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Service Parts Management

Service parts management uses sensors and analytics to predict when spare parts will be needed and to deliver required parts as needed. Solutions aim to provide real-time visibility into the install base by collecting and analyzing IoT data directly from connected assets and integrating this real time data with historical usage data. Analytics can be used to model demand cycles, forecast intermittent demand, and optimize multi-echelon inventory. They can also improve downstream demand visibility from a distribution or service network. By connecting to the dealer network or service providers, parts manufacturers can identify sell-through demand down to the daily level. By predicting demand, providers can develop stocking plans based on service level objectives, budget limitations, and forecasts, to optimize stock inventory and customer service levels. These systems usually work together with supply chain management systems to ensure that the service parts supply chain is able to meet forecasted demand.

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