Decision support systems for business



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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

WILEY

A JOHN WILEY & SONS, INC. PUBLICATION

Copyright © 2010 by John Wiley & Sons, Inc. All rights reserved.



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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

658.4'038011-dc22

2010028361

Printed in Singapore

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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

I

INTRODUCTION

3

What is a DSS?

13

Uses of a Decision Support System

17

The Book

19

Suggested Readings

19

Questions

21

On the Web

22

2

DECISION MAKING

23

Rational Decisions

25

Bounded Rationality and Muddling Through

29

Nature of Managers

31

Appropriate Decision Support

33

Electronic Memory

33

Bias in Decision Making

33

Appropriate Data Support

36

Information Processing Models

37

Tracking Experience

45

Group Decision Making

46

Intuition, Qualitative Data, and Decision Making

47

How Do We Support Intuition?

48

Virtual Experience

51

Business Intelligence and Decision Making

53

Analytics

57

Competitive Business Intelligence

58

Conclusion

60

Suggested Readings


60

Questions

65

On the Web

66

Vii

viii


CONTENTS

Part II D55 COMPONENTS

67

3 DATA COMPONENT

Specific View Toward Included Data Characteristics of Information
Timeliness

Sufficiency

Level of Detail

Understandability Freedom from Bias Decision Relevance Comparability

Reliability

Redundancy

Cost Efficiency Quantifiability

Appropriateness of Format More Is Never Better!

Databases

Database Management Systems Data Warehouses

Data Scrubbing Data Adjustment Architecture

Car Example

Possible Criteria Data Warehouse Information Uses "How To"

Discussion

Suggested Readings Questions

On the Web

4 MODEL COMPONENT

125

Models and Analytics

125

Options for Models

129

Representation

130

Time Dimension

132

Linearity of the Relationship

134

Deterministic Versus Stochastic

135

Descriptive Versus Normative

136

Causality Versus Correlation

137


Methodology Dimension

138

Problems of Models

147

CONTENTS


Data Mining

Intelligent Agents

Model-Based Management Systems
Easy Access to Models

Understandability of Results Integrating Models

Sensitivity of a Decision

Model Management Support Tools Car Example

Brainstorming and Alternative Generation Flexibility Concerns

Evaluating Alternatives
Running External Models
Discussion

Suggested Readings Questions

On the Web

4S INTELLIGENCE AND DECISION SUPPORT SYSTEMS

Programming Reasoning
Backward-Chaining Reasoning

Forward-Chaining Reasoning
Comparison of Reasoning Processes
Uncertainty

Representing Uncertainty with Probability Theory
Representing Uncertainty with Certainty Factors
Discussion

Suggested Readings Questions

On the Web

5 USER INTERFACE
Goals of the User Interface

Mechanisms of User Interfaces User Interface Components

Action Language

Display or Presentation Language Knowledge Base

Car Example
Discussion

Suggested Readings Questions

On the Web

ix

148

156

159

159

163

166

168

174


177

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x


CONTENTS

Part III ISSUES OF DESIGN

277

6

INTERNATIONAL DECISION SUPPORT SYSTEMS

279

Information Availability Standards


289

Data Privacy

290

Data Availability

295

Data Flow

296

Cross-Cultural Modeling

297

Effects of Culture on Decision Support System

303

Discussion

310

Suggested Readings

310

Questions

312

On the Web

313

7 DESIGNING A DECISION SUPPORT SYSTEM

315

Planning for Decision Support Systems

319

Designing a Specific DSS

320

Design Approaches

329

The Design Team

340

DSS Design and Reengineering

341

Discussion

344

Suggested Readings

344

Questions

346

On the Web

347

8

OBJECT-ORIENTED TECHNOLOGIES AND DSS DESIGN

349

Kinds of Development Tools

350

Non-Object-Oriented Tools


350

Object-Oriented Tools

352

Benefits of Object-Oriented Technologies for DSS

365

Suggested Readings

366

Questions

367

On the Web

367

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IMPLEMENTATION AND EVALUATION

369

Implementation Strategy

369

Ensure System Does What It Is Supposed To Do the Way It Is Supposed

To Do It

372

Keep Solution Simple

375

Develop Satisfactory Support Base

375

Institutionalize System

380

Implementation and System Evaluation

382

Technical Appropriateness

382

CONTENTS


Overall Usefulness
Implementation Success
Organizational Appropriateness
Discussion

Suggested Readings Questions

On the Web

Part IV EXTENSIONS OF DECISION SUPPORT SYSTEMS

10 EXECUTIVE INFORMATION AND DASHBOARDS

KPIs and Balanced Scoreboards Dashboards

Dashboard as Driver to EIS

Design Requirements for Dashboard Dashboard Appliances


Value of Dashboard and EIS Discussion

Suggested Readings Questions

On the Web

11 GROUP DECISION SUPPORT SYSTEMS

Groupware

GDSS Definitions
Features of Support

Decision-Making Support Process Support

GDSS and Reengineering Discussion

Suggested Readings Questions

On the Web

INDEX

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Information is a crucial component of today's society. With a smaller world, fastercommunications, 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. A 16) 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.

xiii

AV


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 inte-
grated 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


XV

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.




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