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Chapter 2 • Foundations and Technologies for Decision Making 81

different configurations of inputs and processes. However, because a descriptive analysis
checks the performance of the system for a given set of alternatives (rather than for all
alternatives), there is no guarantee that an alternative selected with the aid of descriptive
analysis is optimal. In many cases, it is only satisfactory.
Simulation is probably the most common descriptive modeling method. simulation
is the imitation of reality and has been applied to many areas of decision making.
Computer and video games are a form of simulation: An artificial reality is created, and
the game player lives within it. Virtual reality is also a form of simulation because the envi-
ronment is simulated, not real. A common use of simulation is in manufacturing. Again,
consider the production department of a firm with complications caused by the marketing
department. The characteristics of each machine in a job shop along the supply chain
can be described mathematically. Relationships can be established based on how each
machine physically runs and relates to others. Given a trial schedule of batches of parts,
it is possible to measure how batches flow through the system and to use the statistics
from each machine. Alternative schedules may then be tried and the statistics recorded
until a reasonable schedule is found. Marketing can examine access and purchase pat-
terns on its Web site. Simulation can be used to determine how to structure a Web site for
improved performance and to estimate future purchases. Both departments can therefore
use primarily experimental modeling methods.
Classes of descriptive models include the following:

• Complex inventory decisions
• Environmental impact analysis
• Financial planning
• Information flow
• Markov analysis (predictions)
• Scenario analysis
• Simulation (alternative types)
• Technological forecasting
• Waiting-line (queuing) management
A number of nonmathematical descriptive models are available for decision mak-
ing. One is the cognitive map (see Eden and Ackermann, 2002; and Jenkins, 2002). A
cognitive map can help a decision maker sketch out the important qualitative factors and
their causal relationships in a messy decision-making situation. This helps the decision
maker (or decision-making group) focus on what is relevant and what is not, and the
map evolves as more is learned about the problem. The map can help the decision maker
understand issues better, focus better, and reach closure. One interesting software tool
for cognitive mapping is Decision Explorer from Banxia Software Ltd. (banxia.com; try
the demo).
Another descriptive decision-making model is the use of narratives to describe a
decision-making situation. A narrative is a story that helps a decision maker uncover the
important aspects of the situation and leads to better understanding and framing. This is
extremely effective when a group is making a decision, and it can lead to a more com-
mon viewpoint, also called a frame. Juries in court trials typically use narrative-based
approaches in reaching verdicts (see Allan, Frame, and Turney, 2003; Beach, 2005; and
Denning, 2000).

good enough, or satisficing
According to Simon (1977), most human decision making, whether organizational or indi-
vidual, involves a willingness to settle for a satisfactory solution, “something less than the
best.” When satisficing, the decision maker sets up an aspiration, a goal, or a desired

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