Demand and Wash Management

Click and then Demand and Wash.
If you visit this page often, click next to the name to add it to the Quick Access menu.

1. Under Calendar Heatmap, switch from the default Occupancy Forecast The number of rooms (or percentage of the total number of rooms) that G3 RMS expects the property to achieve for the period. For the calculation, see the Demand and Wash - Overview topic (under Data Details). to the Peak Demand Peak, or Total Demand, is the combination of the rooms on books and the remaining unconstrained demand. view.
2. Point to a cell in the heat map to see the occupancy forecast for that day.
3. Click a month in the heat maps to view that month plus the following in the calendar view below. Click the arrows to view the next or previous 6 months.
4. Click Legend to see what demand levels the colors represent. Customize these settings in Heat Map.

The calendar displays remaining unconstrained demand The remaining unconstrained demand for a date in the future. This value is either generated by G3 RMS or, in case of an active user demand override, the user override value plus or minus a possible system adjustment. G3 RMS adjusts a demand override according to the booking pace, so the override remains accurate after its implementation. (RD) and occupancy forecast The number of rooms (or percentage of the total number of rooms) that G3 RMS expects the property to achieve for the period. For the calculation, see the Demand and Wash - Overview topic (under Data Details). percentages (OF) by Forecast Group and Room Class. Use the following options to change the information displayed in the calendar:

• Click to filter the information displayed in the calendar:
  • Select days of the week to view only certain days in the calendars. Days that you don't select appear grayed out.
  • Select a Dates with filter to display days with an Occupancy Forecast Less Than or Greater Than the percentage that you type in the % field.
  • Select a checkbox under Show Overrides to highlight only those dates in the calendar that have active overrides.
  • Click Apply to save the filters. Click Reset to restore the default filters.
• Select a Room Class to filter calendar data by Forecast Group and Room Class.
• Click the month and year button above the calendar to change the two months that you are viewing.
• Select a Forecast Group from the left-hand calendar to view two months of data for just that Forecast Group.
• Select a different Forecast Group from the right-hand calendar to compare two Forecast Groups side-by-side for the same month.
• To find the Forecast Group that is associated with a specific rate code:
  • Click the search icon .
  • Select the Rate Code.
  • Click Apply. The Forecast Group that is associated with the Rate Code displays in the Forecast Group menu.

If set up, you can use the Inventory Group filter at the top of the screen. The default selection is Property, or all Room Classes. Change the default selection in Preferences.

Changing Inventory Groups impacts Demand and Wash Management. For example, the Occupancy Forecast in the heat maps includes only the data for the Room Classes assigned to the Inventory Group. You can also use the Inventory Group filter to override the demand only for a specific Inventory Group.

G3 RMS displays all Forecast Groups, including those that have a Forecast Type of Wash or None.

Detail	Description
On Books	The number of rooms sold as of the current System Date.
Occupancy Forecast (displays as OF on the calendar)	The constrained forecast of the occupancy for the specified period, expressed as a percentage of the total number of rooms. View the Demand and Wash Definitions video in Resources on the right for how this forecast relates to other demand metrics. By default, this value uses the Physical Capacity for the total number of rooms, which includes out of order rooms. A property (or a brand for all its properties) can contact IDeaS to switch this to use Effective Capacity, which excludes out of order rooms. As an example, your property has 100 rooms, the system's Occupancy Forecast is for 50 rooms and 50 rooms are out of order. If the Occupancy Forecast uses the default Physical Capacity, then the Occupancy Forecast is 50%, since 50% of your Physical Capacity is forecasted to be sold. However, if it uses Effective Capacity, then the Occupancy Forecast is 100%. Note: Consider the Occupancy Forecast at the market segment and the room type levels as an estimate instead of a detailed forecast. That's because G3 RMS calculates the unconstrained demand forecast at the Forecast Group and Room Class level, not at the market segment and room type level. For the constrained Occupancy Forecast, G3 RMS distributes the data from the higher levels down to the market segment and room type levels. This distribution is based on the how much business each market segment and room type produced in the past at the higher level (Forecast Group and Room Class). If G3 RMS doesn't see past or future bookings for a market segment, G3 RMS considers the market segment discontinued and will no longer produce a forecast for it. For past bookings, G3 RMS looks at the historical period for which it initially received data (excluding dates with ignored data), typically two years.
System Demand	The amount of unconstrained remaining demand calculated by G3 RMS.
User Demand	The remaining unconstrained demand based on an override. G3 RMS adjusts demand overrides based on the booking pace to ensure they remain accurate, see G3 RMS monitors and adjusts Demand Overrides for details. The User Demand value equals the RD value displayed on the calendar. If no override exists, the value equals the System Demand.
Wash	Wash is the drop in occupancy due to cancellations, no-shows, group cut-offs, and so on. For future dates, it is the expected drop in Peak Demand Peak, or Total Demand, is the combination of the rooms on books and the remaining unconstrained demand.. For past dates, it is the expected wash as of the last optimization. For example, for yesterday the last optimization was at 1 pm when the system expected 4 rooms wash out of 40 rooms on books. Final Wash shows as 10%. See calculation and use of Wash for details.

1. G3 RMS collects the following from your property's demand history:

   • Historical occupancy, ADR, and booking pace at the property, market segment, and room type level. Data that the system ignores displays in the Forecast Investigator.

