Which of the following is NOT considered a valuable forecast evaluation activity?

The selection of paying close attention to historical weather data as not being a valuable forecast evaluation activity is appropriate because while weather data can influence demand, it is not a direct evaluation method for assessing the accuracy of a forecast. The main purpose of evaluating a forecast is to compare projected demand against actual demand and to understand the performance of forecasting methods over time.

Tracking actual demand against projected demand allows for the timely identification of discrepancies between what was forecasted and what actually occurred, which is essential for adjusting future forecasts. Utilizing statistical measures such as Mean Absolute Deviation (MAD) and standard deviation helps quantify the variation and accuracy of forecasts, providing insights into the reliability of the forecasting process. Additionally, identifying and eliminating bias in forecasts ensures that systematic errors are addressed, improving the overall quality of future predictions.

In contrast, while historical weather data may provide context for certain demand patterns, it serves more as a factor that can influence forecasts rather than being a method to evaluate the forecast itself. Therefore, focusing on weather data does not align with the core activities aimed at improving forecast accuracy and evaluation.