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I. INTRODUCTION
In December 000, Airbus formally committed to develop and launch a super jumbo plane known as the A80 at a launch cost of $1 billion. Prior to and after Airbus' commitment, Boeing started and canceled several initiatives aimed at developing a "stretch jumbo" with capacity in between its existing jumbo (the 747) and Airbus' planned super jumbo.
In addition to making the super jumbo one of the largest product launch decisions in corporate history, this figure represented 6% of total industry revenues in 000 ($45.6 billion) and more than 70% of Airbus' total revenues in 000. The inherent risk associated with this major strategic commitment is magnified by the fact that Airbus must spend the entire amount before it delivers the first plane. History has shown that many firms including General Dynamics, and, more recently, Lockheed, have failed as a result of attempting such bet-the-company product development efforts. If, however, the launch effort does succeed, Airbus is expected to dislodge Boeing as the market leader in commercial aircraft after more than 50 years of market dominance by the latter.
This paper presents an analysis of this new product commitment and, more generally, of competition in very large aircraft (VLA is defined as planes capable of seating more than 400 passengers).
II. CASE BACKGROUND
In the early 10s, Airbus and Boeing independently began to study the feasibility of launching a super jumbo. Both agreed there was a growing need for a super jumbo because of increasing congestion at major hubs. Alternative solutions were seen as either infeasible, in the case of greater flight frequency, or ineffective, in the case of flights to secondary airports. Fairly quickly they realized that there was room in the market for only one competitor.
Finally, Boeing and Airbus agreed to collaborate on a joint feasibility study for a Very Large Capacity Transport (VLCT) plane that could hold from 550 to 800 passengers. When the collaboration began in January 1, they envisioned the plane would cost $10 to $15 billion to develop (with estimates ranging from $5 to $0 billion) and would sell for $150 to $00 million each. Their preliminary demand estimate was reported to be 500 planes over the next 0 years.
In July 15, however, the collaboration ended. Airbus realized that Boeing's participation in the joint effort may have been only to stall the market so that Airbus did not develop anything itself. The two firms also disagreed at a very fundamental level about industry evolution. Boeing maintained that increased fragmentation in the form of point-to-point travel would solve the problem of congestion at major airports. Airbus, on the other hand, believed that hub-to-hub travel would continue to grow.
With the collaboration over, both competitors returned to independent study of the super jumbo market. For its part, Boeing considered two updated and "stretched" versions of its popular 747 jumbo jet. In fact, Boeing never formally announced it was going to develop the stretch jumbo yet did, in January 17, announce it was canceling the development effort. A little more than two years later, however, Boeing reversed course once again and now said it was going to build a stretch jumbo at a cost of $4 billion. The 747X-Stretch was supposed to hold up to 50 passengers and, according to Boeing, would be available by 004, two years ahead of Airbus' A80.
Concurrently, Airbus forged ahead with development of a super jumbo jet and finalized plans in 1 to offer a family of very large aircraft. The first model, the A80-100, would seat 555 passengers and second passenger model, the A80-00, would seat 650 passengers in the three-class configuration and up to 0 in an all-economy version. Airbus also planned to build a freighter version, the A80-800F, capable of carrying up to 150 tons of cargo. In terms of pricing, the A80's list price is significantly higher than the 747's list price, $0 million vs. $185 million. Developing the first passenger model and the freighter version of the super jumbo is expected to cost $1 billion.
Between June 000, when the Airbus supervisory board gave approval to begin marketing the plane, and December 000, airlines placed orders for 50 super jumbos and bought options on another 4 planes. With these orders in hand, including a number from important 747 customers such as Singapore Airlines and Qantas Airlines, the Airbus board officially launched the new plane. According to its internal projections, Airbus forecast a need for more than 1,500 planes of this size over the next 0 years, expected to capture up to half the market. In addition, Airbus estimates it will break even with sales of 50 planes (on an accounting, but not cash flow basis) and they currently have 100 firm orders and extra 100 options.
On March th, 001, Boeing announced it was stopping the development of its stretch jumbo and would begin development of a new aircraft known as the sonic cruiser (7E7). This plane would fly faster (Mach 0.5 vs. Mach 0.80), higher, and more quietly than existing aircraft. It would also be significantly smaller than the stretch jumbo (00 passengers vs. 50 passengers), though it would cost more to develop ($ billion vs. $4 billion). The sonic cruiser is not only more consistent with Boeing's predictions regarding industry evolution towards greater point-to-point travel, but also adds a third dimension speed to the capacity/range product space.
III. FINANCIAL MODELS
A Base case Go to Heaven.
