Lead time is the elapsed time between a brand issuing a purchase order to a supplier and the resulting inventory becoming sellable in its fulfillment network. It bundles four sub-segments: manufacturing time at the factory, transit (ocean, air, or ground), customs clearance, and inbound receiving at the 3PL or owned warehouse. The clock stops at sellable — received, putaway, and pickable — not at “arrived on the dock.”
Two adjacent terms get confused with supplier lead time. Cycle time is the manufacturer’s internal production-only span — a subset of lead time. Order lead time (or customer lead time) is the customer-facing span from order placement to doorstep arrival — a fulfillment-side measure on a different axis. Operator planning conversations go sideways quickly when these three get used interchangeably.
Lead time has both a mean and a standard deviation, and the variance — not just the mean — drives planning. A nominal “10-week lead time” often runs 8–16 weeks in practice once factory delays, port congestion, customs holds, and receiving backlogs are included. Safety stock is sized against that variance. The brand that plans only to the mean stocks out on every right-tail shipment and treats each one as a one-off, even when the tail is the actual operating reality.
Lead time is the primary input to the reorder point: roughly (average daily demand × average lead time) + safety stock, with safety stock sized against demand and lead-time variance. A 12-week lead time also means demand is being forecast 12 weeks out — every error compounds across that horizon. And lead time compounds with payment terms to set the cash conversion cycle: a 90-day manufacturing-plus-transit lead time on net-30 terms locks COGS-weighted cash up for roughly four months before the first unit sells.
Operators have two levers. Pull the mean down where unit economics justify the cost — partial air freight on hot SKUs, dual-sourcing closer to market, paying for priority manufacturing slots. Or pull the variance down through supplier scorecarding, buffer inventory at the bottleneck stage, and tighter receiving discipline. Variance reduction is usually cheaper per stockout-day-saved than mean reduction, and most DTC brands under-invest in it because the tail events feel like one-offs. Both levers should scale with SKU importance — A-items in an ABC analysis deserve tighter measurement than the long tail.