dss questions and answers

Decision Making in a Digital Age

Teaching Objectives

Students should be able to answer the following questions:

1. How can information systems help individual managers make better

decisions when the problems are nonroutine and constantly changing?

2. How can information systems help people working in a group make

decisions more efficiently?

3. Are there any special systems that can facilitate decision making among

senior managers? Exactly what can these systems do to help high-level

management?

4. What benefits can systems to support management decision making

provide for the organization as a whole?

Key Terms

The following alphabetical list identifies the key terms discussed in this

chapter. The page number for each key term is provided.

Activity-based costing, 453 DSS software system, 440

Copyright © 2005 Pearson Education Canada Inc.

Balanced scorecard, 352 Geographic information system

(GIS), 445

Business intelligence, 435 Group decision-support system

(GDSS), 447

Customer decision-support system

(CDSS), 446

Knowledge discovery, 439

Data-driven DSS, 438 Model, 440

Data visualization, 445 Model-driven DSS, 436

Drill down, 450 Sensitivity analysis, 441

DSS database, 440

Teaching Suggestions

When discussing the systems presented in this chapter with students, you

should stress to your students that these systems are often so well

integrated that they may not really have heard much about them. When

presenting this chapter, you should demonstrate the value of the systems.

For example, the value of TPS and MIS might be easy to understand and

already known by many. But the nature of the knowledge obtained through

use of a decision-support system is usually not so easy to understand or


obtain. You definitely want to stress how DSS, GDSS, and ESS support

business intelligence.

Certainly students will recognize the importance of decisions on what the

selling price of an item will be or the decision on where a production facility

or retail outlet should be located. However, students are not likely to

recognize the importance of the data that go into the decision, the source of

that data, the many more limited decisions that are made prior to the final

big decision, the complexity of each decision, the side-effects of the decision,

or how the decision is really made. Decisions can be very complex, and

students need to understand the ways decision-support systems help

managers handle complexities and better understand all that goes into the

decisions.

Remind students that decision-support systems cover a wide variety of

systems, tools, and technologies. Spend some time differentiating between

model-driven DSS and data-driven DSS. When covering this material in class,

pose and discuss the following questions with your students. Exactly how do

the systems support decisions? Do DSS make decisions? Do DSS help make

decisions? Do DSS just provide the data for decisions? Perhaps one of the

best ways to teach this chapter is through the use of examples. Use the case

study, Window On boxes, and examples in your community.


Besides stressing the graphical nature of most DSS, it is important to discuss

how semistructured and unstructured decisions are supported. The

relationship between DSS and management science is another point you

should make. Many of the DSS use linear programming, network methods,

and decision models to aid decision making. The use of analytical models is

an important distinction between DSS and MIS; these models are designed

for semistructured decision making. The association between database

management systems and DSS is also an important concept to stress.

The key to the DSS of the future is to engage both users and IS managers in

DSS design and development. Knowledgeable executives should speak

candidly with IS staff about deliverables, capabilities, outcomes, needs, and

what decisions should be supported by a proposed system.

“Window On” Boxes

Window on Organizations: Data Drives Insights at WH Smith PLC

List the ways this DSS helps WH Smith's employees to make

decisions.


Information from every sale is now stored in a central repository that is

accessible via the Web by store managers and corporate staff. The new

system enabled WHSmith managers and staff to reduce manual paperwork,

reduced the manual processing of the paperwork, and provided easy access

to more current, detailed, consistent information for all stores. The new DSS

helps store managers understand what is happening in their stores as well as

in other WH Smith stores. The DSS enables the store managers to analyze

customer buying patterns, anticipate trends, design promotional displays,

and derive pricing strategies.

How has it provided value for the firm?

The DSS should result in additional sales due to its support for promotional

display decisions and pricing strategies. As well, profit should rise due to

support for inventory adjustments.

Suggest other ways the system can help them make decisions and

increase profits.

Student answers for this question will vary. However, managers can use the

DSS to evaluate which gift items it should sell at which store. The DSS can

help managers analyze their inventory, determining where inventory


reductions can be made. Managers can use the DSS when making

forecasting, repricing, and seasonal pricing evaluations.

