ACRM Solution Overview
An ACRM solution should ideally have the following high level features:
• Automatically process key revenue management modules at
night for up-to-date flight capacities, overbooking levels, demand
forecasts, allocations and bid prices.
• Interactively run revenue management modules and options
to review and modify model outputs as well as change model inputs.
• Ability to create weekly, monthly and yearly management
reports on service failures, load factors, and revenues.
• Pro-actively manage flights by alerting users when certain
conditions are met or not met in terms of potential service failures
or revenue opportunities.
• Manage flights in a simple and more efficient way with user-friendly
A revenue management solution for air cargo will have the
following major components:
• Capacity Management
This includes forecasting physical capacity available for cargo
after accounting everything that has a higher boarding priority
than cargo, estimating the show up behavior, and combining the two
to optimally set overbooking levels. The overbooking levels or percentages
when multiplied by the physical capacity provide the capacity available
for sale or authorized capacities.
• Allotment Management
Allotment management focuses on two main aspects. It optimally determines
the split between allotment and free sale space on flights based
on allotment requests, free sale demand forecasts, flight capacities,
and routing options and costs. It also determines the allotment
requests to be accepted and the amount to be granted.
• Network Management
This determines the allocations for different categories of free
sale demand based on free sale demand forecasts, free capacity forecasts,
and routing options and costs. This also optimally determines the
weight and volume hurdle prices for the flight departures.
In air cargo revenue management, there are two general planning
horizons. The first one is known as ‘flight period’
and this is typically associated with seasonal schedule. Allotment
management is performed at the flight period level; however, there
may be ad hoc allotment requests during the flight period. The second
planning horizon is known as ‘booking period’ and is
typically associated with the period when flights are open for booking.
Most airlines open the flights for booking about 30 days before
departure and some open only 14 days before departure. In general,
a significant percentage of cargo bookings occur within two to five
days of departure. Capacity and network management are performed
during the booking period.
In summary, an ACRM solution addresses the following business functions:
FORECASTING - determine available cargo space by flight for future
RATE FORECASTING - predict flight leg-level booking behavior in
terms of no-shows, cancellations, and over/under tendering.
- determine the amount of additional capacity to be made available
for booking, to offset the impact of no-shows, cancellations,
MANAGEMENT - determine the mix between permanent bookings and free
sale as well as the allocations among various stations and
FORECASTING - project origin/destination demand based on historical
data and current bookings.
PRICING - determine minimum acceptable price (‘bid price’)
for a shipment considering network demand and capacity.
MODEL – calculate route costs considering handling, fuel,
trucking, interline, etc.
- generate operationally feasible routes considering shipment, aircraft,
and network characteristics
VALUE DETERMINATION – ability to assign values to customers
based on certain criteria such as volume of business, revenue, type
of cargo, and usage
There are about five major categories of data required to support
a cargo revenue management solution.
• Reference data
This includes information on aircraft, ULD, cities served, products,
costs, etc. For example, aircraft reference data will include all
the aircraft types operated by the airline and basic information
on each aircraft type such as default payload, belly volume, and
configuration. ULD reference data may contain volume, weight, and
dimension for each ULD type.
Passenger flight schedule data includes three basic types. The first
one is seasonal schedule which is available at the beginning of
each season. This provides information on all flights that operate
during the season. Flight information includes flight number, leg
origin, leg destination, equipment, days of operations, etc. The
second one is changes to seasonal schedule and this may be available
on a weekly or monthly basis and it overrides the existing seasonal
schedule. The third one is operational schedule changes that usually
occur within the last 48 to 24 hours. Schedule and schedule changes
are the primary data as all the revenue management controls are
calculated or forecasted for the flights that are in the current
active schedule. Seasonal schedule and changes to seasonal schedule
are generally available from the flight scheduling system. Operational
schedule changes are available from flight operations system. In
addition to flight schedule, freighter and truck schedule is also
needed. Freighter and truck schedule are generally obtained from
the cargo reservations system.
• Post departure flight data
Post departure flight information is actual data for a flight when
it departed and it includes data such as payload, underload, cargo,
mail, bag, passenger, etc. This information is required to forecast
payload, mail and other components that are required for calculating
cargo capacities. Post departure flight data is generally available
from departure control system or load planning system.
• Passenger forecast
This is required in the case of passenger airlines for determining
capacity consumed by passenger related aspects. This includes passenger
forecasts by cabin class for future flight departures. Passenger
forecasts are used in calculating expected passenger weight and
bag weight on board, bag volume occupied in belly, and bag containers
at departure. This is then used in cargo capacity calculations.
Passenger forecasts are provided by the passenger revenue management
• Air waybill data
This includes three categories of air waybill data; booked, tendered,
and flown. Booked and tender data are used for calculating the show
up behavior. Booked information is also used for demand forecasting
purposes. Flown air waybill data is used for reporting purposes.
Air waybill data includes shipment data such as origin, destination,
commodity, weight, volume, and pieces, customer data such as customer
ID, flight data such as flight number, departure date, and flight
origin and destination, and other information such as product and
Implementing air cargo revenue management is quite challenging and
it typically takes anywhere from nine months to two years for a
full solution. The duration for implementation is primarily driven
by four key aspects: integration/interfaces with other air line
systems, data collection, business process alignment/changes, and
customization requirements. The recommended approach is to implement
the solution in three phases: capacity management first, followed
by allotment management, and finally bid price management. The reasons
for implementing the revenue management solution in this order are
• This approach ensures that simple and easy to understand
modules are implemented first to increase the level of comfort and
confidence in revenue management among the users.
• The effort and duration required for the first phase or
capacity management is relatively short and the benefits are typically
• The extent of business process changes required is relatively
small or almost nothing.
• Data required for the first phase is generally available
without much of a challenge and the interfaces to other systems
are in a batch mode
The above four aspects become more challenging as implementation
proceeds from first to second and third phases.
Air cargo revenue management is a relatively new field and is still
evolving in terms of concepts, models, and implementation aspects.
Only a handful of airlines have actually implemented air cargo revenue
management solutions and one of the main reasons is the lack of
awareness of the impact of revenue management to the air cargo business.
This is partly due to the fact that air cargo business units in
most airlines are still not viewed as separate business units with
their own profit and loss structure. However, more and more airlines
are now feeling the pressure to get the most out of their cargo
operations. This is creating the need and awareness and has been
pushing the adoption rate of air cargo revenue management. The solutions
available in the market place have also reached a level of maturity
to address the unique revenue management business needs of the air
cargo industry. Airlines that have implemented air cargo revenue
management have actually realized significant revenue benefits.
We will certainly see more and more airlines starting to use cargo
revenue management solutions over the next decade.