Page 90 -

Chapter 2 • Foundations and Technologies for Decision Making 89

Decision implementation can also be supported by ES. An ES can be used as an advi-
sory system regarding implementation problems (such as handling resistance to change).
Finally, an ES can provide training that may smooth the course of implementation.
Impacts along the value chain, though reported by an EIS through a Web-based
enterprise information portal, are typically identified by BAM, BPM, SCM, and ERP systems.
CRM systems report and update internal records, based on the impacts of the implementa-
tion. These inputs are then used to identify new problems and opportunities—a return to
the intelligence phase.

sectiOn 2.8 revieW QuestiOns

1. Describe how DSS/BI technologies and tools can aid in each phase of decision making.
2. Describe how new technologies can provide decision-making support.

Now that we have studied how technology can assist in decision making, we study some
details of decision support systems (DSS) in the next two sections.

2.9 Decision suPPort systeMs: caPabilities

The early definitions of a DSS identified it as a system intended to support managerial
decision makers in semistructured and unstructured decision situations. DSS were meant
to be adjuncts to decision makers, extending their capabilities but not replacing their judg-
ment. They were aimed at decisions that required judgment or at decisions that could not
be completely supported by algorithms. Not specifically stated but implied in the early
definitions was the notion that the system would be computer based, would operate inter-
actively online, and preferably would have graphical output capabilities, now simplified
via browsers and mobile devices.

a Dss application
A DSS is typically built to support the solution of a certain problem or to evaluate an
opportunity. This is a key difference between DSS and BI applications. In a very strict
sense, business intelligence (bi) systems monitor situations and identify problems and/
or opportunities, using analytic methods. Reporting plays a major role in BI; the user
generally must identify whether a particular situation warrants attention, and then analyti-
cal methods can be applied. Again, although models and data access (generally through
a data warehouse) are included in BI, DSS typically have their own databases and are
developed to solve a specific problem or set of problems. They are therefore called
Dss applications.
Formally, a DSS is an approach (or methodology) for supporting decision making.
It uses an interactive, flexible, adaptable computer-based information system (CBIS)
especially developed for supporting the solution to a specific unstructured manage-
ment problem. It uses data, provides an easy user interface, and can incorporate the
decision maker’s own insights. In addition, a DSS includes models and is developed
(possibly by end users) through an interactive and iterative process. It can support all
phases of decision making and may include a knowledge component. Finally, a DSS
can be used by a single user or can be Web based for use by many people at several
locations.
Because there is no consensus on exactly what a DSS is, there is obviously no agree-
ment on the standard characteristics and capabilities of DSS. The capabilities in Figure 2.3
constitute an ideal set, some members of which are described in the definitions of DSS
and illustrated in the application cases.
The key characteristics and capabilities of DSS (as shown in Figure 2.3) are:

M02_SHAR9209_10_PIE_C02.indd 89 1/25/14 7:45 AM