Hotel Math 101
(the Metrics behind
STAR Reports and Data)
The SHARE Center
Supporting Hotel-related Academic Research and Education
Steve Hood
Senior Vice President of Research
Smith Travel Research
Outline
• Property Data
• Comp Set Data
• Industry Data
• Corporate Data
• International Issues
• Additional Data
Property Data
Starts with Raw Data
• ____________for every hotel is obtained from
clients via corporate feeds or web entry
• Sample monthly file:
Hotel ID
12345
23456
34567
45678
56789
Hotel Name
Fairfield Memphis
Courtyard Nashville
Marriott Knoxville
Renaissance Atlanta
Residence Inn DC
Date Rooms Available
201007
3,100
201007
6,200
201007
9,300
201007
7,750
201007
4,650
Rooms Sold Room Revenue
2,000
200,000
4,000
450,000
7,000
1,000,000
6,000
900,000
3,000
390,000
• Daily file would look the same except for the
date field, YYYYMMDD or 20100725
STR Data Guidelines
• Supply (__________) – the number of rooms
in a hotel multiplied by the days in the month
• Demand (_________) – number of rooms sold
by a hotel, does not include comp rooms or
“no-shows”
• Revenue – total room revenue generated from
the _________, includes __________not
resort fees, nothing else such as _______
Key Performance Indicators
From these raw data values, STR calculates the
three key performance indicators (KPIs), which are
used for reports:
•
Occupancy - %
•Average Daily Rate (ADR)- $
•Revenue per Available Room (RevPAR)- $
important metric, based upon all rooms, some
feel like it is better measurement of profitability
Occupancy
Definition
The percentage of available rooms that were
sold during a specific time period.
Calculation
Occupancy is calculated by dividing the demand
(number of rooms sold) by the supply (number of
rooms available), this is a percentage
Occupancy = Demand / Supply
Monthly Occupancy - Formula
A
B
1
C
Supply Demand
D
Revenue
2
Jan-10
3100
2345
198765
3
Feb-10
2800
2002
175432
4
Mar-10
3100
1776
175012
5
Apr-10
3000
2468
234567
6
May-10
3100
2987
312345
E
F
(Formula)
G
Occupancy
(%)
2345/3100
You could multiply times 100 or format as a percentage
75.65%
ADR
Definition
A measure of the average rate paid for rooms
sold during a specific time period.
Calculation
ADR is calculated by dividing the room revenue
by the demand (rooms sold), this is a dollar
amount
ADR = Revenue / Demand
Monthly ADR - Formula
A
1
B
C
D
Supply
Demand
Revenue
E
F
G
(Formula)
ADR ($)
2
Jan-10
3100
2345
198765
198765/2345
84.76
3
Feb-10
2800
2002
175432
175432/2002
87.63
4
Mar-10
3100
1776
175012
98.54
5
Apr-10
3000
2468
234567
95.04
6 May-10
3100
2987
312345
104.57
You could format as a “$” or as a number with 2 decimals
RevPAR
Definition
A measure of the revenue that is generated by a
property in terms of each room available. This
differs from ADR because RevPAR is affected by
the amount of unoccupied rooms, while ADR only
shows the average rate of rooms actually sold.
Calculation
RevPAR is calculated by dividing the dividing the
room by the average rate of rooms actually sold.
RevPAR = Revenue / Supply
Monthly RevPAR – Formula
A
1
B
C
D
Supply
Demand
Revenue
E
F
G
(Formula) RevPAR ($)
2
Jan-10
3100
2345
198765
D2/B2
64.12
3
Feb-10
2800
2002
175432
D3/B3
62.65
4
Mar-10
3100
1776
175012
D4/B4
56.46
5
Apr-10
3000
2468
234567
D5/B5
78.19
6 May-10
3100
2987
312345
D6/B6
100.76
You could format as a “$” or as a number with 2 decimals
Percent Changes
Definition
The comparison of s(TY) numbers vs. Last
year(LY) numbers. The percent change
illustrates the amount of growth (up, flat, or
down) from the same period last year.
