Excellent work in reducing unit costs in Q2’16, exceeded expectations.
Disappointing revenue performance.
Excellent ancillary revenues.
Accumulated losses around 200 crore, losses since start of operations around INR 150 crore.
Financial & certain performance data reported by AirAsia India is inconsistent, inaccurate, and unreliable.
Before we begin the analysis of AirAsia India’s performance, it must be noted that the quarter reports of AirAsia are unreliable, on at least four counts, as observed:
The quarter report for Q1’16 (“SECOND QUARTER REPORT ENDED 30 JUNE 2015”) states that in Q1’15, AirAsia India reported a net loss of RM 0.4 Million. However, the quarter report for Q1’15 (“SECOND QUARTER REPORT ENDED 30 JUNE 2014”) states that AirAsia India reported a net loss of RM 13.8 Million. This translates to a difference of RM 13.4 Million / INR 25.9 crore.
The quarter report for Q4’15 (“FIRST QUARTER REPORT ENDED 31 MARCH 2015”) states that in Q4’14, AirAsia India reported a net loss of RM 12.4 Million, which, based on the RM-INR conversion rate prevalent then, converts to INR 22.7 crore. However, the P&L statement in the same Q4’15 report states that AirAsia India had a net loss of only INR 8 crore.
The quarter report for both Q2’16 (“THIRD QUARTER REPORT ENDED 30 JUNE 2015”) and Q2’15 (“THIRD QUARTER REPORT ENDED 30 JUNE 2014”) states that in Q2’15, AirAsia India recorded a net loss of RM 15.7 Million, which converts to INR 29 crore based on the RM-INR conversion rate prevalent then. However, in the Q2’16 report, AirAsia India is stated as having incurred a net loss of INR 52.9 crore.
The flown capacity (ASK) reported by AirAsia India in its quarterly reports is 12%, 5% and 3% higher than what the airline has reported to the DGCA in Q2’16, Q1’16, and Q415. However, in teh two sources of data, the number of flights by the airline match perfectly, and the number of passengers flown are reasonably close.
As a result of (3), we will refrain from comparing Q2’16 data with Q2’15 data, but will only compare Q2’16 data with Q1’16 and Q4’15 data.
As a result of (4), we will refrain from using the AirAsia India flown capacity as reported in the quarterly reports, as this leads to very misleading performance numbers. We stick to the DGCA data.
We had already mentioned the first three points, but the discovery of issue (4) made us withdraw our earlier analysis and revise the numbers. This is the revised analysis.
Due to the ambiguity resulting from points (1), (2) and (3) above, the total losses accumulated by AirAsia India including Q2’16 is around INR 200 crore. Total losses since start of commercial operations (ignoring June 2014) stands at INR 150 crore as reported by AirAsia India.
Q2’16 (July 01st – September 30th, 2015) was AirAsia India’s first full quarter of 5 aircraft operations. In this period, the airline flew 416,182 passengers (excluding no shows: 401,905. No shows : 3%), which is a 38% rise compared to Q1’16, though the number of flights increased by 50%. This explains Q2’16’s load factors of 76%, as against Q1’16’s load factors of 83%. The load factors in Q2’16 were lower than the 79% witnessed in the other lean season – Q4’15. Load factors include no show passengers.
The airline operated 34 daily flights as of 30th September 2015, and flew its millionth passenger in the first half of August 2015.
Q2 is historically a lean season. Capacity in Q2’16 grew by 56% over Q1’16, despite flights increasing by only 50%. This is in line with the average stage length of each flight increasing to 1,208 km/flt from 1,146 km/flt. Low load factors, increase in average stage length, and the low pricing power in the lean season have together resulted in the average fare dropping to INR 2,684 in Q2’16 from INR 3,350 in Q1’16. In Q2’16, AirAsia India did not inaugurate any new routes, but added a frequency on the Bengaluru – Vizag sector, and hence, there was no significant effect of low yields due to new routes.
Ancillary revenues at the airline have picked up very well. From being just 8% of total revenue in Q4’15, to 10% in Q1’16, it touched 15% in Q2’16. This has been aided by the increase in cargo per flight, to an average of 1,205 kg per flight in Q2’16 compared to 1,074 kg/flt in Q1’16 and 971 kg/flt in Q4’15.
However, on a unit basis, the airline’s revenue per available seat kilometre (RASK) suffered a 27% drop from Q1’16 figures, to settle at INR 2.22/seat-km, due to the factors mentioned in the preceding paragraphs. The unit revenues are 22% lower than the Q4’15 lean season.
AirAsia India’s cost performance is very good, and has touched record low values in Q2’16.
