This research evaluates the structural role of Management Information System (MIS) architectures to enhance decision-making quality and operational throughput in modern organizations. The rapid expansion of enterprise data pipelines has created complex computational environments where data silos, structural inconsistencies, and information latency hinder effective decision-making frameworks. To address these integration challenges, this study employs a qualitative descriptive and systematic synthesis methodology to evaluate multilayered MIS frameworks using a comprehensive literature corpus spanning enterprise systems and data analytics models. The analytical data were processed through identification, classification, structural comparison, and algorithmic synthesis of preceding research parameters. The results demonstrate that integrated MIS frameworks significantly improve decision-making quality by delivering accurate, relevant, and low-latency structured data assets. Furthermore, the ingestion of digital technology modules and automated data analytics layer strengthens system efficiency, interdepartmental network coordination, and strategic reporting velocity. However, challenges related to hardware infrastructure costs, system scalability, and technical constraints remain critical. In conclusion, organizations must balance investments between hardware infrastructure, technical human resource competence, and robust data govermance protocols to maximize the throughput of automated information systems.