A logistics company is looking to reduce delivery delays and improve inventory management.

For a logistics company aiming to reduce delivery delays and optimize inventory management, SAP offers AI-powered solutions that enhance supply chain efficiency and forecasting. The correct answers are SAP AI Business Services, SAP Predictive Analytics, and SAP Digital Manufacturing Cloud, as these solutions directly address logistics challenges with AI-driven capabilities.

SAP documentation highlights: “Create a risk-resilient and sustainable supply chain with built-in AI that is connected and contextualized. Enabling you to predict customer demand and adjust to change.” SAP AI Business Services provide reusable AI capabilities, such as machine learning for demand forecasting and anomaly detection, which help “optimize supply chain operations by analyzing real-time data and market trends.” SAP Predictive Analytics, embedded in solutions like SAP S/4HANA, supports “predicting customer demand and adjusting inventory levels” to minimize delays and overstocking. SAP Digital Manufacturing Cloud leverages AI to “optimize production scheduling and inventory management,” ensuring efficient logistics operations by integrating real-time data from manufacturing and supply chain processes.

The incorrect options—SAP BusinessObjects Planning and SAP Cloud ERP—are not primarily AI-driven for logistics. SAP BusinessObjects Planning focuses on financial planning and analytics, not logistics-specific AI applications. SAP Cloud ERP, while encompassing AI capabilities, is too broad and not specifically tailored to logistics compared to the selected solutions. SAP’s case study on Henkel illustrates how AI in SAP Business Technology Platform enhances supply chain resilience, supporting the relevance of the chosen solutions.