   • Booked or Stayed occupancy room type data, based on availability.
   • BAR historical pricing and pricing pace from rate shopping data for your competitors.
2. Based on actuals The occupancy, revenue or ADR that the property achieved, once the day is in the past. Actual occupancy is also called Final Rooms Sold., G3 RMS calculates unconstrained historic demand, or how many rooms you could have sold if you had unlimited guest rooms and never placed a single restriction on that day.

1. G3 RMS searches the unconstrained demand history for patterns to create demand models by Forecast Groups. These patterns are: 

   • Seasonality (seasons can be as short as one week)
   • Day of the week
   • Length of stay
   • Price sensitivity
   • Pace (booking and cancellation)

     Bonus fact: G3 RMS removes data that doesn't fit into any pattern as noise, or un-forecastable data. The amount of noise compared to the amount of stable patterns in booking data determines the level of uncertainty in the system’s forecasts.

2. G3 RMS forecasts future unconstrained demand for the entire forecast window by Forecast Group, Room Class, and length of stay. View the forecasts at this detail in the Daily Details window.

   1. Transient Demand:
      

      • The demand forecast varies by different pricing levels, considering how demand relates to price. And G3 RMS uses rate shopping data to understand your competitors' impact on demand.

      • Learn how transient forecasting varies by time to arrival.

   2. Group Demand:

      • Historic group demand is typically less evenly distributed than transient, for example, all group demand of a month occurred in one week. G3 RMS distributes the expected group demand more evenly, in that example, to all weeks of the month.

      • If your reservation system sends TENTATIVE-Non Adjust group data, or if an integrated sales and catering system (like Delphi) provides that information, G3 RMS can better distribute group demand to specific dates. With this data, G3 RMS can observe patterns for non-deduct groups and calculate the probability that they turn definite.

What if your actuals don't match what G3 RMS expected? G3 RMS is a self-learning system and adjusts constantly.

• During optimization: The system checks its forecasts for the future against what really happened, then it adjusts. For example, if rooms for a future date picked up much slower than expected, the system might adjust down its forecast and change decisions. G3 RMS checks the entire forecasting window, for each Forecast Group, Room Class, and length of stay.
• Updates of the demand models: Approximately every two weeks the system checks for changes in the demand models, like the day of the week demand pattern for a Forecast Group, and monitors future bookings. If the new pattern continues over a long period, like 10 to 12 weeks, the system decides to use the new pattern in its forecasts.

  Aside from its regular checks, G3 RMS checks the demand models also after some of the changes that trigger the Sync flag. Because it checks all demand models, the resulting forecast changes can seem disproportionate, see Special Events for an example.

• After large demand changes: G3 RMS constantly reviews the history to decide if recent or older data produces better forecasts. If the system notices that the demand patterns change quickly, it tends to rely more on recent history to forecast. If patterns change slowly, it relies less on recent history.

  For example, an economic downturn, the loss of a large corporate account, or a new competitor across the street causes the demand to slow down, compared to historical results. If the slowdown continues for about two weeks, G3 RMS might decide to use more recent data to forecast demand. This enables the system to quickly react to changes in overall strength of demand, for example, by forecasting a slow April using the slow preceding months of February and March instead of the strong April of prior years.
  

G3 RMS uses different data to forecast unconstrained transient demand, depending on how far away the arrival date is:

• Six months and more: 
  G3 RMS relies more on data from previous years, for example, how you performed in a similar period last year.
  

  

• Between six and three months:
  The system shifts away from using past data as more reservations are booked for the arrival period.
  

  

• Less than three months: 
  The system relies mostly on actual pace for the arrival period.
  

  

Wash is the drop in occupancy due to cancellations, no-shows, group cut-offs, and so on. For future dates, it is the expected drop in Peak Demand Peak, or Total Demand, is the combination of the rooms on books and the remaining unconstrained demand.. For past dates, it is the expected wash as of the last optimization. For example, for yesterday the last optimization was at 1 pm when the system expected 4 rooms wash out of 40 rooms on books. Final Wash shows as 10%. To maximize revenue, G3 RMS uses overbooking to make up for the loss caused by wash. Review how G3 RMS calculates overbooking.

To forecast wash for all Forecast Groups, G3 RMS looks at their historical wash patterns. For the wash of individual groups, the system also searches for patterns in:

• Booking lead time (days between the booking and arrival date).

• Days prior to arrival (between today and arrival date).

• Peak vs. shoulder block.

• Length of stay.

• Size of group block.

• Market segments.

G3 RMS forecasts wash for each group that is on books, both for picked up reservations and for available block. It uses the Forecast Group wash patterns, group-specific data like picked up versus total group block and, if available, cut-off date. See Overriding Wash for Individual Groups.

With Group Occupancy Forecast Overrides, you enter the expected final pickup by Forecast Group and let G3 RMS distribute the wash to all groups in that Forecast Group. For example, you add a 200 room Group Occupancy Forecast Override to a Forecast Group, and G3 RMS distributes that to all groups in that Forecast Group. The system calculates the Wash percentage for each group and the remaining group demand for that Forecast Group.

This type of wash override isn't as precise as at the individual group level, but for some clients, the gain in efficiency due to fewer overrides outweigh that downside. To learn more about the steps, setup and best practices, review Group Occupancy Forecast Override.