To help us assess the valuation impact of various strategic actions in this sequence of competitor interactions, we built financial models of Airbus's super jumbo development project. We begin our reviews of these models with a projection of Airbus's investments in and returns from the super jumbo over a 0-year horizon. The model uses inputs from Airbus as well as from equity research reports on Airbus and EADS by analysts at Lehman-Brothers (LB), an industry consulting and data tracking service. All the data taken from the case are summarized in Appendix 1.
Before getting into the details of the model, two limitations are worth noting. First, this investment is incredibly complex and we have, by necessity, vastly simplified inputs to create a more tractable model. Second, many of the inputs are informed estimates because Airbus has released few details other than expected investment costs. Critical details surrounding pricing, volume, and funding remain shrouded in secrecy.
The discussion here focuses on the key assumptions of the model and the principal results. A first important assumption is that we estimate project value as of year-end 001. We also take into consideration that Airbus has spent $700 million on the plane by December 000 (Airbus Briefing, 000). Finally, we calculate the value accruing from years 1 to 1 (001 to 01) and did not use any terminal value.
In the base case, which is reproduced in Appendix , we assume Airbus will sell 50 planes per year in steady state after an initial ramp-up period (1 aircraft the first year, approximately 5% of production capacity then 8 for the second year which is approximately 75%) for a total of 750 planes by 01. This number is slightly less than its stated goal of capturing half the projected market for super jumbos (1/ 1,550 planes = 775 planes). By way of comparison, most analysts are predicting that Airbus will sell from 515 planes to 665 planes in their base case scenarios. More interestingly, Airbus' assumption exceeds the average number of 747's Boeing has sold over the past 0 years (4 planes per year).
We also assume the realized price in 008 will be $5 million, which will produce an operating margin of 5%. Also, analysts tend to assume that Boeing, a monopolist with more than 1,000 planes of cumulative production, has operating margins of 15% to 0% on its jumbo the 747.
Using a discount rate of %, these inputs imply a positive NPV of $1.1 million, consequently the IRR of the project is 10.47% which is higher than the discount rate. With respect to the break even point, we reach an accounting break even point (basic method applied by Airbus) at 4 aircraft sold, different than 50 announced by Airbus. On the other hand, if we improve the formula by taking into account commercial discounts or prices evolution, then we find a break even at 77 AC reached in 014.
B Pessimistic case Go to Hell.
If we stop our assumptions at the end of the first study, then the problem is solved we just have to launch the AXX!
The difficulty comes from the fact that the debate offers different opinions among specialists (economics, accountings…). Some say that this project is viable; others will say that Airbus made a big mistake.
Though we can think that people from Airbus thought twice before taking this decision, we decided to change assumptions linked to the future. Indeed, in 001, nobody can really know what the next years will bring to this industry. Moreover, in 001, AXX was not called A80 yet the project was just at its beginning, the studies were not mature which involves that design, performances or even investments linked to the dedicated tooling were not definitely frozen. All the data given in the case (Appendix 1) could be modified…just to see if Airbus was not a bit optimistic.
In this second study, we have taken 4 main assumptions.
The first one is based on demand which decreases significantly in 011 and 017. This is done to simulate either economic crises, either a new Boeing (7XX?) that come on the market, either the effect of terrorism.
The second one is about commercial discounts that have to be applied. The first 00 aircrafts will be discounted at 5%, as suggested in the case text and afterwards, each A/C will be discounted at 10 %.
The third assumption is about production costs. In 001, the industrial process wasnt defined at all and the aircraft definition was not either. All difficulties met due to the large volume of this A/C, the flexibility of parts or the tolerances concerns involved costly solutions sometimes. The assumption of increasing the production cost is therefore realistic
The fourth one is about Tax rate, which is increase every year in the financial model. All the assumptions about this study are summarized in Appendix .
The conclusion about this study could be catastrophic… The NPV found after 0 years was so negative the forecasted period has to be increased with 10 years. And even on a period of 0 years, the NPV is still negative. The basic break even does not change a lot in the method used by Airbus, as we find 0. But as this method does not take into account the real price paid by customers, the second one is more realistic facing the NPV results, as it gives a break even at 161 A/C!!!!
Some will think that this case is really pessimistic, but at the beginning of 001, who could have thought about September the 11th?
Moreover, Boeing has enough experience and resources to make a new A/C if it decides its reliable. Economic crises unfortunately also exist.
What is the good way of thinking between these extreme studies?
To help us taking the best decision as possible, we need to study the main parameters that have an influence on NPV to know their effects.
IV IMPACT OF VARIABLE DATA
This section analyzes the impact of variable data such as pricing, sales forecasts, production cost, additional investments and tax rates.
We assume that only one data changes while others remain same.
A- The key factors.
A-1) Pricing
Pricing in very large aircraft are of additional interest because pricing pressures drive the theoretical predictions that the entrant will introduce the new product (the super jumbo, in this case) and that intermediate products will be unprofitable for the incumbent.
