Hotel Math 101

1
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
2
Outline

• Property Data
• Comp Set Data
• Industry Data
• Corporate Data
• International Issues
• Additional Data

3
Property Data
4
Starts with Raw Data

• ___Raw sales data_____for every hotel is obtained
  from clients via corporate feeds or web entry
• Sample monthly file
• Daily file would look the same except for the
  date field, YYYYMMDD or 20100725

5
STR Data Guidelines

• Supply (___Room available__) the number of
  rooms in a hotel multiplied by the days in the
  month
• Demand (_room 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 room___, includes __________not resort
  fees, nothing else such as _______

6
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____-
• __revenue per available room____-
  important metric, based upon all rooms, some
  feel like it is better measurement of
  profitability

7
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 room of available___),
this is a percentage Occupancy Demand / Supply
8
Monthly Occupancy - Formula
A B C D E F G
1 Supply Demand Revenue (Formula) Occupancy ()
2 Jan-10 3100 2345 198765 75.65
3 Feb-10 2800 2002 175432 71.5
4 Mar-10 3100 1776 175012 57.29
5 Apr-10 3000 2468 234567 82.87
6 May-10 3100 2987 312345 96.35
You could multiply times 100 or format as a
percentage
9
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
10
Monthly ADR - Formula
A B C D E F G
1 Supply Demand Revenue (Formula) ADR ()
2 Jan-10 3100 2345 198765 84.76
3 Feb-10 2800 2002 175432 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
11
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 _room__by the ____total number of
rooms available____. RevPAR Revenue / Supply
12
Monthly RevPAR Formula
A B C D E F G
1 Supply Demand Revenue (Formula) RevPAR ()
2 Jan-10 3100 2345 198765 64.12
3 Feb-10 2800 2002 175432 62.65
4 Mar-10 3100 1776 175012 56.46
5 Apr-10 3000 2468 234567 78.189
6 May-10 3100 2987 312345 100.76
You could format as a or as a number with 2
decimals
13
Percent Changes

• Definition
• The comparison of __This year__(TY) numbers vs.
  _Last year__(LY) numbers. The percent change
  illustrates the amount of growth (__up, flat,
  down__) from the same period last year.
• Calculation
• Percent Change ((This Year Last Year) / Last
  Year) 100

14
Demand Percent Change
  A B C D E F G
1   This Year   Last Year   Percent Change Percent Change
2   Demand   Demand   (Formula) Demand
3 Jan-10 2345   2456   -4.5
4 Feb-10 2002   2112   -5.21
5 Mar-10 1776   1750   1.486
6 Apr-10 2468   2345   5.245
7 May-10 2987   2555   16.91
You could multiply times 100 or format as a
percentage
15
ADR Percent Change
  A B C D E F G
1   This Year   Last Year   Percent Change Percent Change
2   ADR   ADR   (Formula) ADR
3 Jan-10 84.76   81.93   3.45
4 Feb-10 87.63   88.85   -1.37
5 Mar-10 98.54   100.07   -1.52
6 Apr-10 95.04   95.24   -0.21
7 May-10 104.57   116.93   -10.57
You could multiply times 100 or format as a
percentage
16
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

17
Multiple Time Periods

• Multiple time periods for monthly data include
• Year-to-Date (YTD)
• Running 12-Month (_12-moth 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 __aggregates raw data_____

18
YTD Supply, Demand, Revenue
  A B C D
1   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) sum(B2B6) sum(C2C6) sum(D2D6)
8 May YTD 15100 11578 1096121
Use the SUM function to aggregate the raw values
19
YTD Occupancy, ADR, RevPAR
  A 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 3100 1776 175012      
5 Apr-10 3000 2468 234567      
6 May-10 3100 2987 312345      
7 YTD 15100 11578 1096121 76.7 94.67 72.59
8 (Formula)       C7/B7100 D7/C7 D7/B7
Aggregate raw values, then apply same formulas as
before
20
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

21
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

22
YTD Percent Changes
  A B C D E F G H I J K L M N O P
    This Year This Year This Year This Year This Year This Year Last Year Last Year Last Year Last Year Last Year Last Year Percent Changes Percent Changes Percent Changes
1 Date  Sup-ply Dem-and Revenue Occu-pancy ADR Rev-PAR Sup-ply Dem-and Revenue Occu-pancy ADR Rev-PAR Occupancy ADR RevPAR
2 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 15100 11578 1096121 76.7 94.67 72.59 15100 11218 1086120 74.3 96.82 71.93 3.2 -2.2 0.9
8 (Formula)                         (E7-K7)/K7100 (F7-L7)/F7100 (G7-M7)/G7100
Aggregate 1st, KPI formulas 2nd, Change
formulas 3rd
23
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

24
Full Availability Example - Subject
  A 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 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
25
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
26
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

