Chapter 10 – Supporting Decision Making
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10 Supporting Decision Making
CHAPTER OVERVIEW
Chapter 10: Supporting Decision Making shows how management information systems, decision support
LEARNING OBJECTIVES
After reading and studying this chapter, you should be able to:
1. Identify the changes taking place in the form and use of decision support in business.
5. Explain how the following information systems can support the information needs of executives, managers, and
business professionals:
7. Give examples of several ways expert systems can be used in business decision-making situations.
SUMMARY
• Information, Decisions, and Management. Information systems can support a variety of management decision–
making levels and decisions. These include the three levels of management activity (strategic, tactical, and
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• Decision Support Trends. Major changes are taking place in traditional MIS, DSS, and EIS tools for providing
the information, and modeling managers need to support their decision making. Decision support in business is
• Management Information Systems. Management information systems provide pre-specified reports and
responses to managers on a periodic, exception, demand, or push reporting basis to meet their need for information
to support decision making.
• OLAP and Data Mining. Online analytical processing interactively analyzes complex relationships among large
• Decision Support Systems. Decision support systems are interactive, computer-based information systems that
use DSS software and a model base and database to provide information tailored to support semi-structured and
• Executive Information Systems. Executive information systems are information systems originally designed to
support the strategic information needs of top management; however, their use is spreading to lower levels of
• Enterprise Information and Knowledge Portals. Enterprise information portals provide a customized and
personalized Web-based interface for corporate intranets to give their users easy access to a variety of internal and
• Artificial Intelligence. The major application domains of artificial intelligence (AI) include a variety of
applications in cognitive science, robotics, and natural interfaces. The goal of AI is the development of computer
• AI Technologies. The many application areas of AI are summarized in Figure 10.26 , including neural networks,
fuzzy logic, genetic algorithms, virtual reality, and intelligent agents. Neural nets are hardware or software systems
Chapter 10 – Supporting Decision Making
• Expert Systems. Expert systems are knowledge-based information systems that use software and a knowledge
base about a specific, complex application area to act as expert consultants to users in many business and technical
KEY TERMS AND CONCEPTS
1. Analytical Modelling (407):
Analytical modelling involves the interactive use of computer-based mathematical models to explore decision
alternatives using what-if analysis, sensitivity analysis, goal-seeking analysis, and optimization analysis.
a. Goal-Seeking Analysis (409):
Making repeated changes to selected variables until a chosen variable reaches a target value.
2. Artificial Intelligence (418):
The goal of AI is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and
feel. A major thrust of artificial intelligence is the simulation of computer functions normally associated with
human intelligence, such as reasoning, learning, and problem solving
3. Business Intelligence (395):
4. Data Mining (410):
Using special-purpose software to analyze data from a data warehouse to find patterns and trends.
5. Data Visualization Systems (405):
6. Decision Structure (394):
7. Decision Support System (397):
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8. Enterprise Information Portal (414):
9. Enterprise Knowledge Portal (416):
10. Executive Information System (412):
An information system that provides strategic level information tailored to the needs of top management.
12. Expert System Shell (428):
The software and user interface that allows knowledge engineers to build rule-bases.
13. Fuzzy Logic (431):
A computer-based system that produces approximated answers given incomplete or partially incorrect data.
14. Genetic Algorithms (432):
15. Geographic Information System (405):
16. Inference Engine (425):
The algorithms that process rules and facts and makes associations resulting in a recommended course of action.
17. Intelligent Agent (436):
A software based user surrogate for gathering and processing information.
18. Knowledge Base (425):
19. Knowledge Engineer (429):
20. Knowledge Management System (416):
Knowledge management systems help organize and share unstructured information within an organization.
21. Management Information System (400):
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22. Model Base (398):
23. Neural Network (430):
24. Online Analytical Processing (OLAP) (401):
OLAP is a system using multidimensional databases to help managers analyze transaction data summaries to
uncover patterns, trends, and exception conditions.
25. Robotics (423):
26. Virtual Reality (434):
The use of audio, visual, and tactile human/computer interfaces to enable human users to experience computer-
generated environment.
ANSWERS TO REVIEW QUIZ
Q.
A.
Key Term
Q.
A.
Key Term
1
6
Decision structure
16
20
Knowledge management system
2
10
Executive Information System
17
9
Enterprise knowledge portal
3
21
Management information system
18
2
Artificial intelligence
4
7
Decision Support System
19
25
Robotics
5
3
Business intelligence
20
26
Virtual reality
6
22
Model base
21
15
Geographic information systems (GIS)
7
1
Analytical modeling
22
11
Expert system (ES)
8
1d
What-if analysis
23
18
Knowledge base
9
1c
Sensitivity analysis
24
16
Inference engine
10
1a
Goal-seeking analysis
25
12
Expert system shell
11
1b
Optimization analysis
26
19
Knowledge engineer
12
24
Online analytical processing (OLAP)
27
23
Neural network
13
4
Data mining
28
13
Fuzzy logic
14
5
Data visualization system
29
17
Intelligent agent
15
8
Enterprise information portal (EIP)
30
14
Genetic algorithms
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ANSWERS TO DISCUSSION QUESTIONS
1. Are the form and use of information and decision support systems for managers and business
professionals changing and expanding? Why or why not?
