Decision support systems for business intelligence - 2nd ed

DECISION SUPPORT

SYSTEMS FOR BUSINESS

INTELLIGENCE

DECISION SUPPORT

SYSTEMS FOR BUSINESS

INTELLIGENCE

SECOND EDITION

Vicki L. Sauter

University of Missouri - St. Louis

College of Business Administration

St. Louis, MO

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Library of Congress Cataloging-in-Publication Data:

Sauter, Vicki Lynn, 1955-

Decision support systems for business intelligence / Vicki L. Sauter. - 2nd ed.

p. cm.

Rev. ed. of: Decision support systems. 1997.

Includes bibliographical references and index.

ISBN 978-0-470-43374-4 (pbk.)

1. Decision support systems. 2. Decision making. I. Sauter, Vicki Lynn, 1955-

Decision support systems. II. Title.

HG30.213.S28 2010

658.4Ό3801 l-dc22 2010028361

Printed in Singapore

10 98765432 1

This book is dedicated, with love, to

My Late Father, Leo F. Sauter, Jr.,

My Husband, Joseph S. Martinich,

and

My Son, Michael C. Martinich-Sauter,

with thanks for their steadfast inspiration and encouragement.

CONTENTS

PREFACE xiii

Part I INTRODUCTION TO DECISION SUPPORT SYSTEMS 1

1 INTRODUCTION 3

WhatisaDSS? 13

Uses of a Decision Support System 17

The Book 19

Suggested Readings 440

Questions 442

On the Web 443

INDEX

PREFACE

Information is a crucial component of today's society. With a smaller world, faster communications, and greater interest, information relevant to a person's life, work, and recreation

has exploded. However, many believe this is not all good. Richard S. Wurman (in a book

entitled Information Anxiety) notes that the information explosion has backfired, leaving

us stranded between mere facts and real understanding. Similarly, Peter Drucker noted in a

Wall Street Journal (December 1,1992, p. A16) editorial entitled "Be Data Literate—Know

What to Know" that, although executives have become computer literate, few of them have

mastered the questions of what information they need, when they need information, and

in what form they need information. On that backdrop enters the awakening of business

intelligence and analytics to provide a structure for harnessing the information to be a tool

to help companies be more competitive.

This is both good news and bad news for designers of decision support systems (DSS).

The good news is that if, as Drucker claims, the future success of companies is through the

astute use of appropriate information, then DSS have a bright future in helping decision

makers use information appropriately. The bad new is that where DSS are available, they

may not be providing enough support to the users. Too often the DSS are designed as a

substitute for the human choice process or an elaborate report generator.

Decision support systems, by definition, provide business intelligence and analytics to

strengthen some kind of choice process. In order for us to know what information to retain

and how to model the relationships among the data so as to best complement the human

choice process, DSS designers must understand the human choice process. To that end, this

book illustrates what is known about decision making and the different styles that decision

makers demonstrate under different conditions. This "needs assessment" is developed on

a variety of levels: (a) what is known about decision making (with or without a computer)

in general; (b) how that knowledge about decision making has been translated into specific

DSS needs; (c) what forms of business intelligence needs are associated with the problem

or the environment; and (d) how does one actually program those needs into a system.

Hence, all topics are addressed on three levels: (a) general theory, (b) specific issues of

DSS design, and (c) hands-on applications. These are not separate chapters but rather an

integrated analysis of what the designer of a DSS needs to know.

The second issue that drives the content and organization of this book is that the focus

is totally upon DSS for business intelligence. Many books spend a significant amount of

time and space explaining concepts that are important but ancillary to the development of a

DSS. For example, many books discuss the methods for solution of mathematical models.

While accurate solution methods for mathematical models are important for a successful

DSS, there is much more about the models that needs discussion in order to implement a

good DSS. Hence, I have left model solutions and countless other topics out of the book in

order to accommodate topics of direct relevance to DSS.

Finally, I believe in DSS and their contribution. Those who know me well know that

when I believe in something, I share it with enthusiasm and zeal. I think those attributes

show in this book and make it better. Writing this book was clearly a labor of love; I hope

it shows.

PREFACE

MAJOR FEATURES OF THE BOOK

Integration of Theory and Practice: It is the integration of theory with practice and abstract

with concrete that I think makes this book unique. It reflects a personal bias that it is

impossible to understand these design concepts until you actually try to implement them. It

also reflects a personal bias that unless we can relate the DSS concepts to the "real world"

and the kinds of problems (opportunities) the students can expect to find there, the students

will not understand the concepts fully.

