Wednesday, October 23, 2019

Alaska's Shifting California Love

Over the past few years, Alaska as attempted to make good on their desire to be the West Coast’s go-to airline. After spending $2.6B to purchase Virgin America, Alaska's route network received a significant shot in the arm, boosting their already growing California network.

While many remember the 2017 SJC and SAN investments, Alaska's interest in California has been growing for quite some time especially in San Deigo. Starting around 2010, Alaska started increasing its San Diego service, both in terms of destinations and flights. The first wave started with vacation destination gaps, Hawaii and Mexico, which was followed up with a wave of Intra-California flights to Fresno, Monterey, and Santa Rosa.

San Diego saw modest growth between 2013 and 2017 with seasonal Mammoth Lakes service launched in 2013 (discontinued in 2018) and Kona service launched in 2015. Finally, in the latter part of 2016 thru 2018, Alaska really refocused its growth in the market and launched 16 new destinations. This massive expansion accounted for 14% of Alaska's 2018 year-over-year ASM growth and 26% of their departure count growth.

Recently, Alaska announced new destinations were coming to San Diego (SBP and RDM) as well as depth to MCO, BOI, STS, SJC, and BOS. Within the same RDM announcement, LAX and SFO also saw a healthy dose of growth.

In the past, the combined AS/VX saw rapid growth. From 2010 to 2019, the combined company had an average ASM CAGR of 6.5%, however, after weaker performance, the company's growth hit the brakes in 2019 with an anemic 2% ASM growth. In 2020, growth is projected to increase, however, a meager 3-4%. Taken in a vacuum, Alaska's August 28th and September 4th announcements would consume roughly 50% of its 2020 growth rate.

However, Alaska implemented adjustments within its California network. In the first and second quarter, Alaska exited or seasonally reduced a significant amount of transcontinent and midcontinent routes. These markets that were exited starting in 2020 will free up roughly 1.7B ASMs compared to the recent announcements of 1.1B ASMs added to the network. The gap of roughly 0.6B ASMs will open the equivalent of another 1% of year-over-year ASM growth that has yet to be announced. Seasonal reductions would open another modest amount of ASMs which also could be reallocated.

Reds = exits; Blue = seasonal reductions

To understand why Alaska made these seasonal reductions and market exits, we again go back to the RASM curve. Examining Alaska’s RASM curve, most of the markets are below, some pretty significantly below the 1Q2019 RASM curve. This tends to point towards some performance issues with many of the routes which were reduced. This should not be too terribly surprising. Most of these routes were launched within the last 1-2 years. It often takes time for the market to produce system-level returns.

I really do not believe performance was the entire story here. Alaska's midcontinent expansion out of San Diego never really made sense to me. If you are going to be California's go-to airline, why would a carrier introduce routes that were not really that important to the originating California market? The markets that Alaska has removed from their schedule were largely markets with customers that fly to California. Rather than concentrating on a singular California city, for Alaska to successfully grow the exited markets, it would have required growing a customer base across seven different cities where Alaska was not necessarily a major player in the market.

Digging deeper into the San Diego market, Alaska has significant gaps within their San Diego portfolio. Of the eleven markets with over 300 passengers originating from SAN, Alaska only has service to five of the markets. Building a San Diego customer base would require Alaska to offer meaningful service other top originating markets to grow a base within the city.

While Alaska did withdraw from many non-originating markets, we can see them reallocating their service in other key markets (SJC, BOS, and MCO). To me, this does not point to a withdraw in the SAN market, rather a recalibration. If I was a betting individual, I suspect we will see a redeployment of additional E175s with medium frequency to many of the top short to medium-haul markets. If the aircraft and capacity are available, this type of deployment would increase relevancy in SAN while balancing new ASM exposure compared to longer-haul and larger-gauge markets.

If we are to see more redeployment within San Diego by Alaska, my best bet would be DEN, OAK, PHX, and maybe LAS, all top demand markets from SAN. These routes would likely be funded in part from the drawdown from the midcontinent and transcontinental that we saw announced within the last month. Further, I would suspect if these routes are going to operate within 2020, they would be announced within weeks to a couple of months to hit the ideal 2020 booking curve.

Given the recent moves by Alaska, it appears to me that Alaska is not withdrawing from their San Diego investment rather time will show their recent withdraws to be adjustments in a much longer-term strategy.

Wednesday, October 16, 2019

Why is JetBlue leaving Hobby?

