Warehouse metrics
The hours a shiftnever planned for.
Overtime share is the proportion of worked hours that fell outside a shift's planned capacity — not a flat headcount times shift length, but the hours actually logged against the wave and zone plan that shift was built for, with whatever ran past it broken out on its own. WareBee reads the same task-completion and shift data that built the plan in the first place, so the hours a zone worked beyond its own plan show up as their own figure, not folded into one payroll total nobody breaks apart.
See why the shift ran short
What it is
What ran past the plan, counted on its own.
On WareBee's digital twin, overtime share is the proportion of worked hours that fell outside a shift's planned capacity — planned meaning the headcount, role mix and shift length that plan was actually built for, not a round number applied after the fact. WareBee reads the same task-completion and time-and-attendance events that build the shift plan in the first place, so the hours a zone worked beyond its own plan are visible as their own figure rather than folded into one payroll total nobody breaks apart. A share sitting close to nothing means most work closed inside the hours it was planned for; a rising one means a growing slice of paid time is coming from outside the plan altogether.
The share moves with whatever actually pushed a shift past its own boundary, not with how busy the day felt from the floor. A wave released on a fixed clock instead of the pick rate already running in that zone starts behind before the first pick happens, and closing it out eats into hours nobody planned for. A staffing plan built from an earlier quarter's assumption rather than the volume the forecast is currently showing carries a gap that has to close somehow, and overtime is usually what closes it. Idle time that's never separated from productive time — waiting on a delayed trailer, a blocked aisle, a task queued behind the wrong priority — still runs the clock, so by the time a wave finally closes, the hours it borrowed from outside the plan have already been paid.
There's an instinct to ask what a normal overtime share looks like, the same instinct that wants one answer for what a normal speed limit is — as if a single figure could travel between shifts built nothing alike. WareBee resists it: your share sits next to a peer set matched on order profile, SKU count and footprint, and the read that comes back says something about your own shift pattern, not about a number that was never computed with your kind of business in mind.
What moves this number
What pushes a shift past its own plan.
Each one is measured on your digital twin from data you already generate, so an overtime figure traces back to a cause rather than a general sense that the floor ran long.
A wave released on the clock, not the pick rate
Timing a release to a fixed interval instead of what the zone is actually clearing pushes the whole wave's finish line later, and the hours needed to close it land outside the plan.
Release times set from actual pick rates and equipment cycle times keep a wave inside its planned window instead of starting behind before the first pick happens. Where release still runs on a fixed clock, every extra minute the wave needed shows up as overtime rather than as a release problem anyone traced back.
A staffing plan built for an average day
Headcount set from an earlier quarter's assumption rather than this week's forecast leaves a gap between paid hours and the volume that actually turned up.
Expected order volume converts into task minutes and headcount by role and shift, and the plan re-cuts automatically once real order flow drifts from what was forecast. A plan that never gets re-cut carries its shortfall into every wave it touches, and overtime is what closes the difference.
Idle time nobody separates from productive time
Waiting on a delayed trailer, a blocked aisle or a slow system still runs the paid clock, and none of it shows up as its own line until the shift already ran long.
True idle time is captured in the same event model as every scan, separated from productive time rather than blended into it. Waiting that never appears on a task report still gets paid, and once a shift has already run past its plan, that unrecorded time is baked into the hours it took to get there.
A late trailer or a stalled wave dragging the close
Closing tasks queued behind a dock still working a late truck, or a wave that hasn't cleared upstream, push the last tasks of a shift past its planned end.
Dock schedules and wave-close events are tracked in the same model as pick and pack, so a closing task waiting on upstream work is visible before the shift's end, not discovered once the clock's already run over. Only the tasks actually blocked by the delay push past plan — the rest of the shift keeps its normal finish.
Trace the extra hours to the wave that created them.
A single overtime-share figure for the warehouse hides which waves are actually generating it. Once yours is read against a peer set matched on order profile, SKU count and footprint, the next question is whether the extra hours are coming from a release timed to a fixed clock, a staffing plan that's drifted from the forecast, idle time nobody's separated out, or a dock delay dragging the close — the same task, time and dock event data that builds the figure breaks it down to cause.
From there it's a scheduling question before it's a headcount one. A different release trigger, a re-cut staffing plan or a resequenced dock assignment can be tested on the digital twin against the same order mix already producing the current figure, so the effect on overtime shows up before a live rota changes. Once approved, the change reaches the WMS as the wave release rules, shift patterns and dock schedules it already runs on.
- Overtime share read against a peer set matched on order profile, SKU count and footprint
- Every hour outside the plan traced to release timing, staffing, idle time or dock delay
- Staffing and scheduling changes tested on the twin before a live rota changes
Questions
Overtime share, traced back to its cause.
What exactly counts toward overtime share?
It's the proportion of worked hours that fell outside a shift's planned capacity — the headcount, role mix and shift length that plan was actually built for. WareBee reads the same task-completion and time-and-attendance events that build the plan in the first place, so hours worked beyond a zone's own plan are counted as their own figure rather than folded into a single payroll total.
Does a rising overtime share always mean the team is understaffed?
No, and treating it that way usually points at the wrong fix. A share can rise because a wave released on a fixed clock started behind before the first pick happened, because idle time nobody separated out still ran the paid clock, or because a staffing plan drifted from the forecast it was built against — three different causes that show up as the same figure until the underlying events are broken apart.
How is overtime share different from labour cost per line?
Labour cost per line prices the minutes a specific line consumed, whatever shift they fell in. Overtime share is a proportion of the whole shift's hours, split between what the plan expected and what ran past it, without pricing any individual line. A shift can carry a high overtime share while its average labour cost per line stays ordinary, if the extra hours were spread thinly rather than concentrated on expensive lines.
Why not cap overtime share at one fixed percentage?
Only because there's nothing else honest to check it against. Two shifts carrying entirely different batching pressure and cut-off loads can log the same overtime share for opposite reasons — one running exactly as its plan expects, the other quietly failing it. WareBee's peer set — matched on order profile, SKU count and footprint — is what tells those two apart, checking your share only against shifts asking the same thing of their floor.
What data does WareBee need to measure overtime share?
Task-completion and time-and-attendance events, alongside the wave and zone plan your WMS or workforce system already produces, are enough for a first read — no new hardware or integration project. That combination is what lets hours worked beyond a zone's own plan be traced back to the wave, the staffing gap or the dock delay that actually caused them, rather than left as one payroll total nobody breaks apart.
Does a corrected staffing plan or resequenced dock assignment reach the WMS?
Yes. Once a supervisor approves a revised release trigger, a re-cut staffing plan or a resequenced dock assignment, it goes out as the wave release rules, shift patterns and task assignments the WMS already runs on, so the change that lowered overtime share on the twin is the one the floor actually works to. Actuals flow back afterwards, so the next reading starts from what genuinely happened.