Yes Changes are driven by the rapid developments in end user computing and networking as well as the rapid
2. Has the growth of self-directed teams to manage work in organizations changed the need for strategic,
tactical, and operational decision making in business?
Self-directed teams were largely a fad a decade ago. The basics for decision making have not changed
3. What is the difference between the ability of a manager to retrieve information instantly on demand
using an MIS and the capabilities provided by a DSS?
Flexibility
Managers have traditionally relied on the capabilities of a management information system. These systems
4. Refer to the Real World Case on Valero Energy and others in the chapter. Information is one part (albeit
a very important one) of decision making, with managers being the other. What experiences and
qualifications are important in preparing managers for “fact–based” decision making? How are those
obtained?
Experience
• Industry
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5. In what ways does using an electronic spreadsheet package provide you with the capabilities of a decision
support system?
Spreadsheet’s similarities to a DSS:
• Statistical tools
• Cross-tabulation tools
6. Are enterprise information portals making executive information systems unnecessary? Explain your
reasoning.
EIPs are deployed by organizations as a way to provide web-enabled information, knowledge, and decision
support to executives, managers, employees, suppliers, customers, and other business partners. EISs on the
One might argue that these tools will merge.
7. Refer to the Real World Case on Kimberly-Clark and virtual reality in the chapter. Is the company fixing
something that was not broken? Explain.
8. Can computers think? Will they ever be able to? Explain why or why not.
Yes. If by thinking we mean employ reasoning to solve problems. We simply program in specific sets of
9. Which applications of AI have the most potential value for use in the operations and management of a
business? Defend your choices.
Fuzzy logic: machine control (at the sensor/movement level)
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10. What are some of the limitations or dangers you see in the use of AI technologies such as expert systems,
virtual reality, and intelligent agents? What could be done to minimize such effects?
Limitations:
First, these systems may put people out of work, just as robots did with many production line employees.
ANSWERS TO ANALYSIS EXERCISES
a. Use BizRate.com to check out a product of interest. How thorough, valid, and valuable were the product
and retailer reviews to you? Explain.
b. How could nonretail businesses use a similar Web-enabled review system? Give an example.
Many examples exist. Some news media outlets use review systems to build community. Readers are invited
to comment on stories. In addition to building community, this may provide a mechanism for editors to monitor
c. How is BizRate’s Web site functionality similar to a decision support system (DSS)?
Decision support systems provide summaries of critical information, real-time monitoring, and exception
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2. Enterprise Application Integration
a. Visit one of the portal sites listed above. Configure the site to meet your own information needs. Provide a
printout of the result.
products with this feature, and describe these products in your own words.
Various types of features include web accessibility to support mobile executives, analytical tools, single page
3. Case Based Marketing
a. What is the source of expertise behind Amazon’s online book recommendations?
While the logic used by Amazon remains proprietary, the website suggests that its expertise comes from a
history of customer purchases.
b. How do you feel about online merchants tracking your purchases and using this information to
recommend additional purchases?
This would make a good discussion question. Consider introducing Opt-in v. Opt-out approaches as a
c. What measures protect consumers from the government’s obtaining their personal shopping histories
maintained by Amazon?
d. Although Amazon doesn’t share personal information, it still capitalizes on its customers’ shopping data.
Is this ethical? Should Amazon offer its customers the right to opt out of this information gathering?
Student opinions will vary. Even in brick-and-mortar stores, successful merchants capitalize on what they learn
4. Palm City Police Department
a. Build a spreadsheet to perform this analysis and print it out.
See Analysis Exercise Data Solutions files [Chapter 10 – Solutions.xls]
b. Currently, no funds are available to hire additional officers. On the basis of the citywide ratios, the
department has decided to develop a plan to shift resources as needed to ensure that no precinct has more
than 1,100 residents per police officer and no precinct has more than seven violent crimes per police officer.
Chapter 10 – Supporting Decision Making
ANSWERS TO REAL WORLD CASES
Case Study Questions
1. What is the difference between a “dashboard” and a “scorecard”? Why is it important that managers
know the difference between the two? What can they learn from each?
Differences
Dashboard
• Not attached to a methodology
Importance
Dashboards and scorecards are hot topics. Managers should understand the differences and implications of
these differences in order to be conversant in these subjects. The outputs from these systems may help
determine, in large part, their performance review.
Utility
2. In what ways have the companies mentioned in the case benefited from their adoption of “fact–based”
decision making? Provide several examples from the case to illustrate your answer.
Benefits
• Improved efficiency
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3. Information quality is central to the approach toward decision making taken by these organizations.
What other elements must be present for this approach to be successful (technology, people, culture, and so
forth)?
Required elements
• Forward looking metrics
Real World Activities
1. A number of major companies have launched projects geared toward improving their business analytics
and decision-making capabilities in the last few years. Go online and research other examples in this trend.
What are the similarities with the ones chronicled in the case? What are the differences? Prepare a report
that includes a section contrasting your new examples with the ones in the case.
