, Berg-Schlosser 2007, most recently Coppedge et al. 2011), these procedures blur many important distinctions of the respective components (“lost in aggregation”). This problem becomes even worse when respective country ratings and rankings are based on such aggregated indices, as with the HDI, but also assessments of the “quality” of democracy in various countries. By contrast, this paper proposes an alternative procedure based on set theory and fuzzy set scores. This allows the calibration and aggregation of several components in a multi-dimensional vector space by retaining the individual contribution of each component. A special macro has been developed for this purpose. The usefulness of this procedure is demonstrated both for indices of democracy and the HDI. This also has important implications for the practical-political use of such indices.