Why the pick and pack labor calculator matters
Packing is the bottleneck almost every growing store hits second, right after picking, and it is far more sensitive to item-count mix than to total orders. This page turns that decision into a handful of inputs you can defend in a budget review: volume, unit cost, rate of adoption, and time. The output is a planning baseline, not a promise — it tells you whether the idea deserves a vendor quote, a pilot, or a pass.
- • Biggest swing factor: orders per packer per hour
- • Second-order factor: monthly order volume
- • Often ignored: multi-item order share, which slows the bench disproportionately
What actually changes the answer
orders per packer per hour moves this number first, then monthly order volume. Run a conservative case and an upside case before you commit. If the maths only works in the upside case, treat it as a time-boxed test with a kill date rather than a line in next year's plan.
What to do with the result
Time twenty packs across your real order mix before staffing. Averages taken from single-item orders will understate headcount by a third.
FAQ
What does the pick and pack labor calculator work out?
It applies Units = ceil(demand × (1 + buffer) ÷ throughput per unit) to the values you enter for orders to pack per month, orders packed per person per month, fully loaded monthly cost per packer, buffer for peak days. Packing is the bottleneck almost every growing store hits second, right after picking, and it is far more sensitive to item-count mix than to total orders.
How accurate is this pick and pack labor calculator?
Assumes consistent order mix. Gift wrapping, serialisation and kitting each cut throughput sharply. Replace the defaults with your own invoice, usage export, payroll data, statement, or vendor quote before making a commitment — the maths is exact, so the answer is only as good as the inputs you feed it.
Which input should I stress-test first?
orders per packer per hour. Re-run with a pessimistic value for it; if the decision flips, that assumption is the thing you need real data on before signing anything. After that, check monthly order volume and multi-item order share, which slows the bench disproportionately.
Which scenario should I start from?
Start with the preset closest to your situation — lean case, expected case, scaled case — then edit the sliders. Presets are realistic starting points, not benchmarks to match, and every change updates the result instantly.
What should I do after running the numbers?
Time twenty packs across your real order mix before staffing. Averages taken from single-item orders will understate headcount by a third. A useful planning benchmark to compare against: Manual packing runs 20–35 orders/hour depending on item count and gifting.
Can I share or save this calculation?
Yes. Your inputs are written into the page URL, so copying the link shares the exact scenario you are looking at — the person who opens it sees the same numbers. You can also export the inputs and results to CSV or PDF from the result card and keep it with the rest of your workings.
How this calculator is built
Independently maintained
Written by Sam Doshi and the RevenueLab editorial team. We don't sell the data feeds this tool is built on.
Sourced from primary data
Benchmarks come from public AdSense / Stripe / IRS disclosures and reader-submitted data — never third-party "$X per view" claims. Full methodology.
Last editorial review
Reviewed on a rolling quarterly cycle. Dated reviews are published on the methodology record for each calculator.
Editorial standards
See our editorial policy and disclaimer. Results are estimates, not advice.