Although the book contains many examples of many aspects of DSS, there is one

example that is carried throughout the book: a DSS to facilitate car purchases. I have

selected this example because most students can relate to it, and readers do not get bogged

down with discussion of company politics and nuances. Furthermore, it allows a variety of

issues to be compared in a meaningful fashion.

Focus on the "Big Picture": The representation throughout the book focuses on

"generic" DSS, which allows discussion of design issues without concern for whether it is

a group system, an organizational system, or an individual system. Furthermore, it allows

illustration of how seemingly specialized forms of DSS, such as geographic information

systems, actually follow the same principles as a "basic" DSS.

Although I show implementation of the concepts, I do not overfocus on the tools. There

are example screens of many tools appearing in the book. Where I show development, I

create my examples using HTML, Javascript, and Adobe® Cold Fusion.® Most information systems students today have an understanding of HTML and Javascript. Cold Fusion

commands are sufficiently close to these that even if you elect to use another tool, these

examples can be understood generally by students.

Strong Common Sense Component: We technology folks can get carried away with the

newest and greatest toy regardless of its applicability to a decision maker. It is important

to remember the practicalities of the situation when designing DSS. For example, if we

know that a company has a commitment to maintaining particular hardware, it would not

make sense to develop a system relying upon other hardware. These kinds of considerations

and the associated implications for DSS design are highlighted in the book. This is not to

say that some of these very interesting but currently infeasible options are not discussed.

Clearly, they are important for the future of management information systems. Someday,

these options will be feasible and practical so they are discussed.

Understanding Analytics: Some research indicates that companies do not have enough

people who can apply analytics successfully because they do not understand modeling

well. In this book, I try to emphasize the questions that should surround the use of analytics

to ensure they are being used properly and that the decision maker fully appreciates the

implications of their use. The goal is not only to help the reader better understand analytics

but also to encourage builders of DSS to be aware of this problem and build sufficient

modeling support in their systems.

Integration of Intelligence: Over the years expert systems have evolved into an integrated component of many decision support systems provided to support decisions makers,

not replace them. To accomplish such a goal, the expert systems could not be stand alone,

but rather need to be integrated with the data and models used by these decision makers.

In other words, expert systems (or intelligence) technology became a modeling support

function, albeit an important one, for decision support systems. Hence, the coverage of the

topic is integrated into the modeling component in this book. However, I do acknowledge

there are some special topics needing attention to those who want to build the intelligence.

PREFACE

These topics are covered in a supplement to Chapter 4, thereby allowing instructors to use

discretion in how they integrate the topic into their classes.

International Issues Coverage: As more companies become truly multinational, there

is a trend toward greater "local" (overseas) decision making that must of course be coordinated. These companies can afford to have some independent transaction processing

systems, but will need to share DSS. If the DSS are truly to facilitate decision making

across cultures, then they must be sensitive to differences across cultures. This sensitivity

includes more than just changes in the language used or concern about the meaning of

icons. Rather, it includes an understanding of the differences in preferences for models and

model management systems and for trade-offs and mechanisms by which information is

communicated and acted upon. Since future designers of DSS will need to understand the

implications of these differences, they are highlighted in the book. Of course, as with any

other topic, the international issues will be addressed both in "philosophical" terms and in

specific technical (e.g.,coding) terms.

Object-Oriented Concepts and Tools: Another feature of the book that differentiates

it from others is a use of object-oriented technology. Many books either present material

without discussion of implementation or use traditional programming tools. If students

have not previously had experience with them, object-oriented tools can be tricky to use.

However, we know that a reliance upon object-oriented technology can lead to easier

maintenance and transfer of systems. Since DSS must be updated to reflect new company

concerns and trends, designers must be concerned about easier maintenance. So, while the

focus of the book is not on object-oriented programming, the nuances of its programming

will be discussed wherever it is practical. In addition, there is a chapter that focuses upon

the topic that can be included in the curriculum.

Web Support and Other Instructional Support Tools: There is a complete set of Web

links that provide instructional support for this book. Example syllabi, projects, and other

ideas can be viewed and downloaded from the Web. All figures and tables appear on

the Web so you can use them directly in the class or download them to your favorite

demonstration package to use in class. In addition, there are lots of Web links to sites you

can use to supplement the information in the book. Some of those links provide access to

demo versions of decision support packages for download and use of some sample screens.

