What does the moving average model focus on?

The moving average model primarily emphasizes the average of historical demands over a specified time period. This approach is particularly useful in forecasting because it smooths out short-term fluctuations and highlights longer-term trends in the data. By taking a simple average of past data points, the moving average allows businesses to make predictions about future demand based on established patterns, effectively reducing the influence of random variations in the data.

This method is straightforward and relies on historical data, making it accessible and easy to understand for practitioners who need to make quick and informed decisions based on demand patterns. It does not directly account for seasonality, regression analyses, or explicit growth rates; instead, it focuses on obtaining a stable estimate by averaging past demand figures, thus emphasizing the importance of historical demand trends in forecasting future needs.