In forecasting, which approach assumes that the most recent data is the best predictor of future trends?

The naïve approach to forecasting is based on the principle that the most recent data point is the best predictor of future values. This method assumes that future demand will be the same as the most recent demand observed, making it a very straightforward and easy-to-implement forecasting technique.

This approach can be particularly effective in environments where the data does not show significant variability or trends, as it capitalizes on the latest observation for prediction. Its simplicity can be an advantage, especially when there is limited data or when speed is essential in decision-making.

In contrast, other forecasting methods such as trending, moving average, and seasonal analysis incorporate a more extensive history of data and attempt to account for patterns, cycles, or trends over time. However, they may not always reflect the immediacy that the naïve approach relies on, especially in rapidly changing environments where recent data is more indicative of current conditions.