Here’s a number worth calculating for your own operation: take a typical order’s total elapsed time from
release to completion, then add up the minutes actually spent processing it. In most plants the processing
share is small — often in the single-digit percentages. The rest is waiting.
That ratio is the opportunity, and attacking it requires no additional capacity.

Where The Waiting Happens

Queuing before operations, which is the largest component in most plants and grows sharply as utilisation
rises. Work waiting for a machine that’s busy is time nobody records as a problem.
Batch waiting. In a batch of two hundred, the first piece finished waits for the two hundredth before the
batch moves. Half the batch quantity is effectively idle at every stage.

Transport and Staging Between Operations.

Inspection and approval queues, where material sits complete but unavailable.
Material waiting — the job is released but a component hasn’t arrived.

The Levers That Work

Reduce batch sizes. This is the highest-impact change available and the most resisted, because smaller
batches mean more changeovers. But the lead time reduction is roughly proportional, and if you attack
changeover time in parallel the trade-off improves substantially. Halving setup time makes halving batch
size free.
Overlap operations. Move partial batches to the next stage rather than waiting for completion. A batch of
two hundred transferred in lots of fifty starts downstream work far earlier, and the effect compounds
across stages.
Manage utilisation deliberately. Queue time rises non-linearly with load — a work centre at ninety-five
percent utilisation has dramatically longer queues than one at eighty. Running slightly below full load
produces shorter, more predictable lead times, which is counterintuitive to anyone measured on utilisation.
Release work later. Releasing jobs early doesn’t make them finish sooner; it makes the queue longer and
every job’s lead time worse. Controlled release to match capacity is free and immediate.
Move inspection inline. Material sitting in a quality queue is pure lead time. In-process checks at the
operation remove the wait entirely.
Confirm material before release. A job released without full material availability will stop midway and
consume queue space while it waits.

Measuring it Properly

Track lead time as a distribution, not an average. Customers experience your variability, not your mean — a
plant averaging twelve days with a range of eight to thirty is harder to buy from than one averaging fifteen
with a range of fourteen to sixteen.

Also track the ratio of processing time to total elapsed time. It’s the single most diagnostic number
available, and improving it is what lead time reduction actually means. Measure it on a handful of
representative products by physically following a job through, at least once. The walk-through usually finds
waiting nobody had recorded anywhere.

What Follows

Shorter lead times reduce forecast horizon, which reduces forecast error, which reduces safety stock. The
inventory benefit frequently exceeds the service benefit, and it arrives without any change to how much
stock you deliberately hold.
ticktick.ai tracks queue and processing time by operation and controls job release against real capacity.