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Predictive analytics empowers supply chain optimization by forecasting demand trends, enabling businesses to align inventory levels with future requirements. For example, retail companies can use predictive models to anticipate peak demand during holiday seasons, ensuring sufficient stock availability. This proactive approach minimizes overstocking and understocking risks, reducing costs while maintaining customer satisfaction. Predictive analytics also aids in logistics planning, supplier coordination, and delivery scheduling, enhancing the overall efficiency and responsiveness of the supply chain. Why Other Options Are Incorrect: • A: Visualizing historical data lacks the forward-looking capabilities of predictive analytics. • C: Automation benefits from analytics but cannot entirely replace human oversight. • D: Cost reduction should not compromise customer satisfaction, a critical supply chain goal. • E: Human expertise remains essential for interpreting and acting on analytical insights.
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