AI Powered Predictive Analytics in SAP Supply Chains: Driving Smarter Decisions
DOI:
https://doi.org/10.15680/bjka7514Keywords:
Predictive Analytics, Artificial Intelligence (AI), SAP Supply Chain Management, Demand Forecasting, Inventory Optimization, Supplier Risk Assessment, SAP S/4HANA, Supply Chain ResilienceAbstract
In today’s volatile business environment, supply chains face increasing complexity due to demand fluctuations, disruptions, and operational inefficiencies. AI‑powered predictive analytics embedded within SAP supply chain systems offers an opportunity to enhance decision‑making by forecasting demand, optimizing inventory, mitigating risk, and speeding up response times. This paper investigates how integrating predictive analytics into SAP (especially SAP S/4HANA and SAP Integrated Business Planning) supports smarter decisions in supply chain management. We analyze recent implementations, examine the technical architectures, and evaluate performance improvements and challenges. Our study employs a mixed‑methods approach: a systematic literature review combined with case study analyses and quantitative metric comparisons from organizations that have adopted AI‑based forecasting, inventory optimization, and supplier risk assessment within SAP frameworks. Findings indicate that predictive analytics leads to significant improvements: up to 20‑35% reduction in stockouts, 10‑30% decrease in inventory holding costs, improved forecast accuracy by 25‑40%, and greater resilience to disruptions. However, organizations face hurdles including data quality, model interpretability, integration complexity, and workforce readiness. This paper discusses both the advantages and disadvantages, illustrates real‑world results, and offers recommendations. Finally, we propose directions for future work such as integrating real‑time streaming data, explainable AI (XAI) in forecasts, and leveraging IoT data more fully. The results provide both theoretical and practical insights for supply chain managers, SAP implementers, and researchers, highlighting how AI‑powered predictive analytics within SAP environments can drive smarter, more resilient supply chains.
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