2. If you had to apply the ideas discussed in the case to your academic career, what would your dashboard
and/ or scorecard look like? What would be the sources of information? How you would measure whether
you are making progress toward attaining your goals? Break into small groups to discuss these issues.
Data sources
• Online sources (Blackboard, etc for grades, syllabus, assignments)
• Syllabus
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RWC 2: Kimberly-Clark Corp.
Case Study Questions
1. What are the business benefits derived from the technology implementation described in the case? Also
discuss benefits other than those explicitly mentioned in the case.
Benefits – case
• Rapid testing
2. Are virtual stores like this one just an incremental innovation on the way marketing tests new product
designs? Or do they have the potential to radically reinvent the way these companies work? Explain your
reasons.
Incremental innovation
Kimberly-Clark is just automating/virtualizing existing methods. Otherwise, testing products, packaging,
3. What other industries could benefit from deployments of virtual reality like the one discussed in the case?
Leaving aside the cost of the technology, what new products or services could you envision within those
industries? Provide several examples.
Other industries
• Entertainment
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Real World Activities
1. What is the current cutting-edge technology in virtual reality, and how are companies using it? Go online
2. With technologies like these, will consumers entirely do away with retailers sometime in the future,
shopping only through virtual representations of a retail store? Will consumers even want it to look like a
retail store? Break into small groups to propose arguments for and against these questions.
RWC 3: Goodyear, JEA, OSUMC, and Monsanto: Cool Technologies Driving Competitive Advantage
Case Study Questions
1. Consider the outcomes of the projects discussed in the case. In all of them, the payoffs are both larger
and achieved more rapidly than in more traditional system implementations. Why do you think this is the
case? How are these projects different from others you have come across in the past? What are those
differences? Provide several examples.
The case provided no indication to suggest that payoffs were any larger than any other IT project or that results
were achieved more rapidly. In these examples, the projects hit right at their business’ core. Goodyear builds
2. How do these technologies create business value for the implementing organizations? In which ways are
these implementations similar in how they accomplish this, and how are they different? Use examples from
the case to support your answer.
These implementations provided a competitive advantage by reducing product development time or production
3. In all of these examples, companies had an urgent need that prompted them to investigate these radical,
new technologies. Do you think the story would have been different had the companies been performing well
already? Why or why not? To what extent are these innovations dependent on the presence of a problem or
crisis?
No. An organization’s sense of urgency comes from top management. Jack Welch demonstrated that even a
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Real World Activities
1. Choose one of the companies introduced in the case and search the Internet to update the current status
of their project. Also take a look at their competitors, and discover how they have responded to the
introduction of the developments mentioned in the case. Have they attempted to imitate them?
Goodyear
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2. As these technologies go beyond the capacity and abilities of human beings, what is the role of people in
the processes they affect? Do you think these technologies empower us by allowing us to overcome our
limitations and expand our range of possibilities? Instead, do they relegate people to the role of uncritically
accepting the outcomes of these processes? Break into small groups to discuss these issues, and note which
arguments that support one or the other position arise as a result.
People can and should act as fail-safes in the event of a system malfunction. Yes, these technologies are
RWC 4: Hillman Group, Avnet, and Quaker Chemical
Case Study Questions
1. What are the business benefits of BI deployments such as those implemented by Avnet and Quaker
Chemical? What roles do data and business processes play in achieving those benefits?
Benefits:
• focuses attention on processes and process improvements
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Data role:
Data consist of various process metrics indicating efficiency and effectiveness. These measures might include:
2. What are the main challenges to the change of mindset required to extend BI tools beyond mere
reporting? What can companies do to overcome them? Use examples from the case to illustrate your answer.
Challenges:
• lack of top management support for change
3. Both Avnet and Quaker Chemical implemented systems and processes that affect the practices of their
salespeople. In which ways did the latter benefit from these new implementations? How important was their
buy-in to the success of these projects? Discuss alternative strategies for companies to foster adoption of new
systems like these.
Salesperson benefits:
Salespeople benefited by using this information to identify potentially dissatisfied customers and taking
appropriate action early on to remedy the situation. Since management could identify high performing teams
Real World Activities
1. Search the Internet for other examples of both “mere reporting” and transformational implementations
of business intelligence tools. In which ways are these similar to the ones discussed in the case? In which ways
are these different? What seem to be the main distinction between reporting and process-transformation BI
rollouts? Prepare a report to summarize your findings.
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Note: students’ answers will vary. The following sample may provide some useful material for discussion.
Reporting example:
The Illinois governor, wanting to ensure tax payers receive full benefit from state employee’s time required all
resulted in a lot of bogus data.
Transformational example:
In one General Electric organization, remote sales staff depending on their laptops shipped their laptops to their
Differences
In the reporting example, the professors were given an additional task which provided them no direct benefit
2. How do you think the possession or access to certain information shapes the political dynamics of
organizations? Do you believe companies should be open about widespread access to information, or will they
be better off by restricting it? Why? Break into small groups with your classmates to discuss these issues, and
take turns advocating the two alternative positions.
Political dynamics:
Openness:
This answer takes a global view. The recommended degree of openness will depend in large part on the culture
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this example’s author