The Economic Order Quantity (EOQ) model is a formula that calculates the ideal number of units a business should order at one time to minimize total inventory costs. First introduced by Ford W. Harris in 1913, it remains one of the most widely used tools in inventory management. The core idea is simple: order too frequently and you waste money on repeated ordering costs, but order too much at once and you waste money storing all that inventory.
How the Formula Works
The EOQ formula finds the “sweet spot” order size where the combined cost of ordering and holding inventory is as low as possible. It looks like this:
EOQ = √(2 × D × S ÷ H)
Three inputs drive the calculation. D is your annual demand, meaning the total number of units you expect to sell or use in a year. S is the cost of placing a single order, covering things like administrative labor, shipping fees, and receiving inspections. H is the holding cost per unit per year, which represents everything it costs to keep one unit sitting in your warehouse for twelve months.
You multiply annual demand by the ordering cost, double that number, divide by the holding cost per unit, and take the square root. The result tells you exactly how many units to order each time you place a purchase.
The Two Costs You’re Balancing
The entire model revolves around a tug-of-war between two categories of expense.
Ordering costs go up when you place more frequent, smaller orders. Each order carries a fixed price tag regardless of size: someone has to process the paperwork, a truck has to make a delivery, and staff have to receive and inspect the shipment. If you order 12 times a year instead of 4, you pay those fixed costs three times as often.
Holding costs go up when you place fewer, larger orders because you end up with more inventory sitting on shelves. These costs include warehouse rent, utilities, insurance, labor to manage the stock, depreciation on goods that lose value over time, shrinkage from theft or damage, and the opportunity cost of having money tied up in products instead of invested elsewhere. For many businesses, holding costs run between 20% and 30% of an item’s value per year.
The total annual inventory cost is calculated as:
Total Cost = (Order Quantity ÷ 2) × H + (D ÷ Order Quantity) × S
The first half captures holding costs (based on your average inventory level, which is half your order size). The second half captures ordering costs (based on how many orders you place per year). The EOQ is the order quantity where these two halves are equal, producing the lowest possible total.
A Quick Example
Say you sell 10,000 widgets per year. Each order costs $50 to place, and it costs $2 per year to store one widget. Plugging into the formula: EOQ = √(2 × 10,000 × 50 ÷ 2) = √500,000 = roughly 707 units per order. That means you’d place about 14 orders per year (10,000 ÷ 707), spacing them roughly every 3.7 weeks.
If you ordered 1,000 units at a time instead, your holding costs would jump because you’re storing more inventory on average. If you ordered 200 at a time, you’d place 50 orders a year and spend far more on ordering. The EOQ of 707 minimizes the combined expense.
What the Model Assumes
The EOQ formula works cleanly because it makes several simplifying assumptions. Demand is constant and known, so you sell roughly the same number of units every week. The cost per unit doesn’t change regardless of order size (no bulk discounts). Ordering costs and holding costs stay fixed. Lead time, the gap between placing an order and receiving it, is also constant. And inventory arrives all at once rather than trickling in.
These assumptions rarely hold perfectly in real life. Demand fluctuates with seasons, promotions, and market shifts. Suppliers often offer price breaks for larger orders. Lead times can stretch unexpectedly. Despite this, the model is surprisingly robust in practice. Even when conditions deviate moderately from the assumptions, the EOQ typically produces an order quantity close to optimal because total cost is relatively flat near the minimum. Being off by 10% or 20% from the true ideal order size usually increases total cost by only a few percent.
Connecting EOQ to Reorder Points
The EOQ tells you how much to order, but not when to order. That’s where the reorder point comes in. The reorder point is the inventory level at which you trigger a new purchase so that stock arrives before you run out. It’s calculated as:
Reorder Point = (Average Daily Demand × Lead Time) + Safety Stock
Safety stock is a buffer you keep on hand to absorb unexpected spikes in demand or delays in delivery. Together, EOQ and the reorder point form a complete replenishment system. For example, if you sell 100 units per day, your lead time is 10 days, and you maintain 500 units of safety stock, your reorder point is 1,500 units. Every time inventory drops to 1,500, you place an order for the EOQ amount. The EOQ controls your lot size while the reorder point controls your timing.
EOQ Compared to Just-in-Time
Just-in-Time (JIT) inventory takes the opposite philosophy: instead of calculating an optimal batch size, you order small quantities as close to the moment of need as possible, keeping almost no inventory on hand. Research comparing the two approaches has found that JIT tends to win at lower demand levels, while EOQ gains a cost advantage for high-demand items where the efficiencies of batch ordering really add up.
The comparison also depends on the nature of the product. The higher the item’s value, the more expensive it is to hold in storage, which favors JIT. When ordering costs are high relative to holding costs, or when suppliers don’t offer meaningful quantity discounts, JIT also tends to come out ahead across a wider range of demand levels. Many modern businesses use a hybrid approach, applying JIT principles for expensive or volatile items and EOQ logic for stable, high-volume products.
When the Basic Model Falls Short
The standard EOQ formula doesn’t account for quantity discounts, which are common in real purchasing. If a supplier offers a lower unit price when you buy 1,000 instead of 500, you need a modified version of the model that weighs the savings on unit cost against the higher holding cost of keeping more inventory. This version calculates total cost at each price break and compares them.
Seasonal or unpredictable demand is another gap. Businesses with major demand swings often pair EOQ with forecasting tools or switch to dynamic ordering policies during peak periods. Similarly, when lead times are unreliable, the reorder point needs a larger safety stock buffer, which raises holding costs beyond what the basic formula predicts.
Even with these limitations, the EOQ model gives businesses a disciplined starting point for inventory decisions. It forces you to quantify your actual ordering and holding costs rather than guessing, and it provides a benchmark you can adjust as conditions change.