Certified Supply Chain Professional (CSCP) Practice Exam

In forecasting, what is the purpose of the weighted moving average?

1. To prioritize less important data

2. To average out extreme data points

3. To give increased importance to recent data

4. To eliminate historical data

The correct answer is: To give increased importance to recent data

The weighted moving average is a forecasting technique that assigns different weights to past observations, with the intention of giving increased importance to more recent data. This approach recognizes that recent data may be more relevant to predicting future trends than older data. By weighting the data points, forecasters can better capture the underlying patterns, trends, and seasonal effects that may influence future outcomes. For instance, in a scenario where market conditions are rapidly changing, relying heavily on older data might lead to inaccurate forecasts. The weighted moving average helps address this by ensuring that changes in the most recent data are reflected more significantly in the forecast, thereby enhancing its accuracy. The other options do not align with the primary purpose of the weighted moving average. Prioritizing less important data does not capture its intent, nor does it average out extreme data points as its primary function. While the method does not eliminate historical data, it ensures that the data used for forecasting reflects current trends and issues effectively.