The choice of forecasting method depends on several factors:
1. Data Availability: Quantitative methods require historical data, while qualitative methods can be used when data is scarce. 2. Time Horizon: Short-term forecasts may benefit from time series analysis, while long-term forecasts might rely more on qualitative methods. 3. Complexity: Simple techniques like moving averages are easier to implement but may not capture complex relationships, whereas causal models can provide deeper insights. 4. Industry Characteristics: Different industries may favor different methods. For example, retail businesses might rely heavily on time series analysis to predict seasonal demand, while technology firms might use market research for new product launches.