MOQ Risk Calculator

Your supplier quotes a minimum order quantity. This tells you how much of it you have to sell before it stops losing money, how likely that is, and what the order is worth in expectation.

Built for buyers who commit to finished goods long before demand is known: technical and industrial distributors, importers and brand distributors of consumer durables, and private-label ecommerce sellers. One order, a supplier minimum, and a lead time you cannot shorten.

Your numbers

How much of the cost you would recover. 0 if it has no recovery value
Not the whole life of the item: the weeks this order has to last, which is your supplier lead time plus the time until your next order. Eight weeks at 20 a week is 160.
The low to high spread around your expected demand: 8 outcomes in 10 land between 274 and 1,354 units. Demand is skewed upward, so the top half of the band is longer than the bottom half.

Results update as you type. Nothing is sent anywhere, the calculation runs in this browser tab.

What the MOQ forces

Supplier MOQ1,000 unitsthe smallest order they will accept
Economically recommended559 unitswhat these economics would buy with no minimum in the way, at the 46% point of the demand spread
Excess forced by the MOQ441 unitsunits you are buying because the supplier will not sell fewer, not because they earn their place
Cash tied up€88,0001,000 units at €88, of which €38,808 is in the units you would not otherwise have ordered
Expected loss on leftovers€17,976371 units left over on average, losing €48 each after recovery. Carrying cost is not in this figure

The order in detail

€7,796
Expected earnings at the MOQ
margin earned minus value destroyed
629
Expected units sold
low case 274, high case 1,354
371
Expected leftover
worth €14,708 on recovery
21%
Stock-out risk
missing about 103 sales, before any damage to the customer relationship

Assumptions used

Everything the answer above rests on. Print this page and the numbers and the assumptions go to your supplier together, a break-even you can point at is a different conversation from an opinion about volume.

Margin per unit sold€41€129 price − €88 cost
Loss per unit left over€48cost minus €40 you expect to recover
Break-even sell-through54%loss per leftover ÷ (margin + loss), independent of how demand turns out
Chance of reaching it56%share of 4,000 simulated demand outcomes at or above 542 units
Demand assumed600 units expectedwith a ±88% spread: 10% of outcomes below 274, 10% above 1,354 units
Leftover value45% of costwhat you expect to recover on stock you cannot sell
Not includedcarrying cost, relationship damageholding excess stock costs a distributor roughly a quarter of its value per year, and a stock-out on a new item costs more than the missed margin. Both make this estimate optimistic in opposite directions

What a minimum order quantity actually asks of you

A MOQ is usually presented as a price condition: order a thousand and the unit price drops. What it really is, is a transfer of risk. The supplier produces in an efficient batch and you carry whatever the market does not take. The relevant question is therefore not "is the unit price good?" but "what share of this batch do I have to sell before the order stops destroying value, and how likely am I to get there?".

That break-even share is fixed by the economics alone, not by the forecast. One unit sold earns the gross margin; one unit left over destroys the cost minus whatever you recover on it. Break-even sits where those cancel out, the loss per leftover unit divided by the sum of both. With a healthy margin and stock that still has recovery value, half the batch may be enough. With a thin margin on a product that is written off unsold, you can need eighty percent sell-through before the order makes sense, which is a very different conversation to have with your supplier.

Where these numbers come from

  • Sector patterns are built-in assumptions, a launch curve shape and, where the sector has one, a seasonal pattern. Each one names the research it rests on, or says plainly that it is our judgment, on where the curves come from. How wide the range is comes from your own answer about how new the product is, not from the sector. They are not pooled customer data, and nobody else's numbers are mixed into your result.
  • The economics are your inputs, applied openly, every calculation on this page is shown with its formula. There is no model that "knows better" than the numbers you entered.
  • Nothing is uploaded. The calculation runs in this browser tab. If you supply your own launch history, it is parsed here and stored on this device only; there is no server to send it to, and no account to create.
Don't have a demand estimate?

SKUZero simulates one from launches like yours. Your own past launches if you upload them, or typical sector patterns if you have none. Same engine, same economics, applied to a real first-buy decision.

Open SKUZero →

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