Running an airline is a highly complex activity. There are plethora of variables that disrupt operations. In essence, an airline’s schedule is its business plan. Stick to the plan (all things being equal) and you make money, as forecast. But fall behind schedule, with fixed revenues and variable costs, you will lose money. Come in ahead of schedule, and you make better than expected profits, as actual costs are lower than projected. An airline cannot pad its schedule too much because of competition – there is a limit to gaming the system.
With this in mind, we have developed a metric which we are calling the AirInsight Operations Index. This metric takes into account a number of data points about operational performance. We believe the metric is a useful way to account for the variables and demonstrate how well an airline is performing against its plan. We will illustrate the AirInsight Operations Index with two examples. In our model, zero represents performance at plan. If the curve rises above zero, performance is running behind plan and when the curve goes below zero, performance is better than plan.
Example 1: Comparing Boeing 717 operations.
The Boeing 717 is used by AirTran (now part of Southwest Airlines) and Hawaiian, and will soon be used by Delta as they acquire the former AirTran fleet. Tracking performance over time, the chart below illustrates that as AirTran transferred its operations to Southwest, its 717 fleet performance declined. Since that take-over, our index shows that the 717 at AirTran started to perform more poorly; in 1Q12 the airline saw its average 717 flight arrive 3 minutes early but in 1Q13 average flights were 2 minutes behind schedule. In 1Q12 25% of the 717 flights had late arrivals; in 1Q13 34% of the arrivals were behind schedule. We estimate airline’s costs rose 9.2% between these two periods, losing the impact of cost savings from early arrivals in 1Q12 to late arrivals in 1Q13 cost the operation approximately $6m. By comparison Hawaiian, with operational costs for its 717s with reported higher costs than AirTran’s, has been more consistent over the period, with a trend towards improving performance in 2013. The divergence in trends is quite distinct, as Southwest’s 717 performance has deteriorated while Hawaiian’s 717 has improved. Our index accounts for stage lengths.
Example 2: Looking at the Long-Range Fleet Performance at Hawaiian
Again using Hawaiian as an example, the next chart measures performance of the long-range fleet using our new metric. It appears that the Boeing 767 fleet is less economically effective for the airline than its Airbus A330 fleet. This could be expected, given the age differential of the fleets, the A330 being much newer.
The 767-300s have noticeably higher arrival delay (typically 10 minutes) than the A330s. Both fleets fly similar routes that should allow for crews to “catch up” to schedule. Yet 49% of the 767-300 flights arrive delayed, 42% of the 767-300ER flights arrive delayed while only 37% of the A330 flights arrive late. Though the A330 costs 6.2% more to fly, it is able to deliver better schedule efficiencies. Even though the airline as a whole sees schedule impact from late arrivals, we estimate the A330 delay costs at less than an eighth of the 767-300 and less than a third of the 767-300ER. The A330 continues to offer operators compelling economics, as our story last week demonstrates.
Our metric provides analysts a useful measure to see how effectively an airline is operating against its business plan – and in effect rates airline operational management. Combining a number of factors in measuring performance, we believe our proprietary metric is a useful guide of airline operational performance. Many people and tasks have to be in symphony to accomplish an on-time schedule with its attendant financial implications.
AirInsight will continue to develop its new analytical metrics over the coming year, and plans to offer access to a proprietary integrated database that incorporates on-time performance, fleet, and airline financial data, along with an analytical tool that enables easy searches by airline, aircraft type, down to tail number. For further information, please contact us at firstname.lastname@example.org.