Economic order quantity (EOQ)
Economic order quantity is the optimal order size that minimizes total inventory costs by balancing the cost of placing orders against the cost of carrying inventory. EOQ helps determine how much to buy at once for recurring purchases, finding the quantity where total annual ordering and holding costs are lowest.
Examples
EOQ calculation: A company uses 10,000 units annually of a component costing $50 each. Ordering costs are $100 per order, and annual holding cost is 20% of unit value ($10 per unit). EOQ = √(2 × 10,000 × $100 / $10) = 447 units. Ordering approximately 450 units at a time minimizes total costs.
EOQ vs price breaks: EOQ analysis suggests ordering 500 units at a time, but a price break at 1,000 units offers 10% discount. Comparing total costs (purchase + ordering + holding) for each quantity determines whether the price break justifies the larger inventory investment.
EOQ limitations: A component's EOQ calculation suggests 200 units, but the supplier's MOQ is 500 units. EOQ provides a target, but practical constraints may override the theoretical optimum.
Definition
The classic EOQ formula is: EOQ = √(2DS/H), where D is annual demand, S is order cost, and H is annual holding cost per unit. This formula assumes constant demand, fixed costs, and instantaneous replenishment, which rarely hold perfectly in practice.
EOQ provides a starting point for order quantity decisions rather than a definitive answer. Real-world factors including MOQs, price breaks, shelf life, storage constraints, and demand variability all influence actual order quantities.
Holding cost components include capital cost (the cost of money tied up in inventory), storage cost, insurance, obsolescence risk, and handling. Different organizations calculate holding cost differently, affecting EOQ results.
Order cost includes procurement processing time, receiving and inspection, accounts payable processing, and any supplier surcharges for small orders. Understanding order cost components helps identify opportunities to reduce them and thus reduce optimal order sizes.
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