Which of the following is NOT one of the two approaches to forecasting demand?

The choice of training data analysis as the option that is not one of the two recognized approaches to forecasting demand is correct because it does not specifically designate a forecasting technique in the same way the other options do.

Moving averages and exponential smoothing are both established methods used in demand forecasting that help in analyzing historical data to predict future patterns. Moving averages smooth out fluctuations over a specific time frame, providing a clearer view of trends. Exponential smoothing further refines this process by applying decreasing weights to older observations, which makes it sensitive to recent changes in the data. The exponentially weighted average method is a variation of exponential smoothing that describes a systematic way of applying weights to past data for a more nuanced forecast.

Training data analysis, in contrast, is a broader concept that refers to the process of examining and learning from historical data to improve the performance of forecasting models but does not represent a specific forecasting technique. It's more of an overarching strategy rather than a method, which sets it apart from the other options that are direct forecasting methods.