In just a couple weeks, JetBlue will be packing its bags and leaving Houston Hobby (HOU) for Houston Intercontinental (IAH). The move, which was announced over the summer, may have come as a surprise to many. But this is not the first time a carrier picked up and left Hobby for Intercontinental. Remember, Frontier in 2012 leaving due to "customer feedback"? 

In JetBlue's press release they specifically state: 
"JetBlue regularly evaluates network performance, demand and customer feedback to strengthen its focus city strategy. The move to Bush Intercontinental is aimed at strengthening JetBlue’s relevance in New York and Boston, while also growing the carrier’s customer base in Houston where travelers love the airline’s award-winning service and competitive fares to and from the Northeast." 
Clearly, JetBlue was not happy with their performance at HOU and believe their Boston and New York customers would prefer IAH. So, we will evaluate JetBlue's statements regarding market performance as well as examining some of the Houston economic factors which likely drove the change.

It is important to understand JetBlue's history in Houston. JetBlue launched JFK to Houston service in 2006 with three daily A320 flights. Within a year, the A320 service was swapped for mostly E190 service. In the middle of 2008, the service was further downgraded from three flights to two. For the next five years, flights out of Houston remained largely unchanged outside modest fleet adjustments here and there.

As JetBlue started to build up its Boston franchise, Boston to Houston was launched in 2013. Initially, the route operated with two daily flights to Boston, however, lagging performance forced JetBlue to change the Houston set up. In the latter part of  2014, both New York and Boston were trimmed to one daily A320 flight in each market.

Taking a look at JetBlue's 2013 RASM curve, Houston to Boston service revenue production was significantly below JetBlue's RASM curve. JFK appears to be inline with system unit production. However, for both of these routes, it is important to remember that being below a RASM curve does not guarantee a route is losing money nor a route on the RASM curve to be making money. The greater the deviation from the RASM curve, the high the probability a route is over or under-performing to expectations. Given the large Boston deviation, Boston appears to be significantly underperforming.

For the Boston to Houston to close the gap between the RASM curve and our estimated RASM, the route would have needed to produce an additional $5,000 per flight. I want to reemphasize what this gap actually means. A gap above or below the RASM curve does not mean a carrier in making or losing money. Rather, it shows a perceived revenue opportunity cost of not operating a flight producing system-level revenue results.

While the performance on the route has significantly improved since the route was launched, the revenue performance still appears to be below where a route operating at this distance should be. Further, the route has largely remained stagnant since 2015 in improving the unit revenue.

One of the largest drivers in underperformance on JetBlue's BOS-HOU was its load factor. The carrier started the route incredibly soft, filling just over 50% of their seats. This significantly lagged its competitor's Southwest and United. Even with downgauging aircraft and cutting flights from two to one, the route still lags competitors' load factor to this day.

We can break down each carriers' load factor. In doing so, we quickly see that JetBlue's load factor softness is due to network design, not lack of demand. In fact, JetBlue outperforms other carriers' local load factor (load factor contributed only to passengers flying between Boston and Houston as their origin and final destination). This outperformance has only increased since the route was launched in 2013. However, without a network in Houston nor Boston for passengers to connect, JetBlue cannot flow additional passengers on the BOS-HOU leg.

With revenue gains stagnant and an inability to flow passengers via BOS-HOU, why look north? Hint: It is due to the local Houston economics. The IRS and Census Bureau provides a significant amount of data to understand and target areas of wealth in Houston.

Below, we pulled the 2016 IRS 1040 tax filings by zip code. Within the data, we can see how many tax returns were filed, the number of dependents, and a range of income metrics. Below, we mapped this data to show the population size and the average adjusted gross income by zip code. The two black dots are the location of Hobby (south side) and Intercontinental (northside).

Quickly, we notice the larger and wealthier population clusters are on the north and west side of Houston. While there are smaller, wealthier zip codes closer to downtown, Hobby is not necessarily that much more convenient. According to Google Maps, a traveler departing early in the morning from the west side of downtown (zip code 77027) would experience a 25-minute ride to Hobby vs 30-minute ride to Intercontinental. Mileage is incredibly deceiving. The access and egress from Hobby is largely city streets compared to the highway infrastructure around Intercontinental.

Further, Hobby does not have convenient access to some of the largest headquarters within the area. We were able to find a collection of mapped Fortune 1000 headquarters. When mapped the data shows the southside of Houston is largely a Fortune 1000 headquarter desert. Intercontinental, however, does have access to nearby headquarters as well as equally competitive access to headquarters located downtown and on the Houston west side.