Calculation
Percent Change = ((This Year – Last Year) /
Last Year) * 100
Demand Percent Change
A
B
C
D
1
This Year
Last Year
2
Demand
Demand
E
F
G
Percent Change
(Formula)
Demand
3
Jan-10
2345
2456
-4.52
4
Feb-10
2002
2112
-5.21
5
Mar-10
1776
1750
1.49
6
Apr-10
2468
2345
5.25
7
May-10
2987
2555
16.91
You could multiply times 100 or format as a percentage
ADR Percent Change
A
B
C
D
1
This Year
Last Year
2
ADR
ADR
3
Jan-10
84.76
81.93
4
Feb-10
87.63
88.85
5
Mar-10
98.54
100.07
6
Apr-10
95.04
95.24
7
May-10
104.57
116.93
E
F
G
Percent Change
(Formula)
You could multiply times 100 or format as a percentage
ADR
Daily vs. Monthly Data
• Formulas for KPIs and Percent Changes are
the same
• The date fields are different:
201007 – monthly
20100725 – daily
• Most daily percent changes are based upon
________, in other words
_____________________________
Thu 20100715 compared to Thu 20090716
Sat 20100731 compared to Sat 20090801
Multiple Time Periods
• Multiple time periods for monthly data include:
Year-to-Date (YTD)
Running 12-Month (12 Month Moving Avg)
Running 3-Month
• Multiple time periods for daily data include:
Current Week
Month-to-Date (YTD)
Running 28-Day (different than Running 4-wk)
• The metrics for these time periods are based upon
the aggregated raw data.
YTD Supply, Demand, & Revenue
A
1
B
C
D
Supply
Demand
Revenue
2
Jan-10
3100
2345
198765
3
Feb-10
2800
2002
175432
4
Mar-10
3100
1776
175012
5
Apr-10
3000
2468
234567
6
May-10
3100
2987
312345
7
(Formula)
8
May YTD
sum(B2:B6)
15100
sum(C2:C6)
11578
Use the SUM function to aggregate the raw values
sum(D2:D6)
1096121
YTD Occupancy, ADR, & RevPAR
A
1
B
C
Supply Demand
D
E
Revenue
Occupancy
2
Jan-10
3100
2345
198765
3
Feb-10
2800
2002
175432
4
Mar-10
3100
1776
175012
5
Apr-10
3000
2468
234567
6
May-10
3100
2987
312345
7
YTD
15100
11578
1096121
8 (Formula)
F
76.7
G
ADR RevPAR
94.67
C7/B7*100 D7/C7
Aggregate raw values, then apply same formulas as before
72.59
D7/B7
Other Multiple Time Periods
• The Raw data for other monthly and daily time
periods are calculated the same way by
aggregating the raw data for every month or day
in the entire time period
• The calculated metrics (Occupancy, ADR, and
RevPAR) for multiple time periods are always
calculated from ___________________
• Numbers for multiple time periods never use
averages of monthly values
Percent Changes for Multiple
Time Periods
• The percent changes for multiple time periods are
based on the aggregated values or the calculated
metrics which are derived from the aggregated
values for this year compared to the same
values for last year
• Percent changes for daily data are based upon
groups of comparable days, with the exception of
Month-to-Date numbers which are based on a
date-to-date comparison
YTD Percent Changes
A
B
C
D
E
F
G
H
I
This Year
Supply
J
DemOccuand Revenue pancy
M
N
O
Jan-10
3100
2345
198765
3100
2456
201234
3
Feb-10
2800
2002
175432
2800
2112
187654
4
Mar-10
3100
1776
175012
3100
1750
175123
5
Apr-10
3000
2468
234567
3000
2345
223344
6
May-10
3100
2987
312345
3100
2555
298765
7
YTD
94.67 72.59 15100 11218 1086120
P
Percent Changes
OccuRevRevenue pancy ADR PAR
2
76.7
ADR
Rev- Sup- DemPAR ply
and
Date
8 (Formula)
L
Last Year
1
15100 11578 1096121
K
74.3 96.82 71.93
Occupancy
ADR
3.2
RevPAR
-2.2
0.9
(E7-K7)/K7*100 (F7-L7)/F7*100 (G7-M7)/G7*100
Aggregate 1st, KPI formulas 2nd, % Change formulas 3rd
Full Availability – Subject Hotel
• Occasionally a subject hotel may report a Supply
number that is different than the number of rooms
in the property times the days in the period
• If this happens in the case of the subject hotel,
their STAR report will always reflect the Supply
and the corresponding Occupancy based upon
the number _________________.
