Pearson New International Edition International pcl tp indd 1

FRONT OFFICE SEMANTICS
Group history:
Number of rooms blocked for and ultimately used by a group during similar events held
in the past.
Transient Guests
Most FOMs predict the booking activity of transient guests by use of historical and
current data. Accurate predictions of future data, however, are also critical. FOMs can
increase their knowledge of future data by examining trend lines, which are based on
internal and external data sources.
MANAGING FORECAST DATA
Objective 5
Introduce the
relationship between 
room demand forecasts 
and pricing, and note 
the need to evaluate the 
effectiveness of the 
demand forecasting 
process.
Objective 3
Explain how an FOM 
can use PMS data 
relating to transient 
and group guests to 
make room demand 
forecasts.
Objective 2
Discuss how 
historical, current, and 
future data help the 
FOM to estimate 
room demand.
Objective 4
Review the basic types 
of reports that FOMs 
can use to monitor and 
manage their guestroom 
demand forecasts.
Objective 1
Review the role and 
responsibilities of the 
FOM in the 
management of rooms 
forecast data.
Managing Occupancy 
Forecast Reports
Using Predictive 
Data Sources
Tracking Room 
Demand
The FOM as 
Forecaster
• Impact on Pricing 
• Evaluation of
Effectiveness
Other Forecasting 
Issues: 
ROADMAP 3
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FRONT OFFICE SEMANTICS
Trend line:
Documentation (usually displayed on a graph or chart) of changes in data values. Trend lines
may show increases, decreases, or no change in comparative data values.
Internal Data
FOMs can predict the reservation behavior of transient guests by analyzing several
important internal trend lines. Specific data important to a particular hotel are influ-
enced by the property’s unique characteristics; however, most FOMs evaluate inter-
nal trend lines relative to these data:
•
Occupancy percentage
•
Room count
•
Reservation activity
•
Cancellation activity
•
No-shows
•
Arrivals
•
Early departures
•
Stayovers
To see how internal data are used, consider Figure 8, which contains data about
the Altoona Hotel’s transient occupancy the past year and this year. It is time for the
FOM to predict July’s transient guest occupancy. Data analysis indicates that the
FOM should expect an increase in transient occupancy this July in comparison with
last July based on the current trend of this year’s monthly increases over the same
months last year. Although the amount, if any, of actual increase will not be known
until the end of July, a prediction of a 2 percent to 3 percent increase in transient
guest occupancy appears reasonable.
Figure 9 shows the information in Figure 8 in a bar graph. Note that the linear
trend line identified in the figure could easily be extended for the months beyond
June, even if last year’s data from July and subsequent months are not added to the
chart. Of course, when such data are added, the predictive validity of the trend line
is enhanced.
The mathematics involved in these projections may be of interest to some, but
most FOMs are content to allow their PMS to make the calculations. If a PMS does
not provide a forecasting feature, FOMs who are familiar with Microsoft Excel can