Page 87 -

86 Part I • Decision Making and Analytics: An Overview

information system supported decision making. Indeed, many previous technology-
related waves (e.g., business process reengineering (BPR), knowledge management,
etc.) have faced mixed results mainly because of change management challenges and
issues. Management of change is almost an entire discipline in itself, so we recognize its
importance and encourage the readers to focus on it independently. Implementation also
includes a thorough understanding of project management. Importance of project man-
agement goes far beyond analytics, so the last few years have witnessed a major growth
in certification programs for project managers. A very popular certification now is Project
Management Professional (PMP). See pmi.org for more details.
Implementation must also involve collecting and analyzing data to learn from the
previous decisions and improve the next decision. Although analysis of data is usually
conducted to identify the problem and/or the solution, analytics should also be employed
in the feedback process. This is especially true for any public policy decisions. We need
to be sure that the data being used for problem identification is valid. Sometimes people
find this out only after the implementation phase.
The decision-making process, though conducted by people, can be improved with
computer support, which is the subject of the next section.

sectiOn 2.7 revieW QuestiOns
1. Define implementation.
2. How can DSS support the implementation of a decision?

2.8 hoW Decisions are suPPorteD

In Chapter 1, we discussed the need for computerized decision support and briefly
described some decision aids. Here we relate specific technologies to the decision-
making process (see Figure 2.2). Databases, data marts, and especially data warehouses
are important technologies in supporting all phases of decision making. They provide
the data that drive decision making.
support for the intelligence Phase

The primary requirement of decision support for the intelligence phase is the ability to scan
external and internal information sources for opportunities and problems and to interpret
what the scanning discovers. Web tools and sources are extremely useful for environmental

Phase
ANN
MIS
Intelligence
Data Mining, OLAP
ES, ERP
Design ESS, ES, SCM
CRM, ERP, KVS DSS
Management ES
Science
Choice ANN

Implementation ESS, ES CRM
KMS, ERP SCM
figure 2.2 DSS Support.

M02_SHAR9209_10_PIE_C02.indd 86 1/25/14 7:45 AM