• STR does not change the Supply number of the
subject hotel on their own STAR report
Full Availability Example - Subject
A
1
B
C
D
E
F
Report# Actual
ed
Date Rms Supply Supply Demand Revenue
G
H
Formula
Occupancy
2 Jan-10 100
3100
3100
2345
198765 D2 / E2 * 100
75.6
3 Feb-10 100
2800
2744
2002
175432 D3 / E3 * 100
73.0
4 Mar-10 100
3100
2945
1776
175012 D4 / E4 * 100
60.3
5 Apr-10 100
3000
2700
2468
234567 D5 / E5 * 100
91.4
6 May-10 100
3100
3100
2987
312345 D6 / E6 * 100
96.4
Occupancy for Subject based on reported Supply, not Actual
Weekday/Weekend and Day of
Week Data vs. Monthly Data
• Sometimes a hotel will submit daily data that
does not add up exactly to the monthly number
• There are good reasons for this; some systems
do not accept adjustments to daily data, only to
the month numbers
• STR will slightly adjust the daily numbers based
upon the monthly data when they are aggregated
by day of week and weekday/weekend
Use percentages for each day, ensures WD/WE adds up
Percent Changes and WD/WE or
Day of Week Data
• ____________ (WD/WE) Percent Changes
compare all the aggregated weekday or
weekend data (per month or other time period)
this year to the same data last year
• ____________(DOW) Percent Changes
compare all the aggregated daily data for a
single day (per month or other time period) this
year to the same data last year
Running 4 Week Data
• The Weekly Reports compare individual daily
data for the Current Week to the Running 4
Week numbers
• The Running 4 Week numbers are the
aggregated data __________________, i.e.:
_____________
• A hotel can compare their Monday performance
metrics to the average of the last 4 Mondays
Competitive Set
Data
Key Performance Indicators
for the Competitive Set
• Numbers for the comp set are derived based on
aggregated raw data
• Supply, Demand, and Revenue numbers are the
combined values of each hotel in the comp set
• Occupancy, ADR, and RevPAR numbers are
bases on the aggregated Supply, Demand, and
Revenue
Including or Excluding the Subject
Hotel in the Competitive Set
• STR allows companies to choose whether to
include or exclude the data for the subject hotel in
the numbers for the comp set
• Historically companies usually included the data
for the subject hotel, but more recently most
companies have decide to exclude the subject
• People feel that having the subject data included
in the comp set numbers distorts the comp set
Comp Set Supply, Demand, & Revenue
A
B
C
D
E
Supply
Demand
Revenue
1
Property
Date
2
11111
May-10
3100
2222
187654
3
22222
May-10
3255
2468
198765
4
33333
May-10
2945
2345
223344
5
44444
May-10
2790
1987
165432
6
5555
May-10
3410
3210
298765
7
Comp Set
May-10
15500
12232
1073960
8
(Formula)
sum(C2:C6)
sum(D2:D6)
sum(E2:E6)
Aggregate raw values for each member of the comp set
Comp Set Occupancy, ADR, & RevPAR
A
1
Property
B
Date
C
D
E
F
G
H
Supply
Demand
Revenue
Occupancy
ADR
RevPAR
2
11111 May-10
3100
