Prior sustainability models have taken exact basic indicator (BI) values of an entity's sustainability and computed an exact value of the entity's sustainability index. However, BI values are either uncertain or difficult to obtain. In this work, we propose a novel approach that transforms BI data in the form of intervals containing all possible BI values to an interval containing all possible values of the sustainability index. This interval is termed the sustainability index interval (SII). Computation of the SII is achieved through solution of a minimization and a maximization problem using global optimization techniques. Although the underlying global optimization problems are nonconvex, they are shown to possess a number of properties that can be utilized to reduce the burden associated with SII's computation. Based on these properties, a branch-and-bound algorithm is developed, which exactly quantifies the SII in a finite number of iterations. (c) 2011 American Institute of Chemical Engineers AIChE J, 2012