Hotel Math 101,The Metrics used by the Hotel Industry

The SHARE CenterSupporting Hotel-related Academic Research and Education

Outline• Property Data

• Comp Set Data

• Industry Data

• Corporate Data

• International Issues

• Additional Data

Property Data

How Does STR Obtain Raw Data?• Most raw property sales data is directly exported from

the systems of the hotel companies. This helps 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 usedto enter monthly ordaily data.

(Users can also enter Segmentation data via the web – later)

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 20100725

Hotel ID Hotel Name Date Rooms Available Rooms Sold Room Revenue12345 Fairfield Memphis 201007 3,100 2,000 200,00023456 Courtyard Nashville 201007 6,200 4,000 450,00034567 Marriott Knoxville 201007 9,300 7,000 1,000,00045678 Renaissance Atlanta 201007 7,750 6,000 900,00056789 Residence Inn DC 201007 4,650 3,000 390,000

Fictitious data, of course

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.

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 complimentary rooms or “no-shows” (reservations not cancelled)

• Revenue – total room revenue generated from the sale of rooms, not including taxes. Includes service charges not resort fees, nothing else such as F&B

The Uniform System of Accounts is available from the AHLA or HFTP and is definitely worth taking a look at.

Raw Data Issues - Supply

• STR instructs hotels and companies to always report based upon “full availability” (the number of rooms in the hotel times the days in the month) even if some rooms may be out of service (painting, repairs, renovations).

• This is one of the things that STR checks when loading data. If the Supply number is different than “full available”, the data provider is contacted to verify the numbers. (There is a small range of acceptability.)

• A hotel could have added or dropped a room. Then the number of rooms in the Census database is changed.

Advanced topic/issue

Raw Data Issues – No Shows & Cancellations

• No-shows – Hotels may charge a guest if they reserve a room and do not show up or cancel within the specified timeframe. The amount would be included in Room Revenue. There would be no addition to Room Demand.

• Group Attrition or Cancellation fees – If a group reserves a block of rooms and either does not fill their block or cancels the event, there may be some fee charged by the hotel. This amount would not go in Room Revenue. There would be not addition to Room Demand.

Advanced topic/issue

Raw Data Issues - Revenue• Service charges – Some hotels (in some countries)

may add a charge similar to a gratuity which may or may not be actually paid to the staff. – This should be included in Room Revenue.

• Resort fees – Some hotels add an amount to include special amenities (spa, golf, tennis, fitness, pool) – This is not included in Room Revenue.

• There are other special considerations that are covered in the Uniform System of Accounts related to Frequent Guest, Wholesalers (commission, OTAs), Packages, Mixed-use situations, and barter transactions.

Advanced topic/issue

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

Occupancy

DefinitionThe percentage of available rooms that were sold during a specific time period.

CalculationOccupancy is calculated by dividing the demand (number of rooms sold) by the supply (number of rooms available). This is a percentage.

Occupancy = Demand / Supply

Monthly Occupancy - Formula

A B 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 3100 1776 175012 C4 / B4 * 100 57.3

5 Apr-10 3000 2468 234567 C5 / B5 * 100 82.3

6 May-10 3100 2987 312345 C6 / B6 * 100 96.4

You could multiply times 100 (then format as a number withone decimal) or format as a percentage (adds % symbol)

Hotel Math 101 Excel.xlsx - Occupancy!A1

Hint – High Occupancies

• Normally Occupancies for a hotel will always be below 100%.

• It is not uncommon for a hotel to have a daily Occupancy of 100% if they sell out for a night.

• It is less common for a hotel to have a monthly Occupancy of 100%

• There are occasions where a hotel will have an Occupancy greater than 100%. This might happen in the case of an Airport hotel that could actually sell the same room twice in the same day.

ADR

DefinitionA measure of the average rate paid for rooms sold during a specific time period.

CalculationADR 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) ADR ($)

2 Jan-10 3100 2345 198765 D2 / C2 84.76

3 Feb-10 2800 2002 175432 D3 / C3 87.63

4 Mar-10 3100 1776 175012 D4 / C4 98.54

5 Apr-10 3000 2468 234567 D5 / C5 95.04

6 May-10 3100 2987 312345 D6 / C6 104.57

You could format as a “$” (adds symbol)or as a number with two decimals

Hotel Math 101 Excel.xlsx - ADR!A1

RevPARDefinitionA 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.

CalculationRevPAR is calculated by dividing the room revenue by the total number of rooms available. This is a dollar amount.

