American Airlines Managment Essay, Research Paper
American Airlines is a corporation that exhibits all of the characteristics of a firm in an
industry where good tactical management is the key to long term sucess and
survival. The airline industry is a prime example of a market where cutthroat
competitive activity is the status quo. Airlines that survive in this environment do so
through the understanding and continued improvement of the way in which tactical
management tasks are addressed. Success is dependent upon doing all of these
tasks well including demand forecasting, logistical programming, marketing and
production. The key point to remember is that since American Airlines is a tactical
entity, its key area of concentration is equilibrium maintenance. A continual endeavor
must be made to match supply closely to demand, especially anticipated demand. If
it is not likely that production can be amended to more closely match demand, then
promotion should be used to affect demand.
American Airlines dedicates large amounts of time and resources to the types of
facilities necessary to support the tactical management tasks noted above. This
report is an attempt to illustrate the types of information system requirements of
each task in the tactical management sequence, as well as describe some of the
systems and methods used by American Airlines. In addition, this report offers some
off the shelf alternatives, where they exist, which could handle many of the same
requirements, albeit on a smaller scale. Since demand forecasting is one of the key
drivers of production, i.e. how many products a firm should supply, this will be the
first management task to receive consideration.
All firms engaged in activities as a tactical entity will, in some form or another,
attempt to get a handle on expected demand for their products within a certain
future time period such as a week, month, quarter or year. The main thing to bear in
mind is that this is a tactical environment and, aside from any earth shattering new
developments or shocks to the existing environment, forecasts for expected
demand/maximum-likelihood share of market may be made with a fair degree of
accuracy with little variance. There are several key points that are important to this
process which must be considered when making a next period forecast of demand.
These items include, but are not limited to, intelligence concerning activities of
competitors, market projections for the industry by industry insiders/analysts, and a
great deal of historical data.
Competitive intelligence is a parameter which attempts to add subjective
background to the environment in which demand forecasting is carried out.
Information comes from a variety of sources such as secondary information gathered
from written sources, direct observation, and from competitors themselves through
press releases, industry gatherings and trade journals. This information provides
some indication of what the competition plans to do as far as pricing, new products,
promotions and distribution/sales. This data has a dual purpose since it may also be
used within model based contingency planning when management scrutinizes
competition in an effort to uncover developing threats and opportunities.
Experienced tactical managers have the valuable ability to incorporate this type of
information, which is not easily quantifiable, as a complement to the numerical
aspects of demand forecasting. However, this is not to say that there is no
information system requirement for this input into the demand forecasting process
simply because it is difficult to assimilate into an objective, quantifiable form. On the
contrary, a database should be set up in the context of an expert system to contain
information gathered on competitors. It must be readily accessible, updated and
accurate in order to aid tactical management in this process.
Another input item for demand forecasting comes from aggregate market
projections. These types of analyses are readily accessible, mostly in the form of
secondary information found in trade journals and economic publications. Airlines
and transportation in general comprise a large industrial group within the economy
of the United States and, accordingly, there is a large interest in its economic future.
Wall Street brokerage firms and other financial firms are resplendent with analysts,
some of which are charged with the task of tracking the airline industry?s past
economic performance, as well as anticipated future projections. All of this
knowledge is available from many sources and, again, wise tactical managers will
take the time to incorporate it. System facilities required for this type of support for
demand forecasting are databases which can contain quantifiable economic
information. Since this input to demand forecasting is quantifiable, a database with
analytical utilities for ranking and analyzing stored economic projections and raw
data are used. This facility may also be presented to management in the guise of a
dressed up expert system containing decision table constructs which will allow them
to adjust many demand forecasting parameters in order to make the most accurate
forecast.
Arguably the most important input into the demand forecasting process is a firm?s
actual historical data from its own internal records sources. Historical sales data may
be thought of as the most dependable and accurate input into demand forecasting
since it is derived by the firm itself rather than arriving in a second hand fashion from
sources outside of the organization. Historical sales data is helpful not only in
developing a demand forecast, but is also used as a check against post production
performance when the time arrives to compare actual demand to the forecast. This
information will likely come from another massive record keeping database which
records sales transactions from the point of sale. For American Airlines, as well as the
rest of the airline industry in general, this requirement is served through a
reservation system of some kind. The reservation system must be capable of
handling queries, data inflows and other types of processing from thousands of
nodes. Dummy terminals, which simply display data, will not be sufficient to satisfy
reservation system requirements, and any implementation will involve connections
and terminals designed to carry two-way traffic. Additional discussion of reservation
systems, including specifically what American Airlines has installed, will follow later in
this paper.
