In quality engineering, engineering intuition is often ineffective and inconclusive for interpreting the behaviors of quality characteristics and their possible effects on process loss. Loss functions can be utilized in process design and optimization by aligning losses in a way which minimizes expected losses, even when responses are correlated and losses are the result of co-movements of those responses, i.e., synergy or antagonism of loss. Most of the current literature on multidimensional quality does not provide enough information about the effects of responses moving simultaneously in the same/opposite direction on process loss. To fill this gap, this manuscript focuses on co-movement effects and provides an efficient approach based on multivariate upside-down normal loss function. The procedure and its advantages are illustrated by an example.