Focus forecasting in supply chain: The Case study of fast moving consumer goods company in Serbia
Abstract
This paper presents an application of focus forecasting in a fast moving consumer goods (FMCG) supply chain. Focus forecasting is tested in a real business case in a Serbian enterprise. The data used in the simulation refers to the historical sales of two types of FMCG with several different products. The data were collected and summarized across the whole distribution channel in the Serbian market from January 2012 to December 2013. We applied several well-known time series forecasting models using the focus forecasting approach, where for the future time period we used the method which had the best performances in the past. The focus forecasting approach mixes different standard forecasting methods on the data sets in order to find the one that was the most accurate during the past period. The accuracy of forecasting methods is defined through different measures of errors. In this paper we implemented the following forecasting models in Microsoft Excel: last period, all average, moving average, exponential smoothing with constant and variable parameter α, exponential smoothing with trend, exponential smoothing with trend and seasonality. The main purpose was not to evaluate different forecasting methods but to show a practical application of the focus forecasting approach in a real business case.
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