How do fuel and exchange rates affect airline pricing strategies?

Pricing and revenue management teams aim at maximizing the expected net revenues produced from a given itinerary. Their fundamental levers are the price structures (demand segmentation rules and price levels) and the inventory allocation (demand forecasts and inventory optimization and allocation). Robust airline pricing and revenue management strategies involve the analysis and visualization of some critical variables and their long term behavior. These variables affect the optimum prices and inventory allocation directly or indirectly, in sometimes complex ways and substantial amounts.

Jet fuel cost. For example, jet fuel cost -the most important component of total airline costs- is a critical variable. Jet fuel cost has a fixed component and a marginal (also called “variable”) component. The fixed component is associated to executing the itinerary, regardless of how many passengers are carried, so, it is innocuous for the purposes of price and capacity optimization under fixed itinerary.

The marginal component of cost is directly related to how many passengers are carried in each flight: if the airplane flies empty, then there is zero marginal cost. Marginal fuel cost may represent 20–25% of total fuel cost (real figures depend on load factors, trip length, aircraft type, etc). Just to have an idea, carrying an extra passenger and luggage on an intercontinental flight, ceteris paribus, may consume an extra couple of hundred dollars in jet fuel. So, an increase (decrease) in jet fuel cost produces an extra cost (saving) directly associated to each passenger carried by the airline. For this reason, the marginal fuel cost takes part in the revenue optimization function. In other words, to maintain optimality, ticket prices and inventory allocation should be continuously adjusted in a fluctuating fuel cost scenario, even if everything else stays constant.

According to the 2013 IATA Airline Cost Management Group Report, approximately one third of the total costs of airlines corresponded to jet fuel, the rest being roughly evenly distributed across different areas (10.6% for aircraft ownership, 6.5% for reservation, ticketing, sales and promotion, 5% for airport charges, etc.). But, thanks to a dramatic increase in oil extraction volumes in the US (mainly due to more drilling in the Gulf of Mexico and the emergence of hydraulic fracturing techniques or “fracking”), airlines have enjoyed a reduction of 42% in the cost of jet fuel over the twelve months period ended in November 2015. This represents a reduction of approximately 13% in the total cost.

How should this substantial cost saving have translated into prices? A typical customer would probably expect the airlines to have reduced their average prices by roughly the same 13%. The logic behind this being that by transfering that full cost saving into prices the airlines would be fair with their customers and, at the same time, collect the same net revenue. However, from the perspective of a revenue manager and leaving strategic constraints aside (strategic mandates may break the revenue management -short term- objectives, forcing the process to aim at suboptimal -short term- net revenues), this logic is erroneous; the analysis is a bit more sophisticated:

• airlines shouldn’t aim at maintaining net revenues, but at maximizing them;
• only the marginal component of the fuel cost affects the optimization;
• demand reacts to price changes in a “segmented” fashion.

With the numbers mentioned above, we estimate that the reduction in marginal fuel cost produced only a 2.8–3.5% reduction in total airline costs, so, this is the number to be considered in the price reoptimization. On the other hand, assuming that the initial, optimum average price was around 450US$ and that the total marginal costs (fuel + distribution + other) were around 15% of the average ticket price, then, the optimum price was at a price elasticity (in absolute value) of 1.2, a reasonably high value. Airlines know how to take advantage of elasticities, translating small average price reductions in visible incremental demand, using the segmentation capabilities of the fare structures and revenue management techniques.

The important conclusions here are:

• the impact of fuel cost fluctuations on optimum prices gets substantially softened due to marginal cost being only a fraction of total fuel cost;
• prices should be adjusted by demand segment, taking into account the specific elasticities of the different demand segments.

Despite the above, it is frequent among airlines to adjust fares based on total fuel cost instead of just marginal cost, and use a single price adjustment (typically YQ or Q-surcharges) across demand segments instead of a differential adjustment. These are suboptimal procedures, because they either decrease prices too much, thus diluting revenues, or contract the demand more than necessary (spilling). It is worth noting here that many airlines also use hedging strategies against fuel cost risk (Zacks), making fuel cost more predictable or capped; however, hedging is not a pricing strategy, but a financial strategy that doesn’t add long term value. So, it is an option to use the final (hedged) marginal fuel cost in the price and inventory optimizations, but, we believe, temporary hedging advantages (or disadvantages) as arguments to reduce (or increase) prices may make airline pricing strategies inconsistent and put its added value at risk.

Of course, all this analysis has been done assuming that all the rest of the variables stay constant (“theoretical” scenario). It is very likely that under a substantial fuel cost reduction airlines decide to increase capacity, since routes or frequencies that could not break-even before can break-even in the new scenario. Increased capacity puts extra pressure on average ticket prices. On the other hand, the airline cannot optimize prices not looking at what competitors are doing: if a competitor goes beyond the optimum price reduction, the airline will be forced to adjust its prices beyond the theoretical optimum level in order to protect market share and revenue.

