Forecasting Data
The process of forecasting room availability generally relies on historical occupancy data. To facilitate forecasting ,the following daily occupancy data should be collected:
Number of expected room arrivals
Number of expected room walk-ins
Number of expected room stayovers(rooms occupied on previous nights that will continues to be occupied for the night in question)
Number of expected room no-shows
Number of expected room understays(check-outs occurring before expected departure date)
Number of expected room check-outs
Number of expected room overstays (check-outs occurring after the expected departure)
Over- all, the above data are important to room availability forecasting since they are used in calculating various daily operating ratios that help determine the number of available rooms for sale.
Occupancy History of the ABC
Room Room Room Room
Day Date Guests Arrivals walkins Reser. Noshow
Mon 1/3 118 70 13 63 6
Tues 2/3 145 55 15 48 8
Wed 3/3 176 68 16 56 4
Thurs 4/3 117 53 22 48 17
Fri 5/3 75 35 8 35 8
Sat 6/3 86 28 6 26 4
Sun 7/3 49 17 10 12 5
Total 766 326 90 288 52
Occupied Overstay Understay Room
Rooms Rooms Rooms Check-outs
90 6 0 30
115 10 3 30
120 12 6 63
95 3 18 78
50 7 0 80
58 6 3 20
30 3 3 45
558 47 33 346
1. Percentage of No-shows – The percentage of no-shows indicates the proportion of reserved rooms that the expected guests did not arrive to occupy on the expected arrival data .This ratio helps the front office manager to decide, when and how many rooms can be sold to guests who come as walkins. The percentage of no-shows is calculated by dividing the
number of room no-shows for a specific period of time(day, week, month, or year) by the total number of room reservations for that period.
Percentage of No-shows = Number of Room No-shows
Number of Room Reservation
= 52/288x 100=18.06%
Some hotels track no-show statics in relation to guaranteed and non guaranteed reservations. Properly forecasting no-show rooms also depend on the hotels mix of business, eg corporate group generally have a much lower no-show %age than other types of groups or individual business .A hotel with a large corporate market will most likely have a very low no-show %age as compared to a hotel having little group business.
The %age of no-shows can be controlled through a number of
policies and procedures such as requesting deposit in advance from guests, call the guests before date of arrival to confirm arrangements, check the reputation of travel agents, tour operators ,duplicate reservations etc before confirming the reservations.
Percentage of walk-ins – The percentage of walk-ins is calculated by dividing the number of rooms occupied by walk-ins for a specific period by the total number of room arrivals for same period .The %age of hotel ABC can be calculated
as follows.
Percentage of walk-ins= number of walk-in rooms x100
Total number of room Arrival
= 90/326×100
= 27.61 %
Walk-in guests occupy available rooms that are not held for guests with reservations. Often, hotels can sell rooms to walk-in guests at higher rates since these guests may have less time & opportunity to consider alternate properties. Front desk agents are asked to show a guestroom to a walk-in guest—-which is much more effective than trying to sell
rooms over phone. Walk-in guest sales help to improve both occupancy and revenue. Walk-ins also give a chance to find new guests who can prove CIPs in future. However, from a planning perspective , it is always considered better to have reservations in advance than to count on walk-in traffic
Percentage of Overstays; – It represents rooms occupied by guests who stay beyond their originally scheduled departure dates. Overstay guests may have arrived with guaranteed or non-guaranteed reservations or as a walk-in. Number of overstay rooms for a period by the total number of expected room check-outs for the same period. The %age of overstay
for hotel ABC is calculated as under ͚
Percentage of Overstays = Number of Overstay Rooms
Number of Expected checkouts
= 47 x100
346-33+47
= 13.06 of exp. Checkouts
The process of forecasting room availability generally relies on historical occupancy data. To facilitate forecasting ,the following daily occupancy data should be collected:
(exp.checkouts= Actual check-outs-understay+under stay To help regulate room overstays , front-office agents are trained to verify an arriving guests departure date at the time of check-in. such verifications can be critical ,especially when the hotel is at or near full occupancy and there are no provisions for overstay guests. Overstays may also prove problematic when specific rooms have been blocked for arriving guests. This is especially important for suits or other rooms that
may have special importance to an incoming guest.
Percentage of Understays
It represents rooms occupied by guests who check-out before their scheduled departure dates. Understay guests may have arrived at the hotel with guaranteed or non-guaranteed reservations or walkins. The percentage of understays is calculated by dividing the number of understay rooms for a period by the total number of expected room
check-outs for the same period. Using the data given , the percentage of understays is calculated as under
Percentage of understay= Number of Understay Room
Number of Expected Check-outs
= 33 x100
346 -33 +47
= 9.17 % of expected check-outs
Guests leaving before their stated departure date creats empty rooms that typically are difficult to fill. Thus , understay rooms tend to represent permanently lost room revenue. Overstays ,on the other hand, are guests staying beyond their stated departure date and may not harm room revenue .when the hotel is not operating at full capacity, overstay results in additional, unexpected room revenues. To regulate understay and over stay rooms ,front office staff should
1. Confirm or reconfirm each guests departure date at registration. Some guests may already know of a change in plans, or a mistake have been made in the original processing of the reservation.
2. Present an alternate guestroom reservation card to a registered guest explaining that an arriving guest holds a reservation for his or her room. Guests may be informed in advance about their scheduled check-out date.
3. Review group history. Many groups ,especially associations ,holds large closing events for the entire group on the last day of meeting.
4. Contact potential overstay guests about their departure date to confirm their intention to checkout.
5. Room occupancy data should be examined each day, rooms with guests expected to check out should be flagged.
6. Guests who have not left by check-out time should be contacted and asked about their departure intention.
Forecast Formula
Once relevant occupancy statistic have been gathered, the number of rooms available for any given date can be determined
by the following formula;
Total number of Guestroom
– Number of out-of-order Rooms
– Number of Room stayovers
– Number of Room Reservations
– Number of Room Overstays
+ Number of Room reservations x %age of No-shows
+ Number of Room Understays
= Number of Rooms Available for sale
Note the above formula does not include walk-ins. The y are not included because the number of walk-ins a hotel can accept is determined by the number of rooms available for sale and it various on daily basis. Following data is available about Hotel ABC, calculate number of rooms available for sale
Total number of rooms 120, on April 1st. there are three out-of-order rooms, 55 stayovers, 42 scheduled arrivals (reservations) percentage of no-shows 18% .Based on the historical data ,six understays and fifteen over stays are also expected. The number of rooms projected to be available for sale on 1st. April can be determined as follows.
Total number of Guestroom =120
– Number of out-of-order Rooms = -3
– Number of Room stayovers = -55
– Number of Room Reservations= -42
– Number of Room Overstays = -15
+ Number of Room reser. x %age of no-shows=+8
(42 x 18 % = 8 rooms)
+ Number of Room Understays = +6
= Number of Rooms Available for sale = 19
Therefore ABC hotel is having 19 rooms for sale on 1st. April once this figure determined ,front office management can decide
1. Whether or not to accept more reservations
2. Helps to determine its level of staffing.
3. Helps to determine the number of rooms that cn be sold to walk-ins.
Front-office planning decisions must remain flexible ,as they are subjected to changes and room availability forecasts are based on assumptions whose validity may vary on any given day.
