An efficient design is one of the most critical activities for ensuring structural integrity and operational reliability of an industrial plant. Failure of the piping components is a serious hazard leading to loss of assets and endangering environment safety. Typically a hydrocarbon or a power plant is comprised of piping, equipment and structures. The structures are mainly intended to support the piping or equipment mounted on them. In general the composite system including piping, structures and equipment should be analyzed as an integrated assembly. However this is not practical for a variety of reasons and a decoupled analysis (i.e. piping, structure equipment are analyzed as separate independent systems) is carried out as a current practice. Invariably this method is an approximation and generates solution errors which could lead to unrealistic results and unsafe design. The challenge is to estimate the effect of interaction between the different systems and their impact on the overall solution error. In the study a method has been presented for deriving a coupling parameter for static interaction between the primary and secondary systems. The coupling parameter indicates the degree of interaction between the primary and the secondary systems. This is related to the solution error and could give adequate cue to the analyst whether to go for a decoupled or an augmented analysis. Possibly this is a novel approach and not found in the literature till date. The theory has been developed on a mathematical framework and is quite general and not limited to small systems. Numerical simulation has been presented to validate the theory followed by a real life case study. •Practical constraints entail decoupled analysis (DCA) of primary & secondary systems for strength design.•Different types of models for DCA result in solution errors could lead to unsafe design.•In this work a decoupling parameter (DP) has been developed based on fundamental theory.•DP gives a measure of the possible solution error in the results of DCA which helps in assessing reliability of design.•Results of numerical simulation for the validation and a real life case study have been given.