APPLICATION OF AUTOREGRESSIVE INTEGRATED MOVING AVERAGE AND HOLT WINTERS METHODS FOR OPTIMUM SALES FORECASTING IN THE MANUFACTURING SECTOR

This study investigated into the application of autoregressive integrated moving average (ARIMA) and Holt winters methods for optimum sales forecasting of Nestle Nigeria plc, Lagos Nigeria. The purpose of this study is to examine sales forecasting model using ARIMA and Holt Winters methods for short-term decision-making. The specific objectives are to: assess the future sales of Nestle Nigeria Plc. using ARIMA forecasting model, evaluate the future sales of Nestle Nigerian Plc. using Holt Winters forecasting model, examine the optimum forecasting model between ARIMA and Holt Winter for Nestle Nigeria Plc, determine the appropriate forecasting model for Nestle Nigeria Plc. short term forecasting. Secondary data were sourced from yearly sales revenue data of Nestle Nigeria Plc., from 1990 to 2017 and analysed with the aid of Minitab software. Holt winters multiplicative model MAPE, MAD and MSD were 2.3, 1.7 and 4.8 respectively, while ARIMA is 1.8, 1., and 5.4 respectively. The result shows that the appropriate model is ARIMA model for Nestle Nig. to predict short term forecasting since, it has the lower value of the performance metrics. The result also revealed that ARIMA method seem more effective and powerful going by the MAPE result. It was recommended that in advance of attempting simple method of prediction, it is helpful in trying more complex ones equally they have the capacity to make available additional and precise outcomes in certain conditions.