True order fulfilment cost.

Fulfilment cost per order includes pick/pack labour, packaging materials, warehouse rent allocated per order, and returns processing. Typical in-house fulfilment: 3-6 per order. 3PL (third-party logistics): 4-8 per order (upper rate but no warehouse/staff to manage). Amazon FBA: 3-12 depending on product size and weight.

2,000 orders/month × (1.50 pick/pack + 1.80 materials + 0.50 warehouse + 0.20 returns) = 4/order × 2000 = 8,000/month, 96k/year. For 50 AOV this is 8% of revenue - typical. Above 12% signals inefficient fulfilment; below 5% usually indicates under-counting (forgot returns or warehouse allocation).

Fulfilment cost drives break-even for shipping offers. A store offering 'free shipping over 50' with 4 fulfilment cost needs 50 orders to break even just on the shipping offer. Understanding fulfilment cost changes how to structure shipping promotions, bundle offers, and free-shipping thresholds.

A worked example

Try the defaults: orders per month of 2,000, pick/pack labour per order of 1.5, packaging materials per order of 1.8, warehouse rent per order of 0.5. The tool returns 4.00. You can adjust any input and the result updates as you type — no submit button, no reload. That's the real power here: seeing how sensitive the output is to one or two assumptions.

What moves the number most

The result responds to Orders per Month, Pick/Pack Labour per Order, Packaging Materials per Order, Warehouse Rent per Order, and Returns Processing per Order. 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.

The formula behind this

Per-order cost = labour + materials + warehouse + returns. Monthly = per-order × orders. Annual = monthly × 12. Everything the calculator does is shown in the formula box below, so you can check the math against your own spreadsheet if you want.

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.