Unit aircraft fuel expenses fell by 13% in Q2’16 compared to Q1’16, despite fuel prices falling by only 9%. Higher average stage length of 5% can only contribute little to improved fuel consumption. However, tankering and uplifting fuel from stations with low sales tax on fuel may explain a part of the lower fuel expenses. Sales tax at Vishakhapatnam is just 1%, Goa 12.5%, Guwahati 22%, Imphal 20%, and Delhi 20%. Delhi, Guwahati, Imphal and Vishakhapatnam operations, and increased operations to Goa in Q2’16 may have significantly contributed to the drop in fuel costs.
Inexplicably, the staff costs have dropped in Q2’16 compared to Q1’16, from INR 31 crore to INR 29 crore. While there is no obvious explanation for such a drop, it has resulted in the unit staff costs to drop by 41% in Q2’16.
Unit maintenance costs have increased by 2% in Q2’16.
Due to longer flights, capacity has increased by 56% but flights by only 50%, in Q2’16 compared to Q1’16 resulting in the 7% drop in unit user charges and related expenses, which are largely a per-flight expense.
Unit lease expenses have dropped significantly by 29% in Q2’16, attributable to increased aircraft utilisation, higher capacity and no aircraft having to remain on ground in Q2’16. Average lease rental per aircraft per month is INR 2 crore.
Other operating expenses, most of which are fixed, have been diluted by the higher capacity, dropping by 25% in Q2’16.
Other Income, which is treated as part of operations by AirAsia India, increased by 10%, positively impacting the bottom line.
The cumulative effect of increasing frequency, network changes, and increased aircraft utilisation, amongst others, has reduced unit total operational costs at AirAsia India by 21% (including other income which can also be a negative quantity as in Q4’15). This is a brilliant performance, though the drop in staff costs is yet to be clearly identified. One explanation is perhaps the reduction in training expenses due to stagnation of fleet growth, and perhaps the voluntary exit of certain crew.
Break Even Figures
In Q2’16, AirAsia India realised a per-passenger cost of INR 4,621, which is 10% lower than the INR 5,166 cost per passenger in Q1’16, but 15% higher than the INR 4,009 cost per passenger in Q4’15.
In Q1’16, AirAsia India incurred a loss of INR 1,469 per passenger. At the same unit passenger revenue of INR 3,154, AirAsia India would have needed a break-even load factor of 112%.
AirAsia India lost INR 1.04 per seat flown every kilometer, which is 5% lower than INR 1.09/seat-km in Q1’16, but 30% higher than the unit loss incurred in Q4’15.
AirAsia India’s cost structure is depicted in the pie chart. Fuel constitutes 36% of the airline’s expenses.
Cancellations and OTP
Only 6 flights were cancelled by AirAsia India, in Q2’16. The airline operated 3,032 flights, with an average on time performance (OTP) of 87%.
In Q3’16, AirAsia India inducted its 6th aircraft into operations, in the second half of November 2015. Daily flights have gone upto 40, with increase in frequencies and the inauguration of a new route, Delhi – Vishakhapatnam.
Our forecast for AirAsia India’s performance in Q3’16:
Quarter’s Load factors to increase to around 85%.
Capacity to increase by 12% and passengers carried (including no shows) to touch around 520,000.
Average unit passenger revenue may rise by around 20%+ compared to Q2’16.
Certain unit costs to slightly increase due to addition of 6th aircraft and sending one aircraft for half a month for scheduled heavy maintenance.
Certain unit costs to very slightly increase due to weather related delays and diversions.
Ancillary Revenue percentage to drop in light of higher average fare.
For break even, unit passenger revenue must rise by around 45% (compared to Q2’16)
Very slim chance of an operational break-even. More likely in Q1’17 (April – June 2016).
DGCA published data pertaining to an airline’s performance, commonly quoted by the media, such as Load Factors and OTP, is unreliable and misleading.
The data errors can only be recognized in single fleet airlines and/or airlines that have only recently started operations. In both cases, simplicity allows for cross verification of data.
Investigation into the data errors was suggested by a senior officer of a full service Indian airline.
The most interesting of all airline performance indicators is load factors. Load factors are often looked upon as indicators of successful commercial operations at an airline.
DGCA publishes certain airline related data based on an ICAO (International Civil Aviation Organisation, a UN body) ATR (Air Transport) ‘FORM A’. This form is filled and submitted by airlines to the DGCA, which the DGCA then uses to report load factors airline wise.
The manner in which the DGCA computes load factors is by dividing Passenger-Kilometers (PK) by Available seat Kilometers (ASK). PK is a product of total passengers flown and the total kilometres flown by the airline in a particular month. ASK is the number of seats on all flights multiplied by the total kilometres flown by the airline in that particular month. Dividing PK by ASK simplifies to the ratio of Passengers Flown by Available Seats, which is the definition of load factor.
Another way of computing load factors is to determine the available seats using data not reported in ICAO ATR FORM A. This is the number of seats on every flight. FORM A mentions the number of departures in a month. In single fleet airlines such as IndiGo, Go Air, AirAsia and Vistara, the number of seats on every aircraft is uniform fleet-wide. This means that every flight on each of the above mentioned airlines flies 180, 180, 180 and 148 seats, respectively.
