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

Focus forecasting in supply chain: The case study of fast moving consumer goods company in Serbia