Resumen

ACKERMANN, Andres E. F.  y  SELLITTO, Miguel A.. DEMAND FORECASTING METHODS: A LITERATURE REVIEW. Innovar [online]. 2022, vol.32, n.85, pp.83-99.  Epub 27-Jul-2022. ISSN 0121-5051.  https://doi.org/10.15446/innovar.v32n85.100979.

Demand forecasting is a business management methodology for estimating the future value of customer demand. Making this type of forecast means recognizing behavior patterns in historical series and predicting future behaviors, or even identifying and extrapolating causal factors that affect market behavior. Hence, this article aims to review the literature on demand forecasting methods in order to gather the methods and models currently used in business administration related to the consumption and production of goods and services. A qualitative literature review was implemented with the purpose of providing a general descriptive view of the dominant methods used in demand forecasting. A mapping of the available literature was conducted to build the state of the art on the topic through the scientific production included in Scopus and Google Scholar databases. Results show that qualitative and causal methods are better associated with medium and long-term forecasts. In addition, the analysis of time series and the methods of the diverse types of averages and exponential smoothing are mentioned as the most suitable for short-term forecasts. A resource that is commonly deployed is the construction of specific demand forecast models, using techniques, aspects, concepts and characteristics from different methods and models. However, it is important to monitor the adopted model, keep field and forecast data under control, and, in case of deviations, correct the model.

Palabras clave : Demand forecasting methods; forecasting; demand forecasting; literature review.

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