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Now is the time for airline “revenue management” to evolve to “profit” management. Post-purchase ancillary revenue, including on-board meals and change fees, has led many managers to consider “total” revenue management as opposed to only managing the base fare.

Ancillary, on the other hand, often comes with quite different profit margins than the base fare.

Many revenue management systems rely upon associated revenue accounting systems to value different fare classes. On a real-time basis in a specific market, a “Y” fare is precisely valued – at $515 or $585 or whatever. And based on these systems, revenue management determines how many seats to set aside for each fare class. But now such systems – revenue accounting and revenue management – need to incorporate ancillary behavior.

Some revenue management systems now allow users to adjust the value of a passenger booked in different fare classes, adding expected ancillary profitability and subtracting unique costs of certain fare types to revenue accounting’s base valuation. 

To properly calculate the appropriate adjustment, revenue accounting systems need to track ancillary revenue by fare class.

Let’s work through some examples.

 

Bare Bones Fare @ $150

The passenger is subject to all ancillary fees, so $150 may dramatically understate their total revenue impact on the airline. What is the propensity of travelers on the lowest fares to purchase various ancillary services? What is the likelihood they will check a bag for an extra $25? What is the probability they will not fly and have to forfeit their entire non-refundable ticket – $150 – while simultaneously freeing up a seat for someone else?

Bare bone, base fare …………………………………………………….....$150

Propensity to pay for a checked bag (50%)…………..add $12.50

Less cost of checked bag……………………………………...............(5.00)

Propensity to pay for a drink/on-board meal (20%)….......$2.00

Less costs…………………………………………………………................….(1.00)

Propensity to cancel/change (5%) and resell seat……..…  $7.50

Profit impact of $150 passenger……………………………….…....…$166

Full Fare @ $350

The full fare passenger on the other hand, receives many ancillary services included in his fare. And such passengers often pay full fare because they value the additional flexibility it affords – the passenger can change their flight at no additional cost. In this case, the profit impact of the passenger needs to include the cost of the ancillary services they receive.

Full Fare………………………………………………………………….....………$350

Cost of a checked bag (50%)…………………….………………....…..…$(5)

Cost of on-board meal/drink………………………………………......…..$(5)    

No-show/change (30%)…………………………………….……..….....…$(105)

Overbook by an extra seat……………………….……......................…$45

Earned frequent flyer miles…………………………………….......……..$(15)

Profit impact of $350 passenger……………………………………...$265

Instead of a possible $200 upsell from saving a seat for a full fare passenger (from $150 to $350), this reduces the upsell profit potential to less than $100 ($265 versus $166). This would significantly change the allocation of seats to the higher fare – given the uncertainty of demand for the higher fare, the RM system is much more prone to accept more lower fare $150 passengers.

Most revenue management algorithms assess the upside to holding inventory for higher fare passengers. But in this example, the nominal difference in fares ($150 vs. $350) dramatically overstates the upside in terms of “profit” impact. Also, the spread falls by more than 50% (from $200 to $99). So the revenue management system algorithm would tend to set aside fewer seats for full fares than it would for solely on the base fares.

Of course, airlines don’t just offer two fares – there are often 15 or more fares for the same market. Depending upon advanced purchase and other fare rules, each fare needs to be analyzed for ancillary propensity so that the revenue management system can properly value each in comparison to the others. Thus, an example input table of “adjustments” could be:

Upsell from next lowest fare

Fare Grouping  

Average Fare  

 Adjustment  

Adjusted Value  

Upsell  

Y (Full fare)

$350

$(85)

$265

$20

B

$250

$(5)

$245

$0

H

$200

$45

$245

$35

Q

$175

$35

$210

$44

V

$150

$16

$166

 

 

Since the adjustments are based on ancillary propensities, the adjustments will not follow any predictable or linear pattern between the highest and the lowest fares. In most cases, based on total value, the difference between the lowest restricted fare and the highest unrestricted fare will decrease. Also note that, including ancillary propensity, what might appear to be a logical progression may disappear (there is no incremental value for a “B” passenger relative to an “H” passenger in the above example). In fact, ideally, the fare hierarchy should be based not on the base fares but on the total value of a passenger.

Increasingly, due to the growth of ancillary fees, the profit potential of a passenger can differ significantly from the fare he pays: low fare passengers especially are subject to a variety of fees which increase their total revenue, and their total profit value to the airline; similarly, a full fare passenger receives benefits in his fare that reduces the profitability of those passengers relative to their fare. As ancillary fees have grown, airline revenue management departments need to incorporate ancillary revenue – and costs – into their network optimization models to properly allocate seats among fares – they need to adopt a “profit” management approach.


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