Question

Metro Food Vending operates vending machines in office buildings, the airport, bus stations, colleges, and other businesses and agencies around town, and it operates vending trucks for building and construction sites. The company believes its sandwich sales follow a seasonal pattern. It has accumulated the following data for sandwich sales per season during the past 4 years.

SANDWICH SALES (thousands)
SEASON 2019 2020 2021 2022
Spring 51,3 55,6 49,3 47,3
Summer 62,9 64,8 71,2 74,5
Fall 42,7 44,3 45,7 40,6
Winter 36,9 42,7 34,8 41,5

Could the company use the exponential smoothing procedure for making good forecast? Why or why not?

Answer 1

Yes, Metro Food Vending can use exponential smoothing to forecast sandwich sales; the method is suitable for data with a consistent seasonal pattern, although its effectiveness may vary with data volatility.

Step-by-step explanation:

The question regards whether Metro Food Vending can use the exponential smoothing procedure for making good forecasts of its sandwich sales, which are believed to follow a seasonal pattern. You analyze the collected sales data to check for consistent seasonal fluctuations and consider the data's smoothness. Exponential smoothing could certainly be used; however, its effectiveness will depend on the volatility of the data. If there is a regular pattern, Exponential Smoothing with Seasonality (also known as Holt-Winters Exponential Smoothing) could be an appropriate model because it accounts for trends and seasonality in a time series. On the other hand, if the seasonality changes dramatically due to external factors, the method might not perform as well, and the company might need to adapt their model or combine this approach with other forecasting methods to improve accuracy.