Fare-Class Demand Unobscuring for Accurate Airline Seat Forecasts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing demand forecasting methods in the transportation industry, particularly in airlines, fail to accurately account for obscured and constrained demand in fare classes, leading to revenue loss due to bookings at lower prices than passengers are willing to pay, and result in spiral down cycles of fare deterioration.
Innovation Solution
A method involving unobscuring and unconstraining demand by analyzing seat bookings, converting them into integer values, and updating the bookings table to reflect unobscured and unconstrained demand, thereby improving forecasting accuracy and aligning bookings with passenger willingness to pay.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If demand forecasting uses traditional bookings data, then the forecasting process is simple, but the forecasting accuracy is low due to obscured and constrained demand
Solution Approach 1:
The patent segments demand into different components: observed demand, obscured demand, and constrained demand. By dividing the forecasting process into these segments and applying specific adjustment methods to each, the system achieves more accurate overall demand forecasting while managing complexity through structured decomposition of the problem.
Solution Approach 2:
The patent introduces intermediary calculations and adjustment factors that mediate between raw bookings data and final demand forecasts. These intermediaries include obscuration adjustments and constraint adjustments that transform observed data into accurate demand estimates, resolving the contradiction between simplicity and accuracy.
2Productivity
If airlines book seats at lower price points, then more seats are sold, but revenue is reduced due to fare class deterioration
Solution Approach 1:
The patent applies preliminary actions by adjusting demand forecasts before making booking decisions. By pre-calculating obscuration and constraint adjustments, the system identifies optimal fare class thresholds and booking strategies in advance, preventing revenue loss from premature fare class deterioration while maximizing seat utilization.
Solution Approach 2:
The patent implements feedback mechanisms where demand forecasting results inform booking decisions, which in turn update the forecasting model. This closed-loop system continuously learns from actual booking patterns and adjusts forecasts to prevent both overbooking at low fares and underutilization of capacity, resolving the contradiction between seat utilization and revenue preservation.
Data Source
AI summary
A computer-based system for unobscuring and/or unconstraining demand is disclosed. Via use of the system, actual airline seat bookings may be restated in an unobscured and/or unconstrained form, facilitating improved demand forecasts for subsequent seat bookings. In this manner, seat protects may be better allocated to align with actual demand, thus increasing revenue.