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Lecture 9

HTM 4454 Lecture Notes - Lecture 9: Leap Years, Effective Demand


Department
Hospitality and Tourism Management
Course Code
HTM 4454
Professor
Perdue
Lecture
9

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HTM 4454: Revenue Management
Section II: Process and Calculations
LO 7: Forecasting
1. Forecast Inventory
a. Overall room supply
b. Number of continuing guests/ check outs
c. By room (product type)
2. Forecast Demand For EACH RATE
a. Starting at Rack (BAR) and continue through the rate structure
b. Forecast booking curve/ reservations at each rate
3. Forecasting Components – for effective demand forecasts
a. Historical Data – using available historical data to develop a
preliminary estimate using an extrapolation method
b. Current Data – using current macro and micro economic data to
adjust the preliminary forecast
b.i. Reservations Pace data
b.ii. Events data
b.ii.1. Ex. HB2 in NC, Zika Virus in Miami
c. Future Data – adjust for anticipated changes in the market and
competitive environment
c.i. Ex. Transportation System changes
d. Qualitative/ feel adjustments – beware of getting too caught up in the
numbers and data
4. Hotel Data Tracking
a. Historical
a.i. By Day/ Segment
a.i.1. Fulfilled bookings
a.i.2. Reservations
a.i.3. Length of stay
a.i.4. STR Data
a.i.5. By Day
a.i.5.a. Occupancy rate %
a.i.5.a.i. By room type/ rate code
b. Current data
b.i. By Day/ Segment
b.ii. By Day
c. Future Data
5. Historical Data Forecasting
a. Time series days – sequence of days points, successive measurement
over a time interval – hourly, daily, weekly, etc.
b. Extrapolation models – predicting future trends based on the past
b.i. Assumption – underlying factors causing change are constant
c. Time Series types
c.i. Stationary- no significant upward of downward trend (no
discernable trend)
c.i.1. Forecasting – “smoothing” models to correct for
noise
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