It appears based on the information above, JetBlue really only had a few choices. They could stay with the status quo and keep a subpar route, remove the seventeenth-largest Boston demanded market from their network, or move airports and hope for better performance. With JetBlue's ambition to grow Boston to over 200 daily departures, removing one of the top O&D markets is really not an ideal plan. Neither is keeping the status quo on an underperforming market. So JetBlue is doing their next best option and moving to Intercontinental on October 27th.

Do you believe I missed something or think I am incorrect? Let's have the discussion below! You can also suggest future topics for me to review.

Wednesday, October 9, 2019

Mistakes were made: How I failed to understand the basics

After getting the call that US Airways was withdrawing from Colorado Springs, I went into an immediate reaction to help prepare my leadership with the best possible explanation for US Airways' decision. I started to pull what data I knew. It was inevitable the press would be calling the following morning. Following my (flawed) analysis, we took the stance that the route failure was likely due to the cost inefficiencies of the 50 seater aircraft in the market. If US Airways had operated the right aircraft within the market, the route would have continued to be successful. (Press coverage)

Like most US airports at the time, we heard the 50 seaters were dead men walking and airlines upgauging to drive unit costs lower was the way of the future. Based on my analysis, our revenue and load factor performance were on par with other US Airways flights. It was only logical to believe the route failure was based solely on aircraft costs.

In reality, route level trip cost modeling based on public data is incredibly complex, unlike ticket revenues prorates. Ticket revenue prorate methodology generally follows either the square root of mileage or IATA predetermined prorates. These two methodologies deliver result in very similar results. Since IATA prorates are not public, revenue modeling used by most large data suppliers, including my models, typically follow the square root of mileage methodology.

For trip cost modeling, there is no industry standard for an airline to prorate indirect costs (aircraft ownership, maintenance, headquarters overhead, etc). Each airline's finance department determines their individual methodology. Without an industry-standard cost model, any cost model based on public data pushed to the route level will have material gaps. So much so, I would argue such models should not be used when analyzing route level performance nor presenting business cases to airlines. More on that another time.

Now, it's cringe time. When joining the industry ten years ago, I believed that the airline profitability formula was simple RASM - CASM = Profitability. The term stage length adjustments or understanding the decaying relationship between RASM and distance never crossed my mind. In my mind, all RASM was equal. No adjustments needed.

After US Airways informed us they were leaving, I produced a chart similar to the below. The below chart attempts to show COS-PHX RASM was significantly above US Airways mainline CASM. Therefore, we assumed if US Airways would just operate mainline aircraft, COS would be profitable, hence the statement "... the carrier could be losing money in the Springs because it was flying 50-seat regional jets on the route that are more expensive to operate than larger aircraft." If you didn't realize it from the graph, this is wrong. 

Further analysis backed up my hypothesis. According to DOT data, COS station outperformed the US Airways network across three core metrics we were tracking: RASM, load factor, and passengers flying nonstop on the route. Segment fares were soft but with the threeway battle in Denver, it was not surprising.

If you are new analyzing airlines, the presentations above likely did not throw red flags. At best, the RASM chart shows the bell shape curve that skews right towards higher performance. So, what is wrong? Well, it's all in the curves.

One of the first steps airport professionals do when analyzing route performance is graph a scatter plot of RASM vs distance. US Airways' COS-PHX route was right in line with the RASM curve for the US Airways' network (note: different data providers may show RASM differences). RASM curves demonstrate what an airline typically demands it's unit revenue performance over a unit of distance to be.

US Airways' 2008 RASM curve looks similar to a typical RASM curve. The shorter the stage length, the higher the RASM. Because of this, taking a simple market-level RASM and measuring to see if it is above or below the system CASM really was meaningless. Further, the bell-shaped curve that I produced for my leadership was simply a system representation of US Airways' network build rather than performance. 

Digging deeper into the performance of COS-PHX, on the surface, the route may not have caused significant concerns. The 2008 RASM appeared to be inline with system averages. However, it is important to trend the route performance over time and consider the entire environment in which the route was operating. However, it is important to note, while we do not know exactly what the route's CASM was, generally the smaller the aircraft the higher the CASM. While Colorado Springs was operating in line with system stage length RASM, however, it was produced on some of US Airways' highest CASM producing aircraft. 