2222
187654 71.7
84.46 60.53
3
22222 May-10
3255
2468
198765 75.8
80.54 61.06
4
33333 May-10
2945
2345
223344 79.6
95.24 75.84
5
44444 May-10
2790
1987
165432 71.2
83.26 59.29
6
5555 May-10
3410
3210
298765 94.1
93.07 87.61
7
Comp Set May-10
15500
12232
8
(Formula)
1073960
78.9 87.80
69.29
D7/C7*100 E7/D7 E7/C7
Apply KPI formulas to aggregated comp set data
Percent Change Numbers
for the Competitive Set
• Percent Change numbers for the comp set are
calculated similarly to the ones for the subject
property
• These numbers show increases or decreases in
performance this year versus last year
Comp Set Occupancy, ADR, & RevPAR
Percent Changes
A
1
2
B
C
D
E
This Year
OccuDate pancy ADR
G
H
I
J
Last Year
Rev- OccuPAR pancy
3 Comp Set May-10 78.9 87.80 69.29
4 (Formula)
F
82.6
ADR
K
Percent Changes
RevPAR
93.86 77.50
Occupancy
-4.4
ADR
RevPAR
-6.5
-10.6
(C7-F7)/F7*100 (D7-G7)/G7*100 (E7-H7)/H7*100
Calculate TY & LY KPIs, then apply % Change formulas
Index Numbers
• The Index numbers compare the performance of
the subject property to the comp set
Subject / Comp Set * 100
• A number greater than 100 means the subject
property _outperformed___________ the comp
set and a number below 100 means the comp set
______________the subject property
• Index numbers are available for Occupancy,
ADR, RevPAR and the Percent Changes
Index numbers are percentages, multiple * 100 or format as %
Occupancy, ADR, & RevPAR Indexes
A
B
C
D
Subject Property
1
2 May-10
Occupancy ADR
E
F
G
Comp Set
H
I
Index Numbers
Rev- OccuRevPAR pancy ADR PAR Occupancy
96.4 104.57 100.76
J
ADR
78.9 87.80 69.29
3 (Formula)
Calc KPIs for Subject & Comp, then apply Index formula
RevPAR
Index Percent Change Numbers
• First you calculate the Index numbers this year
for Occupancy, ADR, and RevPAR
• Next you calculate the Index numbers for last
year using the same formulas
• Then you can calculate the Percent Changes for
the Index numbers, this shows whether the
Subject is improving
• Indexes could be below 100 TY, but if Percent
Changes are positive, Subject is improving
Occupancy, ADR, & RevPAR Index
Percent Changes
A
B
C
D
1
E
F
G
H
I
J
Index Numbers
2
This Year
3
Date
4
May-10
5 (Formula)
Last Year
Percent Change
OccuOccupancy ADR RevPAR pancy ADR RevPAR Occupancy
122.1 119.1
145.4
99.8 124.6
124.4
22.3
(B2-E2)/E2
*100
ADR
RevPAR
-4.4
(C2-F2)/F2
*100
Calc indexes TY & LY, then apply % Change formulas
16.9
(D2-G2)/G2
*100
Ranking Data – What is it?
• STAR Property Reports include Ranking
information for Occupancy, ADR, RevPAR and
each Percent Change, comparing the subject
hotel to the comp set
• The Ranking data would be in the format of “X of
Y”, where X is the subject hotel’s position and Y
is the number of participating properties in the
comp set, for example “2 of 7” would mean the
subject hotel had 2nd best value in the comp set of 7
Ranking data gives you more than just the KPIs & Indexes
Occupancy Ranking Data – How?