RevPAR = Revenue / Supply

Monthly RevPAR – Formula

A 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 3100 1776 175012 D4 / B4 56.46

5 Apr-10 3000 2468 234567 D5 / B5 78.19

6 May-10 3100 2987 312345 D6 / B6 100.76

You could format as a “$” or as a number with two decimals

Hotel Math 101 Excel.xlsx - RevPAR!A1

Hint – Importance of RevPAR

• RevPAR is a critical metric for the Hotel Industry since it is a combination of Occupancy and ADR.

• A hotel could have a 100% Occupancy because of a low ADR. The RevPAR will reflect that.

• A hotel could have a very high ADR, but only sell one room. The RevPAR will reflect that as well.

• Frequently when a hotel (or the GM or Sales Manager) is evaluated or measured, RevPAR is the metric that is being looked at.

Percent ChangesDefinitionThe 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.

CalculationThe 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! (“order of operations”)

Demand Percent Change

  A B C D E F G

1   This Year   Last Year   Percent Change

2   Demand   Demand   (Formula) Demand

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   2345  (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

Hotel Math 101 Excel.xlsx - 'Demand Percent Change'!A1

Hint - Percent Changes in General

• Percent Changes are closely scrutinized by the industry

• A positive Percent Change indicates that the number this year is greater than the number last year. The number is growing or improving.

• A negative Percent Change indicates that the number this year is less than the number last year. The number is decreasing or getting worse.

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)

ADR Percent Change

  A B C D E F G

1   2010   2009   Percent Change

2   ADR   ADR   (Formula) ADR

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

Hotel Math 101 Excel.xlsx - 'ADR Percent Change'!A1

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.

Hint – RevPAR % Change

• RevPAR Percent Change is roughly the combination of Occupancy and ADR Percent Change. (This is great to know for checking your math.)

• If Occupancy Percent Change is 2% and ADR Percent Change is 2%, than RevPAR Percent Change will roughly be 4%. You have to actually do the math to get the exact amount.

• If Occupancy Percent Change is 2% and ADR Percent Change is -2%, than RevPAR Percent Change will roughly be 0%. Again, you have to do the math to get the exact amount.

• In addition to monthly data, daily data is critical to the hotel industry. Data is analyzed at the daily level as well as aggregations of daily data. Here are common groups of days:

– Week = Sunday through Saturday

– Weekday = Sunday through Thursday

– Weekend = Friday and Saturday, this does differ in various parts of the world, i.e. the Mideast

– Day of Week = data for individual days of the week, i.e. Day of Week per month or Day of Week per year

Hotel Date-Related Definitions

Daily vs. Monthly Data

• The formulas for daily KPIs and Percent Changes are the same as for monthly

• Obviously, the date fields are different:201007 – monthly20100725 – daily

• Monthly percent changes always compare the current month this year to the same month last year. So July of 2011 would be compared to July of 2010.

201107 is compared to 201007

Comparable Dates for Daily Data• Daily percent changes are not based upon exact

dates. July 15 in 2010 is a Thursday, but July 15 in 2009 is a Wednesday.

• Most daily percent changes are based upon “comparable days”, in other words the same day of week last year with the closest date:

Thu 20100715 is compared to Thu 20090716Sat 20100731 is compared to Sat 20090801

• The comparable dates will always be off by one or two days, depending upon leap year.

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 WeekMonth-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

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(B2:B6) sum(C2:C6) sum(D2:D6)

8 May YTD 15100 11578 1096121

You can use the SUM function to aggregate the raw values

Hotel Math 101 Excel.xlsx - 'YTD Supply, Demand, Revenue'!A1

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/B7*100 D7/C7 D7/B7

Aggregate raw values, then apply same formulas as before

Hotel Math 101 Excel.xlsx - 'YTD Occ, ADR, RevPAR'!A1

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.)

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.

STR frequently uses Running 12-Month data in historic graphs

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

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

Aggregate 1st, KPI formulas 2nd, % Change formulas 3rd

This Year

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

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

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

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

Full Availability Example - Subject

  A B C D E F G H

1 Date#

RmsActual Supply

Report-ed

Supply Demand Revenue FormulaOccu-pancy

2 Jan-10 100 3100 3100 2345 198765 E2 / D2 * 100 75.6

3 Feb-10 100 2800 2744 2002 175432 E3 / D3 * 100 73.0

4 Mar-10 100 3100 2945 1776 175012 E4 / D4 * 100 60.3

5 Apr-10 100 3000 2700 2468 234567 E5 / D5 * 100 91.4

6May-

10 100 3100 3100 2987 312345 E6 / D6 * 100 96.4

Occupancy for Subject based on reported Supply, not Actual

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

Competitive Set Data

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. (They are never based upon a straight average of the Occupancies or ADRs of the comp set.)

