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78 Part I • Decision Making and Analytics: An Overview

identified, and their mutual relationships are established. Simplifications are made,
whenever necessary, through assumptions. For example, a relationship between two
variables may be assumed to be linear even though in reality there may be some non-
linear effects. A proper balance between the level of model simplification and the rep-
resentation of reality must be obtained because of the cost–benefit trade-off. A simpler
model leads to lower development costs, easier manipulation, and a faster solution but
is less representative of the real problem and can produce inaccurate results. However,
a simpler model generally requires fewer data, or the data are aggregated and easier
to obtain.
The process of modeling is a combination of art and science. As a science, there
are many standard model classes available, and, with practice, an analyst can determine
which one is applicable to a given situation. As an art, creativity and finesse are required
when determining what simplifying assumptions can work, how to combine appropri-
ate features of the model classes, and how to integrate models to obtain valid solutions.
Models have decision variables that describe the alternatives from among which a
manager must choose (e.g., how many cars to deliver to a specific rental agency, how to
advertise at specific times, which Web server to buy or lease), a result variable or a set
of result variables (e.g., profit, revenue, sales) that describes the objective or goal of the
decision-making problem, and uncontrollable variables or parameters (e.g., economic
conditions) that describe the environment. The process of modeling involves determin-
ing the (usually mathematical, sometimes symbolic) relationships among the variables.
These topics are discussed in Chapter 9.

selection of a Principle of choice

A principle of choice is a criterion that describes the acceptability of a solution
approach. In a model, it is a result variable. Selecting a principle of choice is not part
of the choice phase but involves how a person establishes decision-making objective(s)
and incorporates the objective(s) into the model(s). Are we willing to assume high
risk, or do we prefer a low-risk approach? Are we attempting to optimize or satisfice?
It is also important to recognize the difference between a criterion and a constraint
(see Technology Insights 2.1). Among the many principles of choice, normative and
descriptive are of prime importance.

technOLOgy insights 2.1 the Difference between a criterion
and a constraint

Many people new to the formal study of decision making inadvertently confuse the concepts of
criterion and constraint. Often, this is because a criterion may imply a constraint, either implicit
or explicit, thereby adding to the confusion. For example, there may be a distance criterion that
the decision maker does not want to travel too far from home. However, there is an implicit
constraint that the alternatives from which he selects must be within a certain distance from his
home. This constraint effectively says that if the distance from home is greater than a certain
amount, then the alternative is not feasible—or, rather, the distance to an alternative must be less
than or equal to a certain number (this would be a formal relationship in some models; in the
model in this case, it reduces the search, considering fewer alternatives). This is similar to what
happens in some cases when selecting a university, where schools beyond a single day’s driv-
ing distance would not be considered by most people, and, in fact, the utility function (criterion
value) of distance can start out low close to home, peak at about 70 miles (about 100 km)—say,
the distance between Atlanta (home) and Athens, Georgia—and sharply drop off thereafter.

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