Hotel Math 101, The Metrics used by the Hotel Industry

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

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

3. Property Data

4. How Does STR Obtain Raw Data? • Most raw property sales data is directly exported from the systems of the hotel companies. This 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)

5. Sample Raw Data • Here is a sample monthly raw data file that STR would receive, containing data for multiple hotels: • In most cases, companies provide their own unique hotel identification without a hotel name • A daily file would look the same except for the date field, YYYYMMDD or 20100725 Fictitious data, of course

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

7. STR Data Guidelines • STR uses a strict set of definitions based on the “Uniform System of Accounts for the Lodging Industry” • Supply (Rooms Available) – the number of rooms in a hotel multiplied by the days in the month • Demand (Rooms Sold) – number of rooms sold by a hotel, does not include 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.

8. 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

9. 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

10. 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

11. 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

12. 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 of rooms available). This is a percentage. Occupancy = Demand / Supply

13. Monthly Occupancy - Formula Hotel Math 101 Excel.xlsx - Occupancy!A1 You could multiply times 100 (then format as a number with one decimal) or format as a percentage (adds % symbol)

14. 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.

15. 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

16. Monthly ADR - Formula Hotel Math 101 Excel.xlsx - ADR!A1 You could format as a “$” (adds symbol) or as a number with two decimals

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

18. Monthly RevPAR – Formula Hotel Math 101 Excel.xlsx - RevPAR!A1 You could format as a “$” or as a number with two decimals

19. 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.

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

21. Demand Percent Change Hotel Math 101 Excel.xlsx - 'Demand Percent Change'!A1 You could multiply times 100 or format as a percentage

22. 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.

23. 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)

24. ADR Percent Change Hotel Math 101 Excel.xlsx - 'ADR Percent Change'!A1 You could multiply times 100 or format as a percentage

25. 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.

26. 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.

27. 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

28. 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 – monthly • 20100725 – 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

29. 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 20090716 • Sat 20100731 is compared to Sat 20090801 • The comparable dates will always be off by one or two days, depending upon leap year.

30. Multiple Time Periods • Multiple time periods for monthly data include: • Year-to-Date (YTD) • Running 12-Month (12-Month Moving Avg) • Running 3-Month • Multiple time periods for daily data include: • Current Week • Month-to-Date (YTD) • Running 28-Day (different than Running 4-wk) • The metrics for all of these time periods are based upon the aggregated raw data

31. YTD Supply, Demand, & Revenue Hotel Math 101 Excel.xlsx - 'YTD Supply, Demand, Revenue'!A1 You can use the SUM function to aggregate the raw values

32. YTD Occupancy, ADR, & RevPAR Hotel Math 101 Excel.xlsx - 'YTD Occ, ADR, RevPAR'!A1 Aggregate raw values, then apply same formulas as before

33. 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.)

34. 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

35. 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

36. YTD Percent Changes This Year Aggregate 1st, KPI formulas 2nd, % Change formulas 3rd

37. 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

38. 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

39. 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

40. 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

41. Full Availability Example - Subject Occupancy for Subject based on reported Supply, not Actual

42. 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

43. Competitive Set Data

44. 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.)

45. 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

46. Comp Set Supply, Demand, & Revenue Property Aggregate raw values for each member of the comp set

47. Comp Set Occupancy, ADR, & RevPAR Property Apply KPI formulas to aggregated comp set data

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

49. Comp Set Occupancy, ADR, & RevPAR Percent Changes Hotel Math 101 Excel.xlsx - 'Comp Set KPI Percent Changes'!A1 Calculate TY & LY KPIs, then apply % Change formulas

50. 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 %