27
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

28
Competitive Set Data
29
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

30
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

31
Comp Set Supply, Demand, Revenue
  A B C D E
1 Property Date Supply Demand Revenue
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(C2C6) sum(D2D6) sum(E2E6)
Aggregate raw values for each member of the comp
set
32
Comp Set Occupancy, ADR, RevPAR
  A B C D E F G H
1 Property Date Supply Demand Revenue Occupancy ADR RevPAR
2 11111 May-10 3100 2222 187654  71.68  84.45  60.54
3 22222 May-10 3255 2468 198765  75.82  80.54  61.07
4 33333 May-10 2945 2345 223344  79.63  95.24  75.84
5 44444 May-10 2790 1987 165432  71.22  83.26  59.29
6 5555 May-10 3410 3210 298765  94.13  93.07  87.61
7 Comp Set May-10 15500 12232 1073960 78.9 87.80 69.29
8 (Formula)   D7/C7100 E7/D7 E7/C7
Apply KPI formulas to aggregated comp set data
33
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

34
Comp Set Occupancy, ADR, RevPAR Percent
Changes
  A B C C D D E F F G G H I I J J K
1     This Year This Year This Year This Year This Year Last Year Last Year Last Year Last Year Last Year Percent Changes Percent Changes Percent Changes Percent Changes Percent Changes
2   Date Occu-pancy ADR ADR Rev-PAR Rev-PAR Occu-pancy ADR ADR Rev-PAR Rev-PAR Occupancy ADR ADR RevPAR RevPAR
3 Comp Set May-10 78.9 87.80 87.80 69.29 69.29 82.6 93.86 93.86 77.50 77.50 -4.4 -6.5 -6.5 -10.6 -10.6
4 (Formula)                       (C7-F7)/F7100 (D7-G7)/G7100 (D7-G7)/G7100 (E7-H7)/H7100 (E7-H7)/H7100
Calculate TY LY KPIs, then apply Change
formulas
35
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 ____________ 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
36
Occupancy, ADR, RevPAR Indexes
  A B C D E F G H I J
    Subject Property Subject Property Subject Property Comp Set Comp Set Comp Set Index Numbers Index Numbers Index Numbers
1   Occu-pancy ADR Rev-PAR Occu-pancy ADR Rev-PAR Occupancy ADR RevPAR
2 May-10 96.4 104.57 100.76 78.9 87.80 69.29
3 (Formula)            
Calc KPIs for Subject Comp, then apply Index
formula
37
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

38
Occupancy, ADR, RevPAR Index Percent Changes
  A B C D E F G H I J
1   Index Numbers Index Numbers Index Numbers Index Numbers Index Numbers Index Numbers Index Numbers Index Numbers Index Numbers
2   This Year This Year This Year Last Year Last Year Last Year Percent Change Percent Change Percent Change
3 Date Occu-pancy ADR RevPAR Occu-pancy ADR RevPAR Occupancy ADR RevPAR
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
39
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 hotels position and Y
  is the number of participating properties in the
  comp set, for example 2 of 7 would mean the
  subject hotel had _________________________

Ranking data gives you more than just the KPIs
Indexes
40
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 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
41
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 1234 2345 3456 4567 (Subject) 5678 6789
Value 97 95 95 95 92 88
Rank 1 of 6 2 of 6 2 of 6 2 of 6 5 of 6 6 of 6
Subject had the 2nd highest ADR (with 2 others)
in comp set
42
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

43
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

44
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

45
Full Availability Example
  A 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 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    
6 5555 May-10 110 3410 3410 3210 298765    
7 Comp Set May-10   15500 (14949) 12232 1073960 78.9 (81.8)
8 (Formula)     sum (D2D6)   sum (F2F6) sum (G2G6) D7/F7 100  
Formulas are based upon Actual Supply, not
Reported
46
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

47
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

48
Non-Reporting Hotel Example
  A 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 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    
7 Comp Set Sample s   410 12710 10245 908528 80.6 88.68
8 Comp Set Census s   500 15500 12494 1107961    
9 (Formula)     C7 31 D8 G7 / 100 E8 H7    
Calc Occ ADR based on Sample, multiply Total
Supply
49
Industry Data
50
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

51
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

52
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
  non-participant 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
53
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

54
Industry Supply, Demand, Revenue
  A 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 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
9 Tract Scale   700   21700 18224 1656674
10 (Formula)       sum (E2E8) sum (F2F8) sum (G2G8)
Accumulate Actual Modeled Supply, Demand,
Revenue
55
Industry Occupancy, ADR, RevPAR
  A 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 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      
9 Tract Scale   700   21700 18224 1656674 84.0 90.91 76.34
10 (Formula)       F9/E9 100 G9/F9 G9/E9
Apply KPI formulas to accumulated raw data
56
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

57
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

58
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

59
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

60
Corporate Data
61
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

62
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

63
Corporate Aggregations

• Hotels can be grouped based upon common fields
  such as Brand, State, or Operation
• Hotels can also be grouped based upon
  user-defined variables, such as Sales Regions or
  Hotel Types
• Raw data can be aggregated using Standard
  Weighting or Portfolio Weighting

64
International Issues
65
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

66
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

67
Additional Data
68
Additional Issues/Topics

• Segmentation Data (Group, Transient, Contract)
• Additional Revenue Data (FB, Other, Total)
• Data within a Trend Report
• Data within a Hotel Review or Destination Report