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: 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 = 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

Monthly Occupancy - Formula B C D E F G 1 Supply Demand Revenue (Formula) Occupancy (%) 2 Jan-10 3100 2345 198765 2345/3100 75.65% 3 Feb-10 2800 2002 175432 4 Mar-10 1776 175012 5 Apr-10 3000 2468 234567 6 May-10 2987 312345 You could multiply times 100 or format as a percentage

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 B C D E F G 1 Supply Demand Revenue (Formula) 2 Jan-10 3100 2345 198765 198765/2345 84.76 3 Feb-10 2800 2002 175432 175432/2002 87.63 4 Mar-10 1776 175012 98.54 5 Apr-10 3000 2468 234567 95.04 6 May-10 2987 312345 104.57 You could format as a “$” or as a number with 2 decimals

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 dividing the room by the average rate of rooms actually sold. RevPAR = Revenue / Supply

Monthly RevPAR – Formula B 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

Percent Change = ((This Year – Last Year) / Last Year) * 100 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 E F G 1 This Year Last Year   A B C D E F G 1 This Year Last Year Percent Change 2 Demand (Formula) 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 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 E F G 1 This Year Last Year Percent Change   A B C D E F G 1 This Year Last Year Percent Change 2 ADR (Formula) 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 You could multiply times 100 or format as a percentage

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 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 1096121 Use the SUM function to aggregate the raw values

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 1776 175012 5 Apr-10 3000 2468 234567 6 May-10 2987 312345 7 YTD 15100 11578 1096121 76.7 94.67 72.59 8 (Formula) C7/B7*100 D7/C7 D7/B7 Aggregate raw values, then apply same formulas as before

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 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 1096121 76.7 94.67 72.59 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 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 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

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 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 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 B C D E F G H 1 Property Date Supply Demand Revenue Occupancy ADR RevPAR 2 11111 May-10 3100 2222 187654  71.7  84.46  60.53 3 22222 3255 2468 198765  75.8  80.54  61.06 4 33333 2945 2345 223344  79.6  95.24  75.84 5 44444 2790 1987 165432  71.2  83.26  59.29 6 5555 3410 3210 298765  94.1  93.07  87.61 7 Comp Set 15500 12232 1073960 78.9 87.80 69.29 8 (Formula) 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 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

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 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 3 (Formula) Calc KPIs for Subject & Comp, then apply Index 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   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

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# 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

Subject had the 2nd highest ADR (with 2 others) in comp set 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 $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

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 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 1073960 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

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   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 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 1107961 9 (Formula) C7 * 31 D8 * G7 / 100 E8 * H7 Calc Occ & ADR based on Sample, multiply * Total Supply

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   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 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 1656674 10 (Formula) sum (E2:E8) sum (F2:F8) sum (G2:G8) Accumulate Actual & Modeled Supply, Demand, & Revenue

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 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 1656674 84.0 90.91 76.34 10 (Formula) 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 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