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
systems, executive information systems, expert systems, and artificial intelligence technologies can be applied to
decision-making situations faced by business managers and professionals in today’s dynamic business environment.
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.
2. Identify the role and reporting alternatives of management information systems.
5. Explain how the following information systems can support the information needs of executives, managers, and
business professionals:
a. Executive information systems
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
• Decision Support Trends. Major changes are taking place in traditional MIS, DSS, and EIS tools for providing
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business intelligence software tools, as well as their use by lower levels of management and individuals and teams of
business professionals. In addition, the growth of e–commerce and e-business applications has expanded the use of
enterprise portals and DSS tools by the suppliers, customers, and other business stakeholders of a company.
• Management Information Systems. Management information systems provide pre-specified reports and
• 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
external business applications, databases, and information services that are tailored to their individual preferences
• 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
based on simple models of the brain’s neuron structure that can learn to recognize patterns in data. Fuzzy logic
Chapter 10 – Supporting Decision Making
KEY TERMS AND CONCEPTS
1. Analytical Modelling ():
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 ():
Making repeated changes to selected variables until a chosen variable reaches a target value.
2. Artificial Intelligence ():
3. Business Intelligence ():
Business intelligence comprises “concepts and methods to improve business decision making by using fact–
based support systems.”
4. Data Mining ():
Using special-purpose software to analyze data from a data warehouse to find patterns and trends.
5. Data Visualization Systems ():
6. Decision Structure ():
7. Decision Support System ():
Decision support systems are computer-based information systems that provide interactive information support
to managers and business professionals during the decision making process.
8. Enterprise Information Portal ():
9. Enterprise Knowledge Portal ():
Chapter 10 – Supporting Decision Making
10. Executive Information System ():
An information system that provides strategic level information tailored to the needs of top management.
11. Expert system ():
12. Expert System Shell ():
The software and user interface that allows knowledge engineers to build rule-bases.
14. Genetic Algorithms ():
15. Geographic Information System ():
16. Inference Engine ():
The algorithms that process rules and facts and makes associations resulting in a recommended course of action.
18. Knowledge Base ():
19. Knowledge Engineer ():
A specialist who works with experts to capture the knowledge they possess in order to develop a knowledge
base for expert systems and other knowledge-based systems.
20. Knowledge Management System ():
Knowledge management systems help organize and share unstructured information within an organization.
21. Management Information System ():
22. Model Base ():
23. Neural Network ():
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24. Online Analytical Processing (OLAP) ():
25. Robotics ():
26. Virtual Reality ():
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
Decision structure
16
Knowledge management system
2
Executive Information System
17
Enterprise knowledge portal
3
Management information system
18
Artificial intelligence
4
Decision Support System
19
Robotics
5
Business intelligence
20
Virtual reality
6
Model base
21
Geographic information systems (GIS)
7
Analytical modeling
22
Expert system (ES)
8
What-if analysis
23
Knowledge base
9
Sensitivity analysis
24
Inference engine
10
Goal-seeking analysis
25
Expert system shell
11
Optimization analysis
26
Knowledge engineer
12
Online analytical processing (OLAP)
27
Neural network
13
Data mining
28
Fuzzy logic
14
Data visualization system
29
Intelligent agent
15
Enterprise information portal (EIP)
30
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
stakeholders of a company.
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 versus the capabilities provided by a DSS?
Flexibility
4. Refer to the Real World Challenge at the beginning of the chapter. Does DHL stand to lose anything by
integrating its operations under a single, global brand? If so, what? Is there a way to keep the best of
both alternatives?
DHL is in the process of unifying its many brand names under a single international brand name and company.
Customers who are used to dealing with a smaller, localized brand may see this as a loss of control over their
Chapter 10 – Supporting Decision Making
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
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
7. Refer to the Real World Solution in the chapter. How would a local marketing manager decide that the
tool is no longer applicable, or maybe to a particular situation? If the use of the tool eventually does away
with the need for local marketing managers, then what?
A local marketing manager might decide that the tool is not measuring properly, or is measuring incorrectly, or
that he/she has figures that show to tool to be incorrect. It is important to note that the tool measures customer
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
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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)
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
1. BizRate.com: eCommerce Website Reviews
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.
When searching for digital cameras I found users could select cameras by price, megapixels, type of user, built
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
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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
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.
This exercise will give students some first hand experience with the topic. Individual results will vary.
products with this feature, and describe these products in your own words.
3. Case Based Marketing
a. What is the source of expertise behind Amazon’s online book recommendations?
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?
Various laws and courts protect privacy. These laws and practices may be changed or broken. Thus, in the
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
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e. What obligations do organizations have to secure your private data from unauthorized access?
There is a wealth of information that should be secured from prying eyes on the Internet. Some of these data
are:
a) names
b) addresses
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
5. Are You Getting all the Information You Need?
a) Recruit a classmate who routinely uses the same search engine you use. Conduct identical searches. What
search engine did you use? Did you indeed get different results?
computers.
b) Analyze the first page of results from the experiment in question “a”. How are your results different?
What assumptions did the search engine make about your preferences?
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c) Assume you have been tasked with finding a suitable location in the U.S. for a new manufacturing site.
How might a search engine’s assumptions affect your research regarding public acceptance?
ANSWERS TO REAL WORLD CHALLENGE/SOLUTION
Real World Challenge
1. What are some of the ways in which local marketing managers can choose to invest their marketing
budgets? What are the pros and cons of each? How would you make that allocation decision?
Marketing outlets
• print
pros: cheap; flexible; temporary
cons: limited reach; no click-through (depending on QR Code penetration in the market)
Allocation rationale
• personal experience
• performance metrics
2. Consider the four questions that the company is attempting to answer. How can technology help with
those kinds of situations? How would you apply technology to this problem?
Potential brand growth
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• business intelligence applications
3. Is it possible for information technology to supplement (or even replace) the expertise, experience, and
judgment of a local marketing manager who knows his industry and/or country? Why?
Can technology help?
Can technology replace local managers?
• no, marketing depends significantly on building local relationships
Real World Solution
1. What are some of the assumptions on which the new allocation tool was built? How likely are those
assumptions to stay the same in the future? In other words, how enduring would this tool be?
Assumptions
• consumers progress through a series of steps in the purchasing process that represent different stages of
consumer development
2. What are some of the challenges Deutsche Post DHL may face as it seeks to implement the new tools
worldwide? How do these challenges change the job of the local marketing managers?
Challenges
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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
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
• Develop innovative products
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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)
Metrics
• Hours studied per week (graph)
• Assignments outstanding (count)
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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
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
New products/services
• Kitchen design
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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
to research this topic and prepare a presentation to share your work.
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.