<![CDATA[Currently, spare parts inventory management continues to draw attention from practitioners and academics alike, as the unavailability of spare parts can lead to significant financial losses. Forecasting or demand forecasting is a crucial factor in spare parts management. Through forecasting, future demand can be determined, enabling the establishment of the appropriate inventory levels. This article discusses a literature review focused on demand forecasting for spare parts. The article was obtained using the PRISMA method. Eleven scholarly articles obtained were examined using the empathize and define stages of design thinking. The review yielded two problem statements: high inventory costs due to excessive spare parts inventory (overstock) and low service levels, as well as high opportunity costs resulting from insufficient spare parts inventory (stockout). The trend in demand forecasting methods used for spare parts over the last five years includes parametric, non-parametric, contextual, and combined forecasting approaches. Contextual methods, including installed-based forecasting, have been widely used in the past five years. Due to its potential to improve spare parts demand forecasting, contextual forecasting methods have gained increased attention from researchers.]]>
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