The room committing problem is the hidden cause of suboptimal occupancy and avoidable overbooking. Read how the cybHotel algorithm optimises room assignment, managing OTAs, housekeeping and complex constraints.
The “Room committing” problem”
The Room Committing Problem is the operational bottleneck that limits occupancy in hotels. It involves assigning a specific physical room to each reservation, rather than just a room type, taking into account dates, requested features, cleaning times and guest preferences. If managed poorly, the process generates empty rooms due to planning errors, overbookings and check-in delays, with a direct impact on revenue and the customer experience.
Many hotels assign the specific room immediately after booking. The reasons are manifold: sale of individual rooms, manual assignment by the front office, integration with PMSs that immediately set the room number.
This approach seems logical (“booking = room allocated”), but it carries the risk of potential inefficiencies. In fact, assigning too early:
- It reduces flexibility for future bookings.
- Create “gaps” that cannot be filled by other bookings.
- Increase the rejection rate, i.e. the number of requests rejected despite having rooms available.
- It reduces the possibility of immediate check-in upon guests' arrival
Fit Bookings Together Better
The literature on room committing [1,2] show that immediately assigning a specific room to each new reservation often leads to sub-optimal occupancy plans, with requests being rejected despite the number of rooms theoretically being sufficient.
The algorithms proposed in the scientific field tackle the problem by “interlocking” already accepted bookings more intelligently when a new request arrives, reducing the number of requests that cannot be accommodated in the room schedule.
The OTA Challenge
Rooming list management becomes even more complicated with bookings from external channels (OTA, portals, GDSThese systems do not know the real distribution of the specific rooms, but only how many rooms are available by type and by day.
When an OTA sells a room, it creates a reservation for a room type (e.g. “Superior Room”), not for a specific room (e.g. “Room 205”) and without taking the room plan into account.
Avoidable overbooking
Room committing is often delegated to the desk, with the result that a reservation is immediately assigned a room number.
This can generate avoidable overbookingnot due to excess demand, but to a sub-optimal allocation of rooms to already accepted bookings.
The optimal criterion for accepting a new booking provides that, for all days of stay, the total number of requested rooms is less than or equal to the total available, but this criterion is only necessary and does not guarantee that a feasible assignment to specific rooms exists.
Indeed, some bookings specifically require a particular room: regular guests, corporate contracts, accessibility needs. The allocation must guarantee that room for the entire duration.
Additionally, the rooms can be out of order for maintenance or technical problems, or temporarily unassignable because being cleaned.
The cybHotel Approach
The system cybHotel it takes up the idea of better interlocking bookings and brings it into operational practice, with an algorithm that works dynamically mainly at two key moments: at the time of booking at the time of check‑in.
1. At the time of Booking
When a new booking arrives (from an OTA, direct channel or elsewhere), the algorithm:
- Take into account all already accepted bookings and periods of unavailability
- Assess the new request against its constraints (dates, type, preferences).
- Recalculate a compatible assignment for the entire set (existing bookings + new one).
- Reassign rooms, if necessary, to maximise occupancy.
The algorithm acts as a bridge between the logic based on sales channel types and the reality of physical rooms.
2. At the Time of Check-in
The algorithm can also be executed at the time of the request for check‑in, when the guest is at the property. This is where constraints related to the actual status of the rooms (clean, being cleaned, to be cleaned, out of order) come into play, which purely theoretical models do not take into account.
If necessary, the algorithm reviews the assignment so that only rooms are assigned to the waiting customer already cleaned and ready, taking into account the priorities and constraints of the specific room. This drastically reduces waiting times and operational conflicts.
Operational Benefits
- Reduction of the rejection ratefewer requests rejected due to scheduling conflicts, with the same inventory.
- Increase in occupancy and RevPAR: more nights sold, with a greater impact in the high season and periods of high demand.
- Elimination of avoidable overbookingOverbooking due to sub-optimal allocations can be prevented.
- Smoother check-insconscious use of the cleaning status and assignment priorities.
- Greater front office efficiencyfewer manual reassignments, fewer desk conflicts and a drastic reduction in operational workload.
- Management of complex constraintsout-of-service rooms and restrictive assignments are managed efficiently
Conclusions
In room committing, the moment and the mod assigning specific rooms matters as much as the number of available rooms. Early committing leads to suboptimal occupancy and avoidable overbooking; a dynamic approach, which reassigns at the time of request and check-in, makes it possible to make better use of inventory, properly manage bookings and improve room turnover.
Article written with the support of Perplexity, an AI assistant for research and technical writing.