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Dear IATA,

In your recently published Annual Review there is a small, but disturbing, graph that shows how global passenger and cargo loadfactors developed between 2000 and 2016. While the passenger loadfactor increased from around 70% to close to 80%, the cargo loadfactor moved sideways between 45% and 50%.

However, the published cargo loadfactors are distorted and misleading. The root cause for these distorted analyses, is the method through which these particular cargo loadfactors are calculated.

The industry’s standard of dividing freight tonne kilometres (FTKs) by available tonne kms (ATKs) is outdated. In the vast majority of all passenger and freighter flights, it is the volume capacity (in cubic metres) which is the bottleneck, not the weight capacity (in tonnes).

This is caused by the aircraft’s higher capacity density (available tonnes/available cubic metres) than the density of the goods that need to be moved. A loadfactor based on used/available cubic metres, would therefore provide a far more accurate overview on how full the plane is. Changing to such a metric would have a dramatic impact on the overall cargo loadfactor.

This difference in freight and capacity density implies that the volume loadfactor will be higher in most cases than the weight loadfactor. And by no a small margin.

During my years as a consultant, I have analysed the cargo loadfactor of numerous airlines and countless flights. The common finding from these analyses was that the volume loadfactor of widebody passenger and freighter flights was between 10%-20% points higher than the weight loadfactor.

This new metric would also reduce the overall distorting effect of the cargo loadfactor of narrowbody passenger flights on the overall cargo loadfactor. The design of these aircraft result in a difference between the freight and capacity density far greater than on widebody flights. For example: a Boeing 737 with a capacity of 2,000kg/4cu metres moves a shipment of 500kg / 3 cu metres. I would argue that the loadfactor of 75% based on volume is a more accurate figure on how the cargo capacity is utilised, than the 25% weight load factor.

I would not be surprised if these two factors combined would result in an overall volume loadfactor of 20-30% higher than the current weight loadfactor as you publish.

A loadfactor of 70-80% tells a very different story of the industry as a whole than a loadfactor of 50%. And that is why the graph in your Annual Review disturbs me.

Without the above context, cargo airlines seem less efficient in using the available cargo capacity, than they actually are. Politicians, regulators and other stakeholders could draw the wrong conclusions, with all sorts of undesirable decisions as a result.

It is your mission to represent, lead and serve the airline industry. Getting a more accurate loadfactor seems to fit perfectly within this ambition.

May I thus ask you to take this on and start discussing an alternative, better way of representing the capacity utilization in our industry?

Yours truly,

Niall

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  • David Harris

    September 04, 2017 at 2:56 am

    But even after switching from weight-based to volume-based load factors, there is still the problem of useful capacity vs. non-useful capacity. That is, belly space on routes with little or no cargo demand, and belly space in the aircraft in many low-cost carrier fleets, may be theoretically “available”, but including it in the capacity part of the load-factor equation just distorts the result.

  • Joy Banerjee

    September 06, 2017 at 1:19 am

    There are some valid points in this letter. Unfortunately cargo load factors will always rely upon certain assumptions. Cargo capacity on a given aircraft type is quite variable, depending on the route, the prevailing weather pattern, the passenger configuration (more economy seats, more bags, less cargo capacity), etc.
    The challenge in switching from a weight based load factor to a volume based load factor lies not only in its reporting (internally airlines may report volume, however at many airports they report weight), but also in the question of how to draw historic comparisons.
    Nevertheless a discussion is warranted, and the solution may not be as complicated as it may seem. Possibly start with a review of pivot weights per ULD?