Demand forecast accuracy is crucial for retailers and CPG companies as it helps optimize inventory levels, reduce stockouts and overstocks, improve customer satisfaction, and enhance supply chain efficiency. Accurate forecasting enables better decision-making, cost reduction, and increased profitability. To improve the accuracy of demand forecasts, companies should consider: Using machine learning algorithms to analyze large amounts of data and identify patterns that human planners may not see Incorporating internal business decisions, such as promotions, price changes, and product introductions, into your forecasts Factoring in external factors that can impact demand, such as weather, local events, and competitor pricing Leveraging granular data and flexible aggregation to create forecasts that support a wide range of planning processes and planning horizons Continuously evaluating and adjusting their forecasting models based on real-world changes and feedback from demand planners