Cut hotel labor costs 6–12% without cutting guest service.
HotelCadence is AI workforce management software for hotels: it turns live PMS data into hour-by-hour demand forecasts, then builds the lowest-cost roster that still hits your service standard. Built for hotel chains.
The data behind this chart
| Hour | Staff required | Manager's forecast | Staff scheduled |
|---|---|---|---|
| 06:00 | 14 | 16 | 16 |
| 07:00 | 22 | 20 | 16 |
| 08:00 | 30 | 24 | 24 |
| 09:00 | 26 | 24 | 24 |
| 10:00 | 20 | 22 | 24 |
| 11:00 | 24 | 22 | 22 |
| 12:00 | 26 | 22 | 22 |
| 13:00 | 20 | 20 | 22 |
| 14:00 | 16 | 18 | 18 |
| 15:00 | 18 | 18 | 18 |
| 16:00 | 24 | 20 | 18 |
| 17:00 | 30 | 24 | 24 |
| 18:00 | 36 | 28 | 28 |
| 19:00 | 38 | 28 | 28 |
| 20:00 | 34 | 26 | 28 |
| 21:00 | 26 | 22 | 22 |
| 22:00 | 18 | 18 | 18 |
| 23:00 | 14 | 16 | 18 |
A 250-room property leaks roughly US$6,000–9,000 a week to rosters built on gut feel, overtime on the days demand was under-called, idle paid hours on the days it was over-called. See what it costs you →
Your PMS knows tomorrow's arrivals. Your roster doesn't.
The Saturday roster is built on Tuesday
Your F&B manager locks the breakfast roster five days out, then a tour group books 80 rooms on Thursday night, and Saturday runs on overtime and apologies.
The data exists. It just never reaches the schedule.
49% of hoteliers say they can't access the data they need; 40% blame disconnected systems. Arrivals, departures and pickup sit in the PMS while the roster is a spreadsheet.
3–8 hours a week, per department head, in Excel
And the 90-day manual forecast that roster is built on runs ~28% error, so the hours are spent building a schedule that's wrong before it's printed.
Connect. Forecast. Schedule. Prove.
Live in weeks, not quarters, no rip-and-replace.
- 1
Connect your PMS
OHIP, Mews or Cloudbeds API, read-only access, connected in 1–2 weeks with guided onboarding.
- 2
Forecast demand
AI forecasts arrivals, departures, occupancy and covers, per department, per hour, refreshed as pickup changes.
- 3
Draft the roster
The lowest-cost, skills-matched schedule that still hits your service standard. AI drafts; your managers approve.
- 4
Prove the saving
Measured monthly against your agreed baseline: labor cost, overtime, build time, coverage.
One hotel, one Saturday. Flip the roster.
Same demand, two schedules. Toggle between the gut-feel roster and the demand-matched one, the amber line is what the PMS knew was coming.
Worked example, figures indicative, based on a 250-room city property.
From PMS data chaos to tonight's roster
See everything
PMS data insights. One live view across Opera Cloud, Mews and Cloudbeds, occupancy, pickup, RevPAR and labor cost per occupied room, refreshed every 15 minutes.
PMS data insights →Know what's coming
AI demand forecasting. Hourly, department-level forecasts that cut forecast error by ~20 points versus 90-day spreadsheet forecasts.
AI demand forecasting →FlagshipStaff to the curve, not the calendar
AI staff scheduling. The lowest-cost, skills-matched roster built against the forecast, 6–12% labor savings, managers stay in charge.
AI staff scheduling →Numbers first. Names on request.
Measured results, property anonymized at client's request.
Measured results, property anonymized at client's request.
Measured results, property anonymized at client's request.
“We stopped arguing about the roster. The forecast is on the screen, the schedule follows it, and overtime came down 18% in the first quarter.”
You can't hire your way out. You can schedule your way out.
APAC is opening 430,000 new hotel rooms while travel & tourism faces a projected 8.6-million-worker gap by 2035 (WTTC). The staff you can't hire has to come from the hours you already pay for.
Every budgeting cycle you wait, a 250-room property leaves US$300,000+ unrecovered. See the full APAC numbers →
The data behind this chart
| Market | Shortfall (millions) |
|---|---|
| China (all sectors) | 16.9 |
| India (all sectors) | 11 |
| Hospitality, global | 8.6 |
The questions every ops director asks first
Does HotelCadence replace our PMS?
No. HotelCadence is an intelligence layer on top of Oracle OPERA Cloud (via OHIP), Mews or Cloudbeds. It reads reservations, arrivals, departures and occupancy through each PMS’s official API, read-only, no rip-and-replace, and turns them into hourly demand forecasts and rosters.
How long does setup take with OPERA Cloud, Mews or Cloudbeds?
Typically 1-2 weeks from API access to your first forecast. OHIP, the Mews API and the Cloudbeds API are standard, guided in-product connections, approve read-only access, and the platform calibrates its forecasts automatically against up to two years of your history.
Will guest service scores drop if we cut labor cost?
The optimizer schedules to your service standard first, then minimizes cost, it moves hours from empty mornings to the check-in peak rather than removing them from busy shifts. Engagements are measured on both labor cost AND service coverage against an agreed baseline.
What data access does HotelCadence need?
Read-only API access to your PMS (reservations, arrivals/departures, occupancy, rate and segment data) and, where relevant, POS covers. No guest personal data is required for forecasting or scheduling.
How is ROI measured?
Before the pilot we agree a baseline: labor cost per occupied room, overtime hours, schedule-build time and service coverage. Every month you get the same numbers measured against it, if the saving is not there, you see that too.
Find your labor-cost gap in one 30-minute call.
Share read-only PMS access beforehand and the demo runs on your own occupancy data, you leave with a written estimate of your gap, whether or not we work together.
“Within the pilot quarter the roster build went from five hours to forty minutes a week.”