The Implementation of Forecasting Method by Incorporating Human Judgment
Business Forecasting (demand forecasting) is an extrapolation process to predict the events that will be happening in the future. Commonly, forecasting methods are divided by two approximations of procedure; those are quantitative and qualitative methods. In a production system, it is important to predict the demand for the next period. This prediction is done by doing the demand forecasting task. This task is the basis of production planning and control in a production system. The case organization in this research deals with a huge number of products. The manager has to do the replenishment order of the product in every period. Usually, the managers do the forecast based on the demand of the last period. This task indeed not an easy task and sometimes the manager determines the ordering size based on she/he intuition and experience (human judgment). This procedure resulted in a high value of forecasting error that gives some impacts to inventory (occurring overstock and stock out). An appropriate forecasting method is needed to avoid the error value when the forecaster decides the size of demand for the next period. This study aims to investigate an appropriate forecasting method for the business retailer by incorporating human judgment. By using 28 period of time series data from a retailer in Surian, Solok Selatan, West Sumatra, quantitative forecasting methods (Mean, Moving Average, Single Exponential Smoothing (α = 0.1)), qualitative forecasting method (pure judgment), and the combination of quantitative and qualitative forecasting methods are used for the purpose of data analyses. The finding of the research shows that the quantitative forecasting method has a clear procedure to do forecasting tasks and suitable for the products that have time-series data. Furthermore, qualitative forecasting method such as human judgment is needed for a particular situation (for example for the new products, promotion event, etc.) and when managers have some contextual information regarding the products under concern.
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