In this paper, we address the simultaneous design of sustainable formulated products and their production process under uncertainty due to the variability in ingredient prices and lack of knowledge of product processability. The problem is formulated as a multiobjective mixed integer nonlinear programming problem where both endogenous and exogenous uncertainties are considered. A two-step strategy is proposed to address uncertainty in formulated products where endogenous is solved at lab scale. Next, the exogenous uncertainties are considered. For the exogenous uncertainty, we compare two strategies. First, we use a scenario reduction technique to obtain the optimal solution when a probability distribution can be computed from market data. The second one considers a sample approximation approach when we only know the range of values of the uncertain variables. The study has been applied to the production of a family of formulated products with different performances and final prices aiming at product efficiency, profitability, and sustainability. The method allows determining the optimal sustainable detergent composition under uncertainty analyzing only a reduced number of scenarios or small samples with good agreement.