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DECISION SUPPORT
SYSTEMS FOR BUSINESS
INTELLIGENCE
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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
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Copyright © 2010 by John Wiley & Sons, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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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 987654321
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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.
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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 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
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viii
CONTENTS
Part
II DSS
COMPONENTS
67
3 DATA COMPONENT 69
Specific View Toward Included Data 72
Characteristics of Information 73
Timeliness 73
Sufficiency 74
Level of Detail 75
Understandability 76
Freedom from Bias 77
Decision Relevance 78
Comparability 78
Reliability 80
Redundancy 80
Cost Efficiency 80
Quantifiability 81
Appropriateness of Format 82
More Is Never Better! 83
Databases 85
Database Management Systems 86
Data Warehouses 87
Data Scrubbing 93
Data Adjustment 96
Architecture 97
Car Example 101
Possible Criteria 101
Data Warehouse 102
Information Uses 102
"How To" 107
Discussion 118
Suggested Readings 121
Questions 123
On the Web 124
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
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CONTENTS
Data Mining 148
Intelligent Agents 156
Model-Based Management Systems 159
Easy Access to Models 159
Understandability of Results 163
Integrating Models 166
Sensitivity of a Decision 168
Model Management Support Tools 174
Car Example 177
Brainstorming and Alternative Generation 177
Flexibility Concerns 179
Evaluating Alternatives 183
Running External Models 189
Discussion 190
Suggested Readings 190
Questions 193
On the Web 195
4S INTELLIGENCE AND DECISION SUPPORT SYSTEMS 197
Programming Reasoning 200
Backward-Chaining Reasoning 201
Forward-Chaining Reasoning 203
Comparison of Reasoning Processes 206
Uncertainty 206
Representing Uncertainty with Probability Theory 208
Representing Uncertainty with Certainty Factors 209
Discussion 211
Suggested Readings 211
Questions 212
On the Web 212
USER INTERFACE 215
Goals of the User Interface 216
Mechanisms of User Interfaces 218
User Interface Components 223
Action Language 224
Display or Presentation Language 233
Knowledge Base 251
Car Example 256
Discussion 271
Suggested Readings 271
Questions 273
On the Web 274
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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
9 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
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CONTENTS
Overall Usefulness 385
Implementation Success 386
Organizational Appropriateness 391
Discussion 392
Suggested Readings 392
Questions 394
On the Web 395
Part IV EXTENSIONS OF DECISION SUPPORT SYSTEMS 397
10 EXECUTIVE INFORMATION AND DASHBOARDS 399
KPIs and Balanced Scoreboards 400
Dashboards 401
Dashboard as Driver to EIS 408
Design Requirements for Dashboard 410
Dashboard Appliances 417
Value of Dashboard and EIS 418
Discussion 423
Suggested Readings 423
Questions 425
On the Web 426
11 GROUP DECISION SUPPORT SYSTEMS 427
Groupware 429
GDSS Definitions 432
Features of Support 434
Decision-Making Support 434
Process Support 438
GDSS and Reengineering 439
Discussion 440
Suggested Readings 440
Questions 442
On the Web 443
INDEX
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PREFACE
Information is a crucial component of today's society. With a smaller world, faster commu-
nications, 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.
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[...]... what is going on in the business and to consider problems from multiple perspectives so as to to provide the best guidance for the decision maker One way to accomplish the goal of bringing together the appropriate information and models for informed decision making is to use decision support systems (DSS) Decision support systems are computer-based systems that bring together information from a variety... 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 www.it-ebooks.info I INTRODUCTION TO DECISION SUPPORT SYSTEMS Decision Support Systems for Business Intelligence... Management Information Systems, Vol 4, No 4, 1988, pp 77-92 www.it-ebooks.info 21 QUESTIONS Schlegel, K., and G Herschel, "Business Intelligence and Decision Making," Gartner Research, Report, No G00152905, Stanford, CT May 2, 2008 Scott-Morton, M S., Management Decision Systems: Computer-Based Supportfor Decision Making, Cambridge, MA: Harvard University, 1971 Shannon, P W., and R P Minch, "A Decision Support. .. purposes of a particular decision The systems generally process a series of heuristics that are believed to mimic that logic They are good at supporting decisions, but only those decisions it has been programmed to process In between those two is the area of DSS and executive information systems (EIS) These two types of systems are intended to help decision makers identify and access information they believe... 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,... a report These systems are not analysis oriented and tend to be slow, batch processing systems As such, they are not good for supporting decisions www.it-ebooks.info 14 INTRODUCTION Figure 1.6 Continuum of information system products The far right of this diagram illustrates expert systems (ES) These systems are intended to reproduce the logic of a human who is considered an expert for the purposes... 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... compound DSS For example, text-oriented systems catalog books, periodicals, reports, memos, and other written documents so that their contents can be made available to decision makers Each document, or a portion of that document, provides some information or even knowledge that could be important to a decision maker when making choices The system allows you to categorize, consolidate, and merge documents... and the value thereof By allowing users to focus on portions of documents, the system helps decision makers save time when they need to refer to the document In addition, intelligent systems can perform content analyses of the texts and recommend sections (and www.it-ebooks.info USES OF A DECISION SUPPORT SYSTEM thus information) the decision maker might not otherwise consider A variation on the text-oriented... S Scott-Morton, Decision Support Systems: An Organizational Perspective, Reading, MA: Addison-Wesley, 1978 Hogue, J T., and H J Watson, "Management's Role in the Approval and Administration of Decision Support Systems, " MIS Quarterly, Vol 7, No 2, June 1983, pp 15-26 Holsapple, C W, "DSS Architecture and Types," in F Burstein, and C W Holsapple (Eds.), Handbook on Decision Support Systems, Vol 1, Berlin: . appropriate information and models for informed decision making is to use decision support systems (DSS). Decision support systems are computer-based systems that bring together information from. DECISION SUPPORT SYSTEMS FOR BUSINESS INTELLIGENCE www.it-ebooks.info DECISION SUPPORT SYSTEMS FOR BUSINESS INTELLIGENCE SECOND EDITION Vicki L. Sauter University. 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
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