1. Hotel Math 101, The Metrics used by the Hotel Industry
The SHARE Center
Supporting Hotel-related Academic Research and Education

2. Outline Property Data Comp Set Data Industry Data Corporate Data
International Issues
Additional Data

3. Property Data

4. How Does STR Obtain Raw Data?
Most raw property sales data is directly exported from the systems of the hotel companies. This help increase the reliability of the data. Companies send STR a raw data file each month, week, and/or day.
Some hotels and smaller companies enter the data on the STR web site. The web site can be used to enter monthly or daily data.

5. Sample Raw Data
Here is a sample monthly raw data file that STR would receive, containing data for multiple hotels:
In most cases, companies provide their own unique hotel identification without a hotel name
A daily file would look the same except for the date field, YYYYMMDD or
Fictitious data, of course

6. Data Error Checks
STR performs a large volume of comprehensive error checks upon the raw data.
New data is compared to prior data for consistency.
There are Occupancy and ADR limits related to geography and type of hotel. STR also tracks special events that would cause unusual Occupancies and ADRs.
Any exceptions are verified with the data provider before the data is accepted.

7. STR Data Guidelines
STR uses a strict set of definitions based on the “Uniform System of Accounts for the Lodging Industry”
Supply (Rooms Available) – the number of rooms in a hotel multiplied by the days in the month
Demand (Rooms Sold) – number of rooms sold by a hotel, does not include comp rooms or “no-shows”
Revenue – total room revenue generated from the sale of rooms, includes service charges not resort fees, nothing else such as F&B
Uniform System of Accounts available from the AHLA or HFTP

8. Key Performance Indicators
From these raw data values, STR calculates the three hotel industry key performance indicators (KPIs) :
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

9. Occupancy = Demand / Supply
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

10. Monthly Occupancy - FormulaB C D E F G 1
Supply
Demand
Revenue
(Formula)
Occupancy (%) 2
Jan-10
3100
2345
198765
C2 / B2 * 100
75.6 3
Feb-10
2800
2002
175432
C3 / B3 * 100
71.5 4
Mar-10
1776
175012
C4 / B4 * 100
57.3 5
Apr-10
3000
2468
234567
C5 / B5 * 100
82.3 6
May-10
2987
312345
C6 / B6 * 100
96.4
You could multiply times 100 or format as a percentage

11. 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

12. Monthly ADR - Formula A B C D E F G 1 Supply Demand Revenue (Formula)2
Jan-10
3100
2345
198765
D2 / C2
84.76 3
Feb-10
2800
2002
175432
D3 / C3
87.63 4
Mar-10
1776
175012
D4 / C4
98.54 5
Apr-10
3000
2468
234567
D5 / C5
95.04 6
May-10
2987
312345
D6 / C6
104.57
You could format as a “$” or as a number with 2 decimals

13. RevPAR = Revenue / Supply
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 room revenue by the total number of rooms available. This is a dollar amount.
RevPAR = Revenue / Supply

14. Monthly RevPAR – FormulaB C D E F G 1
Supply
Demand
Revenue
(Formula)
RevPAR ($) 2
Jan-10
3100
2345
198765
D2 / B2
64.12 3
Feb-10
2800
2002
175432
D3 / B3
62.65 4
Mar-10
1776
175012
D4 / B4
56.46 5
Apr-10
3000
2468
234567
D5 / B5
78.19 6
May-10
2987
312345
D6 / B6
100.76
You could format as a “$” or as a number with 2 decimals

15. Percent Change = (This Year – Last Year) / Last Year * 100
Percent Changes
Definition
The comparison of This Year (TY) numbers vs. Last Year (LY) numbers, whether a raw value or a KPI. The percent change illustrates the amount of growth (up, flat, or down) from the same period last year.
Calculation
The This Year number minus the Last Year number divided by the Last Year number. This is a percentage.
Percent Change = (This Year – Last Year) / Last Year * 100
Remember the parentheses!

