Forecasting Catalog Sales (Time Series)

A catalog company is interested in forecasting monthly sales of its men's clothing line, based on their sales data for the last 10 years.

This example uses the stream named catalog_forecast.str, which references the data file named catalog_seasfac.sav. These files are available from the Demos directory of any IBM® SPSS® Modeler installation. This can be accessed from the IBM SPSS Modeler program group on the Windows Start menu. The catalog_forecast.str file is in the streams directory.

We've seen in an earlier example how you can let the Expert Modeler decide which is the most appropriate model for your time series. Now it's time to take a closer look at the two methods that are available when choosing a model yourself--exponential smoothing and ARIMA.

To help you decide on an appropriate model, it's a good idea to plot the time series first. Visual inspection of a time series can often be a powerful guide in helping you choose. In particular, you need to ask yourself:

• Does the series have an overall trend? If so, does the trend appear constant or does it appear to be dying out with time?
• Does the series show seasonality? If so, do the seasonal fluctuations seem to grow with time or do they appear constant over successive periods?

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