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Lecture 4

HTM 4454 Lecture Notes - Lecture 4: Revpar

Hospitality and Tourism Management
Course Code
HTM 4454

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LO4: Hotel Math Fundamentals
1. STR History
a. Randy Smith
a.i. Collected data for existing mailing list in ‘80s to help create
valid research for complete feasibility studies during the
a.i.1. Rooms available
a.i.2. Rooms sold
a.i.3. REVPAR
b. HVS (Hospitality Valuation Services) – largest hotel feasibility studies
company in the world
2. Internal KPIs (6 total)
a. Occupancy – %
b. ADR – $
c. REVPAR – $ (considered most important)
c.i. Differs from ADR because it is affected by amount of
unoccupied rooms
c.ii. ISSUE WITH REVPAR – This is ONLY counting room revenue
and ignores F&B, Events, etc. revenue
c.ii.1. Especially important for conference hotels
c.ii.2. Data isn’t available for other outlets
c.iii. ISSUE WITH REVPAR – It is a top-line measure – revenue is
great, but we are really looking at PROFIT as well
d. Percent changes (This year – Last year)/ Last year*100
d.i. Occupancy, ADR, and REVPAR
d.ii. Most important indicator is % change REVPAR
3. External KPIs (6 total – 3 Indexes, 3 rating data)
a. Competitive Set Data – group of hotels used primarily for comparison
against a subject property for performance benchmarking purposes
b. The properties that comprise a comp set are competitive in nature;
competing for the same guests and sharing similar qualitative and
quantitative features
b.i. These properties may be geographically dissimilar
c. KPIs for the competitive set – how do you derive?
c.i. KPIs derived based upon he aggregated raw data for each
separate hotel in the comp set
c.i.1. Aggregate data can result in misleading results
d. Including or Excluding Subject Hotel is at the discretion of the each
e. Index Numbers
e.i. (Subject Value/ Comp Set Value)*100
e.i.1. Over 100 – outperformed comp set
e.i.2. Under 100 – underperformed comp set
f. Bandwidth
f.i. Tracks the low and high of the comp set and compares to
subject hotel
f.i.1. Occupancy, ADR, and REVPAR
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