Which approach should a marketing manager use to forecast monthly sales with seasonality?

• A. Use a linear trend line
• B. Use exponential smoothing
• C. Compute seasonality indices
• D. Ignore seasonality

Answer: (C)

Seasonality is the repeating pattern in sales that happens every month. To forecast monthly sales with seasonality, you want to quantify those recurring monthly effects and apply them to a baseline forecast. This is done by computing seasonality indices, which tell you how each month usually performs relative to the overall level. You first estimate a non-seasonal forecast for the period (the underlying level or trend without month-to-month swings), then multiply or add the appropriate seasonal index for each month to get the final forecast. For example, if January typically runs 8% above the average, its seasonal index would reflect that, and January’s forecast would be the base forecast adjusted by that amount.

This approach is especially effective because it directly captures the regular monthly fluctuations, making the forecast align with historical patterns. A linear trend line focuses only on the overall direction and misses the monthly ups and downs. Exponential smoothing can handle seasonality in some forms, but it adds complexity and may be less transparent than using explicit seasonal indices. Ignoring seasonality would ignore a key driver of monthly sales and lead to biased forecasts.