The Harvard Social Science Statistics blog pointed to an NYT article about revenue optimization in the airline industry. Huge props to the Times for explaining the science (and art and politics) of one of the most successful applications of operations research.
In short, valuable business travellers want refundable tickets. Because of this and other reasons, about 10% of booked tickets become no shows. Airlines recoup the loss by over-booking. Implicitly, they trade off the potential for dissatifying a few unlucky passengers (who would be bumped from their flights) and the potential for flying with 10% empty seats (in addition to unsold seats). Optimization algorithms (constantly tuned by entry-level staff) try to strike a balance.
Recently, because the average percentage of seats sold has been going up, the room for such maneuvreing has been squeezed, leading to higher bump rates, and more travellers being stranded. There is some variation across airlines due to the level of sophistication of their revenue optimization algorithms, corporate strategy, etc.
The following charts present data by airline of the bump rates in 2005 and 2006. One would be interested in answering questions such as:
- Which airlines have the best (or worst) bump rate?
- Are some airlines consistently better (or worse) at controlling the bump rate?
- Which airlines have improved (or worsened) from year to year?
- Are the differences of practical significance?
The original chart shown on the left does not reveal the answers readily. My favourite bumps chart offers them up clearly (well, except on the question of significance).
The biggest problem, though, is the header: number of passengers per 10,000 bumped. The data plotted appeared to be the reverse: the number of bumps per 10,000 passengers. Otherwise, there would have been more bumped passengers than passengers!
Source: "Bumped Fliers and No Plan B", New York Times, May 30, 2007.