Decision making, control and information processing for large scale systems are designed and implemented in a distributed manner. Decision integration is a method to improve the quality of decision making. This research effort builds on previous results in attempting to establish the theoretical foundation of operational decision integration for such systems. Properly designed integration always improves the quality of the decisions; this is demonstrated through the use of a distributed hypothesis testing model. The problem of organizing decision making agents into architectures of integration is addressed by analyzing several elementary decision architectures for organizations, and comparing their performance. Explicit algorithmic procedures are developed to determine the optimal decision integration methods for a variety of organizations. Five motivating examples are presented to explicitly demonstrate the effectiveness of the algorithms. These procedures constitute the fundamental building blocks for analyzing the architectures of larger more realistic systems.