16. Demand Percent Change A B C D E F G 1 This Year Last YearA B C D E F G 1
This Year
Last Year
Percent Change 2
Demand
(Formula) 3
Jan-10
2345
2456
(B3-D3)/D3*100
-4.5 4
Feb-10
2002
2112
(B4-D4)/D4*100
-5.2 5
Mar-10
1776
1750
(B5-D5)/D5*100
1.5 6
Apr-10
2468
(B6-D6)/D6*100
5.2 7
May-10
2987
2555
(B7-D7)/D7*100
16.9
You could multiply times 100 or format as a percentage

17. Hint - % Changes for Raw Values
The Percent Changes for raw values such as Supply, Demand, and Revenue are valuable bits of information
Supply Percent Change shows whether there are more or less rooms this year versus last year
Demand Percent Change shows whether there are more or less rooms sold (guests spending the night) this year versus last year
Revenue Percent Change shows whether there is more or less money being made by the hotel or hotels (and therefore being spent by those guests)

18. ADR Percent Change A B C D E F G 1 2010 2009 Percent Change 2 ADRA B C D E F G 1
2010
2009
Percent Change 2
ADR
(Formula) 3
Jan-10
84.76
81.93
(B3-D3)/D3*100
3.4 4
Feb-10
87.63
88.85
(B4-D4)/D4*100
-1.4 5
Mar-10
98.54
100.07
(B5-D5)/D5*100
-1.5 6
Apr-10
95.04
95.24
(B6-D6)/D6*100
-0.2 7
May-10
104.57
116.93
(B7-D7)/D7*100
-10.6
You could multiply times 100 or format as a percentage

19. Hint - % Changes for KPIs
Occupancy Percent Change shows whether the Occupancy this year is greater or less rooms than the Occupancy last year. This could be related to Supply and Demand changes.
ADR Percent Change shows whether the average rate this year is greater or less than the average rate last year.
RevPAR Percent Change shows whether the RevPAR amount is greater or less than the amount last year. This could be related to Occupancy and ADR differences.

20. Daily vs. Monthly Data
The formulas for daily KPIs and Percent Changes are the same as for monthly
The date fields are different:
– monthly
– daily
Most daily percent changes are based upon comparable days, in other words the same day of week with the closest date
Thu is compared to Thu
Sat is compared to Sat

21. 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 all of these time periods are based upon the aggregated raw data

22. YTD Supply, Demand, & RevenueA B C D 1
Supply
Demand
Revenue 2
Jan-10
3100
2345
198765 3
Feb-10
2800
2002
175432 4
Mar-10
1776
175012 5
Apr-10
3000
2468
234567 6
May-10
2987
312345 7
(Formula)
sum(B2:B6)
sum(C2:C6)
sum(D2:D6) 8
May YTD
15100
11578
You can use the SUM function to aggregate the raw values

23. YTD Occupancy, ADR, & RevPARA B C D E F G 1
Supply
Demand
Revenue
Occupancy
ADR
RevPAR 2
Jan-10
3100
2345
198765 3
Feb-10
2800
2002
175432 4
Mar-10
1776
175012 5
Apr-10
3000
2468
234567 6
May-10
2987
312345 7
YTD
15100
11578
76.7
94.67
72.59 8
(Formula)
C7/B7*100
D7/C7
D7/B7
Aggregate raw values, then apply same formulas as before

24. 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 KPIs (calculated metrics of Occupancy, ADR, and RevPAR) for multiple time periods are always calculated from the aggregated raw data
Numbers for multiple time periods never use averages of monthly or daily values. (Some people mistakenly compute YTD occupancy by adding the occupancy of each month and dividing by the number of months.)
Aggregating accounts for different days in different months

25. Hint – Multiple Time Periods
Current Month numbers show the performance for a single month and YTD numbers show how performance is unfolding for the current year.
Running 3-Month numbers show a little more of a performance trend instead of just the Current Month number.
Running 12-Month numbers show a longer performance trend. These numbers can be helpful at the beginning of the year when the YTD number only includes a small number of months. Running 12- Month numbers also remove seasonality effects.

26. 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

27. YTD Percent Changes A B C D E F G H I J K L M N O P
This Year
Last Year
Percent Changes 1
Date 
Sup-ply
Dem-and
Revenue
Occu-pancy
ADR
Rev-PAR
Occupancy
RevPAR 2
Jan-10
3100
2345
198765
2456
201234 3
Feb-10
2800
2002
175432
2112
187654 4
Mar-10
1776
175012
1750
175123 5
Apr-10
3000
2468
234567
223344 6
May-10
2987
312345
2555
298765 7
YTD
15100
11578
76.7
94.67
72.59
11218
74.3
96.82
71.93
3.2
-2.2
0.9 8
(Formula)
(E7-K7)/K7*100
(F7-L7)/F7*100
(G7-M7)/G7*100
Aggregate 1st, KPI formulas 2nd, % Change formulas 3rd