Window on Management: Digital Cockpits Help Steer the Enterprise

What are the management benefits of digital dashboards?

Digital dashboards provide management with easy to use and easy to

understand graphical displays. These displays enable management to

monitor the organization's overall performance, spot trends, keep an eye on

the competition, drill down, and identify problems and opportunities. Pfizer is

monitoring key performance indicators for the firm and measuring the firm's

performance against external environmental changes.

How do these dashboard systems provide value for the firm?

A dashboard provides management with the status of various key indicators.

This enables management to adjust its operations and strategies to

maximize the firm’s goals.


What technical, organization, and management issues did the

companies described here have to address in developing and

installing their digital dashboards?

The Window on Management box does not mention specific technical,

organization, and management issues. However, you should encourage your

students to identify issues that they feel are important. Possible issues

include data integration from different systems, executive information

requirements determination, internal and external scanning capabilities, how

the data will be displayed, what types of decisions need to be supported,

what are the performance indicators that management wants tracked, and

security. Since a variety of technologies are available, management must

select the right technologies to support the decision-making process.

For Discussion Questions

1. As a manager or user of information systems, what would you

need to know to participate in the design and use of a DSS or an

ESS? Why?

Managers and users of information systems would want to specify what

kinds of decisions the systems should support, and where the data for


those decisions should come from. In a typical enterprise, workers are

capturing data, sharing data with other workers, retrieving insights from

captured data, and managing the information as per agreed upon

guidelines. However, data are turned into valuable business information

and insight only when they can be easily captured, systematically

stored, properly retrieved, readily shared, and well-managed. Data

management, DSS, and ESS represent the cornerstone of any data

warehousing program.

Data warehouses have become a critical component in enabling

management to make decisions quickly and accurately. For example,

telecommunications companies use it to manage churn and ensure the

retention of their customers, while retail firms rely on datamining to

maximize product mix and shelf space, and governments use it to

manage federal welfare and healthcare programs. Across industries,

data warehousing programs have achieved a 400 percent ROI, on

average, while increasing productivity, reducing speed of analysis, and

revealing business opportunities that were otherwise hidden from

management among layers of unreachable data. However, if

management is not part of the design and use of a DSS or ESS, then this

information may not be available or utilized, and if not, the firm may not

be able to gain or maintain competitive advantage. One thing is for sure:

the competition is using these systems to enhance decision making.


2. If businesses used DSS, GDSS, and ESS more widely, would they

make better decisions? Explain.

Competitiveness increasingly depends on the quality of decision making.

So naturally, companies often rely on their own history and their past

transactions and activities to make future decisions. When businesses

make decisions, it is usually helpful to use a decision-support system

and firm-wide data. These systems can automate certain decision

procedures, and they can offer information about different aspects of

the decision situation. They can also help managers question existing

decision procedures. It can be useful to explore the outcomes of

alternative organizational scenarios. And, of course, using GDSS can

improve how groups make decisions and also improve the decision that

might have been made by an independent person.

The size of the corporate information base is increasing at the rate of

400 percent every three years. Until recently, the idea of analyzing

years of accumulated transaction data in a single pass seemed

expensive and unachievable. In addition to the difficulties caused by

data format incompatibilities, the computational requirements would

have consumed much of the company's data processing capacity for

days or even weeks. Analysis has been limited to fairly simple queries


run after hours against relatively small subsets of data. In recent years,

scalable hardware and software technologies have fueled data

warehousing, enabling decision makers to unleash the power of analysis

provided as a result.

On the other hand, remember that these systems do not automatically

lead to better decisions unless the decision problem or situation is

clearly understood and the systems are appropriately designed.

Review Questions

1. What is a decision-support system (DSS)? How does it differ

from a management information system (MIS)?

