Key Concepts in Inventory Management Strategies

Why This Matters

Inventory management sits at the heart of optimization systems—it's where mathematical modeling meets real-world operational decisions. You're being tested on your ability to apply cost minimization, demand forecasting, and system design principles to solve practical business problems. Every strategy in this guide represents a different approach to the fundamental tension between holding too much inventory (costly) and holding too little (risky).

Don't just memorize what each strategy does—understand when and why you'd choose one approach over another. The exam will ask you to compare systems, calculate optimal quantities, and recommend strategies based on specific business constraints. Know the underlying trade-offs, and you'll be ready for anything from multiple choice to complex FRQ scenarios.

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Order Quantity Optimization

These strategies use mathematical models to determine how much to order, balancing the costs of placing orders against the costs of holding inventory.

Economic Order Quantity (EOQ) Model

• Minimizes total inventory costs by finding the order quantity where ordering costs and holding costs intersect—the classic optimization problem
• Formula assumes steady demand and predictable lead times, making it ideal for stable, continuous-use items
• Trade-off at its core: order frequently (high ordering costs, low holding costs) vs. order in bulk (low ordering costs, high holding costs)

Reorder Point (ROP) Method

• Triggers orders at a specific inventory level calculated as $ROP = d \times L$ where $d$ is demand rate and $L$ is lead time
• Prevents stockouts by ensuring new orders arrive just as existing stock depletes—timing is everything
• Works alongside EOQ to answer both "how much" and "when" questions in inventory planning

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Demand-Driven Systems

These approaches minimize inventory by aligning supply closely with actual consumption, reducing the buffer between production and demand.

Just-in-Time (JIT) Inventory

• Receives goods only when needed for production, eliminating storage costs and reducing waste to near-zero
• Requires bulletproof supplier relationships—one late delivery can halt entire production lines
• High risk, high reward: maximum efficiency when it works, maximum vulnerability when supply chains break

Material Requirements Planning (MRP)

• Uses demand forecasts to schedule material orders backward from production dates—a "pull" system driven by end-product needs
• Coordinates timing and quantity across multiple components, ensuring all parts arrive when needed for assembly
• Reduces excess inventory by ordering only what's required for planned production runs

Lean Inventory Management

• Eliminates waste across all inventory processes—excess stock, unnecessary movement, waiting time, and defects
• Emphasizes continuous improvement (kaizen) and value stream mapping to identify inefficiencies
• Broader philosophy than JIT: encompasses supplier collaboration, quality control, and process optimization

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Review and Monitoring Systems

These strategies differ in how frequently inventory is checked and what triggers a reorder decision.

Continuous Review System

• Monitors inventory in real-time and places orders immediately when stock hits the reorder point
• Best for high-value or critical items where stockouts carry significant costs—think hospital supplies or manufacturing components
• Higher monitoring costs but faster response to demand spikes or supply disruptions

Periodic Review System

• Reviews inventory at fixed intervals (weekly, monthly) and orders enough to reach a target level
• Simpler to administer—no constant monitoring required, just scheduled check-ins
• Requires larger safety stock since demand variability between reviews must be covered

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Risk Mitigation Strategies

These approaches build buffers into the system to protect against uncertainty in demand or supply.

Safety Stock Management

• Extra inventory held as insurance against demand spikes, supplier delays, or forecast errors
• Calculated using variability measures: $SS = z \times \sigma_d \times \sqrt{L}$ where $z$ is service level, $\sigma_d$ is demand standard deviation, and $L$ is lead time
• Trade-off between service level and cost—higher safety stock means fewer stockouts but more capital tied up

ABC Inventory Classification

• Categorizes items by value and volume: Class A (high-value, low-quantity), Class B (moderate), Class C (low-value, high-quantity)
• Follows the Pareto principle—typically 20% of items (Class A) represent 80% of inventory value
• Prioritizes management attention so you're not treating a $10,000 component the same as a$0.50 bolt

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Collaborative Approaches

These strategies shift inventory management responsibilities across supply chain partners to optimize the entire system, not just one company.

Vendor Managed Inventory (VMI)

• Suppliers monitor and replenish customer inventory directly, using shared data to make stocking decisions
• Reduces customer burden of forecasting and ordering while giving suppliers better demand visibility
• Requires trust and data sharing—success depends on aligned incentives and transparent communication

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Quick Reference Table

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Self-Check Questions

1. Both EOQ and safety stock calculations require input about demand—how do they use this information differently, and what distinct problems do they solve?

2. A company switches from periodic review to continuous review for a critical component. What trade-offs should they expect in terms of costs, stockout risk, and administrative burden?

3. Compare JIT and MRP: both aim to reduce excess inventory, but under what business conditions would you recommend one over the other?

4. If an FRQ describes a company with 5,000 SKUs and limited management capacity, which strategy would you recommend for prioritizing their inventory efforts, and why?

5. Explain how VMI changes the traditional buyer-supplier relationship. What must both parties contribute for this collaborative approach to succeed?