Spatial OLAP systems allow multidimensional analysis of huge volume of spatial data. Spatial vagueness is one of the most transparent and current imperfections of spatial data. Although several works propose new ad-hoc models for handling spatial vagueness in Spatial DBMS, the implementation of those models in conventional systems and Spatial Data Warehouses (SDW) is still in an embryonic state. Thus, to help reduce that uncertainty and its consequences in SOLAP analysis, we present a new approach for designing spatial data cubes based on users tolerance to the risk of misusing datacubes.