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	INSTRUCTIONS & METHODOLOGY
	1. MODEL OVERVIEW
	This Inventory Optimization Model is an enterprise-grade tool designed to optimize inventory
	management decisions using quantitative methods including Economic Order Quantity (EOQ), safety
	stock calculations, ABC analysis, and comprehensive cost modeling.
	The model contains 9 interconnected sheets:
	• Dashboard - Executive summary with KPIs and navigation
	• Assumptions - All configurable model parameters (blue inputs)
	• Inventory Data - Master SKU database with 20 sample items
	• ABC Analysis - Pareto-based classification by annual value
	• EOQ Calculations - Optimal order quantities for each SKU
	• Safety Stock & ROP - Safety stock levels and reorder points
	• Cost Analysis - Complete cost breakdown and efficiency metrics
	• Scenario Analysis - Sensitivity analysis for key parameters
	• Instructions - This guide with methodology documentation
	2. HOW TO USE THIS MODEL
	Step 1: Configure assumptions in the Assumptions sheet (all blue-colored cells are editable)
	Step 2: Enter or replace inventory data in the Inventory Data sheet
	Step 3: Review ABC classification results (auto-sorted by annual usage value)
	Step 4: Review EOQ recommendations for optimal order quantities
	Step 5: Check Safety Stock & ROP for reorder alerts and safety stock levels
	Step 6: Analyze total costs in Cost Analysis sheet
	Step 7: Use Scenario Analysis to evaluate what-if scenarios
	Step 8: Monitor Dashboard for real-time KPIs and stock status alerts
	Color Coding Convention:
	• Blue text = User-editable inputs (hardcoded values)
	• Black text = Calculated formulas (same-sheet references)
	• Green text = Cross-sheet formula references
	3. METHODOLOGY & FORMULAS
	Economic Order Quantity (EOQ):
	EOQ = √(2 × D × S / H)
	Where: D = Annual demand, S = Ordering cost per order, H = Holding cost per unit per year
	Adjusted EOQ = MAX(Ceiling(EOQ), Minimum Order Quantity)
	Safety Stock (combined variability model):
	SS = Z × √(LT × σd² + d² × σLT²)
	Where: Z = Service level Z-score, LT = Lead time, σd = Demand std dev, σLT = Lead time std dev
	Reorder Point (ROP):
	ROP = (Average daily demand × Lead time) + Safety stock
	ABC Classification (Pareto Analysis):
	Class A: Top 80% of cumulative annual usage value (typically 10-20% of SKUs)
	Class B: Next 15% (80-95%) of cumulative value (typically 20-30% of SKUs)
	Class C: Remaining 5% (95-100%) of cumulative value (typically 50-70% of SKUs)
	Total Inventory Cost:
	TIC = Purchase cost + Ordering cost + Holding cost + Safety stock cost + Stockout risk cost
	Ordering cost = (D/EOQ) × S
	Holding cost = (EOQ/2) × H
	4. KEY ASSUMPTIONS & LIMITATIONS
	• EOQ assumes constant, known demand rate and instantaneous replenishment
	• Safety stock model assumes normally distributed demand and lead time variability
	• ABC thresholds (80/95/100) are configurable in the Assumptions sheet
	• Stockout risk cost is an estimated proxy; actual costs depend on customer behavior
	• The model uses sample data for demonstration; replace with actual operational data
	• Scenario analysis uses theoretical scaling relationships (SQRT for EOQ/SS)
	• Lead times are assumed independent across SKUs
	• Quantity discounts and volume pricing are not modeled in this version
	5. DISCLAIMER
	This model is provided with sample data for demonstration and educational purposes.
	All inventory parameters, costs, and SKU data should be replaced with actual operational
	data before use in production decision-making. Results should be validated against
	historical performance and supplemented with domain expertise.