• The values for each hotel in the comp set
including the subject hotel are sorted and then
the position of the subject hotel is determined
within the group
STR#
Value
Rank
1234
87
1 of 6
2345
85
2 of 6
3456
83
3 of 6
4567
(Subject)
82
4 of 6
5678
78
5 of 6
Subject had the 4th highest occupancy in the comp set of 6
6789
75
6 of 6
ADR Ranking Data – Ties
• If two or more hotels are tied, i.e.: they have the
same value, then each hotel would get the same
number
STR#
Value
Rank
1234
$97
1 of 6
2345
$95
2 of 6
3456
$95
2 of 6
4567
(Subject)
$95
2 of 6
5678
$92
5 of 6
Subject had the 2nd highest ADR (with 2 others) in comp set
6789
$88
6 of 6
Multiple Time Periods and
Comp Set Data
• Multiple time periods are handled the same way
for a comp set as they are handled for a subject
property
• The Raw data for monthly and daily time periods
are always aggregated and then calculations are
applied to the aggregated data
Sufficiency of Comp Set Data
• If a Comp Set has 3 or more participating hotels
(submitting actual data) then that comp set is
defined as “Sufficient”
• The numbers for that comp set can then appear
on the STAR report
• Multi-year numbers are considered to be
sufficient if greater than 50% of the months or day
included in the multi-year period are sufficient
Full Availability and Comp Sets
• Occasionally a hotel in the comp set may report a
Supply number that is different than the number
of rooms in the property times the days in the
period
• In those cases, STR uses the Supply number
based upon full availability, not the number that
the hotel reports
Full Availability Example
A
1
B
PropertyDate
C
D
E
F
G
H
I
Occu- OccuActual Reported
pancy pancy
# Rms Supply Supply Demand Revenue (Full) (Report)
2
11111 May-10 100
3100
3100
2222
187654
3
22222 May-10 105
3255
3340
2468
198765
4
33333 May-10
95
2945
2900
2345
223344
5
44444 May-10
90
2790
2199
1987
165432
5555 May-10 110
3410
3410
3210
298765
15500
(14949)
6
7
Comp Set May-10
8 (Formula)
sum
(D2:D6)
12232 1073960
sum
(F2:F6)
sum
(G2:G6)
78.9
D7/F7
*100
Formulas are based upon Actual Supply, not Reported
(81.8)
Non-Reporting Hotels in the
Comp Set
• There may be situations where one or more
hotels in a comp set does not report data for a
month or more
• First, the Supply, Demand, and Revenue for the
participating properties is aggregated. This is
the “Sample” Supply, Demand, and Revenue.
• Next, an Occupancy and ADR is calculated
based on the Sample data
Non-Reporting Hotels in the
Comp Set - continued
• Then the Supply is determined for all hotels in
the comp set, simply the number of rooms times
the days in the month. This is referred to as the
“Census” Supply.
• This Supply number is multiplied times the
Sample Occupancy to derive the Census
Demand
• The Census Demand is multiplied times the
Sample ADR to derive the Census Revenue
Non-Reporting Hotel Example
1
A
B
Property
Date
C
D
Supply
# Rms (Actual)
E
F
Demand
Revenue
2
11111
May-10
100
3100
2222
187654
3
22222
May-10
105
3255
2468
198765
4
33333
May-10
95
2945
2345
223344
5
44444
May-10
90
6
5555
May-10
110
3410
3210
298765
410
12710
10245
908528
500
15500
12494
1107961
7
8
9
Comp Set
Sample #s
Comp Set
Census #s
(Formula)
C7 * 31
D8 * G7 /
100
G
Occupancy
E8 * H7
Calc Occ & ADR based on Sample, multiply * Total Supply
80.6
H
ADR
88.68
Industry Data
Industry Data Basics
• STR uses a variety of segments to analyze
performance of the hotel industry
• There are __________(market, tract) and
________ (scale, location) categorizations
• STAR Reports and corporate data files will
frequently compare a subject hotel to nearby
industry segments
• Publications and Destination Reports will also
display the performance of industry segments
The Methodology for Industry
Data versus Comp Set Data
• The methodology used for arriving at industry
numbers is different than the one for arriving at
comp set numbers
• Actual data is used for hotels that participate and
“modeled data” is used for hotels that do not
participate
• The Actual and Modeled data is aggregated for
all hotels in each industry segment
Modeling of Industry Data
• STR estimates the data of non-participating
hotels to help increase the accuracy of industry
data
• Data for a non-participant is estimated based on
participating hotels that are closest to the nonparticipant based on geography and price level
• No modeled data is ever used in the Comp Set
numbers
Possible to explain technical procedure used for modeling
Key Performance Indicators
for Industry Segments
• The Actual and Modeled data is aggregated for
all hotels in each industry segment
