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44 Part I • Decision Making and Analytics: An Overview

management system to guide all its personnel in their problem solving. Another organiza-
tion may have separate support systems for marketing, finance, and accounting; a sup-
ply chain management (SCM) system for production; and several rule-based systems for
product repair diagnostics and help desks. DSS encompasses them all.

evolution of dss into Business intelligence

In the early days of DSS, managers let their staff do some supportive analysis by using
DSS tools. As PC technology advanced, a new generation of managers evolved—one
that was comfortable with computing and knew that technology can directly help
make intelligent business decisions faster. New tools such as OLAP, data warehousing,
data mining, and intelligent systems, delivered via Web technology, added promised
capabilities and easy access to tools, models, and data for computer-aided decision
making. These tools started to appear under the names BI and business analytics in
the mid-1990s. We introduce these concepts next, and relate the DSS and BI concepts
in the following sections.

sectiOn 1.6 revieW QuestiOns
1. Provide two definitions of DSS.
2. Describe DSS as an umbrella term.

1.7 a FrameWork For Business intelligenCe (Bi)

The decision support concepts presented in Sections 1.5 and 1.6 have been implemented
incrementally, under different names, by many vendors that have created tools and meth-
odologies for decision support. As the enterprise-wide systems grew, managers were
able to access user-friendly reports that enabled them to make decisions quickly. These
systems, which were generally called executive information systems (EIS), then began to
offer additional visualization, alerts, and performance measurement capabilities. By 2006,
the major commercial products and services appeared under the umbrella term business
intelligence (BI).

definitions of Bi

business intelligence (bi) is an umbrella term that combines architectures, tools, data-
bases, analytical tools, applications, and methodologies. It is, like DSS, a content-free
expression, so it means different things to different people. Part of the confusion about
BI lies in the flurry of acronyms and buzzwords that are associated with it (e.g., business
performance management [BPM]). BI’s major objective is to enable interactive access
(sometimes in real time) to data, to enable manipulation of data, and to give business
managers and analysts the ability to conduct appropriate analyses. By analyzing historical
and current data, situations, and performances, decision makers get valuable insights that
enable them to make more informed and better decisions. The process of BI is based on
the transformation of data to information, then to decisions, and finally to actions.

a Brief history of Bi
The term BI was coined by the Gartner Group in the mid-1990s. However, the concept is
much older; it has its roots in the MIS reporting systems of the 1970s. During that period,
reporting systems were static, two dimensional, and had no analytical capabilities. In the
early 1980s, the concept of executive information systems (EIS) emerged. This concept
expanded the computerized support to top-level managers and executives. Some of the

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