Exchange rates. Another set of critical variables in the analysis and optimization of prices are the exchange rates at the different sales territories (or points of sale). If an airline’s prices are published in US dollars, but the currency of the territory is, let’s say, “pesos”, then a fluctuation in the exchange rate US$ / peso will increase or decrease the equivalent price in local currency. This will in turn impact potential revenues generated from that territory (due to the price elasticity of the local demand) and change the relative position of that market against other markets that compete for the same airplane seats in the network. So, prices as well as inventory allocation of that territory will have to be reoptimized everytime exchange rates accumulate relevant changes (JM Chapui). This may become quite cumbersome when many territories are involved, but it is a necessary exercise if the airline doesn’t want to leave substantial money “on the table”.

Over the last couple of years the US dollar has strengthened quickly and substantially compared to most world currencies. This has become a real challenge for airlines and, specifically, for pricing and revenue management teams. According to the September 2014 IATA Airline Cost Management Group Enhanced Report, 35 airlines had collectively lost US$475 MM due to fluctuations in foreign exchange transactions, such as currency hedge. The report concludes that currency rate fluctuations are critical parameters to affect airline operational cost, since they can affect both the financial bottom line, yield calculations and pricing benchmarks.

In 2014, Delta Airlines recorded its weakest performance in the Pacific region during the fourth quarter of 2014, as the Japanese yen devaluated dramatically increasingly against the US dollar. Net of hedges, the pressure of the devaluation reduced Delta’s revenue by US$31 MM, and the airline capacity was down by 0.5% on Pacific routes. A couple of weeks ago, we spoke about the massive airline pricing glitch of American Airlines in February 2015, where people took advantage of a low Danish Kroner to work around the revenue system, by buying London-New York tickets for $75m from the Denmark American Airlines website. More than a computer system glitch, it became an exchange rate speculation game, that quickly spread out around social media and forced the US Department of Transportation to review its consumer protection policies.

The ACMG Enhanced Report concludes that a successful currency management and exchange rate risk mitigation could “easily add 10–20% of the bottom line” while a lack of it “could erode the profits or increase the losses by as much as 50%.” For a “razor-thin” profit margin industry, this can mean the difference between a net profit and loss.

The other tricky part of exchange rates is related to the total cost of travel: hotel prices, car rental, etc, around the world, are typically expressed in US dollars. So, the more expensive the US dollar is for local customers, the more expensive it is for them to travel abroad, especially if they stay for more than a day. Thus, there will be an impact of total price elasticity on local demand for international trips and, probably, a substitution effect benefiting domestic leisure traffic. These effects should primarily get reflected in the demand forecasts that are a critical input to the inventory optimization process.

Other variables to be considered

Real currency. Inflation is another variable that may be critical in the optimization of prices in certain territories (for example, in Venezuela, Ukraine, Argentina, etc), since it impacts the real price levels from the point of view of the local demand. So, not only is it necessary to look at local currencies, but it is also necessary to look at the evolution of real local currencies (vs nominal currencies), to better reflect the real prices being charged in each territory and how demand is affected.

Economic growth. Economic growth has a direct impact on total air traffic. Moreover, the lower the GDP of a country, the higher the impact of economic growth on air traffic (CAPA). So, it is very relevant to understand this variable in order to isolate the pure price effects on demand in the long term and adjust demand forecasts appropriately in the revenue management systems.

What really happened

Let’s look now at the real evolution of prices over the last year. According to IATA, airline ticket prices dropped about 11.6% over a twelve months period when expressed in US dollars. This looks like a pretty big reduction in average price, close to the total fuel cost reduction, which, according to what we said previously, would probably be too much to maintain optimality. However, when using a fixed exchange rate (at values of January of 2011), the decrease of the average ticket price is only 4.2%. Clearly, exchange rates played a major role in the evolution of prices; they basically absorbed most of the fuel cost savings. So, maybe the growth in total capacity (at 6% YoY, according to IATA) of some of the airlines that took advantage of the dramatic fuel cost reduction, will have to be revised. In any case, demand had a healthy growth of around 7% (in RPK YoY).

Final remarks

As we can see, the airline industry is in an uncertain global scenario that calls for further and continuous analysis and research and requires robust and holistic tools to monitor and continuously optimize prices, fare structures and inventory.

How do you incorporate fuel cost fluctuations? What is your experience with exchange rates in price and inventory optimization? What are your main challenges with these issues? I would appreciate your comments below.

This blog first appeared on: http://www.airnguru.com/blog/how-do-fuel-and-exchange-ratesaffect-an-airline-pricing-strategy