About ORMS Functionality

Note: This topic applies to ORMS ADF11.

Data summarization, Forecasting, Optimization & Pricing, along with the User Interface are the fundamental functions behind all of ORMS.

Data summarization/modelization - All data is interpreted in real time into the data model structure, providing the pre-conditioned data to all other processes instantaneously.

Forecasting - Time series method using historical data as the basis for estimating future outcomes to maximize revenue. ORMS uses the following in its forecasting process:

• Integrating the next generation in forecast accuracy.
• 4 Distinct forecast models are applied to reservation data.
• For each lead time and booking class, the historically most accurate model is selected and an expected deviation is applied.
• All past forecast deviations are applied to compute possible deviation from the final forecast (Cone of Uncertainty). The forecast methodology includes an evaluation of past forecast precision per model per milestone, application of expected deviation per milestone, and application of distributions per milestones (LOS, Yieldability, Price Slices).

Optimization - ORMS uses a full depth Length of Stay pattern optimization that generates Length of Stay (LOS) specific hurdles (price points) per product, for 60 days out from the current business date and daily hurdles are applied for the remainder of the booking window.

All data is processed in real time in the ORMS model data structure. Forecasts for any time in the future and adjustment to hurdles are in real time, as justified by reservation activity.

The following diagram displays how the ORMS Data Process works.

For information on initial ORMS setup, see Preliminary ORMS Setup and Preliminary Setup in OPERA for ORMS.