Taking a look at the route's history, in the mid-2000s, the route lagged significantly in load factor (65%) with a $122 average segment fare. The US Airways' Revenue Management team clearly was not happy with this performance. Segment fares appear to be sacrificed drive up leg load factors throughout 2006 - 2007. At the same time, the Network Planning team decreased the gauge of the aircraft. All of these actions did increase load factor, but it did not actually stimulate additional passengers until 2007 when the segment fares were down 20% vs 2005. 

Further, RASM really did not respond until 2007 and stayed flat in 2008 as the team tried to raise fares back to historical levels, likely in response to significant fuel cost pressures. However, as the fares increased, demand would drop off.

In the final year of service, US Airways seemed to be heading back to decreased performance. RASM was near a five-year low, segment fares were there to match, and US was operating some of their smallest (and highest CASM) fleet within the market. At the same time US Airways was also working on upgauging and removing smaller aircraft markets from its Phoenix network. In 2008, US Airways discontinued EUG, CLD, ASE, and OKC, all of which were operated on aircraft similar to their COS-PHX route. 

Clearly, US Airways was having significant issues with fares and passengers in the market, but why? In 2006, Southwest entered Denver with an aggressive growth and fare strategy that pressured the entire Colorado to Phoenix market. Before Southwest's arrival into Denver, Denver to Phoenix fares averaged $120, however, one year later, the fares were averaging below $80. Colorado Springs fares did follow with a premium. 

US Airways did not only see pressure within the local Phoenix market but their California via Phoenix, which was the top flow markets, also saw pressure. As the intensity of the competition in Denver increased, fares Denver to California began to decline. Over the course of five years, fares Denver to California were down 25%. At the same time, fares within the Colorado Springs to California markets were relatively flat, however, passengers declined as much as 20% as passengers decided to forgo Colorado Springs for Denver's fares and service offerings. 

US Airways clearly faced a no-win situation. The growing Denver competition placed significant pressures on Colorado Springs. Any attempts by the US team to increase fares resulted in losing passengers to Denver competitive carriers. The Network Planning team was already operating some their smallest Phoenix aircraft into the market, so the ability to downgauge further was off the table. Finally, other similar-sized markets were being removed from the Phoenix network. Really, US Airways had only one choice, remove Colorado Springs from their network. And that's exactly what they did. 

Friday, September 27, 2019

So, why are we here?

One year ago, I quit my job as a Network Planner at Southwest Airlines. It was a job I absolutely loved, but after a year of daily commuting between Dallas and Oklahoma City, it was time to be home. I was fortunate to work throughout most of the SWA commercial organization: Marketing, Finance, and Network Planning. These positions were highly analytical and dug deep into the company's performance data using SQL, Alteryx, and Tableau. But the high degree of exposure to and understanding of airline data didn't start that way.

When I started in the industry, the economy was still climbing out of the giant crater it buried itself in, I was one year into my first professional job after college as Colorado Springs’ first air service development analyst.

In Colorado Springs at the time, it was common for carriers to cut flights. The economy was declining and there was a three way battle for supremacy in Denver, just an hour up the road. Customers flocked from all of southern Colorado to Denver for the low fares and higher frequencies. Customers demand schedule, price, and service and compared to Denver, Colorado Springs had none.

In the fall of 2009, late in the night as I was traveling somewhere on a dark stretch of I-70, my phone rang. It was my airport director; US Airways was dropping Colorado Springs from their network. We were shocked. Flights were full. Phoenix was a top O&D route out of Colorado Springs. Why would a carrier want to drop what we believed was a high performing route? This brings me to the mission of this blog.

For airport professionals and avgeeks everywhere, finding airline performance data can be difficult, expensive, and often not well understood. Through this blog, I hope to demonstrate the basic principles of airline economics and explain why I believe airlines are making route and capacity moves. I will analyze the vast availability of aviation data from the DOT, FAA, and other sources as they become available. Given the data constraints, my analysis will largely look at historical trends, as forward schedules are not published publicly in a queryable manner.

In time, the blog will also take a look at other aviation data. While initially airline focused, I hope to expand to other data sources as I get access to them. Take a look at the data sources page. If you see a data stream you think should be included in this blog, send me a message.

Finally, one last note. If you are new or still learning the airline world, please work with a consultant or get an experienced mentor within the industry. This blog will not teach you everything you need to know. A great consulting group or mentor should be willing to teach you how to analyze data, put together your condensed business case, and build the right relationships to make your airport as successful as possible.

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