Initial Order Quantity Calculator

How many units should you order for a product with no sales history? Enter what you know — sector, price, cost, lead time, MOQ and a rough demand estimate — and get a first-buy quantity with the stock-out and overstock economics made explicit.

Built for buyers, category managers and demand planners at mid-size distributors and manufacturers — HVAC and seasonal equipment, sanitary and building materials, technical distribution (valves, fittings, components), electrical components and professional equipment. It is aimed at the new-item stocking decision: one order, no sales history, a supplier MOQ and a lead time you cannot shorten.

Your new product

Seasonality is applied from this month onwards
Comma or dot decimals both work
How long until you would reorder
Optional buffer on the coverage horizon
Pallet or carton size, 1 if any quantity goes
What you would get dumping leftovers to a liquidator — typically 10–40%. Editable: returns at 80% exist.
What this sector setting does

Launches like this one land between 51% and 197% of your weekly estimate over the first 26 weeks — that is the range the simulation will explore, not a hidden adjustment. Mild seasonality: a summer dip and a year-end push. An August launch starts about -20% against the yearly average in this sector.

The method you already use, with the risks attached

Most stocking decisions for a new item are made the same way, and it is a sensible way: pull up two or three comparable products, look at what they did, ask a couple of sales reps what they expect, add ten to fifteen percent for launch effect, round up to the supplier's carton size. That reasoning is sound — comparable products really are the best evidence available for an item with no history. What it leaves out is the spread. A single number carries no information about how wrong it could be, and the whole first-buy problem lives in that spread.

This calculator does the same comparison, keeps the spread, and attaches the economics. It simulates a thousand plausible demand paths for your sector, totals each one over the period the first order actually has to cover — lead time plus review time, not an arbitrary six months — and finds the quantity where the cost of being short and the cost of being long balance out. Being short costs the margin you did not earn plus, in distribution, a contractor who found the item somewhere else; being long costs carrying charges of roughly a quarter of the value per year and a liquidation price well below cost. Those two are rarely equal, and the cheaper mistake is the one worth making more often.

Where these numbers come from

  • Sector patterns are built-in assumptions — a launch curve shape and an uncertainty range per sector, written by us and visible on the page. 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?

FirstBuy AI 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 FirstBuy AI →

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