The value of user interaction with revenue management systems
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The Value of User Interaction with Revenue Management Systems. Rick Zeni US Airways AGIFORS Reservations and Yield Management Study Group April, 2002. What is AirMax Day?. AirMax is Sabre’s bid price O&D system used at US Airways US Airways does not use AirMax demand forecasting

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The value of user interaction with revenue management systems

The Value of User Interaction with Revenue Management Systems

Rick Zeni

US Airways

AGIFORS Reservations and Yield Management Study Group April, 2002


What is airmax day
What is AirMax Day? Systems

  • AirMax is Sabre’s bid price O&D system used at US Airways

  • US Airways does not use AirMax demand forecasting

  • AirMax Day was a departure date that was completely controlled by AirMax with no user adjustments


Airmax day objectives
AirMax Day Objectives Systems

  • Quantify the value of analyst interaction with the system

  • Determine where their efforts make the most positive impact

  • Provide feedback to the analyst so they can effectively prioritize their workload

  • Evaluate system performance without the effects of analyst interaction


Airmax day
AirMax Day Systems

  • Wednesday, August 16, 2000

  • Study began 12 weeks prior to departure

  • System had complete control of all domestic flights

  • All user adjustments were removed

  • No user adjustments were made throughout the study period

  • Various performance statistics were tracked


Analsyst days
Analsyst Days Systems

  • The previous and following Wednesdays

  • Tuesdays and Thursdays surrounding all three Wednesdays

  • All three Wednesdays (8/9, 8/16, 8/23) had approximately the same projected load factor at the beginning of the study



Revenue on tuesdays and thursdays
Revenue on Tuesdays and Thursdays Systems

  • Determine whether there were any factors influencing demand during these periods that might obscure the results of Airmax Day

  • Revenue for the Tuesday and Thursday during the week of Airmax Day was lower than in the previous and following week

  • There is an indication that demand during the week of Airmax Day was lower than the previous and following weeks









Load factors
Load Factors Systems

  • Although the demand for AirMax Day was probably lower than for the comparison Wednesdays, the number of bookings for AirMax Day was higher

  • The reservation build for AirMax Day tended to be greater than that for the comparison Wednesdays

  • Among the three Wednesdays, AirMax Day had the highest load factor and the lowest total revenue




Percentage of flights sold out too soon
Percentage of Flights Sold Out too Soon Systems

  • Tendency for AirMax Day flights to sell out sooner than flights on the analyst Wednesdays

  • This is an indication that AirMax was not protecting enough seats for high fare passengers.



Overbooking levels
Overbooking Levels Systems

  • Throughout most of the experiment period, the overbooking levels for AirMax Day were above those for the analyst days

  • This indicates that the system takes a more aggressive approach to overbooking than the analysts are generally comfortable with

  • Users have a greater tendency to lower cabin authorizations than raise them

  • Oversales were highest on AirMax day (none involuntary)



Oversales
Oversales Systems


Spoilage
Spoilage Systems

  • The number of spoiled seats for AirMax Day exceeded those for the other Wednesdays

  • Overbooking levels for AirMax Day could have been set even higher with a low risk of additional oversales


Total spoilage

Posted Flights Systems

146 172 107

Total Spoilage


Planned and posted load factors
Planned and Posted Load Factors Systems

  • Low planned and posted load factors on AirMax Day indicate further overbooking opportunities



Total revenue
Total Revenue Systems


Revenue improvement from analysts
Revenue Improvement from Analysts Systems

  • Revenue on AirMax Day was lower than the average of the previous and following Wednesdays by 7.6%.

  • However, revenue on the Tuesdays and Thursdays during AirMax week was lower than the average of the previous Tuesdays and Thursdays by 4.7%.

  • The portion of the decreased revenue that can be attributed to the lack of user adjustments is 7.6-4.7=2.9%


What advantage do analysts have over the system
What Advantage do Analysts have over the System? Systems

Analysts:

  • Hedge against the future

  • Consider sell-up

  • Consider spill and recapture

  • Have an intuitive feel for market behavior

  • Their demand predictions are not constrained

  • Consider competitive actions

  • Consider schedule changes


Recommendations to the Users Systems

Forecast Adjustments—Continue the practice of adjusting service level demand forecasts, especially when the adjustment is an increase to demand.

Overbooking Levels—Identify flights where the overbooking level may be increased without significantly increasing the risk of oversales. The data indicates that many of these flights exist.


Conclusions Systems

  • Revenue improves up to 3% from analyst interaction

  • The revenue improvements on the analyst days may be mostly attributed to increases to the system demand forecast.

  • Revenue performance could be further enhanced with more aggressive overbooking levels.

  • Results based on only one day should be used with caution!


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