28. 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 the hotel actually reported.
STR does not change the Supply number of the subject hotel on their own STAR report
“Full Availability” is an advanced concept

29. Full Availability Example - SubjectA B C D E F G H 1
Date
# Rms
Actual Supply
Report-ed Supply
Demand
Revenue
Formula
Occu-pancy 2
Jan-10
100
3100
2345
198765
D2 / E2 * 100
75.6 3
Feb-10
2800
2744
2002
175432
D3 / E3 * 100
73.0 4
Mar-10
2945
1776
175012
D4 / E4 * 100
60.3 5
Apr-10
3000
2700
2468
234567
D5 / E5 * 100
91.4 6
May-10
2987
312345
D6 / E6 * 100
96.4
Occupancy for Subject based on reported Supply, not Actual

30. 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 to generate day of week and weekday/weekend numbers
Use percentages for each day, ensures WD/WE adds up

31. Percent Changes and WD/WE or Day of Week Data
Weekday/Weekend (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
Day of Week (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

32. 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 for a single day for the last 4 weeks, i.e.: the last 4 Mondays
A hotel can compare their Monday performance metrics to the average of the last 4 Mondays to see if they are doing better or worse on a single day of the week

33. Questions Briefly describe how STR obtains raw property data
Identify the various metrics used by the hotel industry
Explain how metrics are calculated when it comes to multiple time periods
Compare the differences between how monthly and daily data is treated
Use Excel and sample raw data to demonstrate the formulas used to calculate the various numbers

34. Competitive Set Data

35. Key Performance Indicators for the Competitive Set
Numbers for the comp set are derived based on aggregated raw data for each separate hotel
Supply, Demand, and Revenue numbers are the combined values of each hotel in the comp set
Occupancy, ADR, and RevPAR numbers are based upon the aggregated Supply, Demand, and Revenue

36. 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
Some people feel that having the subject data included in the comp set numbers distorts or dilutes the comp set

37. Comp Set Supply, Demand, & RevenueA B C D E 1
Property
Date
Supply
Demand
Revenue 2
11111
May-10
3100
2222
187654 3
22222
3255
2468
198765 4
33333
2945
2345
223344 5
44444
2790
1987
165432 6
5555
3410
3210
298765 7
Comp Set
15500
12232 8
(Formula)
sum(C2:C6)
sum(D2:D6)
sum(E2:E6)
Aggregate raw values for each member of the comp set

38. Comp Set Occupancy, ADR, & RevPARA B C D E F G H 1
Property
Date
Supply
Demand
Revenue
Occupancy
ADR
RevPAR 2
11111
May-10
3100
2222
187654 3
22222
3255
2468
198765 4
33333
2945
2345
223344 5
44444
2790
1987
165432 6
5555
3410
3210
298765 7
Comp Set
15500
12232
78.9
87.80
69.29 8
(Formula)
D7/C7*100
E7/D7
E7/C7
Apply KPI formulas to aggregated comp set data

39. Percent Change Numbers for the Competitive Set
Percent Change numbers for the comp set are calculated similarly to the ones for the subject property
(This Year – Last Year) / Last Year * 100
These numbers show increases or decreases in performance this year versus last year

40. Comp Set Occupancy, ADR, & RevPAR
Percent Changes A B C D E F G H I J K 1
This Year
Last Year
Percent Changes 2
Date
Occu-pancy
ADR
Rev-PAR
Occupancy
RevPAR 3
Comp Set
May-10
78.9
87.80
69.29
82.6
93.86
77.50
-4.4
-6.5
-10.6 4
(Formula)
(C7-F7)/F7*100
(D7-G7)/G7*100
(E7-H7)/H7*100
Calculate TY & LY KPIs, then apply % Change formulas

41. Index Numbers
The Index numbers compare the performance of the subject property to the comp set
Subject Value / Comp Set Value * 100
A number greater than 100 means the subject property outperformed the comp set and a number below 100 means the comp set outperformed the subject property
Index numbers are available for Occupancy, ADR, RevPAR and the Percent Changes
Index numbers are percentages, multiple * 100 or format as %

42. Importance of Index Numbers
Index numbers tend to be relied upon heavily by the industry to evaluate the performance of hotels
Occupancy, ADR, and RevPAR Index numbers show the current performance of the subject hotel compared to the comp set
The index percent change numbers for these same KPIs show if the subject hotel is improving compared to the comp set
The headquarters of many companies receive corporate index reports listing each hotel with their index numbers
Some companies relate managers’ bonuses to index numbers

