Hotel management homework
xinranHotel 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
- ___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
Sheet1
Hotel ID | Hotel Name | Date | Rooms Available | Rooms Sold | Room Revenue |
12345 | Fairfield Memphis | 201007 | 3,100 | 2,000 | 200,000 |
23456 | Courtyard Nashville | 201007 | 6,200 | 4,000 | 450,000 |
34567 | Marriott Knoxville | 201007 | 9,300 | 7,000 | 1,000,000 |
45678 | Renaissance Atlanta | 201007 | 7,750 | 6,000 | 900,000 |
56789 | Residence Inn DC | 201007 | 4,650 | 3,000 | 390,000 |
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 _______
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
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
Monthly Occupancy - Formula
You could multiply times 100 or format as a percentage
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 |
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
You could format as a “$” or as a number with 2 decimals
A | B | C | D | E | F | G |
1 | Supply | Demand | Revenue | (Formula) | ADR ($) | |
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 |
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
Monthly RevPAR – Formula
You could format as a “$” or as a number with 2 decimals
A | B | C | D | E | F | G |
1 | Supply | Demand | Revenue | (Formula) | RevPAR ($) | |
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 |
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
Demand Percent Change
You could multiply times 100 or format as a percentage
A | B | C | D | E | F | G | |
1 | This Year | Last Year | 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 |
ADR Percent Change
You could multiply times 100 or format as a percentage
A | B | C | D | E | F | G | |
1 | This Year | Last Year | 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 |
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-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_____
YTD Supply, Demand, & Revenue
Use the SUM function to aggregate the raw values
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(B2:B6) | sum(C2:C6) | sum(D2:D6) |
8 | May YTD | 15100 | 11578 | 1096121 |
YTD Occupancy, ADR, & RevPAR
Aggregate raw values, then apply same formulas as before
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/B7*100 | D7/C7 | 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
Aggregate 1st, KPI formulas 2nd, % Change formulas 3rd
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 | 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)/K7*100 | (F7-L7)/F7*100 | (G7-M7)/G7*100 |
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
Occupancy for Subject based on reported Supply, not Actual
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 |
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
Aggregate raw values for each member of the comp set
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(C2:C6) | sum(D2:D6) | sum(E2:E6) |
Comp Set Occupancy, ADR, & RevPAR
Apply KPI formulas to aggregated comp set data
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/C7*100 | E7/D7 | E7/C7 |
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
Calculate TY & LY KPIs, then apply % Change formulas
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 | Occu-pancy | ADR | Rev-PAR | Occupancy | ADR | 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 |
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 %
Occupancy, ADR, & RevPAR Indexes
Calc KPIs for Subject & Comp, then apply Index formula
A | B | C | D | E | F | G | H | I | J | |
Subject Property | Comp Set | 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) |
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
Calc indexes TY & LY, then apply % Change formulas
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 | 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 |
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 _________________________
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
Subject had the 4th highest occupancy in the comp set of 6
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 |
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
Subject had the 2nd highest ADR (with 2 others) in comp set
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 |
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
Formulas are based upon Actual Supply, not Reported
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 (D2:D6) | sum (F2:F6) | sum (G2:G6) | D7/F7 *100 |
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
Calc Occ & ADR based on Sample, multiply * Total Supply
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 |
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 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
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
Accumulate Actual & Modeled 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 (E2:E8) | sum (F2:F8) | sum (G2:G8) |
Industry Occupancy, ADR, & RevPAR
Apply KPI formulas to accumulated raw data
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 |
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 user-defined 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
Hotel IDHotel NameDateRooms Available Rooms SoldRoom Revenue
12345Fairfield Memphis2010073,1002,000200,000
23456Courtyard Nashville2010076,2004,000450,000
34567Marriott Knoxville2010079,3007,0001,000,000
45678Renaissance Atlanta2010077,7506,000900,000
56789Residence Inn DC2010074,6503,000390,000