Certified Supply Chain Professional (CSCP) Practice Exam

Which method is best suited for forecasts involving trends over long periods?

1. Qualitative forecasting

2. Time-series analysis

3. Associative forecasting

4. Exponential smoothing

The correct answer is: Associative forecasting

The best method for forecasting trends over long periods is associative forecasting. This approach utilizes historical data to identify relationships between various factors, allowing forecasters to analyze how changes in one variable can impact another over an extended timeline. By considering both historical trends and the influence of external variables, associative forecasting provides a robust framework for making long-term predictions. In contrast, qualitative forecasting relies heavily on subjective judgment and expert opinions, making it less effective for long-term trends where data-driven insights are crucial. Time-series analysis focuses on patterns and trends within a single dataset over time, which might be useful short-term but lacks the breadth necessary for considering external factors in long-term forecasts. Exponential smoothing is useful for producing forecasts that respond to changes in underlying trends but does not incorporate external relationships, limiting its effectiveness for long-range forecasting that requires understanding varied influences. Thus, associative forecasting stands out as the most appropriate method for forecasts involving trends over an extended period due to its analytical and data-driven nature.