Connect. Forecast. Schedule. Prove.
HotelCadence connects read-only to your property system (Oracle OPERA Cloud, Mews or Cloudbeds), forecasts demand per department per hour, drafts the lowest-cost roster your managers approve, and measures the result against your agreed baseline every month. Live in weeks. No rip-and-replace, no change to guest service standards.
HotelCadence is workforce software for hotels. It reads the bookings already in your property system, forecasts how busy each department will be hour by hour, builds the roster to match, records worked hours and prepares payroll. Department heads approve every roster. From US$6 per scheduled employee per month.
Step 1 · ConnectWhat the connection to your property system involves
A secure connection that only reads Oracle OPERA Cloud, Mews or Cloudbeds. Your administrator switches it on; nothing is installed on property and HotelCadence never changes anything in your property system.
49% of hoteliers say they cannot access the data they need for operational decisions, and 40% blame disconnected systems (Revinate, 2025). Step one exists to end that: one live feed, no exports, no Monday-morning CSVs.
What data flows
- Reservations and pickup, refreshed as bookings land
- Arrivals and departures, hour by hour
- Occupancy and room-type mix
- Rate and market-segment mix
- F&B covers and group/event flags where your property system provides them
Forecast before you touch the roster
A roster is only as good as the demand estimate underneath it, and manual estimates decay fast. A spreadsheet forecast runs about 8% error at 7 days out and 28% at 90 days. Budget-season staffing plans are built on the worst numbers of all.
HotelCadence forecasts per department, per hour: arrivals for the front desk, departures and room turns for housekeeping, covers for F&B. The model is calibrated on 2+ years of your own property system history, backtested so you see its accuracy before the first roster, and refreshed whenever pickup moves, a tour group booking 80 rooms on Thursday night changes Saturday's forecast by Friday morning.
More on hotel demand forecasting →
The data behind this chart
| Forecast horizon | Typical manual error (MAPE) |
|---|---|
| 7 days | 8% |
| 14 days | 11% |
| 30 days | 15% |
| 60 days | 22% |
| 90 days | 28% |
Your managers control the roster
The optimizer drafts the lowest-cost roster that covers the hourly forecast, and every constraint is respected in the draft: skills and cross-training, contract minimum and maximum hours, rest periods, split shifts, casual pools and the local labor rules configured during onboarding.
Department heads see the demand behind each shift, edit what they disagree with and approve before anything publishes. The AI never overrides a human decision, it makes the default correct and cuts roster build time by about 70% from the 3-8 hours a week managers spend in Excel.
Constraints the draft respects
- Skills, certifications and cross-training
- Contract hours, casual pools and split-shift rules
- Rest periods and local labor rules, set up during guided onboarding
- Your service standard, coverage floors per department, per hour
How you know it worked
Every deployment starts with a baseline contract: before go-live, both sides agree the last 12 months as the measuring stick. Then four numbers are tracked against it, monthly, in a report that is identical on your side and ours.
Labor CPOR
Labor cost per occupied room, by department, the headline saving, in your currency.
Overtime hours
Overtime by department and cause, so a saving never hides inside a burnout bill.
Roster build time
Manager hours spent scheduling, the 3-8 hours a week you get back.
Service coverage
Hours staffed to your agreed standard, watched alongside review scores, savings do not count if service slips.
If the saving is not there, you see it in the same report we do, that is the point of measuring against your baseline.
Start with one property and two departments
You do not sign the chain up on day one. The rollout starts on one property: baseline audit, property system connection, forecast calibration and two departments optimized end-to-end, with written monthly measurement against your baseline. Scale to the portfolio only after the numbers hold. See HotelCadence pricing →
Questions about the method
How long does it take to go live?
Once the connection to your property system (OPERA Cloud, Mews or Cloudbeds) is live, forecast calibration and backtesting on your history take 2-3 weeks. Most properties see their first optimized roster inside the first month after go-live.
Do you need write access to our property system?
No. The connection only reads. HotelCadence reads reservations, arrivals, departures, occupancy and rate data; it never changes anything in your property system, never touches guest folios and never changes a booking.
What if our data history is messy?
That is normal, the baseline audit in week one flags gaps and inconsistencies before calibration. Two years of reservation history is ideal; the model can start on less, and you see backtest accuracy on your own data before any roster is built.
Which departments can be scheduled?
Front office, housekeeping and F&B are the standard starting departments because their demand follows the property system signals (arrivals, departures, covers). Spa, concierge and maintenance can follow at rollout.
How is the saving proven?
Against a baseline you agree before go-live: last 12 months of labor cost per occupied room, overtime hours, roster build time and service coverage. The monthly report is identical on both sides, if the saving is not there, you see it the same month we do.
What happens if the saving is not there?
The monthly report says so, in the same numbers you agreed as the baseline, and you keep it. The subscription is annual with no long-term contract, so a negative answer ends there. Details on the HotelCadence pricing page.
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