After satisfying system requirements for generating and handling inputs into the
demand forecasting process, the actual forecast derivation may be viewed as
somewhat mechanical. The main management decision at this point is determining
which type of probabilistic instrument to use with which analytical utility to yield the
most accurate results. Some tactical managers may even require an expert system
that does nothing more than aid them in selecting the proper mathematical tool to
address the forecasting process. There is an array of probabilistic techniques that can
satisfy this management requirement including least squares regression analysis,
weighted scenarios, Markov-based stochastic projections and others. Many tactical
managers may use a combination of these facilities to arrive at a forecast with which
they feel satisfied.
A key point to bear in mind when discussing demand forecasting for a tactical entity
is that it is central to two important aspects of the firm. The demand forecast is
viewed foremost as the progenitor of the firm?s production for which it is the main,
direct input. However, it is also an indicator of the general trend of the firm?s
revenues over time. A forecast whose extrapolation to the next period indicates a
decline in revenues may be an early warning of something novel in the industry or
indicative of a paradigm shift toward a new era. This aspect of troubleshooting will
be discussed more at length in a later section concerning requirements for process
control.
The demand forecast sets the stage for the next management task– logistical
programming and its accompanying system requirements. Logistical programming is
the task charged with accumulating proper amounts of the factors of production in
the proper place at the proper time. The four factors of production (material,
finance, equipment and manpower) have certain input requirements which
determine the amounts of each factor to apply to the production process. Each of
these inputs will necessitate the use of some type of information system to aid
tactical managers in allocation of these factors to production. One of the first inputs
into logistical programming is the supply schedule, which is the main determinant of
the amount of products or services offered by a firm. For the airline industry, supply
schedules manifest themselves in the form of the magnitude of flights offered to the
public.
A demand forecast is the main force behind the supply schedule, but other
normative microeconomic factors play an important role in its composition. One of
these factors, optimal scale of plant, exerts a direct relationship against the supply
schedule and, for American Airlines, consists of the optimal terminal/gate layout at its
busiest hub cities. The goal of proper terminal design is to optimize the number and
size of the complexes which converge on a hub terminal throughout the day. A
complex consists of a group of inbound flights which land within minutes of each
other and take-off within minutes of each other. This is the very heart of a hub and
spoke system which allows a large number of flights due to the number of possible
connections in the hub. Inbound passengers from many cities will all arrive at
approximately the same time, disembark, and make connections to many outbound
flights which leave within minutes of each other. This occurs many times throughout
the day and the system requirement for solving this problem and optimizing the
operation is available in the form of CADD design stations.
CAD/CAM design workstations may be used to solve terminal optimization problems
and allow engineers to simulate the capability of the terminal to handle certain
scenarios. This is, in fact, exactly what American Airlines did when it was searching for
the optimum design for its $80 million expansion of its main hub in Dallas/Fort
Worth in 1983. This simulation model was used by senior management to aid them
in their decision on the best design to handle the desired flow of traffic in the narrow
operational time constraints necessary for the hub to work. In addition to optimizing
the terminal layout, the system was useful in optimizing other related areas. The
system/model was used to determine dynamic gate assignments in order to
minimize baggage handling costs and passenger delays. Another byproduct of the
model was a useful algorithm designed to automatically program and update signs
for directing passengers around the terminal. The functional facility was even used to
determine the best layout for short-term parking in the face of expected increases in
passenger traffic.
Though optimal scale of plant through optimal terminal design is an important
aspect of American Airlines? supply schedule determination, the most important part
of the supply schedule lies in determining the number of flights to and from certain
destinations. For American Airlines and most of the airline industry, flight scheduling
is not a simple matter. Flight scheduling is one of the most important tasks
performed by tactical airline managers because it is central to where and how the
factors of production are allocated. The technical system requirements are myriad,
and they must meet the daunting problem of properly scheduling thousands of
flights per day between hundreds of domestic and international destinations using a
fleet of over 500 aircraft. One main requirement is for a system capable of analyzing
past flight offerings in search of patterns of overbookings and empty flights in order
to adjust schedules to better meet forecasted demand.
Technical requirements for an airline scheduling system would include a data base
structure to house the body of past and present schedules from which managers
could choose when composing a new schedule. The problem is compounded since
airline schedules are determined months in advance. In addition to using
optimization techniques, the system requires certain expert system facilities such as
decision table constructs to aid in schedule development. Diagnostic remedial aids
are used in order to spot bottlenecks in the proposed schedules where patterns of
frequent overbookings are occurring. In addition, remedial systems capable of
offering solutions by reshuffling proposed schedules provides valuable information to
flight scheduling managers. Historical data is fed into the scheduling model from the
database containing past schedules and data concerning past parameters which
influenced those schedules. The system takes this data and combines it with the
demand forecast in order to develop a preliminary schedule. The process requires
diagnostic and remedial systems to optimize the schedule so that the expected
demand will be met in the most efficient manner possible.
