Inventory Cost Optimization & Aging Analysis

<p><strong>Inventory Cost Optimization &amp; Aging Analysis</strong></p><p>This workflow evaluates and optimizes inventory costs across two dimensions: <strong>EOQ</strong> — comparing current order policies against the economic optimum to identify cost savings and reduce excess stock, and <strong>FIFO</strong> — analysing batch-level movements to detect slow-moving inventory and estimate holding cost exposure. It then presents results in an interactive dashboard.</p><p></p><p><strong>Understanding the Formulas</strong></p><ul><li><p><strong>Economic Order Quantity (EOQ)</strong></p></li></ul><p>EOQ= sqrt((2 <em>$["Annual_Demand"] </em>$["Ordering_Cost"]) / $["Holding_Cost_Per_Unit_Per_Year"]))</p><p></p><p>This formula calculates the optimal replenishment quantity that minimizes the combined ordering and holding costs.</p><p></p><ul><li><p><strong>Current Holding Cost</strong></p></li></ul><p>Current&nbsp;Holding&nbsp;Cost=(($Current_Order_Policy_Qty / 2) + $["Safety_stock"]) * $Holding_Cost_Per_Unit_Per_Year</p><p></p><p>Holding cost estimates the annual cost of storing inventory.</p><p>The formula uses average cycle stock (Current_Order_Policy_Qty / 2) plus safety stock because inventory levels fluctuate throughout the replenishment cycle.</p><p></p><ul><li><p><strong>Reorder Point (ROP)</strong></p></li></ul><p>ROP=Average&nbsp;Daily&nbsp;Demand×Lead&nbsp;Time+Safety&nbsp;Stock</p><p>Defines the inventory threshold that triggers a replenishment order to avoid stockouts during lead time.</p>