question - business intelligence

Chapter 1 • Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence 11

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 problems certainly may be uncovered while investigating the causes of symptoms.

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.

ISSUES IN DATA COLLECTION 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). • Outcomes (or results) may occur over an extended period. As a result, revenues,

expenses, and profits will be recorded at different points in time. To overcome this difficulty, a present-value approach can be used if the results are quantifiable.

• It is assumed that future data will be similar to historical data. If this is not the case, the nature of the change has to be predicted and included in the analysis.

When the preliminary investigation is completed, it is possible to determine whether a problem really exists, where it is located, and how significant it is. A key issue is whether an information system is reporting a problem or only the symptoms of a problem. For example, if reports indicate that sales are down, there is a problem, but the situation, no doubt, is symptomatic of the problem. It is critical to know the real problem. Sometimes it may be a problem of perception, incentive mismatch, or organizational processes rather than a poor decision model.

To illustrate why it is important to identify the problem correctly, we provide a clas- sical example in Application Case 1.1.

This story has been reported in numerous places and has almost become a classic example to explain the need for problem identification. Ackoff (as cited in Larson, 1987) described the problem of manag- ing complaints about slow elevators in a tall hotel tower. After trying many solutions for reducing the complaint—staggering elevators to go to different floors, adding operators, and so on—the manage- ment determined that the real problem was not

about the actual waiting time but rather the per- ceived waiting time. So the solution was to install full-length mirrors on elevator doors on each floor. As Hesse and Woolsey (1975) put it, “The women would look at themselves in the mirrors and make adjustments, while the men would look at the women, and before they knew it, the elevator was there.” By reducing the perceived waiting time, the problem went away. Baker and Cameron (1996)

Application Case 1.1 Making Elevators Go Faster!

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