Citation:

Nisarg Dilipkumar Patel, 2026. Building Scalable ERP Modules for Inventory Forecasting and Material Planning  Volume 6 Issue 2: 244-254.

Abstract:

ERP systems continue to play a central role in coordinating operations, but inventory forecasting and material-planning capabilities are often implemented more rigidly than modern analytical demands require. This has become more important as demand volatility, product proliferation, shorter planning cycles, and exposure to disruption have increased the need for high-frequency forecasting and closed-loop planning. To clarify how scalable ERP modules for inventory forecasting and material planning can be designed and governed, this review examines the current journal literature on forecasting methods, data-driven planning, reconfigurable supply networks and data-intensive operations management. The review identifies five recurring themes: modular separation of transaction processing and analytics, event-driven orchestration of data, multi-horizon forecasting, feedback-rich planning loops, and the enduring significance of data quality and model interpretability. Forecast accuracy alone does not guarantee planning value unless forecasts are structurally reconciled with bills of material, replenishment logic, lead-time constraints, and exception-processing rules. Significant omissions are a shortage of first-hand evidence of ERP-native applications, a paucity of coverage of computational scalability, little coverage of master-data governance, and disjointed assessment metrics among forecasting and planning research. This area is important because scalable ERP modules increasingly determine whether firms can convert analytical insight into timely material decisions under operational uncertainty.

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Keywords:

Demand Forecasting, Enterprise Resource Planning, Material Requirements Planning, Microservices Scalability, Inventory Analytics.