What it means
The trade-off behind EOQ is straightforward. Ordering cost, the fixed cost of processing, shipping and receiving each order, falls on a per-unit basis as order size rises, because fewer orders are needed to cover the same annual demand.
Holding cost, storage, insurance, spoilage and the cost of capital tied up in stock, rises with order size, because larger orders mean more average inventory sitting in the warehouse at any given time. EOQ finds the order quantity at which these two opposing forces are balanced and the combined cost is at its minimum.
The model uses three inputs: annual demand, the fixed cost of placing a single order, and the holding cost per unit per year, often expressed as a percentage of the unit's cost to capture the combined effect of storage, insurance, obsolescence risk and the return the capital tied up in stock could otherwise have earned. Average inventory over the order cycle is assumed to be half the order quantity, since stock is assumed to deplete steadily from a full order down to zero before the next order arrives.
The formula itself comes from minimising total relevant cost, the sum of annual ordering cost and annual holding cost, with respect to order quantity. At the mathematical minimum, annual ordering cost and annual holding cost are exactly equal, a property that offers a useful sanity check when applying the formula: if the two costs are not roughly equal at a proposed order quantity, that quantity is not the EOQ.
The basic model rests on simplifying assumptions: constant, known demand, no quantity discounts, and negligible lead time between placing an order and receiving it. Real supply chains extend the model to handle quantity discounts and planned backorders, and pair EOQ with a separate reorder point calculation, based on demand during the supplier's lead time plus a safety stock buffer, to decide when to place each order.
EOQ answers how much to order; the reorder point answers when. Despite its age and simplifying assumptions, EOQ remains a useful first-pass benchmark and is embedded as a default calculation in many inventory management and ERP systems, particularly for stable, high-volume items, often labelled "A" items under ABC inventory classification.
More volatile or intermittent-demand items are usually managed with different, more adaptive methods that do not assume constant demand.
In practice
Real-world examples.
Example
A hardware store using EOQ for a steady-selling bolt SKU orders about 894 units roughly every 16 days rather than guessing at round numbers like 500 or 1,000, cutting its combined ordering and holding costs by more than $1,200 a year compared with its previous ad hoc 2,000-unit order size.
Example
A manufacturer negotiating a supplier discount for orders above 1,500 units uses an EOQ-with-quantity-discounts model to check whether the price break is worth the extra holding cost of carrying more inventory than the base EOQ would suggest.
Example
A distributor applies EOQ only to its high-volume, stable-demand "A" items under ABC classification, while managing its many low-volume, sporadic-demand items with a simpler minimum order quantity set by the supplier instead.
Think of it
“EOQ is the sweet spot order size-big enough to avoid constant orders, small enough to avoid excess stock.
Formula
Calculation
EOQ = square root of ( (2 x Annual Demand x Ordering Cost per Order) / Holding Cost per Unit per Year )
Total annual ordering cost = (Annual Demand / Order Quantity) x Ordering Cost per Order
Total annual holding cost = (Order Quantity / 2) x Holding Cost per Unit per Year
Number of orders per year = Annual Demand / EOQ
Worked example. A retailer sells 20,000 units of a product a year. Each order costs $80 to place. Holding cost is $4 per unit per year.
EOQ = square root of ( (2 x 20,000 x 80) / 4 ) = square root of 800,000, approximately 894 units
Number of orders per year = 20,000 / 894, approximately 22.4, roughly every 16 days
Ordering cost at EOQ = 22.4 x 80, approximately $1,789
Holding cost at EOQ = (894 / 2) x 4, approximately $1,789, confirming that ordering cost and holding cost are equal at the EOQ, as the formula predicts
Comparison. Ordering 2,000 units at a time, 10 orders a year: ordering cost = 10 x 80 = $800; holding cost = (2,000 / 2) x 4 = $4,000; total = $4,800, about $1,222 more than the EOQ-based total. Ordering 200 units at a time, 100 orders a year: ordering cost = 100 x 80 = $8,000; holding cost = (200 / 2) x 4 = $400; total = $8,400, considerably more expensive still. Both alternatives cost more than the roughly $3,578 total at the calculated EOQ.Case study
Seen in the real world.
A regional auto parts distributor ordered its best-selling brake pad SKU in round batches of 5,000 units whenever stock ran low, a habit inherited from a previous manager with no real analysis behind it. Annual demand for the part was a stable 24,000 units, each order cost $120 to place and process, and holding cost was estimated at $3 per unit per year, reflecting warehouse space, insurance and the cost of capital tied up in the part.
Under the existing policy, roughly five orders a year of 5,000 units each meant average inventory of 2,500 units: ordering cost of (24,000 / 5,000) x 120, or $576, and holding cost of 2,500 x 3, or $7,500, a total of about $8,076 a year.
The operations analyst calculated EOQ = square root of ( (2 x 24,000 x 120) / 3 ), approximately 1,386 units. At that order size, the distributor would place 24,000 / 1,386, about 17.3 orders a year, with ordering cost of 17.3 x 120, approximately $2,078, and holding cost of (1,386 / 2) x 3, approximately $2,078, a total of roughly $4,157 a year, nearly half the cost of the existing policy, with ordering and holding costs almost exactly balanced as the formula predicts.
The distributor adopted the EOQ-based order size, saving about $3,900 a year on this one SKU alone, and rolled the same analysis out across its twenty highest-volume parts, together worth an estimated $58,000 a year in combined ordering and holding cost savings. The one complication the analyst flagged was that the new, smaller and more frequent orders required tighter coordination with the supplier's minimum order requirements and freight consolidation, which the distributor addressed by grouping EOQ-sized orders for several parts from the same supplier into a single weekly shipment.
Watch out
Common mistakes.
- Choosing order quantities by habit or round numbers rather than calculating the balance between ordering and holding costs, which can leave meaningful savings unclaimed.
- Applying the basic EOQ formula to items with volatile or seasonal demand, where the model's assumption of constant, known demand does not hold and a more adaptive approach is needed.
- Ignoring available quantity discounts when calculating an order size, since a supplier's price break can sometimes justify ordering more than the base EOQ despite the extra holding cost, but only after that trade-off has actually been calculated.
Questions
People also ask.
Does EOQ tell you when to reorder?
No. EOQ answers how much to order each time; a separate reorder point calculation, based on average demand during the supplier's lead time plus a safety stock buffer, answers when to place that order.
What happens if the actual order size is bigger or smaller than the EOQ?
Total combined ordering and holding cost rises on either side of the EOQ, though the cost curve near the optimum is relatively flat, so an order size reasonably close to the calculated EOQ, rather than the exact figure, still captures most of the available saving.
Is EOQ still relevant with modern inventory software?
Yes, in principle, though the assumptions behind the basic formula, constant demand, no discounts, negligible lead time, are simplifications. Modern systems often use EOQ as a starting point and layer in adjustments for demand variability, discounts and service level targets.
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