Pace Differences Compared to Daily Extracts
In G3 RMS, you might notice pace differences in data from same time last year (STLY) to other systems, like size changes of a group block. These scenarios explain why you might see such discrepancies.
It's important to understand that these data discrepancies are reporting challenges only. They have no impact on your forecast and decisions, where G3 RMS uses market segment and room type level information as the basis for its optimization.
Pace Built from History
Building pace applies only to properties built in G3 RMS after May 2016.
When initially building a property, G3 RMS can use up to 365 days of historical reservation and group block data to build booking pace. By building pace from history, G3 RMS reduces its learning time. The system quickly understands the booking patterns for a full year without having to collect a full year of 
Files with new and changed booking data that G3 RMS receives from the reservation system. It includes reservations, group blocks, and inventory summary data. Also called Snapshots or Daily Extracts.
G3 RMS uses this historical data to build a full year of seasonal booking patterns, including booking pace, for both transient and group business. G3 RMS uses these booking patterns to understand how business picks up and washes within each season across the year, which is particularly beneficial to properties that see different seasonal materialization.
To build pace from history for transient business, G3 RMS uses the original booked date from the individual reservation. For group business, G3 RMS uses the booked date and the originally contracted room nights compared to the final picked-up room nights from the group block reservation.
Differences in Same Time Last Year (STLY) Data
When a property is built using historical data, G3 RMS creates an indication of pace for the same time last year, which it displays in dashboards and reports. Using this method, G3 RMS allows you to see an indication of the business on books at the same time last year, without waiting to gather each daily The primary reservation system, like a PMS or CRS, that provides data to G3 RMS. The data from that one system is used by the RMS to forecast, optimize and produce controls. The controls are sent to all selling systems, which for some integrations may exclude the reservation system. for 365 days.
You should view STLY data as a representation of your status at the same time last year. Due to the constraints of the historical data available to G3 RMS, the data does not show your exact position at the same time last year like you have available from your daily data
STLY for Transient Business
For transient business from history, G3 RMS bases STLY on the volume of individual reservations on books as of the same number of days prior to arrival, accounting for bookings made and canceled. For past bookings, G3 RMS only receives the final status of a reservation. The system does not know if changes to the reservation took place. For example, if a reservation was booked with an incorrect market segment and was later changed, G3 RMS only sees the reservation with its final market segment. G3 RMS also does not receive adjustments to the number of nights. In these cases, G3 RMS builds pace that reflects reservations based on their final details. For all bookings received from
G3 RMS also adjusts for canceled and no-show reservations. These are generally delivered to the system with a room revenue of 0.00. When the reservations were confirmed, they did carry a value. Therefore, for optimal system performance, G3 RMS needs to treat this value as a holding a value between the booking and cancellation date. All properties built or re-built after January 16, 2016 use the rate value as an approximation of the room revenue value. This approximation is not a perfect proxy for the room revenue value. However, it is more valid than assuming these reservations held a 0.00 value, which dilutes metrics such as Average Daily Rate (ADR).
STLY for Group Business
This scenario applies if your implementation began after May 2016.
When pace data is built from history, it is more difficult to get a full picture of group booking patterns than with transient business. That is because, when G3 RMS initially
Thus, when pace is built from history, the STLY statistics for group blocks in G3 RMS might differ from the
Some reservations systems don't send the booking dates of past group blocks for G3 RMS to understand group booking patterns and to show an indication of STLY. In this case, G3 RMS displays STLY only collecting 365 days of daily data.
Group Pace Data Comparison
The following example illustrates the differences between the group data observed from daily data
The illustration shows the following:
- A group was blocked as Tentative (Non-Deduct) at 88 days to arrival. Historical data shows the rooms as on books from this point.
- The group signed a contract, and the block moved from Tentative (Non-Deduct) to Confirmed (Deduct) at 54 days to arrival. The daily data
- At 53 days to arrival, the number of rooms changes from 14 to 18.
- At 41 days to arrival, extra rooms are added to the block temporarily. Again,
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Thus, to determine group booking patterns from historical data, G3 RMS knows only that the block was booked at 14 rooms and ended at 13.
When data capture begins, G3 RMS uses the actual observed pick-up and wash patterns, based on the group block extracts. As the volume of data that G3 RMS collects grows, the system can improve its understanding of group booking patterns. After the initial year of data capture, G3 RMS has a more accurate picture of the STLY business conditions.
Impact on Group Forecasting
To understand the impact on group forecasting, consider the data that G3 RMS uses for forecasting group:
- Past group blocks, based on the variance between original blocked and final picked-up rooms
- Booking patterns, including the blocked rooms, the blocked date and how far in advance bookings were made
- Actual pick-up and wash patterns for future groups, including original number of rooms, final number of rooms and all changes in between
Each day after data capture begins, G3 RMS learns more about the pace and pattern of groups, which helps improve the forecasting. If property has very few groups, and G3 RMS has not learned enough by the time it begins sending decisions, we recommend ongoing group forecast reviews and, if necessary, group demand overrides.
Suboptimal Business Practices
Some group business practices can result in missing or incorrect pace. See Group Block Business Practices for more information.
After G3 RMS Has Daily Data
Even after G3 RMS captures a full year of
- G3 RMS breaks down market segments into analytical market segments, using functionality in Market Segments setup. Since there is no summary level data available at the analytical market segment level, G3 RMS populates some pace from the reservations. Where your reservation system provides summary level data, there might be some differences when comparing summary to transactional data.
- Pseudo room types are removed from G3 RMS. This removal isn't likely to have a significant impact because most pseudo revenue is raised against these room types on the day, rather than held to be posted on a future date or rolling basis, as is the case with normal reservations.
