Abstract

Order Promising (OP) has emerged as a critical capability in modern supply chains, serving as the interface between customer demand and supply chain execution. Traditionally, OP has relied on rule-based Available-to-Promise (ATP) and Capable-to-Promise (CTP) models embedded in Enterprise Resource Planning (ERP) systems. However, the increasing complexity of global supply chains, demand volatility, and the rise of digital commerce have exposed the limitations of static promise mechanisms. This paper develops a theoretical framework for Intelligent Order Promising (IOP) that integrates ERP systems with advanced planning platforms, artificial intelligence (AI), and predictive analytics. The study examines OP not only as a logistics execution tool but also as a strategic lever for customer experience, profitability, and resilience. The framework conceptualizes IOP as a dynamic decision-making layer that balances promise reliability, supply chain efficiency, and customer-centricity. The paper contributes to the literature by positioning IOP as the bridge between transactional systems (ERP) and cognitive supply chain planning, highlighting directions for future research in digital and sustainable supply chains.

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