CT Operations turns the scan data your team already generates through Identity and Network into predictive answers - and specific, costed recommendations, not another chart to interpret.
Founding customer program. Sales conversations for Operations start now, ahead of the Q1 2027 general release - early partners help shape which features ship first.
The data to answer these questions already exists in your scan history. It's just never been turned into an answer.
Every pick, route and session captured by Identity and Network becomes the training data - no separate project to collect it.
ABC classification, demand forecasting, route-efficiency scoring - using whichever method actually wins on your data, not a fixed formula.
"Move item X from A to B, worth €Y/month" - specific enough to act on without a workshop.
Item 3410A0020504 is picked roughly 11.0 times a week (47.79/month), and the trend is rising.
Today it sits in its original home slot - a slow-zone location, well back from the pick start.
CT Operations flags it as a promotion candidate: move it to 2100A0010407, right next to the pick start.
Estimated impact: €114 a month on that single item, from reduced walking distance alone.
In this warehouse's actual forecast run, 14 flagged items like this one added up to roughly €327/month in identified savings - generated automatically from scan history, not a three-week slotting consultant engagement.
Example figures from a live warehouse's ABC repartition analysis in CT Operations.
A consultant-led project, run occasionally, based on a sample of the data - and already out of date by the time it's implemented.
Recommendations regenerate from live scan data, so slotting keeps pace with how your product mix actually shifts.
In one example run: 571 picking sessions analyzed, 110 flagged as inefficient. The worst case walked 2.72× the optimal distance for that route - a specific session, a specific operator, a specific fix.
ABC classification maps your fastest-moving slots against the ones quietly eating walking distance - and tracks how that picture shifts over time.
That "actual layout" is the same Digital Twin floorplan Network uses for coverage - pick activity lights up on it live, and you can scrub back to see how a day or week played out.
Daily or weekly KPI email reports, plus real-time alerts the moment a threshold is crossed - configured once, per warehouse.
See the full list of KPIs we track - and can alert you on - below ↓.
Every metric below runs off your existing scan history. You set the thresholds in the portal, and each one can trigger a proactive email alert the moment it's crossed - not just a number sitting in a report nobody opens.
The recommendations that turn scan data directly into euros - and the anchor that keeps every euro figure honest.
Tests a stock move against your own recorded picking trips before it's ever recommended.
A verified €/year figure with a payback window - e.g. €373/year from 3 moves, paying back in 10 days.
Finds items sitting far from where they're actually picked. Every candidate move passes four checks: does it fit, is it legal, does it create new congestion, and does it actually save.
A verified € per move - refused outright when a move doesn't genuinely pay for itself.
Spots items that get picked together on the same trip but sit stored at opposite ends of the warehouse.
A priced move to bring them together - vetoed if it would cost more than it saves.
The trust anchor behind every figure above: turns meters walked into euros, using a walking pace fitted from your own scans - not an assumed constant.
Claims nothing on its own, by design - it's how every other number here stays honest.
Route- and operator-level diagnostics - priced wherever a real euro figure holds up, left unpriced everywhere it wouldn't.
Compares every trip against the shortest possible walk through the same stops.
Up to roughly €5,200/year - an estimate, a ceiling, not a promise - or just as often the honest read: "routes are already near-optimal, little to gain."
Compares real routes against simple strategies any picker can follow, like the S-shape pattern.
Minutes/day recoverable per operator, surfaced as specific coaching topics - not priced in €.
Flags trips that fall far outside the floor's normal range.
A review worklist, not a savings figure - the job here is catching the outlier, not pricing it.
Scores people on the routes they were actually assigned - never on raw speed.
Fair, defensible coaching targets. Coaching, not surveillance - deliberately no € attached.
Groups similar picking styles together for team-level coaching.
Who benefits from which coaching approach - again, no € attached by design.
Detects whether trips are already being combined, and how much more combining could still save.
An upper bound only - turning that bound into a real number needs order IDs in the data.
Measures time lost waiting behind colleagues in shared aisles.
Minutes/day, per operator - never priced in €, as a matter of policy.
Given a single pick list, proposes a shorter stop order for it.
A shorter walk, shown as a bound - not a promise.
The layout side of the same picture - which slots earn their spot, and what to try before you build anything.
Sorts every slot into fast, middle, or quiet movers.
The map, not the treasure - it's what feeds the Improvement plan above.
Grades every slot A through D, and says whether the problem is distance or height.
A ranked fix-list - distance problems and height problems need different fixes.
Finds heavy-traffic picks sitting at awkward heights and proposes same-column level swaps.
Health improvements, deliberately unpriced - the small time gains that come with them ride on the Improvement plan.
Names each zone's actual problem - crowded, overloaded, or badly arranged.
The right fix for that zone, instead of one generic answer for the whole floor.
Tests a new walkway or cross-aisle against your own history before anyone picks up a tool.
Try it before you build it - savings shown as estimates, not guarantees.
The operational health metrics underneath everything else - not always priced, always worth an alert.
A free, always-current signal map, built from the scanners already on the floor - the same coverage view CT Network uses.
Weak-signal areas located for AP placement - no time loss measured yet, and no cost implied.
Every scan reports back on how the device itself is doing.
Catches a failing scanner before it dies mid-shift.
Compares expected work arrival against staffing, hour by hour.
See the swamped morning and the quiet afternoon coming - a planning aid, deliberately with no € attached.
Classify locations by pick frequency (ABC analysis), then move fast-moving items closer to the pick start. CT Operations automates this using live scan history, flagging specific promotion candidates with an estimated €/month impact.
Use historical order volume and actual pick-time data to estimate picker-hours for a given batch. CT Operations generates this forecast automatically from your existing scan history instead of relying on manual estimates.
Track pick rate, route efficiency versus optimal distance, and session anomalies per operator and per device - calculated automatically from scan data, with sessions outside the normal range flagged for review.