43. Occupancy, ADR, & RevPAR IndexesA B C D E F G H I J
Subject Property
Comp Set
Index Numbers 1
Occu-pancy
ADR
Rev-PAR
Occupancy
RevPAR 2
May-10
96.4
104.57
100.76
78.9
87.80
69.29
122.1
119.1
145.4 3
(Formula)
B2/E2*100
C2/F2*100
D2/G2*100
Calc KPIs for Subject & Comp, then apply Index formula

44. 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
Index of 90 TY and 80 LY yields an Index % Chg of 12.5%

45. Occupancy, ADR, & RevPAR Index
Percent Changes A B C D E F G H I J 1
Index Numbers 2
This Year
Last Year
Percent Change 3
Date
Occu-pancy
ADR
RevPAR
Occupancy 4
May-10
122.1
119.1
145.4
99.8
124.6
124.4
22.3
-4.4
16.9 5
(Formula)
(B2-E2)/E2 *100
(C2-F2)/F2 *100
(D2-G2)/G2 *100
Calc indexes TY & LY, then apply % Change formulas

46. Hint - Index Percent Changes
Here is a hypothetical situation - a subject hotel has Occupancy, ADR, and RevPAR indexes that are all below The General Manager gets a call from the Regional Manager who says, “great job”. Why?
The Regional Manager may be looking at index percent change numbers that are all strongly positive. So the subject hotel is under performing the comp set, but the subject hotel is catching up (improving more than the comp set average).
The opposite scenario could also be true.

47. 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 the 2nd best value in the comp set of 7
Ranking data gives you more than just the KPIs & Indexes

48. Occupancy Ranking Data – How?
The values for each hotel in the comp set including the subject hotel are sorted
Then the position of the subject hotel is determined within the group
Here are sample values of the subject and the comp set
STR#
1234
2345
3456
4567 (Subject)
5678
6789
Value 87 85 83 82 78 75
Rank
1 of 6
2 of 6
3 of 6
4 of 6
5 of 6
6 of 6
Subject had the 4th highest occupancy in the comp set of 6

49. Subject had the 2nd highest ADR (with 2 others) in comp set
ADR Ranking Data – Ties
Just in case two or more hotels are tied when it comes to a specific value, i.e.: they have the same exact number, then each hotel would get the same number
All hotels below with a $95 ADR get a rank of “2 of 6”:
STR#
1234
2345
3456
4567 (Subject)
5678
6789
Value
$97
$95
$92
$88
Rank
1 of 6
2 of 6
5 of 6
6 of 6
Subject had the 2nd highest ADR (with 2 others) in comp set

50. 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 the calculations are applied to the aggregated data

51. Sufficiency of Comp Set Data
If a Comp Set has 3 or more participating hotels (submitting actual data) other than the subject, then that comp set is defined as “Sufficient”. The numbers for the comp set can then appear on the STAR report
Percent change numbers will appear if the comp set had sufficient data this year and last year
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

52. 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

53. 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

54. Non-Reporting Hotel ExampleA B C D E F G H 1
Property
Date
# Rms
Supply (Actual)
Demand
Revenue
Occu-pancy
ADR 2
11111
May-10
100
3100
2222
187654 3
22222
105
3255
2468
198765 4
33333 95
2945
2345
223344 5
44444 90 6
5555
110
3410
3210
298765 7
Comp Set Sample #s
410
12710
10245
908528
80.6
88.68 8
Comp Set Census #s
500
15500
12494 9
(Formula)
C7 * 31
D8 * G7 /
E8 * H7
Calc Occ & ADR based on Sample, multiply * Total Supply

55. “Consistent Sample” related to Comp Set data
If a subject hotel has a non-reporting property (or a property that reports intermittently) in its’ comp set, that can possibly distort the comp set numbers. Or hotels that participate this year but not last year, or visa versa.
You never know if a change in performance is related to what is actually happening with the comp set hotels or the fact that a single hotel’s data is missing
There are ways for a subject hotel to remove a non- reporting property from its’ comp set
(Participation information for the comp set is displayed
on the Response page of the STAR Report)

