How to Calculate EOQ (Economic Order Quantity)

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The EOQ — Economic Order Quantity — is the order size that minimizes the total annual inventory management cost. It was formulated by Ford Harris in 1913 and remains one of the most widely used models in supply chain, especially as a starting point before applying more sophisticated approaches.

The Two Costs That EOQ Balances

The model starts from the observation that there are two costs that move in opposite directions as order size changes:

The EOQ is the point at which both costs are equal and their sum is at its minimum.

The EOQ Formula

EOQ = √(2 · D · S / H)

Where D is annual demand in units, S is the fixed cost per order (in $ COP/order), and H is the holding cost per unit per year (in $ COP/unit/year). H is typically expressed as a percentage of the unit cost of the product — usually between 20% and 30% — to capture the cost of capital.

How to Interpret the Result

Once the EOQ is calculated, you can derive two key indicators: the number of orders per year (D / EOQ) and the time between orders (365 / (D / EOQ) days). These two values tell you how frequently you should reorder to minimize total cost.

Assumptions of the Classic Model

The classic EOQ assumes conditions that are rarely met 100% in practice. This does not invalidate it, but it does require interpreting results with caution:

Limitations and How to Work Around Them

In practice, demand varies and suppliers offer volume discounts. The EOQ still serves as a useful benchmark: if the optimal order size for a discount differs significantly from the EOQ, the extra holding cost may outweigh the discount savings. Calculating both scenarios enables an informed decision.

Additionally, when demand has high variability (Class Z items in XYZ analysis), the EOQ loses precision because the constant demand assumption breaks down. In those cases it should be complemented with an explicitly calculated safety stock.

EOQ in Real-World Contexts

In any case, the EOQ is a solid starting point. Calculate the theoretical value first, then adjust it based on available discounts, logistical constraints, and actual demand variability.

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