Event-Driven Intelligent ERP Architecture for Real-Time Enterprise Financial and Revenue Processing

Abstract

Modern organizations increasingly function with digital ecosystems featuring high-frequency transactions, subscription-based revenue models, and dispersed application landscapes. Traditional ERP systems are based on synchronous processing and batch-oriented integration patterns that can lead to limited scalability, increased transaction latency, and delayed operational insights. Such limitations are especially noticeable in financial and revenue management contexts that rely on real-time responses to rapidly changing dynamics. This paper introduces a new Event-Driven Enterprise ERP Architecture (EDEA) that serves as the foundation for real-time transactions, continuous scalability, and independent automation on an enterprise level. While connecting tax sensors and other cloud-native microservices as well as event streaming services, the architecture leverages the extensibility capabilities of SAP S/4HANA to serve as the transactional backbone via SAP Business Technology Platform. The cloud application services are built with the SAP Cloud Application Programming Model, which allows modular microservice orchestration and an event-driven architecture. We propose a framework consisting of five architectural layers, namely Event Generation, Event Streaming Infrastructure, Microservice Processing Layer, Intelligent Automation Services and Enterprise Analytics. All these layers allow ERP systems to evolve from tightly coupled transactional engines into distributed event-driven ecosystems that can be leveraged in the real-time enterprise. Experimental evaluation of simulated enterprise workload processing up to 40 million business transactions per operational cycle. The findings show measurable increases in enterprise processing efficiency with 38% improvement in transaction throughput, 42% reduced latency to integrate systems, and 35% improved real-time revenue processing efficiency compared to standard synchronous ERP architectures. Model analysis for the performance of modern event-driven processors supporting real-time enterprise systems Management summary with recommendations for optimizing transaction throughput and minimizing resource waste Conclusion that promotes an agile review architecture-based approach to established graph databases. In this study an architecture building block for event-driven enterprise service computing on top of large dimensions ERP ecosystems is contributes.