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102 Part I • Decision Making and Analytics: An Overview

interfaces. Many developments in DSS components are the result of new developments
in hardware and software computer technology, data warehousing, data mining, OLAP,
Web technologies, integration of technologies, and DSS application to various and new
functional areas. There is also a clear link between hardware and software capabilities
and improvements in DSS. Hardware continues to shrink in size while increasing in speed
and other capabilities. The sizes of databases and data warehouses have increased dra-
matically. Data warehouses now provide hundreds of petabytes of sales data for retail
organizations and content for major news networks.
We expect to see more seamless integration of DSS components as they adopt Web
technologies, especially XML. These Web-based technologies have become the center of
activity in developing DSS. Web-based DSS have reduced technological barriers and have
made it easier and less costly to make decision-relevant information and model-driven
DSS available to managers and staff users in geographically distributed locations, espe-
cially through mobile devices.
DSS are becoming more embedded in other systems. Similarly, a major area to expect
improvements in DSS is in GSS in supporting collaboration at the enterprise level. This is
true even in the educational arena. Almost every new area of information systems involves
some level of decision-making support. Thus, DSS, either directly or indirectly, has impacts
on CRM, SCM, ERP, KM, PLM, BAM, BPM, and other EIS. As these systems evolve, the
active decision-making component that utilizes mathematical, statistical, or even descriptive
models increases in size and capability, although it may be buried deep within the system.
Finally, different types of DSS components are being integrated more frequently. For
example, GIS are readily integrated with other, more traditional, DSS components and
tools for improved decision making.
By definition, a DSS must include the three major components—DBMS, MBMS, and
user interface. The knowledge-based management subsystem is optional, but it can pro-
vide many benefits by providing intelligence in and to the three major components. As in
any other MIS, the user may be considered a component of DSS.

Chapter Highlights

• Managerial decision making is synonymous with • In the choice phase, alternatives are compared, and
the whole process of management. a search for the best (or a good-enough) solution is
• Human decision styles need to be recognized in launched. Many search techniques are available.
designing systems. • In implementing alternatives, a decision maker
• Individual and group decision making can both should consider multiple goals and sensitivity-
be supported by systems. analysis issues.
• Problem solving is also opportunity evaluation. • Satisficing is a willingness to settle for a satis-
• A model is a simplified representation or abstrac- factory solution. In effect, satisficing is subopti-
tion of reality. mizing. Bounded rationality results in decision
• Decision making involves four major phases: makers satisficing.
intelligence, design, choice, and implementation. • Computer systems can support all phases of deci-
• In the intelligence phase, the problem (oppor- sion making by automating many of the required
tunity) is identified, classified, and decom- tasks or by applying artificial intelligence.
posed (if needed), and problem ownership is • A DSS is designed to support complex manage-
established. rial problems that other computerized techniques
• In the design phase, a model of the system is cannot. DSS is user oriented, and it uses data and
built, criteria for selection are agreed on, alterna- models.
tives are generated, results are predicted, and a • DSS are generally developed to solve specific
decision methodology is created. managerial problems, whereas BI systems typically

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