American Airlines Managment Essay Research Paper American

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

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


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


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


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


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


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


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