The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.