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Chapter 12 Enhancing Decision Making 497

• Drill down: This is the ability to move from a high-level summary to a more
detailed view.
• Forecasts, scenarios, models: These include the ability to perform linear
forecasting, what-if scenario analysis, and analyze data using standard
statistical tools.

Who Uses Business Intelligence and Business
Analytics?
In previous chapters, we have described the different information
constituencies in business firms—from senior managers to middle manag-
ers, analysts, and operational employees. This also holds true for BI and BA
systems (see Figure 12.4). Over 80 percent of the audience for BI consists of
casual users who rely largely on production reports. Senior executives tend
to use BI to monitor firm activities using visual interfaces like dashboards
and scorecards. Middle managers and analysts are much more likely to be
immersed in the data and software, entering queries and slicing and dicing
the data along different dimensions. Operational employees will, along with
customers and suppliers, be looking mostly at prepackaged reports.

Production Reports
The most widely used output of a BI suite of tools are pre-packaged production
reports. Table 12.5 illustrates some common predefined reports from Oracle’s
BI suite of tools.

Predictive Analytics
An important capability of business intelligence analytics is the ability to
model future events and behaviors, such as the probability that a customer will
respond to an offer to purchase a product. Predictive analytics use statistical
analysis, data mining techniques, historical data, and assumptions about future
conditions to predict future trends and behavior patterns. Variables that can
be measured to predict future behavior are identified. For example, an insur-
ance company might use variables such as age, gender, and driving record as

FIGURE 12.4 BUSINESS INTELLIGENCE USERS

Casual users are consumers of BI output, while intense power users are the producers of reports, new
analyses, models, and forecasts.

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