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Implementing multi-stage inventory optimization successfully requires centralization, harmonization and cleansing of data. Success involves developing a robust baseline of the current situation and compare against optimization application results.  However, companies can face challenges capturing such robust baseline. For instance, at times, business data reports capture incomplete inventory data such as total and not by product, limited to units of measures or currency, not available in some locations/nodes of the supply chain, or measured in purchasing costs.

As shown in the supply chain network graph drawn directly from the data, the ABC Supply Chain Network services five customers from three packaging / finished goods warehouses and supplied by one raw material warehouse. .  Reported inventory data at the raw material warehouse only include total monetary value expressed in currency, not by raw material product nor in units.  While, the processing/finished goods warehouses have inventory data by product in different units of measure, but they are missing the monetary value of such.

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In such cases, multi-stage inventory optimization applications like SAP Integrated Business Planning for inventory (http://scn.sap.com/docs/DOC-65688) can help companies capturing incomplete data.  How?

  • SAP integrated Business Planning for inventory offers single-stage inventory optimization that produces target inventory recommendations for selected nodes in the supply chain network.
  • That is, for each individual node of the supply chain with incomplete inventory data, a company can run a single-stage optimization in order to produce the missing data expressed in units, velocity (days of supply) and/or value (currency).
  • With the resulting single-stage optimization data, the company can complete a robust inventory data baseline needed for bench-marking against the results of implementing a multi-stage inventory optimization of its end-to-end supply chain network.
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