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What is Naive Approach to Demand Forecasting about?
This document presents different forecasting methods to predict demand for 3 product items using historical sales data. The methods analyzed include naive, simple average, moving average, Holt-Winters exponential smoothing, multiple regression, and ARIMA. Accuracy is measured using MAD, RMSE, and MAPE. Multiple regression and ARIMA models are selected as most accurate based on the error measurements. Forecasts for 2018 demand are generated using the best performing ARIMA models.
- Author
- Blessed Mutengwa
- Language
- EN