ANALYSIS OF THE EFFECTIVENESS OF SELECTED DEMAND FORECASTING MODELS
ANALYSIS OF THE EFFECTIVENESS OF SELECTED DEMAND FORECASTING MODELS

Summary/Abstract: Objective– Two methods of prediction were proposed in the article, using sales data. Models were identified and estimated, forecasts were determined, their reliability was verified, and then values obtained for each method were compared. Methodology – The article presents models belonging to two different categories. They are regression function, which is a classic example of cause-and-effect model, and ARIMA model for time-series analysis. Results– The results obtained for both models were satisfactorily described by empirical data, but the regression model is much easier to estimate and does not require complex transformations or calculations, nor the use of specialized software. In the analyzed case, demand forecasting based on the linear regression model is sufficient and reflects the nature of the studied phenomenon.

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