It is useful to begin this examination of pricing by noting several basic facts about it. First, both Boeing and Airbus post list prices for their entire product lines. Boeing, for example, shows a price range for each aircraft on its corporate web site, where the range depends on the specific configuration. Second, both companies announce nominal changes to their price lists annually. Third, planes sell at large discounts to list prices, ranging from 18 40% for Boeing and 16-7% for Airbus and 5 to 40% for the first firm A80 orders placed.
With that background, several indicators of pricing pressure in the very large aircraft segment can be cited. Let start with Airbus' A80 which has a list price of $18-$40 million in 000. Given the 17-1% discount typical for the largest Airbus planes, the realized prices should be around $178-$187 million assuming a list price of $5 million. As it turns out, however, the early sales have occurred at prices as low as $15-$140 million or, in other words, essentially at "steady state" cost. While some of the early launch customers like Qantas and Virgin reportedly paid approximately $150 million per plane.
For instance (base on the current financial model enclosed in Appendix 1), if we assume that Airbus applies an average discount of only 5% on all its sales, then, we must wait until 08 to find a positive NPV for a total number of 1100 aircraft.
A-) Sales Forecasts
A--1) Demand Forecasts
The forecast of the demand is a key factor for the success of the A80 project; however, the demand can be deeply influenced by several external factors such as new entrant in the super jumbo market (e.g. Boeing) economic crisis, increase of fuel cost or, as we have recently experienced the dramatic effect of terrorism. To simplify our study, we will focus on the effect of the new comer on the VLA market.
Because large aircraft take years to design and develop, require enormous up-front investment, and have useful lives of over 0 years (some people think that the 747, for example, will have a useful life of 50-plus years), Airbus and Boeing both generate long-term demand projections for their products. Airbus's Global Market Forecast (GMF) is based on annual demand for new aircraft on each of 10,000 passenger routes linking almost 000 airports. In contrast, Boeing's Current Market Outlook (CMO) forecasts economic growth in 1 regions around the world and then uses these assumptions about growth to forecast traffic flows in 51 intra- and inter-regional markets.
Although both had decreased their growth forecasts in response to the Asian financial crisis in the late 10s, they disagreed sharply, however, about demand for the VLA segment due to their divergent view on industry evolution Boeing towards greater fragmentation and Airbus towards greater capacity planes. Table 1 summarizes their evolving 0-year forecasts regarding the number of VLA deliveries. Its most striking feature is the fact that Airbus' market forecasts have consistently been more than three times larger than Boeing's forecasts. And while both companies' forecasts fell in the late 10s, primarily because of the Asian crisis, Airbus' latest forecasts are down only 15% from their 17 high, compared to nearly 0% for Boeing's.
Table 1
0-Year Forecasts of the Number of VLA Deliveries
(Passenger Jets 500 seats only)
Boeing
CMO
Forecast Airbus
GMF
Forecast
15 n/a 174
16 n/a n/a
17 460 144
18 405 1
1 65 108
000 0 15
Source Boeing Current Market Outlook (CMO) and Airbus Global Market Forecast (GMF), various years.
The magnitude of the discrepancy is surprising given Boeing and Airbus's collaborative efforts in the early and mid 10s, a process that must have involved detailed discussion of different market forecasting techniques. It provides a sense of some of the ambiguities inherent in coming up with long-run demand forecasts for such products. And the direction of discrepancy is interesting, too Boeing's forecasts are lower than Airbus's, not the other way around.
Although Boeing's more pessimistic forecasts may represent its best estimate of future demand, an alternative interpretation is that they fulfill a strategic purpose. One possible purpose, more likely to have been important before Airbus committed to develop the A80, might have been to discourage entry by downplaying super jumbo demand. Additionally, perhaps, Boeing wanted to reinforce its point of view by signaling to third parties- investment analysts, investors, governments, customers, suppliers and even employees- that Boeing is acting responsibly in not launching a very large aircraft. Symmetrically, Airbus might be expected to overstate demand to make the case that it is acting responsibly in launching. Such signals of "taking care" tend to be most important in high-ambiguity environments. As a result, the possibility of strategic manipulation of forecasts understatement by Boeing, overstatement by Airbus merits mention, even though the statistical power with which it can be tested on its own (as opposed to in conjunction with other pieces of evidence) is limited.
Once again, if we compare the average sales of Boeing 747 over the last 0 years (4 aircraft per year) and if we apply this figure to our financial model from 010 then, we need to wait more then 10 years to find a positive NPV.
The demand is therefore a key factor for this study because its influenced by hypothetic competition, economic crises, political events, prices, terrorism etc…
A--) Production Capacity Forecasts
The demand forecast being a key factor, we chose to base our study on the sales forecast. Indeed, if demand is higher than production capacity, then some customers wont be able to be delivered their aircraft. Demand forecasts were therefore a necessary factor, but not enough to take into account Airbus production capacity. As a result, all is summarized in sale forecasts factor.
