Replenishment lead time is the elapsed time from releasing an order until its goods are available for the intended use. It may include supplier processing, picking, transport, receiving and inspection. Define the start and end events before using a lead-time number to plan inventory.
For a retail buyer, a shipment at the loading dock may still be unavailable for sale. For a manufacturer, receipt may be followed by inspection before a component can enter production. A supplier's quoted shipping time may cover only one part of that interval.
How to measure lead time
Actual replenishment lead time = available-for-use timestamp − order-release timestamp
Use consistent time units and a calendar that matches the demand calculation. If an order is released Monday at 9 AM and usable stock is recorded Thursday at 9 AM, elapsed lead time is three calendar days. A “three business day” promise is a different measure when a weekend or holiday intervenes.
| Event | Why retain it |
|---|---|
| Order released | Starts the buyer's replenishment clock |
| Supplier acknowledgment | Shows when the supplier confirmed the order |
| Promised date and revisions | Records expected supply and changes to the promise |
| Actual arrival | Separates transport from later receiving delays |
| Accepted and available | Establishes when the stock can satisfy the intended need |
For a partial delivery, preserve dates and quantities for each receipt. The first-receipt lead time and final-completion lead time answer different questions. Marking the whole order complete at the first shipment can hide the delay on its remaining items.
Quoted, confirmed and actual lead times should remain distinguishable. A changed promise is useful for today's planning, but replacing the original promised date would make later reliability analysis harder.
Lead time vs order cycle
Lead time is the delay after an order is released. The order cycle or review interval describes how often buying decisions occur. Ordering every seven days from a supplier with a four-day lead time does not establish a universal “order on day three” rule; the correct action depends on stock, incoming orders, demand and the replenishment policy.
A continuous-review reorder point commonly covers demand during lead time. A periodic-review order-up-to policy commonly considers the review interval plus lead time. Keep these textbook policies distinct from the particular horizon configured in a software product. MIT's inventory notes distinguish the policies and their service objectives.
Lead time and reorder point
For a simplified continuous-review model:
Reorder point = expected demand during lead time + safety stock
Assume fictional daily demand averaging six units, daily standard deviation of two units, fixed lead time of ten days, independent daily demand and a normal approximation. Using z = 1.65 for an approximately 95% cycle-service target:
Expected lead-time demand = 6 × 10 = 60 units
Safety stock = 1.65 × 2 × √10 ≈ 10.4 units
Reorder point ≈ 70.4, rounded up to 71 whole units
The trigger applies to the relevant inventory position: usable on-hand plus relevant on-order stock, less outstanding demand commitments under the chosen policy. It is not an instruction to purchase another 71 units every time shelf stock falls below 71. See reorder point for the distinction between the trigger and order quantity.
Cycle service is the probability of avoiding a stockout during a replenishment cycle under the model. It is not the percentage of demanded units filled. Real service depends on whether the assumptions and inputs describe the operation.
When lead time varies
Using a mean lead time as if it were fixed can omit supply uncertainty. A common approximation for independent daily demand and independent variable lead time is:
Safety stock = z × √(mean lead time × daily demand variance
+ mean daily demand² × lead-time variance)
For mean demand of 12 units per day, daily standard deviation of three units, mean lead time of five days and lead-time standard deviation of two days:
Safety stock = 1.65 × √(5 × 3² + 12² × 2²)
= 1.65 × √621
≈ 41.1 units
Ignoring lead-time variability in this example gives about 11.1 units. These are model outputs, not prescribed buffers. Correlated demand and delays, stockouts hiding demand, seasonal shifts or infrequent purchases may require a different estimation method and validation against actual outcomes.
Just-in-time inventory does not universally mean zero stock or zero variation. Evaluate the buffer, delivery cadence and recovery options appropriate to the process.
Building a usable history
Suppose five completed orders took 9, 11, 8, 12 and 10 days. Their mean is ten days and sample standard deviation is about 1.58 days. That summarizes those observations; five orders do not establish a stable future distribution or reliable tail-risk estimate.
Group records by relevant item, supplier route and order conditions rather than averaging unlike purchases together. Review incomplete late orders too: using only completed orders can make current performance look better than it is. Preserve expedited orders and unusual disruptions as identifiable cases instead of deleting them merely because they worsen the average.
Compare observations over time and investigate material changes. There is no universal order count after which every supplier's lead-time estimate becomes dependable.
Putting the dates to work
LineNow's PO status workflow connects orders, supplier replies and receiving. Use a living purchase order to preserve promised-date changes alongside actual receipts.
In a demonstration, inspect a partial shipment and verify which date feeds the configured replenishment input. A connected order history does not by itself prove automatic lead-time estimation or a particular refresh schedule. For the broader buying decision, see inventory replenishment software.