56. 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
Advanced concept

57. Full Availability ExampleA B C D E F G H I 1
Property
Date
# Rms
Actual Supply
Reported Supply
Demand
Revenue
Occu-pancy (Full)
Occu- pancy (Report) 2
11111
May-10
100
3100
2222
187654 3
22222
105
3255
3340
2468
198765 4
33333 95
2945
2900
2345
223344 5
44444 90
2790
2199
1987
165432 6
5555
110
3410
3210
298765 7
Comp Set
15500
(14949)
12232
78.9
(81.8) 8
(Formula)
sum (D2:D6)
sum (F2:F6)
sum (G2:G6)
D7/F7 *100
Formulas are based upon Actual Supply, not Reported

58. Questions
Demonstrate how KPIs and percent changes are calculated when it comes to comp set data
Demonstrate how indexes and ranking data are calculated comparing the subject to the comp set
Explain the significance of indexes to the hotel industry
Explain the effect of non-reporting hotels in a comp set
When will different types of comp set data not appear on a STAR report?

59. Industry Data

60. Industry Data Basics
STR uses a variety of segments to analyze performance of the hotel industry
There are geographic (market, tract) and non-geographic (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

61. The Methodology for US Industry Data versus Comp Set Data
The methodology used for arriving at US 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. (This is why STR includes non-participants in their Census database of hotels.)
The Actual and Modeled data are aggregated for all hotels in each industry segment in order to arrive at performance numbers

62. Modeling of US 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 non- participant based on geography and price level
No modeled data is ever used in the Comp Set numbers
STR uses a different method for non-US industry numbers
Possible to explain technical procedure used for modeling

63. Key Performance Indicators
for Industry Segments
The Actual and Modeled data are aggregated for all hotels in each industry segment (market, tract, …)
Supply, Demand, and Revenue numbers are the combined values of each hotel in the industry segment
The Key Performance Indicators (Occupancy, ADR, and RevPAR) are based upon the aggregated Supply, Demand, and Revenue numbers

64. Industry Supply, Demand, & RevenueA B C D E F G 1
Property
Date
# Rms
Type of Data
Supply
Demand
Revenue 2
11110
May-10
100
Actual
3100
2222
187654 3
22220
105
3255
2468
198765 4
33330 95
Modeled
2945
2345
223344 5
44440 90
2790
2456
234567 6
5550
110
3410
3210
298765 7
6660 85
2635
2511
201234 8
7770
115
3565
3012
312345 9
Tract Scale
700
21700
18224 10
(Formula)
sum (E2:E8)
sum (F2:F8)
sum (G2:G8)
Accumulate Actual & Modeled Supply, Demand, & Revenue

65. Industry Occupancy, ADR, & RevPARA B C D E F G H I J 1
Property
Date
# Rms
Type of Data
Supply
Demand
Revenue
Occu-pancy
ADR
Rev-PAR 2
11110
May-10
100
Actual
3100
2222
187654 3
22220
105
3255
2468
198765 4
33330 95
Modeled
2945
2345
223344 5
44440 90
2790
2456
234567 6
5550
110
3410
3210
298765 7
6660 85
2635
2511
201234 8
7770
115
3565
3012
312345 9
Tract Scale
700
21700
18224
84.0
90.91
76.34 10
(Formula)
F9/E9 *100
G9/F9
G9/E9
Apply KPI formulas to the accumulated raw data

66. Percent Change Numbers
for Industry Segments
Percent Change numbers for industry segments are calculated exactly like the ones for the comp set or the subject property
(This Year – Last Year) / Last Year * 100
These numbers show increases or decreases in performance this year versus last year

67. 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 the monthly and daily time periods are always aggregated and then calculations are derived based upon the aggregated data

68. Supply Numbers Over Time
The number of rooms available for an industry segment or any group of hotels, including a comp set, can vary over time due to:
New hotels opening - Hotels closing
Room additions - Room drops
New Supply=Orig Supply+(Opens+Adds)–(Closes+Drops)
The number of rooms available for segments such as scale, class, or brand can vary over time due to:
Conversions in - Conversions out
New=Orig+(Opens+Adds+CvIns)–(Closes+Drops+CvOuts)

69. Seasonally Closed Hotels
Some hotels close for one or more months out of a year
In the US, there are 1,460 seasonally closed hotels
Many are in resorts areas such as beach or ski/mountain locations
Most are closed during some of the winter months, although a few are closed during the summer
Supply numbers for industry segments will also be affected by seasonally closed hotels