A DSS assists management decision making by combining data,

sophisticated analytical models, and user-friendly software into a single,

powerful system that can support semistructured or unstructured

decision making. These systems help end users utilize data and models

to discuss and decide semistructured and unstructured problems, but

they do not solve the problems for the user. Generally speaking, MIS

provide routine, prespecified, and formatted reports based on data

extracted and summarized from the firm's TPS. These reports provide


information on the firm's performance and are used to help monitor and

control the business. In contrast, DSS provide capabilities for addressing

nonroutine decisions and user control. DSS emphasize change,

flexibility, and rapid response and place a greater emphasis on models,

assumptions, ad hoc queries, and display graphics. Additionally, MIS

primarily address structured problems, while DSS focus more on

supporting semistructured and unstructured problems.

2. How can a DSS support unstructured or semistructured decision

making?

Unstructured problems are novel and non-routine and have no

predefined algorithms or solutions. DSS help design and evaluate

alternatives and monitor the adoption or implementation process. DSS

combine data with models to produce various alternative scenarios for

making choices. In large organizations, decision making is inherently a

group process, and DSS can be designed to facilitate group decision

making by providing tools, procedures, and technologies to help people

working on decisions as a group.

3. What is the difference between a data-driven DSS and a model-

driven DSS? Give examples.


A data-driven DSS is a system that supports decision making by allowing

users to extract and analyze useful information that was previously

buried in large databases. Often TPS data are collected in data

warehouses. Multidimensional analysis and datamining tools can then

analyze the data. WH Smith PLC is an example of a data-driven DSS.

A model-driven DSS is primarily a stand-alone system that has a model

at its heart, perhaps a mathematical or spreadsheet representation of

such a model. The emphasis is on the model, scenarios, and what-if

sensitivity, such as linear programming. This chapter provides several

examples of model-driven DSS, including systems used by HBC and

Continental Airlines.

4. What are the three basic components of a DSS? Briefly describe

each.

The three basic components of a DSS include a DSS database, DSS

software system, and DSS user interface. The DSS database is a

collection of current or historical data from a number of applications or

groups, organized for easy access by a range of applications. The DSS

database may be a small database residing on a PC or it may be a

massive data warehouse that is continuously updated by major

organizational TPS. The DSS software system is a collection of software


tools used for data analysis, including a collection of mathematical and

analytical models, OLAP tools, and datamining tools. Various kinds of

models may be in the model base, including libraries of statistical,

optimization, sensitivity analysis, and forecasting models. The DSS user

interface permits easy interaction between users and the DSS software

tools.

5. How can DSS help firms with supply chain management and

customer relationship management?

Supply chain decisions involve determining “who, what, when, and

where” from purchasing and transporting materials and parts through

manufacturing products and distributing and delivering those products

to customers. DSS can help managers examine this complex chain

comprehensively and search among a huge number of alternatives for

the combinations that are most efficient and cost-effective. The prime

management goal might be to reduce overall costs while increasing the

speed and accuracy of filling customer orders.

DSS for customer relationship management use datamining to guide

decisions about pricing, customer retention, market share, and new

revenue streams. These systems typically consolidate customer

information from a variety of systems into massive data warehouses and


use various analytical tools to slice the data into tiny segments for one-

to-one marketing.

6. What is a geographic information system (GIS)? How does it use

data visualization technology? How can it support decision

making?

Geographic information systems (GIS) are a special category of DSS that

use data visualization technology to analyze and display data for

planning and decision making in the form of digitized maps. The

software can assemble, store, manipulate, and display geographically

referenced information, tying data to points, lines, and areas on a map.

GIS can thus be used to support decisions that require knowledge about

the geographic distribution of people or other resources in scientific

research, resource management, and development planning. For

example, GIS might be used to help state and local governments

calculate emergency response times to natural disasters or to help

banks identify the best locations for installing new branches or ATM

terminals. GIS tools have become affordable even for small businesses

and some can be used on the Web.

7. What is a customer decision-support system? How can the

Internet be used for this purpose?


A customer decision-support system (CDSS) supports the decision-

making process of the organization’s existing and potential customers.

The data can come from both internal and external sources, including

enterprise systems and the Web. The Web and Internet can provide

online access to various database and information pools along with

software for data analysis.

8. What is a group decision-support system (GDSS)? How does it

differ from a DSS?

