Quantitative Analysis for Management, 13/e

5.6 Adjusting for Seasonal Variations

Time-series forecasting such as that in the example of Midwestern Manufacturing involves looking at the trend of data over a series of time observations. Sometimes, however, recurring variations at certain seasons of the year make a seasonal adjustment in the trend line forecast necessary. Demand for coal and fuel oil, for example, usually peaks during cold winter months. Demand for golf clubs or suntan lotion may be highest in summer. Analyzing data in monthly or quarterly terms usually makes it easy to spot seasonal patterns. A seasonal index is often used in multiplicative time-series forecasting models to make an adjustment in the forecast when a seasonal component exists. An alternative is to use an ...