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. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. 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Sauter, Vicki Lynn, 1955- Decision support systems. II. Title. HG30.213.S28 2010 658.4Ό3801 l-dc22 2010028361 Printed in Singapore 10 987654321 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 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 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 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 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 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 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. [...]... 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... Management Information Systems, Vol 4, No 4, 1988, pp 77-92 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 System for Motor... 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 I INTRODUCTION TO DECISION SUPPORT SYSTEMS Decision Support Systems for Business Intelligence Copyright... These systems are not analysis oriented and tend to be slow, batch processing systems As such, they are not good for supporting decisions 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 of a particular decision The systems. .. 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,... 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... scheduling The systems include modeling, forecasting, planning, communications, database management systems, and graphics Furthermore, all of the data are drawn from key clinical and financial systems so there is not inconsistency in the data used by different decision makers This allows decision makers to consider problems and opportunities from more dimensions with belter support than ever before For example,... need to improve the information collection and analysis processes Increasingly corporations are attempting to make more informed decisions to improve their bottom lines Some refer to these efforts to use better information and better models to improve decision making as business intelligence Others refer to it as analytics In either case, the goal is to bring together the right information and the right... 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 will be useful in processing poorly structured, underspecified problems They provide flexible mechanisms for retrieving... 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: . 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. 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. 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