Cancellation Report
I just created a report showing cancelled units by date along with the actual revenue lost.
For example:
| Date | Units | Revenue | ADR |
| 1/1/12 | 20 | 2000 | 100 |
| 1/2/12 | 25 | 3000 | 120 |
| 1/3/12 | 15 | 2500 | 166 |
| 1/4/12 | 10 | 1500 | 150 |
This report was created using my OccTrack program.
R&R Crashes on Save
Every once in a while I have encountered this problem when working on a computer at a property. R&R works great until I try to save the report. At that time it saves the report and crashes.The solution is to add the following line to the RRW.INI file in the [DEFAULTS] section:
LIBRARIAN=OFF
You can file the RRW.INI in the WINDOWS folder. Just do a search on the file name.
Here is an example:
[Defaults]
ProgDir32=C:\Program Files (x86)\Liveware Publishing\ReportWorks Infinity\
TemplateDir=C:\Program Files (x86)\Liveware Publishing\ReportWorks Infinity
LIBRARIAN=OFF
DICTIONARY=1
DataDir=H:\hostplus
IndExt=
LibDir=H:\hostplus\reports
ImgDir=
LookupDir=
MemExt=
ImgExt=
Correction
My last email blast stated that the next version of HOST will use an SQL database. Robert Selwah of P-SMS corrected me on this. The next version is 18.6 and will continue to use the Xbase database. The next GENERATION of HOST will be called ATRIO and will use an SQL database. I understand that it is currently in beta release. Robert also informed me that "nobody will be able to directly access the ATRIO database directly". Hopefully there will still be a way to create custom reports. I asked Robert about this but have not yet received a response.-- Howard Hammerman
Revenue Management Goals
Robert Resugent has written and excellent article on "How to set and achieve revenue management goals" It is worth your time to read.
How to Predict Future Occupancy
By Howard Hammerman
When demographers make predictions about population growth they examine trends by age and race. They have found that birth rate varies significantly by these factors. By applying age and race specific birth rates to the current population of age and race totals, their final projections are often very close to the actual numbers that are achieved.
The hotel and resort industry has found that market segment, reservation source and prior stays are good predictors of future occupancy. I have devised a method that uses these factors along with historical trends to produce accurate future occupancy predictions quickly and easily. This paper described the method using only market segment. The same concepts could be used with additional predictors to get even more accurate results.
I will use the example a fictional hotel with 140 rooms. The forecasted month is March, 2012. I call this the “target” month. The current date is November 30, 2011. I call this the “as of” date. For simplicity’s sake, we will assume that the hotel has only two markets: FIT and Group. As of November 30, 2011 the hotel had the following on-the-books (OTB) reservations for the target month:
FIT 1,500 room nights
Group 500 room nights
Total 2,000 equal to 46% occupancy
The following table shows OTB and final occupancy figures for the past five years. The right-most column, the rent-up ratio, is simply the final occupancy divided by the OTB reservations as of a given date -- in this case November 30 of each year.
OTB and Final Occupancy for FIT for March as of Nov 30
|
Year |
OTB Nov 30 |
Final For March |
Rent Up Ratio |
|
2007 |
1,600 |
2,990 |
1.8688 |
|
2008 |
1,460 |
2,700 |
1.8493 |
|
2009 |
1,940 |
2,960 |
1.5258 |
|
2010 |
1,100 |
2,110 |
1.9192 |
|
2011 |
900 |
2,520 |
2.8000 |
|
Averages |
1,400 |
2,656 |
1.8971 |
Scanning these numbers we see that the FIT market was definitely affected by the recession. Occupancy bottomed out in 2010 while the rent up ratio bottomed out in 2009. Both numbers have recovered. Rents up ratios were higher in 2011 than in any of the previous four years. This reflects the growing trend for guests to book their rooms closer to their arrival date.
OTB and Final Occupancy for Groups for March as of Nov 30
|
Year |
OTB Nov 30 |
Final For March |
Rent Up Ratio |
|
2007 |
500 |
560 |
1.1200 |
|
2008 |
780 |
850 |
1.0897 |
|
2009 |
550 |
570 |
1.0364 |
|
2010 |
420 |
460 |
1.0952 |
|
2011 |
380 |
360 |
0.9474 |
|
Averages |
526 |
560 |
1.0646 |
The trend for groups is more stable. For each of the five years under examination, by the end of November more than 90 percent of the reservations that would ever take place had already happened. Note that it is even possible for the number of realized reservations to be less than the current OTB number as a result of cancellations. This is shown for 2011.
