This episode of Techsplainers explores demand forecasting, the process that helps businesses predict future customer needs using historical data and analytics. We examine how modern organizations are leveraging AI, machine learning, and predictive analytics to enhance forecasting accuracy in real-time. The discussion covers qualitative methods like the Delphi method and sales force composites alongside quantitative approaches such as moving averages and econometric modeling. We also explore the six key steps to implementing effective forecasting and four major benefits: informed scaling, accurate budgeting, strategic inventory management, and pointed decision-making. Whether you're managing a supply chain or making strategic business decisions, understanding demand forecasting can help you anticipate market needs with greater precision. Learn more about demand forecasting https://www.ibm.com/think/topics/demand-forecasting
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Narrated by Amanda Downie