Multiplying the number of flights by the number of seats per aircraft will result in the number of seats flown in that month. Dividing the number of passengers flown by the number of seats gives us load factors for the month.
The first and second method should result in the same numbers. However, this is not the case. Below is the reported load factors versus the computed load factors for IndiGo since it started operations. The two methods agree with each other till December 2008. From January 2009, when the DGCA changed its format of reporting data, the errors have been present, and have been unacceptably large and inconsistent.
The data shows that, according to computations, domestic load factors at IndiGo never crossed 90%, and that load factors crossed 80% only on 7 occasions in 9 years. Average domestic load factors at the airline, across 9 years, is recomputed as just 71.5%, with the highest at 83.3% in the month of May 2015. Of course, this arguably assumes that the number of departures and the number of passengers reported by the DGCA are correct.
Similarly, AirAsia India’s and Vistara’s load factors are not always representative of the actual load factors. In the case of these two airlines, the error is small. However, every 1% error in load factor corresponds to a monthly revenue of INR 56 lakhs for an airline the size of AirAsia India, and INR 16 crore for an airline the size of IndiGo.
Vistara’s load factors have never crossed 70%.
Below is that of Go air, for 9 months only:
Considering that the data is derived from what airlines have published, it may be that part of the onus for the error rests on airlines. It is difficult to compute the error in load factors of airlines such as SpiceJet, Jet Airways, Air India, and Air Costa.
Faith in our method of computation is based on cross checking certain computed load factors with the information revealed by a senior airline official.
On Time Performance
Airline on time performance is another parameter met with much enthusiasm. For example, for the month of April of 2015, DGCA reported that AirAsia India had an on time performance (OTP) of 100.0%. DGCA mentions the OTP as observed at only four airports: Bengaluru, Hyderabad, Mumbai and Delhi. Back then, AirAsia India was based only out of Bengaluru.
However, Bengaluru International airport, in its On Time Performance (OPT) report for April, clearly mentions AirAsia India’s arrival OTP as 89% and departure OTP as 98%. This averages to 93.5% OTP, which made headlines as 100%. (Click here for an NDTV piece on this)
Similarly, Go Air’s OTP for Bengaluru was reported by the DGCA as 88.9%, while the airport stated that the airline had an arrival OTP of 73% and a departure OTP of 86%. The DGCA’s OTP for Go Air at Bengaluru was impossibly higher than the higher of the two OTP for the airline for that month.
IndiGo’s OTP at Bengaluru was reported as 77.2%, while the airport stated that the airline had an arrival OTP of 73% and a departure OTP of 81%. In this case, the average of the departure and arrival worked out to 77%, which is acceptable.
In the case of SpiceJet, OTP at Bengaluru was reported as 68.2%, while the airport stated that the airline had an arrival OTP of 78% and a departure OTP of 78%. In this case, the reported OTP is lower than the actual OTP of 78%.
Data reported by the DGCA is very informative. The data is used by analysts and major industry bodies for studies, reports, and analysis. However, no matter how good the analysis, junk data in results in junk data out, with misleading facts and figures about the industry and the performance of airlines.
Poor data standards may give airlines a way to falsely drive up their performance figures, which may be for many reasons, such as driving up investor sentiment.
The DGCA’s capabilities (or the lack of it) have come under question both before and after the FAA downgrade. What is further disappointing is that the data published by the DGCA is not accurate enough to be used for serious academic or analytical purposes. When thumbing through the data for Jet Airways, it was brought to light that the data reported by the DGCA in its Traffic Reports and Traffic Data differ, and both differ from the data reported by the airline.
Interestingly, the errors reported in the ‘Traffic Data’ for Jet Airways as published on its site are at places huge. The ‘Traffic Reports’, released around the 15th of every month, are more accurate, but lack sufficient data for an analysis. Certain data with have an error less than 1% may be ignored on a case basis. But the question still lingers: how two publications from the DGCA can have largely differing data between them – an error that may not be attributed to rounding-off-error.
This discrepancy was brought to light only through Jet Airways’ published data. Since other airlines do not publish such data, the extent of errors and deviations are uncertain.
Further, in the month of November, two airlines, both flying with red colours, have had numerous cancellations and delays. Delays and cancellations are reported by airports. In the case of Bangalore’s Kempegowda International Airport, the airport has been using the term ‘rescheduled’ for one particular carrier (and interestingly not for any other carrier), which effectively masks both delays and cancellations. In such a case, a delayed flight, operating ‘on time’ in accordance with a ‘rescheduled’ departure timing will prevent true OTP data (though the DGCA does not yet list the OTP for the airline in question) and ‘Cancellation Rate’ from being published in Traffic Reports, making comparisons between airlines both difficult and unfair.