A-) Production costs
The assumption of the financial model is that the operating margin is 5%. However, if we refer to the operating margin estimated by Boeing on the 747s which is 15 to 0% then it has a consequence on the Airbus projection. For example, with a 15% operating margin, we need an additional 10 years of full production capacity to get a positive NPV. Even with a 0% operating margin (consistent with Lehman-Brothers estimate) an extra 6 years of full production/demand (we assume that Airbus sells all the aircraft produced) is needed to make the project viable.
As the operating margin is a direct consequence of the Aircraft price (which is taken into account) and the production cost, we chose to study the effect on production cost (that remains the same whatever the A/C price is, whereas the operating margin changes).
A-4) Investment expenditure
Increasing the R&D investment from $11 billion to $1 billion, an additional years of full capacity (150 aircraft) will be required to get a positive NPV with a total number of aircraft about 150…
Therefore, the investment expenditure is also a key factor, all the more as in 001, as the aircraft was not fully defined yet, the precise investment could not be definitely known.
A-5) Tax rate
The taxes paid on OPBT have an influence an NPV. Within the next 0 years, what will be their evolution? To make a rough estimate, the tax rate was defined as a linear function increasing from 8% every year.
B Study Between hell and heaven.
B-1) Process
Those key factor being defined, a third study was achieved in 5 parts. These 5 parts (.1 to .5) are released in Appendix 4.
The purpose of this study is to determine radar graphs that indicate areas defining the Heaven area where NPV0.
As these key factors consist of many other parameters, they had to be simplified by taking their average value, expressed in percentage increase relative to a reference value.
Each study changes one of these 5 parameters so that it can represent a bad situation for the project. As a result, the NPV decreases and becomes negative. During the study, the other parameters are adjusted so that they remain at an acceptable value for the project, until the NPV equals 0 (or be as close as possible from 0).
As a result, we obtain the limit value between Hell (NPV0) and Heaven (NPV0).
The radar graph is a tool that enables to measure the influence of changed parameters on the other ones, by defining the validity area o the project.
In fact, there are thousands and thousands of combination possible to design what we want to forecast, and therefore, there are many different possible curves.
B-) Limit of the process
The 5 studies were just an approach of this, but many more should have been made to have a more precise approach of the possible events and their consequences (nevertheless, the Excel sheet enables all possible combinations).
Moreover, as the key factors were simplified, their precision is lower. For example, the average sales number of aircraft does not take into account the sales distribution among the years. Additional studies therefore need to be made to compensate this lack of precision.
To be more efficient, the graphs need to be built on the same scale (which is not the case in this study due to the page size, to ensure maximum legibility).
B-) The main results.
The figure results are given in appendix 4 for each case (.1 to .5).
- Study .1 Average AC sales not optimistic.
- Study . Average Prices reduction not optimistic
- Study . Average Investments increase not optimistic
- Study .4 Average Production cost increase not optimistic
- Study .5 Average Tax rate increase not optimistic.
The main comparison between those cases can be made on the graphs and tables in appendix 4.
To summarize, comparison between those studies is given in the next table
Study Worst factor (Improved) break even Break even year Years forecasted
.1 AC sales 8 014 0
. Prices reduction 417 015 1
. Investments increase 8 014 1
.4 Production costs increase 515 017 0
.5 Tax rate increase 0 014 0
V - CONCLUSION
As a result, a first glance on the key factors demonstrates that individual extreme evolution of one factor doesnt kill the project for the next 0 or 1 next years.
The break evens change from 8 to 515 depending on the assumptions, and is reached between 014 and 017. Additional studies would probably add more precision on this.
The only factor that really causes difficulties is the AC production costs (study .4) for which NPV can just be positive after 0 years forecasted and AC prices increase.
But this parameter is linked to Airbus, not to the market. Its Airbus turn to find the right production process and ensure the correct design of the aircraft to optimize production costs, or to deal the best prices with subcontractors.
A company such as Airbus trusts in the knowledge of entities such as Design office and production and therefore, as executive management is influenced by this opinion about these entities, he probably thinks that production costs will be quickly reduced, as done on previous aircrafts.
Most of these parameters will never reach so extreme values, and all the more not at the same time. Additional simulations would demonstrate that if or factors tend to be pessimistic in the 0 or 0 years, as they would not reach so bad values, we could have a positive NPV after or 4 years.
This does not mean the project is not risky! But we can just take the assumption now that if things go reasonably wrong in the world in the 0 or 0 next years, this should not kill Airbus if the decision is taken to launch the program, moreover if governments estimate Airbus should not disappear…
As a conclusion, we decide to launch AXX.
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