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Chapter 6
Managerial Support Systems
Objectives and Overview
To consider a topic as broad as IT applications, some type of framework is needed. As a first cut,
we have divided applications into those that are interorganizational systems and those that are
intraorganizational interorganizational systems are
electronic commerce applications, and Chapter 7 covers these e-business applications as well as
other interorganizational applications such as electronic data interchange. To provide some
structure to the broad range of intraorganizational systems, we have divided these applications
Chapter 6 employs the same framework spelled out in Figure 5.1. Chapter 6 moves directly into
a discussion of IT application areas where the applications provide support to a specific manager
or a small group of managers. The following ten major types of managerial support systems are
considered in Chapter 6:
Decision support systems (DSSs)
Data mining
Group support systems (GSSs)
Chapter 6 maintains the same organizational structure as the Sixth Edition, but the chapter has
been updated throughout and infused with new examples, new boxes, and updated lists of key
software products. Several newer concepts are explored, including performance management
systems and business intelligence systems (both an outgrowth of executive information systems).
The box in the GIS section on location intelligence the application of spatial technologies to
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As we said for Chapter 5, Chapter 6 is designed as a standalone chapter, but it is closely related to
both Chapters 5 and 7 as described above. In concert, these three chapters cover the spectrum of
IT applications used in modern organizations. Thus, we see these three chapters as a set that
should usually be covered in numerical sequence. Of course, the amount of classroom time spent
on this set of chapters will vary depending upon the level and purpose of the course. Students
The specific objectives of Chapter 6 are:
To describe ten major types of managerial support systems in use today, including decision
support systems, data mining, group support systems, geographic information systems,
Teaching Suggestions
As we sta
detail must be covered in class. The classroom session(s) should provide a framework for
framework. For us,
this usually means beginning with a PowerPoint slide or an overhead transparency of Figure 5.1
as the general roadmap, and then using a few slides on each application area to be covered in the
In addition to the basic coverage of the chapter, we would urge the instructor to use one or more
of the following enrichment activities in conjunction with Chapter 6.
1. To make a class session really come alive, prepare a demonstration of two or more of the
Chapter 6 Managerial Support Systems
2. Prepare a GIS demonstration using ArcView and a sample data set for the United States, and
follow up this demonstration with an assignment for the students to carry out using ArcView.
4. Employ a case study that illustrates the use of a managerial support system. Three excellent
choices are included in this textbook: Case Study II-2, Real-Time Business Intelligence at
5. If you have a class (particularly a graduate class) where several members of the class have
significant practical experience with information technology, take advantage of that
experience by having the students share examples of which they are aware in the application
6. Take advantage of any special expertise in your class. As an example, one of the authors
found that an undergraduate student in his class was a principal in a small software company
specializing in data mining tools, and the student was happy to make a brief classroom
As mentioned above, the amount of classroom time devoted to this chapter will vary depending
Chapter 6 Managerial Support Systems
Review Questions
1. Describe the three primary components that make up any decision support system (DSS)
and how they interact.
2. Explain the difference between a specific DSS and a DSS generator. Give an example of
each.
A specific DSS is an actual application that assists in the decision-making process. An example
3. Describe two examples of specific DSSs that are being used to assist in decision making.
You may use examples from the textbook or other examples you have read about or heard
about.
4. Explain both data warehousing and data mining. How are they related?
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5. List at least two techniques (decision technologies) that are used in data mining.
A decision tree is a tree-shaped structure that is derived from the data to represent sets of
decisions that result in various outcomes. When a new set of decisions is presented, the decision
tree predicts the outcome.
Neural networks are a branch of artificial intelligence.
6. List at least three uses of data mining.
Market segmentation: Segment existing customers and prospects into appropriate groups for
promotional and evaluation purposes, and determine how to approach
7. What is the purpose of a group support system (GSS)? What are the potential
advantages and disadvantages of using a GSS?
8. Compare the raster-based and vector-based approaches to geographic information
systems (GISs). What are the primary uses of each approach?
GISs are applications based on the manipulation of relationships in space. GISs capture, store,
manipulate, display, and analyze data spatially referenced to earth.
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9. What are the distinguishing characteristics of an executive information system (EIS)?
Why have these systems become a part of business intelligence in many companies?
10. What is knowledge management, and what is a knowledge management system? How
does the concept of a community of practice relate to knowledge management?
Knowledge management is the sharing and transferring of knowledge for the purpose of
11. Briefly describe the several areas of artificial intelligence (AI) research. Indicate why
we in business are most interested in the expert systems and neural networks areas.
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Artificial intelligence is the study of how to make computers do things that are presently done
better by people. The areas of artificial intelligence research are described below.
Natural languages: Creating systems that translate ordinary human language into
instructions which computers can understand and execute
12. Describe two examples of expert systems that are being used to assist in decision
making. You may use examples from the textbook or other examples you have read about
or heard about.
13. Describe two examples of neural networks that are being used to assist in decision
making. You may use examples from the textbook or other examples you have read about
or heard about.
Bank of America uses a neural network to evaluate commercial loan applications.
14. Describe two examples of the use of virtual reality in an organizational setting. You
may use examples from the textbook or other examples you have read about or heard
about.
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Discussion Questions
1. Review question 4 asked about the relationship between data warehousing and data
mining. In addition to data mining, which of the other application areas discussed in this
chapter may be used in conjunction with data warehousing? Explain.
Data warehousing could provide the foundation for GIS applications. Because over 80 percent of
database information contains a geographic component (addresses, zip codes, area codes, etc.), a
2. Two of the important topics in this chapter are decision support systems (DSSs) and
expert systems. Based on your reading of this chapter, you have undoubtedly noticed that
these two application areas have a great deal in common. What are the primary
distinctions between DSSs and expert systems?
A decision support system is an interactive system that allows the user to manipulate data and
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3. Compare group support systems, as described in this chapter, with groupware, as
described in Chapter 5. How do these two application areas relate to one another? Which
one is more important today? Do you think this will be true in the future?
Groupware refers to a wide variety of software designed to support group communication and
4. Several examples of geographic information systems were mentioned in the chapter.
Consider an industry or company with which you have some familiarity, and identify at
least one possible application of GISs in the industry or company. Explain why you think
this is a good prospect for a GIS application.
One po
5. Explain the concept o –
Is drilling-down used in other IT applications? How do these applications relate to EISs?
– touch of a
button in a graphical user interface (GUI). By drilling-down, users can continue to go deeper and
6. What are the three general approaches to obtaining an expert system? What are the
pluses and minuses of each approach?
a. An organization can buy a fully developed system that has been created for a specific type of
application.
7. According to the trade press, the success record of knowledge management systems has
been spotty. Why do you think this is? What steps must organizations take to give their
knowledge management efforts the best chances of succeeding?
Setting up a successful knowledge management system (KMS) is similar to setting up any other
The steps organizations must take to give a KMS effort the best chances of succeeding include:
8. Several examples of expert systems were mentioned in the chapter. Consider an industry
or a company with which you have some familiarity, and identify at least one possible
application of expert systems in the industry or company. Explain why you think this is a
good prospect for an expert system application.
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One possible answer: An area where an expert system could be applied is that of retail credit card
9. Several examples of neural networks were mentioned in the chapter. Consider an
industry or a company with which you have some familiarity, and identify at least one
possible application of neural networks in the industry or company. Explain why you think
this is a good prospect for a neural network application.
10. Which of the application areas considered in this chapter is most useful to a small to
midsized business? Defend your answer.
There are several possible answers to this question, including data mining, an EIS, a DSS, and a
GIS. Any organization with a data warehouse (even if it is small) can use data mining report and