Abstract Recent work in the area of control design has shown that the degree of gain directionality has a significant impact in achievable robust performance. Thus, it is important to obtain process models which give a satisfactory description of gain directionality. In this paper a parametric identification algorithm is applied to a case study of binary distillation. When the actuators are perturbed simultaneously this approach yields models which give a satisfactory description of the high-and low-gain directions. However, a common practical approach for modeling of distillation columns is to perturb the inputs separately and then combine the models into an overall description of the plant dynamics. It is shown that this method might have the drawback that the obtained model yields a poor description of the low-gain direction in the distillation plant. This indicates that modelling of multivariable processes can be improved by application of multivariable identification algorithm.