A Comparative Study of Demand Forecasting for Aftermarket Parts in Heavy Equipment Industry (PT XYZ Case Study)

The global economic crisis has reached the world today, forcing many customers to become more cost aware in their search for better quality and service, corporate organizations discover effective efficient ways compete among them. main objective of this research is choose best forecasting method predict demandfor spare parts at PT. XYZ highly fluctuating, avoid or minimize stockouts. demand high-priced partsand capital goods considered discontinuous if it random contributes a large part inventory value. Fluctuating will be difficult predict, inaccurate estimates can cause huge losses company due obsolescence unfulfilled parts. Running successful operation today requires organizational strength supply needs its customers. This study discusses appropriate fluctuation products an Indonesian companynamed XYZ. compares four methods ABCAnalysis, Moving Average, Simple Exponential Smoothing (SES) (ES) with TrendAdjustment. uses data 2017-2020 forecast 2021 optimum alpha value of0.4065 SES which obtained by calculating using MS Excel Solver 0.5 beta 0.3 ES Trend Adjustment. performance determined based on smallest mean absolute percentage error level accuracy (tracking signal) close zero, results indicate that use trend adjustment compared other three methods.