• Supply, Demand, and Revenue numbers are the
combined values of each hotel in the comp set
• Occupancy, ADR, and RevPAR numbers are
based on the aggregated Supply, Demand, and
Revenue
Industry Supply, Demand, & Revenue
1
A
B
Property
Date
C
D
# Rms Type of Data
E
F
G
Supply
Demand
Revenue
2
11110
May-10
100
Actual
3100
2222
187654
3
22220
May-10
105
Actual
3255
2468
198765
4
33330
May-10
95
Modeled
2945
2345
223344
5
44440
May-10
90
Actual
2790
2456
234567
6
5550
May-10
110
Modeled
3410
3210
298765
7
6660
May-10
85
Actual
2635
2511
201234
8
7770
May-10
115
Actual
3565
3012
312345
21700
18224
1656674
9
Tract Scale
10 (Formula)
700
sum
(E2:E8)
sum
(F2:F8)
Accumulate Actual & Modeled Supply, Demand, & Revenue
sum
(G2:G8)
Industry Occupancy, ADR, & RevPAR
A
1
Property
B
C
Date
D
E
F
G
11110 May-10
100
Actual
3100
2222
187654
3
22220 May-10
105
Actual
3255
2468
198765
4
33330 May-10
95 Modeled
2945
2345
223344
5
44440 May-10
90
Actual
2790
2456
234567
6
5550 May-10
110 Modeled
3410
3210
298765
7
6660 May-10
85
Actual
2635
2511
201234
8
7770 May-10
115
Actual
3565
3012
312345
10 (Formula)
I
#
Type of
OccuRms Data
Supply Demand Revenue pancy ADR
2
Tract
9 Scale
H
700
21700
18224 1656674 84.0
J
RevPAR
90.91 76.34
F9/E9
*100 G9/F9 G9/E9
Apply KPI formulas to accumulated raw data
Percent Change Numbers
for the Industry Segment
• Percent Change numbers for the industry
segment are calculated exactly like the ones for
the comp set or the subject property
• These numbers show increases or decreases in
performance this year versus last year
Multiple Time Periods and
Industry Data
• Multiple time periods are handled exactly the
same for an industry as for a comp set or a
subject property
• The Raw data for monthly and daily time periods
are always aggregated and then calculations are
derived based upon the aggregated data
Sufficiency of Industry Data
• If an Industry segment has 4 or more hotels that
submit actual data, then that segment is defined
as “Sufficient”
• The numbers for that industry segment can then
appear on STAR reports and elsewhere
• Multi-year numbers are considered to be
sufficient if greater than 50% of the months or day
included in the multi-year period are sufficient
Full Availability
• Occasionally a hotel in the industry segment may
report a Supply number that is different than the
number of rooms in the property times the days in
the period
• In those cases, STR uses the Supply number
based upon full availability, not the number that
the hotel reports
Corporate Data
What do Companies Receive?
• Most corporate headquarters receive reports
listing each of their hotels and the various
performance metrics, referred to as “Index
Reports”. These may be subtotaled.
• Some companies receive “Summary Reports”
aggregating data for their hotels based upon
various subtotal groups.
• Many companies receive data files containing this
same type of data to use internally
Who do Companies Compare
Their Hotels to?
• Most commonly, companies compare their hotels
to the corresponding comp sets
• Sometimes they compare their hotels to the
corresponding industry segment of the subject
property, such as a Market or Tract Scale
• They may compare total Brand numbers to the
corresponding Scale total, or to a group of other
brands, referred to as a “Corporate Comp Set”
Corporate Aggregations
• Hotels can be grouped based upon common
fields such as Brand, State, or Operation
• Hotels can also be grouped based upon userdefined variables, such as Sales Regions or
Hotel Types
• Raw data can be aggregated using Standard
Weighting or Portfolio Weighting
International
Issues
Industry Segments
• In the US and in North America, probably the
most popular industry segment to compare hotels
to are Market Scale or Tract Scale
• The Scale category is totally related to chain
hotels
• Outside North America, since there are much less
chain hotels, Class is used instead and the poplar
segments are Market Class and Tract Class
Currencies and Exchange Rates
• Outside the US, most hotels want to see their
STAR reports in their local currency
• STAR obtains daily and monthly exchange rates
for all currencies in the world (at least the
countries that have hotels) from Oanda
• Daily data utilizes the daily exchange rate
• Monthly data utilizes the daily exchange rate for
the last day of the month
• Multi-year data is aggregated in local currency
Additional Data
Additional Issues/Topics
• Segmentation Data (Group, Transient,
Contract)
• Additional Revenue Data (F&B, Other,
Total)
• Data within a Trend Report
• Data within a Hotel Review or Destination
Report