Even with an optimal schedule in place, there will always be disruptions due to
weather and shortages of planes and crews; thus forcing scheduling managers to
constantly rearrange flights. Before 1991, this was a complex task for American
Airlines since dispatchers had to scan data from many different mainframe databases
in order to get a handle on managing daily flights. The schedule was constantly
being reconfigured to meet anticipated external obstacles such as delays due to
inclement weather. In 1991, however, American Airlines invested in a new system
known as Smalltalk which made schedule maintenance easier and more efficient.
Smalltalk uses of object-oriented programming techniques in order to keep flights
running smoothly. The dispatcher simply clicks on an object representing a flight
and, when he changes the flight, the system automatically updates other objects
(flights) in the system in order to propagate the change throughout the entire
system. In fact, it only took three programmers eight months to write the program
which contained only two errors.
Once an optimal schedule has been developed through simulation and optimization
techniques, the next step is to arrange the factors of production in order to generate
enough products and/or services to meet prospective demand. Since manpower
costs equal over one-third of all expenditures for American Airlines, it is the first
factor to receive consideration. Manpower for an airline takes on many forms;
however, almost all of the employees of American Airlines can be classified into one
of three different broad categories. The first category represents the aircraft crew
whose duty stations are on the aircraft: pilots, copilots, navigators and flight
engineers, as well as the cabin crew or flight attendants. The second category is
referred to as maintenance workers, and they are the people that maintain the
aircraft, which includes anything from refuelers to engine mechanics. The final
classification includes all of the ramp workers such as baggage handlers, ticketing
personnel and office workers. By far the most difficult category to allocate within the
manpower group is the aircraft crews.
Manpower requirements for airline crews are derived from the flight schedule. The
main goal for crew schedulers is to develop a schedule for the entire following month
which will ensure that all of the upcoming flights for the month are properly staffed.
Flight crews at most airlines bid by seniority for the flights that they will fly in the
next month and crew schedulers develop flight packages for them. The flight
packages are known in the industry as bidlines. The bidlines in turn are composed of
flight segments called trip pairings, and they customarily cover a one to three day
time frame. Compounding the problem for the schedulers are FAA and union work
rules designed to minimize the risk of accidents resulting from crew fatigue.
Therefore, the main requirement of a generation and optimization system is that it is
able to find the optimal set of bidlines (i.e. the set which yields the lowest cost)
which maximize the utilization of each crew member, evenly distributes flying time
among the bidlines and covers every scheduled flight.
The properties inherent in the crew scheduling dilemma require an expert system
design. The first part of the system uses manpower loading algorithms, the current
and previous month?s schedules (from various databases) and optimization
techniques in order to develop the set of trip pairings, which would adequately cover
all scheduled flights for the upcoming month within FAA and union work guidelines.
The trip pairing process is made even more onerous because American Airlines
operates several fleets of different aircraft and most pilots are trained to fly only one
type. The following diagram illustrates the requirements for a crew assignment
system.
Source: “Recent Advances in Crew -Pairing Optimization Techniques at American
Airlines”, Interfaces, Jan-Feb. 1991, V.21, p. 66.
The second part of the system takes trip pairings and bidlines and analyzes them
(subject to optimization techniques) in order to constantly search for a solution
(schedule) which yields the lowest cost for flight crews possible for a given flight
schedule. The system will continually runs through iterations of the optimization
routine and, if the set of bidlines it determines is more optimal than the last, replaces
the former with the latter. Naturally, the faster the iteration speed of the system,
mainframe or LAN, the sooner the system arrives at the optimal solution. The
following flow chart describes the subproblem iteration methodology.
Source: “Recent Advances in Crew -Pairing Optimization Techniques at American
Airlines”, Interfaces, Jan-Feb. 1991, V.21, p. 67.
American Airlines as well as 9 other airlines and a railroad, makes use of a system of
this design and it accounts for an annual cost savings of $20 million.
Scheduling for ramp workers, gate crews and ticket counter personnel is less
complex and also dependent on the flight schedule. Scheduling systems for these
personnel are less complex but also involve optimization techniques in order to
arrive at the lowest cost for labor while ensuring that arrival and departure times at
each gate are as close together as possible. Manpower loading algorithms are used
to assign more personnel to cover peak times and less personnel in each station for
off-peak hours during lulls in the hubs. Office personnel and repair crews usually
work regularly assigned hours, in the absence of strikes and/or emergencies, and are
quite simple to schedule. It should be noted that Human Resources and Payroll
Departments need to maintain a database containing each employee?s work record,
salary history and personal information in order to keep track of thousands of
employees.
