Forecasting Product Sales for Masters Energy Oil and Gas Using Different Forecasting Methods
Ezeliora Chukwuemeka Daniel, Chinwuko Emmanuel Chuka
Abstract
Ezeliora Chukwuemeka Daniel, Chinwuko Emmanuel Chuka
Abstract
Abstract: This research work addresses the problem of forecasting for product sales using different forecasting techniques and models. It focuses on the application of different forecasting methods in the case study company. Product sales of their monthly sales data were gathered in the case study company over the months for three years. The data were collected, modeled and analyzed using different forecasting methods. The models and methods used were three period moving average, weighted moving average and simple exponential smoothing models. These were used to forecast for monthly and quarterly using the historical data collected. From the result analysis, forecasts of three years in the future were developed. This is to their future sales of the products within the next three years in the future. In conclusion, there is always a need to use more than one forecasting methods, to avoid errors during forecasting and to choose a better forecast.
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Abstract: This research work addresses the problem of forecasting for product sales using different forecasting techniques and models. It focuses on the application of different forecasting methods in the case study company. Product sales of their monthly sales data were gathered in the case study company over the months for three years. The data were collected, modeled and analyzed using different forecasting methods. The models and methods used were three period moving average, weighted moving average and simple exponential smoothing models. These were used to forecast for monthly and quarterly using the historical data collected. From the result analysis, forecasts of three years in the future were developed. This is to their future sales of the products within the next three years in the future. In conclusion, there is always a need to use more than one forecasting methods, to avoid errors during forecasting and to choose a better forecast.
Key concepts: Exponential smoothing, Sales forecasting, Product (mathematics), Demand forecasting, Probabilistic forecasting, Consensus forecast, Econometrics, Technology forecasting