How it works

Connect. Forecast. Schedule. Prove.

HotelCadence connects read-only to your PMS, Oracle OPERA Cloud via OHIP, Mews or Cloudbeds, in 1-2 weeks, 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, not quarters. No rip-and-replace, no change to guest service standards.

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Step 1 · Connect

What does the PMS connection actually involve?

A read-only API connection to Oracle OPERA Cloud via OHIP, Mews or Cloudbeds, live in 1-2 weeks. Your IT team grants scoped API credentials; nothing is installed on property and nothing writes back to the PMS.

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 PMS exposes them
Step 2 · Forecast

Why forecast before touching the roster?

Because 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 PMS 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 →

0%10%20%30%7 days14 days30 days60 days90 days7 days, Manual forecast error: 8%14 days, Manual forecast error: 11%30 days, Manual forecast error: 15%60 days, Manual forecast error: 22%90 days, Manual forecast error: 28%
Manual forecast error roughly triples from 7 to 90 days out, staffing from a stale forecast means paying for the gap.Source: Hospitality revenue-science literature, 2023-2025 (typical ranges)

The data behind this chart

Forecast horizonTypical manual error (MAPE)
7 days8%
14 days11%
30 days15%
60 days22%
90 days28%
Step 3 · Schedule

Who controls the roster, the AI or your managers?

Your managers. 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 your pilot.

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 AI hotel staff scheduling works →

Step 4 · Prove

How do you know it worked?

Every deployment starts with a baseline contract: before the pilot begins, 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 instead of our brochure.

Pilot before scale

Start with one property, two departments, 90 days

You do not sign the chain up on day one. The fixed-scope pilot, from US$7,500 per property, fully credited against year one on rollout, covers the baseline audit, PMS connection, forecast calibration and two departments optimized end-to-end, with the written measurement at day 90. Scale to the portfolio only after the numbers hold. See HotelCadence pricing →

Questions about the method

How long does it take to go live?

The PMS connection (OPERA Cloud via OHIP, Mews or Cloudbeds) takes 1-2 weeks. Forecast calibration and backtesting on your history take another 2-3 weeks. Most properties see their first optimized roster inside the first month of the 90-day pilot.

Do you need write access to our PMS?

No. The connection is read-only. HotelCadence reads reservations, arrivals, departures, occupancy and rate data; it never writes to your PMS, 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 pilot departments because their demand maps directly to PMS signals (arrivals, departures, covers). Spa, concierge and maintenance can follow at rollout.

How is the saving proven?

Against a baseline you agree before the pilot: 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 after the 90-day pilot?

You get a written measurement versus the agreed baseline. Roll out and the pilot fee (from US$7,500) is fully credited against the first-year subscription; walk away and the report is yours either way. Details on the pricing page.

Walk through the method on your data, book a demo

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