The next factor of production for consideration is the equipment to be used in
production to meet forecasted demand. As mentioned above, American Airlines
operates two large fleets of aircraft, as well as several smaller fleets. The main aircraft
types are the McDonnell Douglas 80 and Boeing 727. The smaller fleets are
comprised of Douglas Corporation 10, British Aerospace 146, Boeing 737, Boeing
747, Boeing 757/767 and Airbus 300 aircraft. A particular flight or route might lend
itself to a particular type of aircraft which best matches characteristics of the flight. All
airlines have an extremely high capital/labor ratio which is indicative of the large
dollar expenditures made for aircraft. The airline industry is a mature, tactical
industry and, therefore, lends itself to a capital intensive posture yielding a high
capital/labor ratio. Fleet assignment problems lend themselves to integer linear
programming, which is a good way to arrive at a solution.
Unfortunately, the best aircraft for a certain flight may not be available because of
maintenance routing, flight schedule disruptions due to inclement weather or even
pilot strikes. Objectives that must be maximized include utilization of the most
efficient types of aircraft and determining the mix of aircraft to yield the lowest
operating costs. Other operational constraint parameters the system will be required
to deal with include the fact that certain flights will need to use certain aircraft types,
limits on number of aircraft remaining overnight at each station and the number of
slots available per airport per day. The decision model uses the linear programming
methodology and schedules two or more fleets to a flight schedule simultaneously in
order to ensure the availability of aircraft to meet demand. The flight schedule,
availability of aircraft (which aircraft to use on a particular flight) and gate availability,
as well as other parameters, are fed into the system. It must be ensured that each
flight and its following connection, known as a turn, are served by the same type of
aircraft. Equipment continuity is very important to the model?s integrity and a turn
cannot use two different types of aircraft. Each aircraft must be kept track of and
counted within the system so the model will know whether an aircraft is available. An
aircraft cannot be assigned to two different flights in different areas at the same
time. In addition, a provision or adjustment variable must be made to the model
when the station is not balanced. An unbalanced station occurs when there are more
arrivals than departures or there is an imbalance between the aircraft types used. By
using decision aids and technical utilities, the model will arrive at the optimal fleet
assignment through continuous iteration much the same as the crew bidline model
for flight crew scheduling described above.
The third factor of production which tactical managers must develop system
requirements for is in the area of finance. Aircraft and other related equipment
purchases are a large part of the capital budgeting requirement of an airline the size
of American Airlines. An issue which is central to the capital budgeting plan for
aircraft is the age-old decision, “Should we lease or buy our aircraft?” Leasing and
buying both have very real advantages and disadvantages over each other, and
therefore this type of decision tends to be objective based on whichever method will
achieve the least detriment to the bottom line. Accordingly, there are several very
well-developed methods employed by financial and accounting managers when
evaluating capital budgeting plans. These popular methods include net present
value, internal rate of return, payback period and accounting rate of return.
Whether or not to undertake capital budgeting is not an issue for a capital intensive
firm such as American Airlines. The key problem to be solved in capital budgeting
then becomes which analytical model is the best application for evaluation of various
scenarios such as which aircraft to buy, when to buy and whether to purchase them
or lease from the manufacturer. A capital budgeting system will has to be a technical
and/or analytical utility in the form of an expert system to assist tactical managers in
capital budgeting. One of the main inputs into a capital budgeting system is the
forecasted incremental cash flows per time period attributable to the prospective
project. Data for this requirement comes from historical revenue records for the
aircraft in question. A lease scenario and a buy scenario can be run for each
prospective capital budgeting plan in order to determine which project will most
increase the profits of the firm. Algorithms to perform the number crunching can be
programmed into the system without much trouble since these are well developed
models. Again, the main purpose of capital budgeting is to act as a decision aid to
indicate which analytical methods/models will prove to be the most evaluators of a
project?s viability. After evaluating the project, the system should aid management in
where and how to obtain the needed funds to proceed with an acceptable capital
project.
The final factor of production and its attendant information facility requirements to
receive consideration in the report before discussing production is the material
aspect of the firm. For an airline, materials for production can include, but are not
limited to, items used in delivery of services such as aircraft parts, beverages served
on flights, in-flight meals, office supplies and many, many more. The main objective
is to effectively determine the correct amount of supplies and where to purchase
them at the lowest cost. Another goal is to minimize materials carrying and handling
costs through a quick response system between airline and suppliers akin to the type
endorsed in The Virtual Corporation. Inventories of aircraft repair an
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