ABSTRACT
The importance of building advanced analytical models to support the sales and operations planning (S&OP) process is increasingly recognized. Despite this, there are very few academic or commercial approaches in this regard. This chapter presents an integrated support proposal for S&OP. On the demand side, it includes the use of a Random Forest Regressor to forecast sales in terms of average prices. On the supply side, a mixed-binary programming model that maximizes the present value of the monthly flow of marginal contributions including supply and demand decisions, is presented. The proposal has been successfully tested with different products and configurations, concluding that the well-known techniques of optimizing the supply given a demand or managing the demand given a supply capacity, have a better solution if they are integrated and promotion decisions are incorporated in the presence of limited capacities, economies of scale, and seasonal demand. The concepts used in this model come from the supply chain management, revenue management, and enterprise profit optimization models.
