Exponential smoothing is a forecasting technique that uses a weighted average of past and present data to predict future values. It is suitable for time series data that have a stable or slowly changing trend and no significant seasonal variations. Exponential smoothing assigns more weight to the most recent data, giving it a higher influence on the forecast. This makes it more responsive to changes in demand patterns than other techniques, such as moving average or time series decomposition, which use fixed weights or historical data. The Delphi method is a qualitative technique that involves a panel of experts who provide their opinions and feedback on a topic through multiple rounds of surveys. It is not based on historical data or mathematical formulas, but rather on human judgment and consensus. Therefore, it is not appropriate for developing a forecast. References: CPIM Part 2 Exam Content Manual, Version 7.0, Domain 3: Plan and Manage Demand, Section A: Demand Management, Subsection 2: Forecasting Techniques and Methods, p. 14-15.