Lead time is the elapsed time between placing a purchase order and the units being available to sell. It's not a single number — it's the sum of several stages, each with its own variability.
Total lead time is the sum of all four stages — not just supplier lead time. Brands that plan against supplier lead time alone routinely run out of stock during transit and clearance.
Lead time drives every replenishment decision. It sets the reorder point (how low inventory can go before a new PO must be placed), shapes safety stock (longer lead times need bigger buffers), and dictates how far ahead demand has to be forecast accurately. A 60-day lead time means today's PO decision is committing to demand 60 days from now — and being wrong by 20% over that window means either stockouts or overstock.
For most ecommerce brands, lead time is the operationally relevant metric. Cycle time and takt time matter primarily in manufacturing contexts.
Tracking lead time by stage, rather than guessing at one aggregate number, usually requires more than a spreadsheet once a brand is running multiple suppliers and carriers — the PO-acceptance and receiving timestamps that separate supplier delay from transit delay typically live in whatever system is handling inventory sync between the store and the ERP, while the transit-time half of the equation is a function of carrier setup and rate rules, which is where shipping optimization work comes in.
Because lead time is the input that makes demand forecasting either accurate or wrong by weeks, most of the work in shrinking stockout risk actually happens on the forecasting side rather than the lead-time side itself — matching purchase orders to a demand curve that accounts for lead time variability is covered in more detail in this guide to inventory forecasting for Shopify stores.
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