CPIM Practice Exam

What happens if seasonality is included in a moving average forecast for a product with distinct seasonality?

1. The forecast will always have a bias toward overproduction.

2. At the end of the seasonal upswing, the forecast will show demand continuing to increase.

3. At the end of the seasonal low, the forecast will show demand starting to increase again.

4. The forecast will lag the trend unless deseasonalized.

The correct answer is: At the end of the seasonal upswing, the forecast will show demand continuing to increase.

Including seasonality in a moving average forecast for a product characterized by distinct seasonal patterns enhances the forecast's alignment with the periodic increases and decreases in demand. This choice reflects the nature of moving averages, which work by smoothing out fluctuations in data over time. When seasonality is present, the moving average can capture these trends, leading to the forecast indicating that demand will continue to rise after a seasonal upswing because it considers past data where similar trends occurred. If demand typically rises during certain times of the year due to seasonal effects, incorporating this seasonal behavior would mean the forecast aligns with those anticipated peaks. In contrast to this, other conditions may cause a failure to accurately reflect seasonality. For instance, forecasting could lag behind overall trends if one does not account for such seasonal fluctuations or uses a simple moving average without adjusting for seasonal factors. Therefore, considering seasonality in moving averages allows for more appropriate and reliable predictions that reflect actual market behavior, making option B the most accurate choice.