Based Production and Procurement Synchronization Model for Adaptive Supply Chain Management
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Abstract
Modern supply chains increasingly require synchronized production and procurement decisions because demand variability, supplier constraints, inventory uncertainty, and production dependencies can rapidly propagate across interconnected operations. This paper proposes a conceptual SAP S/4HANA-based Production and Procurement Synchronization Model for adaptive supply chain management. The model integrates demand-driven production planning, material availability assessment, procurement prioritization, inventory visibility, supplier-related decision rules, and feedback-based production adjustment within a unified enterprise planning environment. The theoretical foundation is developed through synthesis of the supplied literature on optimization, influence maximization, network diffusion, combinatorial optimization, and resource-constrained decision-making. Although the provided studies primarily address optimization and network problems rather than SAP implementation directly, their underlying principles provide useful foundations for modeling interdependent production and procurement decisions. The proposed framework treats production orders, material requirements, procurement activities, suppliers, and inventory states as interconnected decision nodes. Optimization mechanisms are used to prioritize constrained materials and production requirements, while adaptive feedback enables procurement and production plans to respond to changing operational conditions. The model indicates that synchronization can reduce decision latency, improve resource allocation, and strengthen supply chain responsiveness. The study further positions integrated production planning and procurement synchronization as a mechanism for improving resilience through coordinated rather than isolated decision-making. The findings are conceptual and should therefore be validated through empirical implementation, simulation, and comparative SAP-based case studies.
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Copyright (c) 2026 Ahmed Al-Karim, Noor Hassan
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Authors retain the copyright of their articles published in this journal. All articles are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited.