Retail Inventory Optimization Cloud Service 22.2.302.0

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A retailer’s most significant investment is their inventory. Understanding the inventory necessary to achieve a target service level is critical to achieving business goals, and doing so with the least investment reduces need for markdowns. The trade-off curve in Inventory Optimization (IO) helps you to understand the trade-off between service levels and the cost of inventory associated. IO will recommend an initial service level. With your target service level defined IO will optimize target stock levels which translate into item-location replenishment policies. The replenishment policies are used to complete a full replenishment simulation giving you visibility of the resulting purchase and placement of inventory in a time-phased plan. This visibility helps you validate your policies and understand the purchasing impact of a small change in service level which can translate to a significant change in inventory investment. The truck scaling process makes purchase orders actionable by recommending scaled order quantities that maximize truck utilization while taking into account business rules. Finally, IO drives successful outcomes in end-of-life by recommending rebalancing transfers between stores to increase sell-through in order to avoid markdowns. Rebalancing can be disabled for lower-margin categories where transferring goods is most often cost-prohibitive.

Note: This update is based on the 22.2.302.1 version.

Note: Supplemental documentation, including Hot Fix Release Notes, is available on My Oracle Support (DocID:2539848.1)

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