Bread Sales Pattern Forecast from Short-Term Data

Abstract

In general, baking companies develop a large number of new products, but only some of them becomeestablished as standard products, and the production of new products may result in a large amount of wasteloss due to unpredictable sales. Therefore, it is necessary to predict the future order volume based on theshort-term order data of new products. In this paper, we propose a method for forecasting and evaluationusing a combination of multiple explanatory variables and models, using shipment data from bakeries fora short period of time, such as one month after the start of sales. In the proposed method, the most accurateresults were obtained by constructing a model with variables that took into account the characteristics ofrandom forests and bread making, and explanatory variables that were modified for the low number ofstores.