Steps in forecasting with seasonal regression : a case study from the carbonated soft drink market

Abstract

Forecasting enables the efficient utilisation of a firm’s resources. There are various types of forecasting models that can be built. Illustrates the steps involved in building a forecasting model utilising seasonal regression with a practical example. The model obtained for the carbonated soft drink brand under consideration estimates a growth rate of 3,568 units per month during the last five years and identifies the seasonal effect during each month of the year. The model also computes the cannibalisation effect that the introduction of a brand extension has had. The development of such models can provide a useful input to both marketing and operations planning.