Forecasting accuracy refers to how closely a predicted outcome aligns with the actual result. It is a critical measure in various fields, including business, economics, and meteorology, as it helps assess the reliability of forecasting methods. High accuracy indicates that a model or method can effectively predict future events, while low accuracy suggests the need for improvement. To evaluate forecasting accuracy, several metrics can be used, such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). These metrics quantify the difference between predicted values and actual outcomes, providing insights into the performance of forecasting techniques. Accurate forecasts can lead to better decision-making and resource allocation.