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. This is done at the company, not hotel level. All companies exclude when it comes to daily data.

• 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

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(C2:C6) sum(D2:D6) sum(E2:E6)

Aggregate raw values for each member of the comp set

Property

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     

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 78.9 87.80 69.29

8 (Formula)   D7/C7*100 E7/D7 E7/C7

Apply KPI formulas to aggregated comp set data

Property

Percent Change Numbersfor 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

Comp Set Occupancy, ADR, & RevPARPercent Changes

  A B C D E F G H I J K

1     This Year Last Year Percent Changes

2   DateOccu-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

Calculate TY & LY KPIs, then apply % Change formulas

Hotel Math 101 Excel.xlsx - 'Comp Set KPI Percent Changes'!A1

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 %

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

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

Occu-pancy ADR

Rev-PAR Occupancy ADR 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

Hotel Math 101 Excel.xlsx - 'Occ, ADR, RevPAR Indexes'!A1

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, the Subject hotel is improving more than the average of the comp set hotels

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

Occupancy, ADR, & RevPAR IndexPercent Changes

  A B C D E F G H I J

1   Index Numbers

2   This Year Last Year Percent Change

3 DateOccu-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

Hotel Math 101 Excel.xlsx - 'KPI Index Percent Changes'!A1

Hint - Index Percent Changes

• Here is a hypothetical situation - a subject hotel has Occupancy, ADR, and RevPAR indexes that are all below 100. 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 underperforming the comp set, but the subject hotel is catching up (improving more than the comp set average). That is reason for the positive feedback.

Hint - Index % Changes continued

• The opposite scenario could also be true. The subject hotel could have indexes all well above 100. But the Regional Manager could call with concern.

• If the Index Percent Change numbers are all negative, it means that the comp set members on average are improving more than the subject hotel and could catch up.

• The RevPAR Percent Change number is a very popular number and is often looked at when it comes to things like bonuses.

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 which includes the subject hotel.

• 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

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 34564567

(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

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 34564567

(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

Percent Change Ranking Data

• The Percent Change Ranking data is also very important. The format is exactly the same as the KPIs.

• The Percent Change Ranking shows which hotel in the comp set had the highest Percent Change. So “2 of 7” would mean the subject hotel had the 2nd best percent change in the comp set of 7. This gives an indication of which hotel is improving the most.

• Remember, the percent changes could be negative (even all of them), so this could indicate that you decreased the least.

Beyond Ranking – Bandwidth Data

• Bandwidth data actually provides more information than Ranking data.

• Bandwidth reports show the daily Occupancy and ADR of the Subject hotel compared to the range of values for the comp set hotels.

• The Bandwidth information will provide an approximation of the high and low values of each metric on a daily basis.

• Samples of Bandwidth reports are available.

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

• So there are two levels of aggregations, first the members of the comp set to get to a single month, and then multiple months to get to the YTD number.

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-month numbers are considered to be sufficient if greater than 50% of the months or day included in the multi-month period are sufficient

Hint – “Missing” Comp Set

• Frequently hotel staff receive their STAR Report and notice that comp set data is missing. The Response Page will help you determine the reason for the missing data.

• If a monthly number is missing, check the number of hotels that reported for that specific month to see if there were more than three.

• If a multi-month, i.e. YTD number is missing, check all the months involved.

• If a percent change number is missing check the related months this year and last year.

Changing Comp Set data over time

• Sometimes a hotel or company will report adjusted numbers after submitting the original data. (This data is carefully checked and verified by STR.)

• In these cases the comp set numbers for a prior month may change after the fact. So a hotel may receive a STAR report this month with a different comp set number than the STAR Report they received during the prior month.

• The reason for the change to the prior number is the adjusted data for one of the hotels in their comp set.

Comparing Weekly and Monthly Reports

• Weekly Reports include a Month-to-Date number that is solely based upon daily data. Hotels watch this number since it is an indication of the monthly performance.

• Sometimes when the Monthly Report arrives, the number is different than the Weekly Reports.