70. Sufficiency of Industry Data
If an Industry segment has 4 or more hotels that submit actual data, then that segment is defined as “Sufficient”, similar to the comp set rule (3 required)
The numbers for that industry segment can then appear on STAR reports and elsewhere. Industry data will not appear when the segment is insufficient.
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

71. “Consistent Sample” related to Industry Segment data
If an industry segment has a non-reporting property (or a property that reports intermittently), that can possibly distort the performance numbers. Or a hotel that participates this year and not last year, or visa versa. Or hotels that open or close during the date range you are looking at.
You never know if a change in performance is related to what is actually happening among the hotels in the industry segment or the fact that a single property’s data is missing
(You can run a Trend report on a specific group of reporting hotels to analyze performance on a consistent sample.)

72. Leap Year Methodology
The STR methodology for Leap Year assumes that February 29th never exists.
If this methodology was not used, there would be an increase in Supply, Demand, and Revenue in Februarys during leap years.
All raw February monthly data (property, comp set, and industry) for leap years is multiplied times 28/29 as if this month only had 28 days.

73. 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
When calculating industry data, STR always uses the Supply number based upon full availability, not the number that the hotel reports
Advanced concept

74. Questions Define an industry segment
Demonstrate how KPIs and percent changes are calculated when it comes to industry segments
Briefly explain how US industry data is “modeled”
When will different types of industry data not appear on a STAR report?

75. Corporate Data

76. What is meant by Corporate Data?
Individual hotels receive STAR reports with data for their subject property compared to their comp set and relevant industry segments
The regional managers and the staff at corporate headquarters of these hotels are also very interested in this data
Most hotel companies receive volumes of corporate data. These could be chains, management companies, and ownership groups.

77. 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 reports may be subtotaled by various fields (region, brand, operation)
Some companies receive “Summary Reports” aggregating data for their hotels based upon various subtotal groups.
In addition to reports, companies also receive data files, so they can analyze this data and merge it with internal information

78. 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”

79. Corporate Aggregations
Hotels can be grouped based upon common fields such as Brand, Region, or Operation (Corporate versus Franchise)
Hotels can also be grouped based upon user-defined variables, such as Sales Territories, Regional Managers, or Hotel Types
The raw hotel and comp set data can be aggregated using various methods, i.e.: Standard Weighting or Portfolio Weighting

80. International Issues

81. US versus WW 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 popular segments are Market Class and Tract Class

82. Non-Reporting Hotels and Industry Data
The US is the only country where property data is modeled for non-reporting hotels. The numbers for Industry segments in the US are based on a combination of Actual and Modeled data.
Outside the US, the numbers for Industry segments are solely based on Actual data of participating hotels. The methodology used to derive metrics for industry segments is exactly the same as for competitive sets. The Occupancy & ADR of participating hotels are used to estimate non-participating hotels.

83. WW Participation Issues
In some areas of the world, STR participation is still growing and the number of hotels submitting data may be smaller
When requesting data back in time, you need to check past participation
There may be enough hotels to pass sufficiency tests for recent months, but not back in time
Also keep participation in mind when you are looking at year-over-year change to be sure it is not affected by new hotels starting to submit data

84. Currencies and Exchange Rates
Outside the US, most hotels want to see their STAR reports in their local currency
STR obtains daily and monthly exchange rates for all currencies in the world (at least the countries that have hotels) from Oanda (
Daily data is converted using the daily exchange rate
Monthly data is converted using the daily exchange rate for the last day of the month

85. Exchange Rates and Multiple time periods
It is important to understand how exchange rates are handled when it comes to multiple time periods for monthly data, i.e.: YTD and Running 3 or 12 month numbers
Raw data is aggregated using the exchange rate for each individual month and then the KPIs are derived. This methodology accounts for changing exchange rates.
Multiple time periods for daily data, i.e.: weekly or Running 28-day numbers are calculated the same way, using the exchange rate for each individual day

86. Currencies and Corporate Data
When companies obtain data from STR, they may request the numbers in multiple currencies, i.e. US Dollars, Euros, and Local.
Analyzing the performance of hotels in a company spread over multiple countries can sometimes be distorted by fluctuating exchange rates.
STR produces some data and reports for companies in a “constant currency”. This methodology applies a single exchange rate i.e.: the rate from January of the current year to the numbers for every month.

87. Additional Data

88. 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
HOST Data

89. Questions?
Steve Hood
, extension 3315