Employee scheduling, built on real demand
Most employee scheduling software fills calendar slots against last year's POS. POS only sees the people who bought. Ariadne measures everyone who walked in, predicts demand by hour and zone, and turns it into a schedule. Use Employees Planner, or feed the WFM the team already runs.
+8.56%
Sales lift when peak coverage is fixed
The understaffing tax is measurable
Every store in a 41-store study was understaffed at peak. Close the gap: +8.56% sales, +7.02% profit.
Read the study
Employee scheduling assigns the right number of people, to the right roles, at the right hours. Done well, it is the cheapest line item in retail to optimize. Done on instinct or last year's POS, it is the most expensive.
Ariadne does both. Employees Planner is the scheduling product built around the demand signal: draft scheduling, operational rules, task management, allocation insights. For teams already on SAP, Workday, UKG, Quinyx, or Microsoft Shifts, the same demand signal exports there too. Read how Ariadne builds the signal under.
Demand-based scheduling vs POS-based scheduling
Most retail schedulers build their plan against POS data, because that is what the WFM tool already has. POS is the wrong input.
Why most schedules are wrong
Customer traffic is dynamic. Most rosters are not. The four gaps below are documented in published research and shopper surveys, and they all share one root cause: the schedule was built without a real demand signal.
77%
Of associates say their store loses sales to bad scheduling
POS sees converted customers. It does not see the people who walked in, waited too long, and left. Scheduling on POS is scheduling on the outcome you wanted to change.
+8.56%
Modeled sales lift from closing the peak gap
In a 41-store study, every store was understaffed during a three-hour peak window. The headline finding is that the schedule never had a peak signal to plan against.
85% → 81%
Year-over-year drop in in-store shopper satisfaction
Shopper satisfaction with in-store experience dropped year over year. Labor coverage is the single biggest controllable input to that score.
+3 pp
Comp-store sales lift correlated with lower frontline turnover
Retailers with lower frontline turnover post higher comp-store sales. Predictable, demand-aligned schedules are one of the top retention levers.
How it works
Step 1: Forecast
Anonymous people counters at the door and across zones produce the raw signal. Ariadne fuses that with weather, local events, and historical patterns to forecast visitor volume up to a week out. The forecast is what your scheduler should be planning against.
See how we capture the signalStep 2: Cover
The forecast exports as labor demand by hour and by zone. Your existing scheduler turns that into shifts, respecting labor rules, contracts, and skill mix. You keep the WFM tool. You stop scheduling blind.
Step 3: Inject
When the floor is quiet, Ariadne flags it in real time so staff move to restocking, training, or back-of-house work instead of standing idle. When traffic spikes unexpectedly, the system pings to surge coverage.
Zone analyticsThe cost of getting this wrong
Many studies. Same conclusion: when the schedule plans against the wrong inputs, the labor budget pays for it.
+8.56%
Modeled sales lift
When peak-hour understaffing is closed, in a 41-store sample.
Mani et al., POMS 201577%
Associates citing lost sales
Of retail associates say their store loses sales due to poor scheduling and staffing.
Logile retail labor survey, 202585→81%
In-store satisfaction
Year-over-year drop in shopper satisfaction with the in-store experience.
Zebra Global Shopper Study, 2024+3 pp
Comp-store sales
Comp-store sales lift correlated with lower frontline turnover. Predictable, demand-aligned schedules are a top retention lever.
McKinsey retail frontline report, 2024Two paths, one demand signal
Ariadne ships with Employees Planner: the scheduling product built around the demand signal. Or feed the same signal into SAP, Workday, UKG, Quinyx, or Microsoft Shifts via documented API.
Inside Employees Planner
Module 01
Ariadne builds the weekly shift schedule against forecasted footfall, by hour and by zone. Drag, edit, and lock shifts. Labor rules, contracts, and skill mix sit beside the draft as real constraints, not afterthoughts.
Module 02
When the floor is quiet, Ariadne routes staff to restocking, training, visual merch, or back-of-house. Idle labor hours become utilization. No last-minute scrambling, no overtime calls.
Module 03
Ariadne shows how staff hours actually mapped to demand, week over week: visitor-vs-staff combi chart, allocation match, idle hours converted, lost-sales risk. Day-of-week labor patterns. Exportable reports.
Or feed the WFM teams already run
Don't see your tool? Ariadne exports CSV and pushes via REST. Most teams are wired up in under a week.
Where this matters most
Peak coverage at the front of store, idle time converted to merchandising and restocking.
Center staff, security, and cleaning rosters aligned to real visitor curves, not just sales.
Concession and retail labor staffed to flight banks. Glasgow Airport reduced complaints 23%.
A single site with existing infrastructure is typically live in two to four weeks. Multi-site rollouts run in waves.
In production
Three deployments, three different decisions made.
FAQ
Either. Ariadne ships with Employees Planner for teams that want a single product: draft scheduling, operational rules, task management, allocation insights. For teams already on SAP, Workday, UKG, Quinyx, or Microsoft Shifts, Ariadne exports labor demand by hour and zone via documented API or CSV. The demand signal is the same either way.
POS only counts people who bought. POS does not count people who walked in, waited, and left. Most lost sales never show up in POS. Ariadne measures every visitor at the door and across zones, so the schedule plans for the people the team almost served, not just the people who already converted.
Ariadne uses anonymous Wi-Fi, Bluetooth, and time-of-flight sensors. No facial recognition, no biometric capture, no PII. Edge anonymization is baked into the architecture. In many sites Ariadne can reuse the access points and infrastructure the customer already owns.
Forecast accuracy is typically above 95% on a 7-day horizon when at least three months of historical data, weather, and local event feeds are available. Methodology and per-environment accuracy are published on the people counting page.
Yes. The same demand-signal model powers concession labor at airports, security and cleaning rosters at shopping centers, and front-of-store coverage at single retailers. The published customers include Glasgow Airport, San Diego Airport, Armani, and Praktiker.
Forecast-based scheduling predicts how many customers will arrive. Demand-based scheduling goes one step further and predicts what those customers will need staff for, by hour and by zone. Ariadne provides the zone-level signal, which is what makes the difference between covering the door and covering the right aisle.
Yes. Ariadne does not capture biometrics, does not identify individuals, and anonymizes at the edge. The system sits outside the EU AI Act's prohibited and high-risk categories because there is no biometric identification, no emotion inference, and no profiling of natural persons.
See how Ariadne's footfall signal exports into the workforce management tool you already run. 20 minutes, real numbers, your stack.
Two questions, twenty minutes, a real walkthrough of your venue's footfall.
What to expect
Got a different question?
Anything that isn't a sales conversation. We'll route it to the right person and get back within one business day.