• There can be two explanations. There may be a hotel in the comp set that submits monthly data but not Daily data. Check the Response pages.

• A hotel may submit monthly data that is different than the sum of all of the daily data. For example, some hotels can only make adjustments to monthly data.

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. STR uses the following methodology to “estimate” data for the non-reporting hotel.

• 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

• So the non-reporting hotel is “estimated” based upon the average of the other reporting hotels

Non-Reporting Hotel Example

  A B C D E F G H

1 Property Date # RmsSupply (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   

7Comp Set Sample #s   410 12710 10245 908528 80.6 88.68

8Comp 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

Non-Reporting Hotels the month after

• Sometimes a hotel that does not report one month may submit the missing data by the next month.

• When the STAR Report is generated the next month, the numbers for the prior month change. Previously the non-reporting hotel was estimated based on the reporting hotels.

• Note that there could be two explanations for the change in the numbers. The missing hotel submitted actual data. The other hotels in the comp set could have submitted adjusted data.

“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)

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

• This eliminates the concerns that a Subject hotel may have that a property in their comp set is providing inaccurate Supply numbers

Advanced concept

Full Availability Example

  A B C D E F G H I

1 PropertyDate # RmsActual 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  

Formulas are based upon Actual Supply, not Reported

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?

Industry Data

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, Destination Reports, and Trend Reports will also display the performance of industry segments

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

Modeling of US Industry Data

Possible to explain technical procedure used for modeling

• STR estimates the data of non-participating US hotels to help increase the accuracy of the 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. (A more detailed explanation is available if needed.)

• Modeling is performed for both monthly and daily US industry data.

Modeling continued

• No modeled data is ever used in the Comp Set numbers or for property or corporate data.

• STR uses a different methodology for non-US industry numbers. Non-US data is not modeled.

• Modeling does not take place if the hotel is closed (permanently) or if it is seasonally closed.

• If a hotel reports actual data after the fact (late), the modeled data is overwritten by the actual data.

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

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 (E2:E8)

sum (F2:F8)

sum (G2:G8)

Accumulate Actual & Modeled Supply, Demand, & Revenue

Property

Industry Occupancy, ADR, & RevPAR  A B C D E F G H I J

1 Property Date#

RmsType of

Data Supply Demand RevenueOccu-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     

9Tract Scale   700   21700 18224 1656674 84.0 90.91 76.34

10 (Formula)       F9/E9 *100

G9/F9 G9/E9

Apply KPI formulas to the accumulated raw data

Property

Percent Change Numbersfor 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

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

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)

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.

• No modeling takes place for seasonally closed hotels.

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-month numbers are considered to be sufficient if greater than 50% of the months or day included in the multi-month period are sufficient

“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.)

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.

Advanced concept

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

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?

Corporate Data

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.

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

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, 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

International Issues

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

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.

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

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 (www.oanda.com)

• 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

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

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.

Additional Data

Additional Issues/Topics

• Segmentation Data (Group, Transient, Contract)

• Additional Revenue Data (F&B, Other, Total)

• Data within a Hotel Review

• Data within a Trend Report

• Data within a Destination Report

Segmentation Data

• Sometimes hotels submit Group, Transient, and Contract numbers (Rooms Sold and Revenue) that may not add up to the totals for the month or day. Sometimes the diffferent data are coming from different systems. (STR checks and verifies the accuracy of this data.)

• STR uses the monthly or daily totals to revise the Segmentation data so that it matches perfectly.

• Separate percentages are determined for each segment for Demand and Revenue and then these percentages are applied to the monthly or daily totals.

Additional Revenue Data

• Some hotels submit extra Revenue numbers in addition to Room Revenue. They will always submit Food and Beverage (F&B) Revenue.

• They may submit either “Other” Revenue and/or Total Revenue. If they only submit one, STR will derive the other value.

• These numbers along with Segmentation (Group, Transient, and Contract) numbers all may appear on monthly or weekly STAR reports.

Hotel Reviews, Destination Reports & Trend Reports

• STR produces publications (known as Hotel Reviews), Destination Reports (primarily for CVBs) and Trend Reports (ad-hoc requests).

• These reports may display performance data for standard industry segments such as markets and tracts (sub-markets) which may include scale or class groups.

• US industry numbers that appear in these reports will typically include modeled data.

• Non-US industry numbers that appear in these reports will not include modeled data.

Questions?Steve Hood

steve@str.com

615-824-8664, extension 3315

www.strglobal.com