Based on a rigorous formulation and analysis, a decentralized control system is structurally decomposed into separate SISO control loops with interactions unmasked. In particular, the decomposition provides a completely equivalent representation of the original multivariable system, and consequently recovers some important dynamic information that is often ignored in most of the existing dynamic analysis methods and interaction measures. Absolute and relative interactions in individual loops are defined and measured and their structural significance is clearly shown. This allows for the effects of interaction on a closed-loop system to be evaluated in a transparent way. This article provides an overview of the usefulness of the proposed decomposition approach and interaction measurement. The evaluation of the severity of loop coupling and performance deviation from independent design are discussed. Possible difficulties imposed by interactions, effects of controller tuning and variable pairing on closed-loop performance are also dealt with.