Solutions
WareBee forCI engineers .
Every improvement needs a baseline, a hypothesis and proof. WareBee gives you all three: process mining shows the real flows, the twin simulates your change, and the savings are quantified before anyone moves a pallet.
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Kaizen with a control group.
Process mining
Reconstruct how work actually flows — detours, rework and bottlenecks the SOP never mentions.
The twin replays timestamped scan and location events in sequence, not the flowchart someone drew at go-live, so a picker's actual route through a wave surfaces on its own. Kaizen stops starting from an interview and starts from a map that already shows where the SOP and the floor diverge.
Simulate before you commit
Test slotting, batching or layout changes in the twin and read the delta in hours and money.
Each scenario replays against the same slice of order history as the baseline, so the before-and-after numbers are never comparing different weeks. A proposal earns its floor time by clearing the bar in the twin first — the ones that don't shelve themselves before a picker ever moves a pallet.
Benchmarking
Performance measured against industry standards — know where the gap actually is.
Your operation is scored against a peer set matched on order profile, SKU count and footprint, not a blanket industry figure that assumes every warehouse looks alike. The gap that surfaces has a metric and a magnitude attached, ready to open the next kaizen ticket instead of a debate about whether it's real.
Experiment safely
Run what-if scenarios on demand volatility, new processes or automation without touching the floor.
A scenario described in plain terms gets recomputed across a full week of real orders overnight, so the answer is waiting before the morning stand-up. A hypothesis that turns out wrong costs a re-run, not a shift's worth of goodwill spent testing it against a live crew.
Tracked savings
Cost per event, before and after — improvement claims your CFO can audit.
Every event carries a cost baseline captured before the change went live, so the after-numbers sit against a fixed reference point instead of a moving target quietly redefined each quarter. When finance asks where the saving came from, the answer is a query away, not a slide someone rebuilt from memory.
Evidence packs
Every recommendation carries its data trail, ready for the steering meeting.
The twin logs which orders, locations and time window a recommendation was modelled against, so the pack that goes into the meeting is the same data the model actually used, not a summary reconstructed afterwards. A challenge from the room gets answered by drilling into the underlying events, not by re-running the analysis from scratch.