FORECASTING OF SALES AND PRODUCTION IN CHEMICAL INDUSTRY USING SPSS WITH TIME SERIES MODELER: A CASE STUDY

Any forecast can be termed as a calculation or estimation which uses historical data and combined with the recent trends to know what will probablyhappen in future event. This is known by everyone that it is impossible to forecast with accuracy of 100% but sound planning of any product dependson forecasting and extrapolation that how trends, such as GDP or unemployment also changes in the coming quarter or year using forecasting bystock analysts. Hence it is necessary to have an estimate of product demand. Forecast of sales and production with the help of previous data maypredict the future demand. In the present work, the sales, production and consumption of raw materials for making caustic soda lye are analyzedand predicted using SPSS with time series modeler. The actual and modeled data are compared and found close agreement with minimum errors.The performance index was considered for evaluation of parameters are R squared value and RMS value.