Sales Forecasting System for Chemicals Supplying Enterprises

Ma. Del Rocio Castillo E., Ma. Magdalena Chain Palavicini, Roberto Del Rio Soto, M. Javier Cruz Gómez

Abstract


In Mexico, the chemicals supplying enterprises have a hard job trying to make its operations planning. The difficulty is created by a combination of handling a large number of products and changeable consumption patterns of each customer. To simplify the operation planning task of those enterprises, a simplified system was envisaged and programmed. This free access and friendly software gives more accurate sales forecasts than the currently obtained by the chemicals suppliers. The developed software is written in PHP language (for web development dynamic content) and HTML (for making Web pages) and by the use of XAMPP software (Apache server module), runs on different operating systems. This program applies five quantitative sales forecasting techniques for each marketable product, with continuous error assessment, in order to select case by case, the monthly more accurate prediction method. The proposed system has been already applied in two companies; the first one used simple moving average, as a quantitative technique to predict its sales, and expert opinion as qualitative technique; the second company used trend projection as quantitative, and Delphi Method as qualitative techniques. Both companies consider that a suitable sales prediction is the starting point for good operations planning. For each product it is required to use a different technique, because the behavior of historical sales in each case is different. The proposed system allows identifying the lowest mistake technique to apply in the following sales monthly forecast, which is necessary to properly plan the operations in the companies under study. Based on the sales data of the last three years it is possible to make a yearly sales forecast, but each month, the monthly forecast should be updated with the last month data.

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DOI: https://doi.org/10.5430/ijba.v6n3p39

International Journal of Business Administration
ISSN 1923-4007(Print) ISSN 1923-4015(Online)

 

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