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Inventory Cost Optimization & Aging Analysis

Supply ChainInventory ManagementWarehousingCost optimizationAging analysis
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Versionv1.0Latest, created on 
May 8, 2026 12:26 PM
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Inventory Cost Optimization & Aging Analysis

This workflow evaluates and optimizes inventory costs across two dimensions: EOQ — comparing current order policies against the economic optimum to identify cost savings and reduce excess stock, and FIFO — analysing batch-level movements to detect slow-moving inventory and estimate holding cost exposure. It then presents results in an interactive dashboard.

Understanding the Formulas

  • Economic Order Quantity (EOQ)

EOQ= sqrt((2 $["Annual_Demand"] $["Ordering_Cost"]) / $["Holding_Cost_Per_Unit_Per_Year"]))

This formula calculates the optimal replenishment quantity that minimizes the combined ordering and holding costs.

  • Current Holding Cost

Current Holding Cost=(($Current_Order_Policy_Qty / 2) + $["Safety_stock"]) * $Holding_Cost_Per_Unit_Per_Year

Holding cost estimates the annual cost of storing inventory.

The formula uses average cycle stock (Current_Order_Policy_Qty / 2) plus safety stock because inventory levels fluctuate throughout the replenishment cycle.

  • Reorder Point (ROP)

ROP=Average Daily Demand×Lead Time+Safety Stock

Defines the inventory threshold that triggers a replenishment order to avoid stockouts during lead time.

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Created with KNIME Analytics Platform version 5.11.0
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