A GDSS is an interactive computer-based system that facilitates the

solution of unstructured problems by a set of decision makers working

together as a group. GDSS have been developed in response to the

growing concern over the quality and effectiveness of meetings. In

general, DSS focus on individual decision making while GDSS support

decision making by a group.

9. What underlying problems in group decision making have led to

the development of GDSS?

The underlying problems of group decision making that have led to the

development of GDSS are the explosion of decision-maker meetings, the


growing length of these meetings, and the increased number of

attendees at these meetings.

10. Describe the three elements of a GDSS.

Hardware, software tools, and people are the three GDSS elements.

Hardware includes the conference facility itself (room, tables, chairs)

that is laid out to support group collaboration. It also includes electronic

hardware such as electronic display boards as well as audiovisual,

computer, and networking equipment. Software tools include electronic

questionnaires, electronic brainstorming tools, idea organizers,

questionnaire tools, tools for voting or setting priorities, stakeholder

identification and analysis tools, policy formation tools, and group

dictionaries. People include the participants, a trained facilitator, and the

staff to support the hardware and software.

11. Name five GDSS software tools.

Although many tools exist, the list provided in the textbook includes

electronic questionnaires, electronic brainstorming tools, idea

organizers, questionnaire tools, tools for voting or setting priorities,

stakeholder identification and analysis tools, policy formation tools, and

group dictionaries.


12. How can GDSS facilitate group decision making?

GDSS enable more people to attend and participate in a meeting, and at

the same time the GDSS can increase meeting productivity. This

increase in productivity is realized because the attendees can contribute

simultaneously. A GDSS can guarantee anonymity, follow structured

methods for organizing and evaluating ideas, preserve the results of

meetings, and can increase the number of ideas generated and the

quality of decisions while producing the desired results in fewer

meetings. A GDSS can support idea generation, complex problem

analysis, and large groups.


13. Define and describe the capabilities of an executive support

system (ESS).

Executive support systems (ESS) help managers make unstructured and

semistructured decisions. ESS focus on the information needs of senior

management and combine data from both internal and external sources.

The ESS creates a generalized computing and communications

environment that can be focused on and applied to a changing array of

problems. The ESS can help senior executives monitor organizational

performance, track activities of competitors, spot problems, identify

opportunities, and forecast trends.

14. How can the Internet and enterprise systems provide

capabilities for executive support systems?

There are several ways that the Internet and Web technology can

enhance such a system. First, the Web interface is a well-known and

understood interface, making it easier to learn and use and less costly to

create. Secondly, the Web is an important source of external data and

information. Enterprise systems eliminate the problem of data being

unavailable or available in different formats, or having to access

hundreds or even thousands of incompatible systems. Enterprise


systems allow data to be gathered from a company-wide perspective so

that it can be more easily analyzed by senior management.

15. What are the benefits of ESS? How do these systems enhance

managerial decision making?

Although ESS benefits are not easily measured, several benefits are

mentioned in the chapter. ESS increase flexibility, provide the ability to

analyze, compare and highlight trends, monitor performance, improve

management performance, and increase management's span of control.

ESS flexibility allows executives to shape the problems, using the

system as an extension of their own thinking. ESS offer executives the

ability to analyze quickly and to compare and highlight trends, freeing

up executives and their staff for more creative analysis and decision

making. ESS can, and do, change the workings of organizations.

Executives are better able to monitor activities below them, allowing

them to push decision making further down in the organization while

expanding the executive’s span of control.

Application Software Exercise


This problem is useful for showing students how a rudimentary DSS

works and for illustrating the concepts of “what-if” analysis and

sensitivity analysis. Instructors may need to spend a little time

explaining breakeven analysis to students. Discuss with the students the

fact that the principal idea behind break-even analysis is that all costs

are variable (which means they vary with output), fixed (which means

they are relatively constant over time), or a combination of both.

Theoretically, after fixed costs are covered, each dollar of sales will have

to cover only variable costs.

The problem here has been simplified so that it treats Selmore as a one-

product company and calculates the breakeven point for one product.

