Stable seasonal pattern models for forecast revision: A comparative study

Many firms prepare forecasts at the beginning of each financial quarter that predict total sales over the upcoming quarter. Such forecasts may be used to make financial projections, or to plan manufacturing capacity and materials purchases. As weekly sales are recorded during the quarter, these quarterly forecasts are often revised, allowing plans and projections to be adjusted appropriately. A formal basis for these forecast revisions may be found in so-called stable seasonal pattern models, which are based on the observation that in many instances, the sales that accrue during a given period of a quarter follow a regular pattern. This paper discusses a number of stable seasonal pattern models – several from the literature, two that are novel – which have been evaluated for making forecast revisions at Sun Microsystems, Inc. Commonalities between the models are elucidated using a general theoretical framework, and a straightforward sample-based mechanism is described that affords great flexibility in the design and use of stable seasonal pattern models. The paper culminates in a detailed comparison of the performance of new and existing stable seasonal pattern models with respect to Sun's sales data.