CPIM Practice Exam

Which forecasting technique relies on the average demand data from several past periods?

1. Qualitative analysis

2. Exponential smoothing

3. Moving average

4. Deseasonalization

The correct answer is: Moving average

The moving average technique is focused on calculating forecasted values based on the average demand from several previous periods. This method smooths out fluctuations in the data by averaging a specific number of past data points, allowing for easier identification of trends over time. One of the key advantages of using moving averages is that it is simple to understand and implement, making it a popular choice in demand planning and inventory management. By considering multiple periods, the moving average reduces the impact of any single outlier data point, providing a more stable forecast that reflects the underlying demand pattern over a specified timeframe. In contrast, qualitative analysis relies on subjective judgment and intuition rather than historical data. Exponential smoothing uses a weighted average of past data, where more recent observations have a greater influence, but it does not simply average several periods like the moving average method. Deseasonalization addresses fluctuations related to seasonality but does not directly focus on the average demand from past periods. Therefore, moving average stands out as the technique specifically designed to leverage historical demand data for accurate forecasting.