Before the next shift
An operations manager can explore disruptions and staffing choices before moving people on the floor. The layout explains why a longer route changes picking work.
See the operation.
Change the outcome.
For a distributor, a late shipment is rarely one problem. Orders, walking routes, people, packing queues, and dock availability interact. This working example makes those dependencies visible.
One late dock.
A hundred moving parts.
A distributor needs to clear its order wave before the 45-minute shipping cutoff. Close an aisle, delay a dock, then rebalance the team—and see the consequences across the floor.
Interactive company scenario · synthetic orders
A transparent scheduling model, not a client result.
01 Inventory racks02 Picking aisles03 Packing04 Dispatch docks
Loading the 3D floor… Automatic motion is off.
Calculating the first order wave…
What the model assumes
All orders are available at minute zero; each visits one synthetic shelf location. Shortest grid paths use 1.5 m cells at 38 m/min, plus 1.1 minutes to pick. Packing takes 0.8–1.16 minutes per order; dispatch adds 0.4 minutes transfer and 0.65 minutes dock service. Workers are pooled within picking and packing. Walking distance is one-way; return walks, congestion, stockouts, shift breaks, SKU complexity, and vehicle loading capacity are excluded. Rebalancing searches worker splits; it does not solve a full warehouse optimization problem. Moving parcels illustrate routes, not a real-time event replay.
A useful 3D interface earns its depth.
One shared picture
Warehouse staff, planners, and leadership can discuss the same racks, paths, and queues. Separating the systems reveals their structure; bringing them together shows the whole flow.
Built around constraints
This example uses synthetic orders. A company version would need its actual floor plan, SKU locations, shift rules, service times, and validated operating data before its outputs could guide a shift.