The following table applies the average ratios shown above to the current OTB numbers and forecasts occupancy four months in advance:
Predicted Occupancy for Mach, 2012
|
Market |
Current OTB |
Ratio |
Forecast |
Occupancy |
|
FIT |
1,500 |
1.8971 |
2,845 |
|
|
Group |
500 |
1.0646 |
532 |
|
|
Total |
2,000 |
|
3,377 |
78% |
Using this method I can predict a total of 3,377 occupied room nights in March. This is not as high as some of the past years but higher than the last two years.
All the required numbers for this analysis can be generated from the HOST PMS. You get them by running the various statistical reports and then copying the needed numbers into a spreadsheet. The remaining calculations are easily done within Excel. Or you can use the OccTrack program created by Hammerman Associates that generates the needed numbers, ration and calculations for you with little more than a single click of a mouse button.
The HOST 4CP report also provides projections. And, by selecting markets you can get the projections for a given market. However, the HOST report simply uses the previous year’s rent up ratio and applies it to the current OTB numbers. This is what the projections would look like if one took this simplistic approach:
Predicted Occupancy for March using the HOST Method
|
Market |
Current OTB |
Ratio |
Forecast |
Occupancy |
|
FIT |
1,500 |
2.8000 |
4,200 |
|
|
Group |
500 |
0.9474 |
474 |
|
|
Total |
2,000 |
|
4,674 |
108% |
The HOST method drastically over-estimates FIT and slightly under-estimates group occupancy. The predicted occupancy is 30 percentage points higher than the number arrived at using my more conservative method. And the predicted occupancy is obviously impossible since it is over 100 percent. Even limiting the projection to 100 percent produces incorrect results.
By using the average rent up ratio over a period of years, the method I described dampens the wide swings that are the result of year to year variations. At the same it bases the projections on the performance of members of sub-groups with similar characteristics (in this case markets), who, theoretically will continue to act alike in the future. As a consequence, this method gets better results.
============================================
Call or email for an OccTrack demo:
howard@hammerman.com
410-430-3019
Revenue Management Tool
Here is a great post in the "Revenue Management Professionals" group of www.linkedin.com
One of the great parts of the Hotel business is change and the resulting development of new tools to adapt to the change.A great example of this was the rush of new technology to support Hotel Revenue Management that started in earnest in 2001 with the explosion of on line distribution channels. Hotels in North America participation in on line channels averaged 8 per property while in Europe it was in the range of 15 channels per property. This spurred on the evolution of Rate Shopping tools followed quickly by Channel Management tools.
Hoteliers embraced these tools that allowed for efficiency in the day to data operation while maintaining their pricing and inventory management strategies.
As the distribution model continued to evolve there was the entry of even more tools focusing on benchmarking and monitoring tools. The big topic recently is all about social media monitoring.
I am often asked asked my opinion on the tools in the market that are being pushed by the provider of the tool along with partnerships they have formed. Don’t be surprised when one of your partners starts adding new tools to recommendations for your property; there is usually a financial relationship behind it.
So how do you know when a tool is worth purchasing? Consider the following when you are making the buying decision:
- What need does this new tool answer in your business?
- Do you have time to use the product?
- If you don’t buy what will happen?
- What will the addition of this tool do to create additional revenue at your property?
- What is the ROI in the tool?
- Have you optimized all the other elements of your operation ?
- Do you use all the tools you are currently buying today?
With technology today new tools can be very exciting; they look flashy and the presentations are excellent. Ask yourself the above questions before you buy. The worst thing that can happen is you buy a new tool that ends up sitting on the shelf.I am a big believer and supporter of new technological solutions that deliver on the needs and grow revenue in the hotel business; I am a bigger believer in optimizing every part of your business and spending based on a Hotel’s Revenue Management Strategy.
OTA Lower Your Revenue
OTAs are consuming larger amounts of the total hotel revenue each year according to a paper published in HotelNewsNow.The share increased from 9.3 percent in 2009 to 10.9 percent in 2011. At the same time the percent of revenue coming from directly into the hotels has decreased from 53.3 percent to 49.1 percent during the same period.
Key Quote: If there was no such thing as OTAs, two things would happen....The industry's occupancy would be slightly lower...and room rates would be considerably higher."
Bottom Line: REVPAR goes down when OTA bookings go up.
