Real travel paths on the floor
The layout drawing still shows a clean milk-run. The afternoon hall shows three empty loops past the same blocked face. Until the path is measured, the drawing wins the meeting and the floor keeps paying.
Actual routes instead of planned lines
Live 3D positions of forklifts give the routes that were driven, not the routes that were hoped for. Replay and spaghetti diagrams show every loaded and empty meter (foot). Medium-precision location around 1–3 m (3–10 ft) is enough for most corridor and buffer reviews. In one documented 30,000 m² (about 323,000 ft²) automotive Tier-2 plant, the RTLS layer supported a cut from 36 to 20 forklifts and from 108 to 60 drivers once routing followed the live map and delivery delays fell.
That path evidence is the core of internal logistics optimization. It also fills the spatially oriented dataset so later correlation and causality analytics can ask which empty corridors keep preceding a starve. Live fleet decisions and stored pattern work share the same tracks.
Dwell, empty miles, and uneven shifts
Heat maps and zone activity reports pull out minutes spent sitting. When forklifts dwell at the same choke points shift after shift, service level drops for everyone downstream. Historical data can show a full year of those patterns without another walk-through. Route analytics then split productive loaded trips from empty repositioning. Empty travel burns utilization without moving anything.
A second documented 30,000 m² (about 323,000 ft²) automotive Tier-2 site using the same logistics RTLS approach reduced forklifts from 15 to 13, lifted productivity from 63% to 75%, and freed four FTEs after empty runs became visible and were cut. Shift analytics show the other imbalance: one crew runs hot while another idles. In a documented 15,000 m² (about 161,000 ft²) logistics-center warehouse, continuous visibility supported workload balancing across shifts with a small RTLS investment and a clear first-year operating saving.
Speed control without losing flow
Path data can also prove a safety or flow rule without guessing. At a documented 55,000 m² (about 592,000 ft²) white-goods plant, RTLS evidence supported bringing average forklift speed down from 15 km/h (about 9 mph) to 6 km/h (about 4 mph) while performance held. The audit trail stayed available the whole time. Controlled speed and service level became one story instead of a trade-off argued from memory.
How empty travel shows up as non-value-added work is under pinpointing non-value-added travel on the floor. Replay after the live moment passes is under when the event has already passed. Fleet-buy impact from the same path evidence sits under when buying more forklifts is the wrong first answer. Productivity from 63% to 75% sits under forklift productivity from 63% to 75%. Speed held at 6 km/h (about 4 mph) sits under slower forklifts with the same performance.
How teams decide the path picture is enough
1. Put one peak half-shift on spaghetti before arguing fleet size - If empty share is high, rentals are the wrong first answer.
2. Name the dwell pockets that repeat every day - Fix the choke or the call rule before adding trucks.
3. Compare shifts on the same hall frame - Uneven utilization is a staffing and dispatch problem, not only a headcount problem.
4. Keep production waits on the same map - Path impact is incomplete if Line 3's starve stays on another screen under production monitoring.
Capability depth sits on the features overview. How a rollout is priced is on pricing.
Get in touch if you want to walk the real travel paths on your own facility model before the next fleet or speed decision.