These provide up-to-date examples of a variety of systems that students can experience or

instructors can demonstrate to bring the practice into the classroom. Other links provide

access to application descriptions, war stories, and advice from practitioners. Still others

provide a link to a variety of instructors (both academic and nonacademic) on the topic.

I strived to provide support for the class from a variety of different perspectives.

You can see the information at http://www.umsl.edu/~sauterv/DSS4BI/. Further, there is

information at the end of every chapter about the kinds of materials found in support of that

chapter, and directions for direct access to the chapter information is given in those chapters.

More important, in the true spirit of the Web, I will update these links as more information

becomes available. So, if you happen to see something that should be included, please

email me at [email protected]. In addition to the DSS support, I have accumulated

links regarding automobiles and their purchase and lease. This Web page would provide

support for people who want to explore the car example in the book in more depth or for

students who want to use different information in the development of their own automobile

DSS. You can link to this from the main page or go to it directly at http://www.umsl.

edu/~sauterv/DSS4B yautomobile_information.html.

PREFACE

ACKNOWLEDGMENTS

If a book is a labor of love, then there must be a "coach" to help one through the process.

In my case, I am lucky enough to have a variety of coaches who have been there with me

every step of the way. First, in a very real sense, my students over the years have provided a

foundation for this book. Even before I knew I was going to produce this work, my students

provided an environment in which I could experiment and learn about decisions, decision

making, and decision support systems. It is their interest, their inquisitiveness, and their

challenge that have led me to think through these topics in a manner that allowed me to

write this book. I have particular gratitude to Mary Kay Carragher, David Doom, Mimi

Duncan, Joseph Hof er, Timothy McCaffrey, Kathryn Ntalaja, Richard Ritthamel, Phillip

Wells, and Aihua Yan for their efforts in support of this book.

Second, there are numerous people at John Wiley & Sons who helped me achieve my

vision for this book. I am grateful to each one for his or her efforts and contribution. In

particular, I would like to thank my editors, Beth Lang Golub, editor of the first edition,

and Susanne Steitz-Filler, editor of the second edition. They each believed in this project

long before I did, and continued to have faith in it when mine wore thin. I could not

have produced this book without them. In addition, I want to thank my style editors, Elisa

Adams and Ernestine Franco, who helped to make my ideas accessible through direct and

constructive changes in the prose. In addition, I would like to thank the reviewers of the

first and second editions who provided superb comments to improve the style and content.

Finally, I want to thank my friends and family for their support, encouragement, and

patience. My husband, Joseph Martinich, has been with me every step of the way—not

only with this book, but in my entire career. I sincerely doubt that I could have done any of

it without him. My son, Michael Martinich-Sauter, has demonstrated infinite patience with

his mother. More important, he has inspired me to look at every topic differently and more

creatively. I have learned much about decisions, decision making, and decision support

from him, and I am most grateful he has shared his wisdom with me. Finally, I want to

acknowledge the sage Lady Alexandra (a.k.a. Allie—the dog), who made me laugh when

I really needed it and whose courage made me appreciate everything more.

INTRODUCTION TO DECISION

SUPPORT SYSTEMS

Decision Support Systems for Business Intelligence by Vicki L. Sauter

INTRODUCTION

Virtually everyone makes hundreds of decisions each day. These decisions range from the

inconsequential, such as what to eat for breakfast, to the significant, such as how best to get

the economy out of a recession. All other things being equal, good outcomes from those

decisions are better than bad outcomes. For example, all of us would like to have a tasty,

nutritional breakfast (especially if it is fast and easy), and the country would like to have

a stable, well-functioning economy again. Some individuals are "lucky" in their decision

processes. They can muddle through the decision not really looking at all of the options

or at useful data and still experience good consequences. We have all met people who

instinctively put together foods to make good meals and have seen companies that seem to

do things wrong but still make a good profit. For most of us, however, good outcomes in

decision making are a result of making good decisions.

"Good decision making" means we are informed and have relevant and appropriate

information on which to base our choices among alternatives. In some cases, we support

decisions using existing, historical data, while other times we collect the information,

especially for a particular choice process. The information comes in the form of facts,

numbers, impressions, graphics, pictures, and sounds. It needs to be collected from various

sources, joined together, and organized. The process of organizing and examining the

information about the various options is the process of modeling. Models are created to

help decision makers understand the ramifications of selecting an option. The models can

range from quite informal representations to complex mathematical relationships.

For example, when deciding on what to eat for a meal, we might rely upon historical

data, such as those available from tasting and eating the various meal options over time and

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