Lead Time – Order-to-Ship Duration

This topic is part of the SG Systems Global manufacturing, logistics, and quality glossary.

Updated October 2025 • Flow & Capacity • Planning, Execution & Proof

Lead Time is the elapsed time from a customer order (or internal demand signal) to shipment of conforming product. It spans order entry, ATP/CTP checks, materials availability, production and inspection, finished-goods release, packing, and dispatch. Lead time is the customer’s clock, not yours; every queue, shortage, rework loop, and approval stall adds to it. In lean terms, it reflects flow efficiency—the ratio of value-added time to total elapsed time—while in regulated environments it reflects data integrity and release discipline. When job release, labeling control, or device-level evidence wobble, orders wait. Because the slowest step dominates the experience, organizations manage lead time by exposing WIP, leveling demand, sequencing intelligently, and letting QA release by exception through eBMR/eMMR rather than by paper chase.

“Lead time is the plant’s truth serum—plans boast, WIP gossips, but lead time tells the truth.”

1) What It Is

Lead time is the elapsed duration to convert demand into shipped product. It can be measured at multiple scopes: customer lead time (promise-to-ship), manufacturing lead time (kitting start to pack), procurement lead time (PO to receipt), and engineering lead time (ECO approval to effective masters). Each scope chains many sub-steps with different owners—sales order entry, capacity checks, finite scheduling, kitting, execution, IPC, QA review, labeling, and logistics. Measuring only an average hides pain; tails and constraint-specific drilldowns matter more than a single mean.

2) Components of Lead Time

Processing (touch) time. Actual conversion work—mix, assemble, test, pack—often a small fraction of total elapsed time.

Waiting (queue) time. Jobs sitting in front of machines, QA benches, printers, or docks; the dominant hidden factory.

Transport & staging. Moves between cells, waiting for forklifts, staging at lineside or outbound lanes.

Inspection & release. IPC holds, data review, batch/FG release, and label checks prior to ASN.

3) Where Lead Time Hides (Typical Delays)

Missing parts & approvals. Quarantined or expired lots; unlabeled master data; artwork approvals stuck in email. Countermeasure: FEFO rotation with directed picking and labeling control with template locks.

Overloaded constraints. Lines packed to 100% utilization cause queues to explode. Countermeasure: level with Heijunka, cap WIP, and hold protective capacity at the constraint.

Changeover thrash. Poor sequence (allergen/color/tooling) triggers deep cleans and lost hours. Countermeasure: family grouping, JIS for final assembly, and strict dispatch rules.

QA review bottlenecks. Paper packets and late IPC data push releases to end-of-shift. Countermeasure: eBMR with real-time checks, audit trails, and review-by-exception.

Logistics misses. Pallets wait for labels, ASN, or carrier windows. Countermeasure: scan-to-ship with GS1/GTIN and EPCIS events on pack.

4) The Math That Matters

Little’s Law. WIP = Throughput × Lead Time. For a given output rate, shrinking lead time requires reducing WIP—usually by throttling job release, not flooding.

Utilization nonlinearity. Queue time rises sharply as utilization approaches 1.0 at any shared machine, QA bench, or label printer; small capacity buffers stabilize lead time.

Flow efficiency. Value-added minutes divided by total elapsed minutes. Plants with 5–15% flow efficiency have 6×–20× improvement headroom without buying assets.

5) How to Reduce Lead Time

Gate release to readiness. Require kit completeness, current documents, trained operators, and finite capacity slots; block expired or unreleased lots via barcode validation.

Kill expedite culture. Expedites are symptoms. Fix master data, supplier performance, and sequence rules; use Kanban with realistic buffers.

Simplify changeovers. SMED, family scheduling, allergen brackets, and Jidoka checks to prevent restart defects.

Digitize proof, not just data. Integrate scales, torque, and vision; enforce dual verification on high-risk steps; let QA review in parallel, not at the end.

Design for logistics. Pre-allocate carriers, print labels from locked templates, and emit EPCIS events on pack so trucks don’t idle.

6) Data Integrity, Release Gates & Compliance

Lead time collapses when release gates are clean. That requires controlled masters under Document Control, contemporaneous capture under ALCOA+, and Part 11 signatures tied to meaning (approve to start, approve to ship). When QA trusts the system they release by exception; when they don’t, everything waits. Provide visibility and immutable audit trails so speed never compromises control.

7) How This Fits with V5

V5 by SG Systems Global shortens lead time by attacking dominant contributors. In V5 WMS, directed picking, FEFO/FIFO, bin location, and barcode validation eliminate search-and-wait and prevent wrong-part starts. In V5 MES, the job queue respects finite capacity; release is blocked until kits, documents, and training are verified; eBMR captures device data in-line so QA can review in-flight. In V5 QMS, deviations auto-open with reason codes, CAPA trends systemic causes of delay, and analytics show flow efficiency by SKU/line. At pack, GS1/GTIN labels, template locks, and EPCIS eventing collapse the last mile to ASN.

8) Practical Walkthrough

A CMO receives a rush order for a nutraceutical SKU, 5k bottles, ship in three days. Sales enters the SO; ATP shows enough bottles, but two excipients are short. Dynamic lot allocation confirms one lot is on hold pending assay. The scheduler avoids wish-casting: a different SKU is pulled forward, and the rush job is tentatively slotted behind the assay ETA. Warehouse performs kitting under FEFO; the system blocks an expired cap lot at scan. Document Control has a new torque spec; only the current instruction renders in the eBMR. On assay release, job release is authorized with Part 11 e-signature. At the line, scales and cappers stream data; out-of-tolerance torque triggers an immediate IPC hold and prompted recheck. QA reviews by exception during the run; by the last case, the record is complete. Labels print from locked templates; EPCIS events publish at case pack; the pre-booked carrier window is hit. Order-to-ship: 2.6 days, no expedite tax.

9) Metrics That Indicate Lead Time Health

Lead time distribution & tails. Track 80th/95th percentiles, not just mean; customers feel the tail.

Flow efficiency. Touch time ÷ elapsed time by product family and constraint; pursue year-on-year improvement.

Release readiness rate. % orders that pass release on first attempt (kit complete, docs current, training valid).

QA review lag. Minutes from last data entry to disposition; % released by exception.

Plan stability. Schedule adherence at 24/48 hours; dispatch override rate.

WIP at constraint. Units in queue vs. cap; time-to-clear after disruption; blocked label prints per 10k packs.

10) Common Failure Modes & Fixes

Paper-choked QA. Manual, late records. Fix: eBMR with device capture and required fields; immutable audit trail; review-by-exception.

Kit fiction. “Available” means “somewhere.” Fix: bin-managed WMS, FEFO rotation, directed staging, scan-to-issue.

Label latency. Waiting on art/claims. Fix: labeling control, template locks, and print-at-pack with reconciliation.

Setup roulette. Random sequencing. Fix: family scheduling, allergen/color brackets, disciplined dispatch.

Expedite addiction. Firefighting as policy. Fix: capacity buffers at constraints, realistic quoting, supplier scorecards, and CAPA on recurring causes.

Related Reading
• Flow & Scheduling: JIT | Heijunka | Finite Capacity Scheduling | Dispatching
• Materials & Traceability: Kitting | Directed Picking | FEFO | GS1/GTIN | EPCIS | Batch Genealogy
• Quality & Release: eBMR | IPC | Finished Goods Release | Labeling Control | CAPA
• Visual & Culture: Kanban Board | Kaizen | Jidoka