M3 Economic Order Quantity Calculator
Order quantity is one of the first parameters a consultant sets on an M3 item and one of the easiest to get lazily wrong. This calculator gives you the textbook optimum and shows how flat or steep the cost curve is around it.
Your numbers
Buyer time, receiving, admin, or changeover cost per replenishment.
Capital, storage, insurance, obsolescence. Often 15 to 30%.
The lot size you are testing against the optimum.
Your results
Classic EOQ assumes steady demand, no quantity discounts and instant replenishment. Apply minimum, multiple and maximum order quantity constraints separately.
Annual ordering plus holding cost vs order quantity
Sweeps Proposed order quantity from 100 to 4000, holding your other inputs fixed.
Review order quantities at scale
Optional: compare current order quantity settings against calculated optima across your item master.
Optional. The tool and every export work without this. No spam.
How to use it
Enter annual demand, the true cost of placing one order, the unit cost and an annual holding cost rate. Slide the proposed order quantity to compare your current or planned lot size against the optimum. The two cost outputs tell you what you would pay per year in ordering plus holding costs at each quantity, and the chart plots the whole curve so you can see how much room you have before the penalty becomes material.
- Include only costs that change with the number of orders
- Use a holding rate that reflects your cost of capital
- Test two or three realistic lot sizes, not just the EOQ
The formula
EOQ equals the square root of (2 x annual demand x cost per order divided by holding cost per unit per year). At the optimum, annual ordering cost equals annual holding cost, which is a handy sanity check. Total relevant cost is demand divided by quantity times order cost, plus quantity divided by two times holding cost. Purchase price is left out because it does not change with lot size unless a price break applies.
Using the result in M3 planning
Treat the EOQ as a starting point for the fixed or period order quantity you maintain on the item. Then adjust for real constraints: supplier minimums, pack sizes, pallet quantities and shelf life. Because the cost curve is shallow near the optimum, rounding to a practical quantity within about 20% of EOQ usually costs only a few percent more. Large deviations deserve a reason.
- Round to pack or pallet multiples
- Cap the quantity for items with short shelf life
- Revisit when demand or cost per order changes
Common mistakes
Teams often use an inflated order cost that includes fixed overhead, which pushes lot sizes too high. Another is using a holding rate of zero because the stock is not visible on the P&L. For manufactured items, replace order cost with setup cost and include the cost of lost capacity during changeover. Finally, remember that EOQ ignores volume discounts, so compare total landed cost if the supplier offers price breaks.
Frequently Asked Questions
Is EOQ suitable for every M3 item?
No. It suits steady demand items bought in discrete lots. Lumpy, seasonal or project items usually need a lot-for-lot or period-based policy, and items with strong volume discounts need a total cost comparison instead.
What holding cost rate should I use?
Add cost of capital, storage, handling, insurance, shrinkage and obsolescence as a share of unit cost. A range of 15 to 30% is common in manufacturing, but your finance team should confirm the figure for your business.
How sensitive is the result to my inputs?
EOQ scales with the square root, so a 20% error in order cost changes the optimum by under 10%. The cost curve is also flat near the minimum, so small rounding errors have little financial effect.
Does it handle minimum order quantities?
Not directly. If the supplier minimum exceeds EOQ, enter that minimum as the proposed quantity and read the cost penalty. That shows what the constraint costs you per year.
If you would rather have order quantities reviewed across thousands of M3 items using your own demand and cost data, Netray can build that as a read-only analysis.
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