In robust design studies, location and dispersion effects play different roles, and balancing them when there are multiple responses is an important and challenging task. We propose to use desirability function to simultaneously optimize multiple responses after assigning weights to reflect the relative importance of location and dispersion effects. Our analytical strategy is to plot the solutions obtained from different weights versus the weights and/or some aspects of the solutions versus the weights. These plots provide valuable information that can be useful in choosing one or more compromise solutions to balance the multiple location and dispersion effects. The proposed approach is illustrated using two real problems. Copyright © 2012 John Wiley & Sons, Ltd.