The actual breakeven calculations in the real business world would be

much more complicated and perhaps too challenging for most students

taking the MIS course. Students will need to know how to use the data-

table command for sensitivity analysis in order to solve this problem.

The solution spreadsheet was designed so that one can easily

recalculate the breakeven point when the selling price is $125 by

entering $125 as the sales price per unit.

Group Project


With three or four of your classmates, identify several groups in

your university that could benefit from a GDSS. Design a GDSS

for one of those groups, describing its hardware, software, and

people elements. Present your findings to the class.

Presentations will depend upon the university group selected by each

student group. For instance, the student group might select the faculty

personnel and tenure committee, which probably engages in lengthy

deliberations about appointments, tenure, and promotions. After

selecting a target group, the student teams must first define the needs

of that group. For instance, the student groups must determine the

kinds of problems they will address through the GDSS, the problems the

GDSS need to solve. At this point, you should encourage your students

to review Section 13.2, “Group Decision-Support Systems (GDSS).”


Case Study – Can DSS Help MasterCard Master the Credit Card

Business?

1. Analyze MasterCard using the competitive forces and value

chain models. Briefly summarize the problems that MasterCard

was facing before 1998 that caused it to change its business

strategy.

MasterCard is operating in a very competitive industry. MasterCard has

several competitors, with Visa being its primary competitor. Although

not mentioned in the case, MasterCard does have competition from

other credit cards companies, such as American Express, Discover, and

the various retail stores that offer their own credit cards. MasterCard

customers can easily switch credit card companies, and banks can opt

to promote one credit card over the other. Although entry of a new

credit card company into the industry is a threat, it would require a

significant investment. MasterCard is using information technology to

support its value chain activities. Information technology has enabled

MasterCard to enhance market penetration and create new services.

Because of the data provided by MasterCard's system, its merchants can

use the data to target specific customers. Wal-Mart is one example

mentioned in the case.


In 1998, Visa had over 50 percent of the credit card charge volume, and

MasterCard was lagging behind with 28.8 percent. In an effort to attract

new business, MasterCard updated and consolidated its computer

centers, building a system that could track every transaction made by

customers for three years. MasterCard added new data fields and made

the customer data and analytical tools available to and directly

accessible by its member banks.

2. Describe the new business strategy MasterCard developed.

What is the role of information systems in its new strategy?

MasterCard's new strategy focused on information leadership and

customer service. Part of MasterCard's strategy was to encourage bank

issuers to promote its cards over its competitors. To spur its bank

issuers, MasterCard sought to make more customer and transaction

information available to the bank issuers than the competition currently

makes available to them.

MasterCard required a system that would keep a record of every

transaction of every customer for three years. Information systems were

crucial to the implementation of MasterCard's strategy. The new

information systems were responsible for collecting, storing, and

consolidating customer data. The new information systems also provide


member banks with online access to their customer data, reports, and

analytical tools.

3. What kind of decision-support systems did MasterCard develop?

How are they related to its business strategy? How do they

provide value for MasterCard and its clients?

MasterCard developed data-driven DSS. The DSS provide 27 tools that

banks can use. Although the Business Performance Intelligence tool also

provides some MIS capabilities, such as providing operational reporting,

it does include a suite of 70 standard reports that banks can use to

analyze their daily, weekly, and monthly transactions. Banks can

compare results from one market with the results from another market.

MarketScope can help merchants and banks generate more purchases

for the merchants if the customers use their MasterCards for their

purchases. MarketScope can analyze the purchases and help the

merchants target market special opportunities to customers.

MasterCard's DSS have helped the company increase its market share.


4. Has MasterCard's strategy been successful? Can MasterCard

hold on to its strategic advantage? Explain your answer.

MasterCard's strategy has been successful. MasterCard encouraged

several companies, such as Citigroup and J.P. Morgan Chase, to push its

credit cards. MasterCard's strategic advantage is not sustainable. The

case clearly points out that VISA is not sitting by and allowing

MasterCard to eat away at its market share. VISA is now running

analyses for its banks on its own computers and is offering a Web

service called Resolve Online.


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