Ask a warehouse manager how efficient their fleet is, and most will point to a dashboard: units picked per hour, orders shipped per shift, maybe a utilization percentage pulled from the WMS. Ask how much of a truck's shift is spent actually moving product, versus driving empty or sitting idle, and the answer usually gets vaguer fast.
That gap is not a reporting problem. It is a visibility problem. Forklifts and tow tractors run constantly, but almost nothing captures what they are doing between the start and end of a task — only that the task happened.
What we found when we measured it
We run continuous 3D visibility on forklifts and mobile robots, built from cameras already mounted on the trucks. At one live site, we measured fleet activity continuously over 25 days. Two numbers stood out: 40% of total driving distance was empty driving, and 29% of shift time was idle.
Neither number implies anyone is doing their job badly. Empty driving is often structural — a truck finishes a drop-off far from its next pickup, or a layout forces a longer return path than the task needed. Idle time accumulates in the gaps nobody schedules for: waiting at a dock, waiting for a pick confirmation, waiting because the next task hasn't been assigned yet. None of this shows up as an incident. It just shows up as a fleet that costs more to run than its throughput numbers suggest.
Why this stays invisible by default
A WMS tracks transactions: pick confirmed, pallet moved, order shipped. It was never built to track the physical path a truck took to get there, or what it was doing in the minutes between transactions. That data exists — the truck moved through real space, at a real time — but nothing was recording it.
Fleet activity numbers like this are usually estimated from sampling: a time-and-motion study, a manual audit, a consultant with a stopwatch for a week. Those methods are a reasonable starting point, but they are a snapshot, not a continuous measurement. A layout change, a new seasonal pattern, or a shift in order mix can move the real numbers within weeks, and the manual study won't catch it until the next one is commissioned.
What changes with continuous measurement
The forklifts and tow tractors already on site are also the infrastructure. Cameras already on the trucks, moving through the warehouse as part of normal operations, build a live 3D record of where every vehicle went and when it was moving versus stationary — no separate scanning step, no new hardware on the floor.
That continuous record turns "roughly how efficient is the fleet" into a number you can track over time, break down by zone, shift, or vehicle, and re-check after every layout or process change — not just after the next audit.
It also changes what "automate this" means. Fleet sizing and AMR deployment decisions are often made on throughput targets alone. A continuous empty-driving and idle-time baseline shows exactly where capacity is already being lost before anyone adds a robot to the mix — and gives a real number to check the automation project against afterward.
The takeaway
Most warehouses are not short on data about what should be happening. They are short on data about what is actually happening between the transactions. Fleet activity — empty driving, idle time, real cycle paths — is one of the largest quiet costs in a warehouse operation, and one of the easiest to start measuring with the trucks already on the floor.