True landed cost per unit.

Contract manufacturing cost is more than the factory quote. Landed cost includes per-unit manufacturing, amortized tooling, ocean/air shipping, and import duties. Most product founders focus only on unit cost and get surprised when landed cost runs 30-60% higher than the factory quote due to shipping and duties.

5,000 units at 8/unit manufacturing + 2/unit tooling amortization + 1.50/unit shipping = 11.50/unit before duty. Import duty typically 3-12% depending on product category, applied to manufacturing + shipping value. At 8% duty: 0.76/unit extra. Total landed cost 12.26/unit. Most factory quotes show only 8/unit - the 4+ gap is where founders go wrong on margin math.

Tooling amortization matters for small runs. 20,000 tooling for 5,000 first order = 4/unit. Second order of 5,000 uses same tooling = 0/unit more. So first order true cost much higher; subsequent orders drop significantly. Factor this when pricing first-run vs re-order to avoid either overpricing first run or underpricing re-orders.

Run it with sensible defaults

Using units per order of 5,000, per-unit manufacturing cost of 8, tooling per unit of 2, shipping per unit of 1.5, the calculation works out to 12.14. Nudge the inputs toward your own situation and the output recalculates instantly. The defaults are meant as a starting point, not a recommendation.

The levers in this calculation

The inputs — Units per Order, Per-Unit Manufacturing Cost, Tooling per Unit, Shipping per Unit, and Import Duty % — do not pull with equal force. Frequency and unit price pull the total in different directions. The biggest surprise for most people is how small recurring amounts compound into large annual figures — that's where this calculation earns its keep.

How the math works

Base = units × (mfg + tooling + shipping). Duty = units × mfg × duty %. Total = base + duty. Per-unit landed = total ÷ units. The working is transparent — you can verify every step yourself in the formula section below. No black box, no opaque "proprietary model".

What to do with a low result

A disappointing result is information, not a judgement. Pick the single input that dragged the figure down most and focus the next quarter on that one factor. Breadth-first improvement rarely works; depth-first on the worst input usually does.

What this doesn't capture

The score is a composite of the inputs you provide. Life context — job security, family obligations, health, housing — doesn't appear in the math but shapes the real picture. Use the number as a prompt, not a verdict.