Hotel chain software: one roster standard across every property, local law at each one
Hotel chain software is the workforce layer for the people side of a hotel group: one set of workload drivers, one forecast method, one labour standard per department and brand, and one monthly report across every property. HotelCadence runs on top of the property management system (PMS) at each property, the system its front desk uses, whether OPERA Cloud, Mews, Cloudbeds or Shiji, mixed groups included. Each hotel keeps its own shift rules, its own currency and its own department heads approving every roster. Priced per scheduled employee per month, from US$6, across the whole group.
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.
Eight properties, eight rosters, one labour report that takes three weeks
Picture a regional operations director with eight hotels across Bangkok, Singapore, Jakarta and Ho Chi Minh City. Three run OPERA Cloud, three run Cloudbeds, two run Mews. Each executive housekeeper rosters in a different spreadsheet. Someone assembles the monthly labour report by hand from eight payroll exports; it lands three weeks after month end and compares labour cost per occupied room across hotels that each define "occupied room" and "housekeeping hours" their own way.
Jakarta looks cheap because it is understaffed at check-in. Singapore looks expensive because it rosters for a Friday peak that stopped coming in 2024. Nobody at the regional office can say which hotel is run well.
A chain is the setting where the five-step method pays most, because the same drivers, the same forecast and the same labour standards make cost to standard comparable. That comparison is what lets the group move hours, share staff and set a budget that each property can meet. Optimizing the staff the group already employs comes first. Central automation projects follow, sized to the gap that remains. Read the five-step method on the how it works page.
Connect each PMS, standardise the method, keep the law local
- 1
Connect every property
Each property's system connects, whichever brand it runs, and HotelCadence only reads from it. Arrivals, departures, stayovers, room types, segments and covers flow per property into one data model, so a Bangkok breakfast and a Singapore breakfast are forecast from the same inputs.
- 2
Set brand standards, allow overrides
Minutes per check-in, minutes per departure room, covers per server: set per brand and service tier, overridden per property where the building or the market demands it. Overrides are visible, so the regional office knows why Jakarta differs.
- 3
Roster per property, inside its law
Each hotel gets its own forecast per department per hour and its own roster, drafted inside the working-hour limits, rest rules and overtime caps of its market. Each market's rules are configured once during onboarding and reused at every property in that market.
- 4
Share staff, report once
Cross-trained staff move between nearby properties when one has the larger peak. The same four numbers report monthly per property and for the group: labour cost per occupied room, overtime, roster build time, service coverage.
What hotel chain software adds above the property
Mixed PMS estates
OPERA Cloud, Mews, Cloudbeds, Shiji, Infor HMS, protel and Amadeus properties in one portfolio. A system change at one hotel changes one connection, nothing else.
Brand-level standards, property overrides
One labour standard per department and brand, with named exceptions per property. Cost to standard means the same thing at every hotel, so the comparison is fair.
Float pools across properties
A Singapore group runs one front-desk pool across three properties; agents move to the hotel with the larger evening peak. Contract rules and skills travel with them.
Labour law per market
Statutory hours, overtime caps and rest rules differ by country. Each property's roster is drafted inside its own market's rules; the group sees compliance per hotel in the same report.
Currency and wage per property
Rosters cost in THB, SGD, IDR or VND at that property's wage grid; the group report converts for the comparison and keeps the local figure beside it.
Role-based access
Department heads edit and approve their own rosters. Cluster managers see their hotels. The regional office sees the portfolio. Finance sees the monthly report. Nobody sees more than their role needs.
What each level sees and decides
| Question | Property level | Group level |
|---|---|---|
| Who approves the roster? | The department head, every time | Nobody at group level; the group sets the standard and reads the result |
| Where does demand come from? | This property's PMS and POS, per department per hour | The same drivers at every property, so forecasts are comparable |
| What is the labour standard? | The brand standard, with this property's named overrides | One standard per department and brand, overrides listed |
| Which labour law applies? | This market's pack: hours, overtime caps, rest rules | Compliance status per property in the monthly report |
| Can staff work at another hotel? | Yes, from a shared float pool with its own contract rules | Pool size and utilisation per cluster |
| What is reported monthly? | Labour cost per occupied room, overtime, build time, coverage against this property's baseline | The same four numbers per property and for the group, same baseline method |
The group owns the method and the number. The property owns the roster. That split is what keeps department heads in charge and the comparison honest.
Three properties, one front-desk pool, check-in wait down 40%
A Singapore group put three city properties on one front-desk float pool and rostered each desk to its own arrival curve. Average check-in wait fell 40% against the baseline while front-office hours across the group fell 7%, at 81% occupancy. Read how it was measured in the Singapore front desk peaks case study.
The same method, applied per property, returned a 9.8% F&B labour saving in Bangkok and a 14% low-season F&B saving in Bali, each against a signed baseline. See all measured results.
Questions regional and group teams ask
Is hotel chain software from HotelCadence a multi-property PMS?
No. A multi-property PMS runs reservations, rates and rooms across the group. HotelCadence runs the people side on top of whichever PMS each property has: demand forecast, labour standards, rosters, attendance and payroll preparation, with a portfolio view. It only reads from them and replaces nothing.
Our properties run different PMS brands. Does that matter?
No. Each property connects through its own system (OPERA Cloud, Mews, Cloudbeds, Shiji, Infor HMS, protel, Amadeus and others) into one shared view. The regional office sees the same drivers and the same report whichever system sits underneath.
How many properties does it take to be worth it?
The group layer earns its place from two properties that share staff or compare cost. Most chains start with one property and two departments, agree the baseline, prove the saving in the monthly report, then roll out by cluster. From 20 properties a partnership plan adds regional data residency and a dedicated success manager.
How is hotel chain software priced?
Per scheduled employee per month, from US$6 for Run the day to US$9 for Develop the team, across the whole group, with local-currency equivalents on the pricing page. Forecasting and auto-scheduling live in Predict and automate. There is no long-term contract.
Can the regional office override a property's roster?
No. The group sets the labour standard and reads the result. The department head at each property edits and approves every roster, because they carry the service promise. Overrides to the standard are named and visible, so the comparison stays fair.
In what order do you roll out across a chain?
One property, two departments, a twelve-month baseline agreed in writing. Live in weeks. The first monthly report proves or disproves the saving. Then the next cluster, with the standards already set and the labour law packs already configured for each market.
30 minutes · your own PMS data if you share access · no obligation.