Key Inventory Management Models

Why This Matters

Inventory management sits at the heart of industrial engineering because it directly impacts two things companies obsess over: cost efficiency and customer satisfaction. You're being tested on your ability to select the right model for a given scenario, calculate optimal quantities, and understand the trade-offs between holding costs, ordering costs, stockout risks, and demand variability. These models aren't just theoretical—they determine whether a company ties up millions in unnecessary stock or runs out of critical components mid-production.

The key insight connecting all these models is the fundamental inventory trade-off: order too much and you waste money on storage and capital; order too little and you risk stockouts, lost sales, and production delays. Different models attack this trade-off from different angles—some assume stable demand, others embrace uncertainty, and others shift responsibility entirely. Don't just memorize formulas—know when each model applies and why it outperforms alternatives in specific contexts.

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Cost-Optimization Models

These models focus on finding the mathematical sweet spot that minimizes total inventory costs. The core principle is balancing the fixed costs of placing orders against the variable costs of holding inventory over time.

Economic Order Quantity (EOQ) Model

• Minimizes total inventory cost by calculating the order quantity where ordering costs equal holding costs—the classic square root formula: $Q^* = \sqrt{\frac{2DS}{H}}$
• Assumes deterministic conditions—constant demand rate, fixed lead time, no quantity discounts—making it ideal for stable, predictable environments
• Foundation for more complex models—understanding EOQ logic helps you grasp why other models modify its assumptions for real-world variability

Lot-Sizing Techniques

• Extends EOQ logic to handle dynamic demand patterns where order quantities may vary period to period
• Silver-Meal heuristic minimizes average cost per period, while Lot-for-Lot orders exactly what's needed—each technique trades off simplicity against optimality
• Critical for MRP systems where demand is lumpy and driven by production schedules rather than continuous consumption

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Reorder Trigger Systems

These models answer the question: when should you place an order? They differ in whether you monitor inventory continuously or check it periodically.

Continuous Review (Q,R) Model

• Triggers orders at a fixed reorder point (R) while ordering a fixed quantity (Q)—inventory is monitored in real-time or near-real-time
• Ideal for high-value or critical items where stockouts carry severe consequences and the cost of continuous monitoring is justified
• Requires calculating R based on demand during lead time plus safety stock: $R = \bar{d}L + SS$

Periodic Review (s,S) Model

• Reviews inventory at fixed intervals and orders enough to reach target level S—order quantities vary based on current stock position
• Reduces monitoring costs by consolidating review activities, making it practical for low-value items or when continuous tracking isn't feasible
• Requires higher safety stock than continuous review because stockouts can occur between review periods—the review interval adds uncertainty

Reorder Point Determination

• Calculates the trigger level that ensures new inventory arrives before existing stock depletes—fundamentally: $ROP = d \times L$ for deterministic cases
• Must account for lead time demand variability in stochastic environments by adding safety stock buffers
• Links directly to service level targets—higher desired service levels push reorder points higher, increasing average inventory

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Uncertainty Management Models

Real supply chains face demand variability and supply disruptions. These models explicitly account for uncertainty rather than assuming it away.

Safety Stock Calculation

• Buffers against uncertainty in both demand and lead time—calculated using: $SS = z \times \sigma_{DL}$ where z reflects your target service level
• Balances stockout risk against holding cost—higher safety stock means better service but more capital tied up in inventory
• Requires accurate variability estimates—garbage data on demand standard deviation produces meaningless safety stock recommendations

Just-In-Time (JIT) Inventory

• Eliminates safety stock philosophy by attacking variability at its source—reduce setup times, improve quality, stabilize demand
• Minimizes holding costs and waste by receiving materials only when needed for immediate production
• Demands operational excellence—strong supplier relationships, reliable logistics, and robust demand forecasting are prerequisites, not nice-to-haves

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Strategic Classification and Planning

These approaches help managers decide where to focus attention and how to coordinate inventory decisions across the supply chain.

ABC Inventory Classification

• Prioritizes management effort using the Pareto principle—typically 20% of items (A-class) represent 80% of inventory value
• A-items get tight control (continuous review, frequent counts), C-items get simple rules (periodic review, larger order quantities)
• Drives policy differentiation—applying the same model to all items wastes resources on low-value stock and under-manages critical items

Material Requirements Planning (MRP)

• Calculates time-phased requirements by exploding the master production schedule through the bill of materials
• Converts independent demand (finished goods) into dependent demand (components and raw materials)—demand is derived, not forecasted
• Integrates with capacity planning and shop floor control to synchronize material availability with production schedules

Vendor Managed Inventory (VMI)

• Shifts replenishment responsibility to suppliers who monitor customer inventory and decide when to ship
• Leverages supplier expertise in demand patterns while reducing customer's planning burden and stockout risk
• Requires information sharing and trust—suppliers need real-time visibility into customer inventory and sales data

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Quick Reference Table

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Self-Check Questions

1. A company has stable, predictable demand and wants to minimize total inventory cost. Which model should they use, and what key assumption makes it appropriate?

2. Compare the (Q,R) continuous review model with the (s,S) periodic review model. Under what circumstances would you recommend each?

3. If an FRQ describes a manufacturing environment with a master production schedule and bills of materials, why would EOQ be inappropriate for managing component inventory?

4. How does ABC classification change the way you apply other inventory models? Give an example of different policies for A-items versus C-items.

5. A company is debating between building up safety stock and implementing JIT. What operational prerequisites must exist for JIT to succeed, and what happens if those conditions aren't met?