Design and Implementation of Intelligent KPI-Based Decision Support Systems for Data-Driven Operations Management in U.S. Enterprises

In an increasingly competitive and data intensive business environment, U.S. enterprises are under growing pressure to enhance operational efficiency, strategic agility, and decision accuracy. Traditional decision making approaches often rely on static reports and fragmented performance indicators, limiting their ability to respond proactively to dynamic operational challenges. This paper presents the design and implementation of an intelligent Key Performance Indicator (KPI)-based Decision Support System (DSS) tailored for data driven operations management in U.S. enterprises. The proposed system integrates real time data analytics, machine learning driven insights, and interactive dashboards to support informed managerial decisions. By aligning organizational objectives with operational KPIs, the system enables predictive performance monitoring, anomaly detection, and scenario based decision evaluation. A modular architecture is developed to ensure scalability, interoperability, and adaptability across diverse enterprise domains. Experimental results and case based evaluations demonstrate that the proposed DSS significantly improves decision timeliness, operational visibility, and performance optimization compared to conventional reporting systems. The findings highlight the potential of intelligent KPI driven DSS platforms as a strategic asset for modern enterprises seeking sustainable operational excellence.