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Chapter 2 • Foundations and Technologies for Decision Making 75

Problem (or opportunity) identification
The intelligence phase begins with the identification of organizational goals and objectives
related to an issue of concern (e.g., inventory management, job selection, lack of or incorrect
Web presence) and determination of whether they are being met. Problems occur because of
dissatisfaction with the status quo. Dissatisfaction is the result of a difference between what
people desire (or expect) and what is occurring. In this first phase, a decision maker attempts
to determine whether a problem exists, identify its symptoms, determine its magnitude, and
explicitly define it. Often, what is described as a problem (e.g., excessive costs) may be
only a symptom (i.e., measure) of a problem (e.g., improper inventory levels). Because real-
world problems are usually complicated by many interrelated factors, it is sometimes difficult
to distinguish between the symptoms and the real problem. New opportunities and prob-
lems certainly may be uncovered while investigating the causes of symptoms. For example,
Application Case 2.1 describes a classic story of recognizing the correct problem.
The existence of a problem can be determined by monitoring and analyzing the
organization’s productivity level. The measurement of productivity and the construction
of a model are based on real data. The collection of data and the estimation of future data
are among the most difficult steps in the analysis. The following are some issues that may
arise during data collection and estimation and thus plague decision makers:
• Data are not available. As a result, the model is made with, and relies on, potentially
inaccurate estimates.
• Obtaining data may be expensive.
• Data may not be accurate or precise enough.
• Data estimation is often subjective.
• Data may be insecure.
• Important data that influence the results may be qualitative (soft).
• There may be too many data (i.e., information overload).

Application Case 2.1

Making Elevators Go Faster!
This story has been reported in numerous places Cameron (1996) give several other examples of dis-
and has almost become a classic example to explain tractions, including lighting, displays, and so on, that
the need for problem identification. Ackoff (as cited organizations use to reduce perceived waiting time.
in Larson, 1987) described the problem of managing If the real problem is identified as perceived waiting
complaints about slow elevators in a tall hotel tower. time, it can make a big difference in the proposed
After trying many solutions for reducing the com- solutions and their costs. For example, full-length
plaint: staggering elevators to go to different floors, mirrors probably cost a whole lot less than adding
adding operators, and so on, the management deter- an elevator!
mined that the real problem was not about the actual
waiting time but rather the perceived waiting time. Sources: Based on J. Baker and M. Cameron, “The Effects of
So the solution was to install full-length mirrors on the Service Environment on Affect and Consumer Perception of
elevator doors on each floor. As Hesse and Woolsey Waiting Time: An Integrative Review and Research Propositions,”
(1975) put it, “the women would look at themselves Journal of the Academy of Marketing Science, Vol. 24, September
in the mirrors and make adjustments, while the men 1996, pp. 338–349; R. Hesse and G. Woolsey, Applied Management
would look at the women, and before they knew it, Science: A Quick and Dirty Approach, SRA Inc., Chicago, 1975;
R. C. Larson, “Perspectives on Queues: Social Justice and the
the elevator was there.” By reducing the perceived Psychology of Queuing,” Operations Research, Vol. 35, No. 6,
waiting time, the problem went away. Baker and November/December 1987, pp. 895–905.

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