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88 Part I • Decision Making and Analytics: An Overview

However, the generation of alternatives for complex problems requires expertise that can
be provided only by a human, brainstorming software, or an ES. OLAP and data mining
software are quite useful in identifying relationships that can be used in models. Most DSS
have quantitative analysis capabilities, and an internal ES can assist with qualitative meth-
ods as well as with the expertise required in selecting quantitative analysis and forecasting
models. A KMS should certainly be consulted to determine whether such a problem has
been encountered before or whether there are experts on hand who can provide quick
understanding and answers. CRM systems, revenue management systems, ERP, and SCM
systems software are useful in that they provide models of business processes that can test
assumptions and scenarios. If a problem requires brainstorming to help identify important
issues and options, a GSS may prove helpful. Tools that provide cognitive mapping can
also help. Cohen et al. (2001) described several Web-based tools that provide decision
support, mainly in the design phase, by providing models and reporting of alternative
results. Each of their cases has saved millions of dollars annually by utilizing these tools.
Such DSS are helping engineers in product design as well as decision makers solving
business problems.

support for the choice Phase

In addition to providing models that rapidly identify a best or good-enough alternative,
a DSS can support the choice phase through what-if and goal-seeking analyses. Different
scenarios can be tested for the selected option to reinforce the final decision. Again, a KMS
helps identify similar past experiences; CRM, ERP, and SCM systems are used to test the
impacts of decisions in establishing their value, leading to an intelligent choice. An ES can
be used to assess the desirability of certain solutions as well as to recommend an appropri-
ate solution. If a group makes a decision, a GSS can provide support to lead to consensus.
support for the implementation Phase

This is where “making the decision happen” occurs. The DSS benefits provided during
implementation may be as important as or even more important than those in the earlier
phases. DSS can be used in implementation activities such as decision communication,
explanation, and justification.
Implementation-phase DSS benefits are partly due to the vividness and detail of
analyses and reports. For example, one chief executive officer (CEO) gives employees
and external parties not only the aggregate financial goals and cash needs for the near
term, but also the calculations, intermediate results, and statistics used in determining
the aggregate figures. In addition to communicating the financial goals unambiguously,
the CEO signals other messages. Employees know that the CEO has thought through the
assumptions behind the financial goals and is serious about their importance and attain-
ability. Bankers and directors are shown that the CEO was personally involved in ana-
lyzing cash needs and is aware of and responsible for the implications of the financing
requests prepared by the finance department. Each of these messages improves decision
implementation in some way.
As mentioned earlier, reporting systems and other tools variously labeled as BAM,
BPM, KMS, EIS, ERP, CRM, and SCM are all useful in tracking how well an implementation
is working. GSS is useful for a team to collaborate in establishing implementation effec-
tiveness. For example, a decision might be made to get rid of unprofitable customers. An
effective CRM can identify classes of customers to get rid of, identify the impact of doing
so, and then verify that it really worked that way.
All phases of the decision-making process can be supported by improved communica-
tion through collaborative computing via GSS and KMS. Computerized systems can facilitate
communication by helping people explain and justify their suggestions and opinions.

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