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AI-Powered Supply Chain Optimization: Integrating CRM, CPQ, and ERP for Enhanced Decision-Making in Boiler Manufacturing

Venkata Saiteja Kalluri

Abstract


In today’s competitive manufacturing landscape, the integration of Artificial Intelligence (AI) into traditional enterprise systems offers a promising pathway to optimize supply chain performance. This paper explores the convergence of Customer Relationship Management (CRM), Configure-Price-Quote (CPQ), and Enterprise Resource Planning (ERP) systems through AI to streamline operations in the boiler manufacturing industry. By leveraging predictive analytics, real-time data synchronization, and intelligent automation, the proposed AI-powered framework enhances decision-making across procurement, production, sales, and customer service. The study uses a case-based approach and simulation models to demonstrate efficiency improvements in lead time, quote accuracy, inventory control, and customer satisfaction. Results indicate a 22% reduction in order processing time and a 17% increase in on-time delivery rates, showcasing the potential of intelligent integration for industry-wide adoption.


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References


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