Decision Support and Business Intelligence Systems
Author: Efraim Turban
Appropriate for all courses in Decision Support Systems (DSS), computerized decision making tools, and management support systems.
Decision Support and Business Intelligence Systems 8e provides the only comprehensive, up-to-date guide to today's revolutionary management support system technologies, and showcases how they can be used for better decision-making. This completely revised and re-titled edition incorporates the expanded coverage of Business Intelligence and reflects the emphasis that most decision support courses are now taking.
Table of Contents:
Preface xxiiiDecision Support Systems and Business Intelligence 1
Decision Support Systems and Business Intelligence 3
Opening Vignette: Toyota Uses Business Intelligence to Excel 4
Changing Business Environments and Computerized Decision Support 6
Managerial Decision Making 9
Computerized Support for Decision Making 11
An Early Framework for Computerized Decision Support 14
Intelligent Price Setting Using an ADS 17
Decision Support at Hallmark for Better Strategy and Performance 19
The Concept of Decision Support Systems 20
The Houston Minerals Case 21
Helping Atlantic Electric Survive in the Deregulated Marketplace 23
A Framework for Business Intelligence 24
Predictive Analytics Helps Collect Taxes 29
A Work System View of Decision Support 30
The Major Tools and Techniques of Managerial Decision Support 31
United Sugars Corporation Optimizes Production, Distribution, and Inventory Capacity with Different Decision Support Tools 33
Implementing Computer-Based Managerial Decision Support Systems 34
Plan of the Book 35
Resources, Links, and the TeradataUniversity Network Connection 37
End of Chapter Application Case Decision Support at a Digital Hospital 41
References 42
Computerized Decision Support 43
Decision Making, Systems, Modeling, and Support 45
Opening Vignette: Decision Making at the U.S. Federal Reserve 46
Decision Making: Introductory and Definitions 47
Models 51
Phases of the Decision-Making Process 53
Decision Making: The Intelligence Phase 55
Decision Making: The Design Phase 57
Decision Making Between a Rock and a Hard Place; or What Can You Do When There Are No Good or Even Feasible Alternatives? 60
Decision Making From the Gut: When Intuition Can Fail 64
Too Many Alternatives Spoils the Broth 66
Decision Making: The Choice Phase 68
Decision Making: The Implementation Phase 69
How Decisions Are Supported 70
Union Pacific Railroad: If You're Collecting Data, Use It Profitably! 72
Advanced Technology for Museums: RFID Makes Art Come Alive 75
Resources, Links, and the Teradata University Network Connection 76
End of Chapter Application Case Strategic Decision Making in the Pharmaceutical Industry: How Bayer Decides Whether or Not to Develop a New Drug 80
References 81
Decision Support Systems Concepts, Methodologies, and Technologies: An Overview 84
Opening Vignette: Decision Support System Cures For Health Care 85
Decision Support Systems Configurations 87
Decision Support Systems Description 88
Web/GIS-Based DSS Aid in Disaster Relief and Identifying Food Stamp Fraud 89
Decision Support Systems Characteristics and Capabilities 90
Components of DSS 92
The Data Management Subsystem 97
Roadway Drives Legacy Applications onto the Web 98
The Model Management Subsystem 104
Web-Based Cluster Analysis DSS Matches Up Movies and Customers 107
The User Interface (Dialog) Subsystem 109
Clarissa: A Hands-Free Helper for Astronauts 111
The Knowledge-Based Management Subsystem 115
IAP Systems's Intelligent DSS Determines the Success of Overseas Assignments and Learns from the Experience 116
The Decision Support Systems User 116
Decision Support Systems Hardware 117
Decision Support Systems Classification 118
Database-Oriented DSS: Glaxo Wellcome Accesses Life-Saving Data 119
Resources, Links, and the Teradata University Network Connection 124
End of Chapter Application Case FedEx Tracks Customers Along with Packages 127
References 129
Modeling and Analysis 131
Opening Vignette: Winning Isn't Everything...But Losing Isn't Anything: Professional Sports Modeling for Decision Making 132
Management Support Systems Modeling 135
United Airlines Model-Based DSS Flies the Friendly Skies 137
Forecasting/Predictive Analytics Boosts Sales for Cox Communications 139
Static and Dynamic Models 142
Certainty, Uncertainty, and Risk 143
Management Support Systems Modeling with Spreadsheets 145
Decision Analysis with Decision Tables and Decision Trees 147
Johnson & Johnson Decides About New Pharmaceuticals by Using Trees 150
The Structure of Mathematical Models for Decision Support 151
Mathematical Programming Optimization 153
Complex Teacher Selection Is a Breeze in Flanders 154
Multiple Goals, Sensitivity Analysis, What-If Analysis, and Goal Seeking 158
Problem-Solving Search Methods 162
Heuristic-Based DSS Moves Milk in New Zealand 164
Simulation 165
Pratt & Whitney Canada Gets Real Savings Through Virtual Manufacturing 65
Simulation Applications 170
Visual Interactive Simulation 171
Quantitative Software Packages and Model Base Management 173
Resources, Links, and the Teradata University Network Connection 174
End of Chapter Application Case Major League Baseball Scheduling: Computerized Mathematical Models Take Us Out to the Ballgame 180
References 181
Business Intelligence 185
Special Introductory Section: The Essentials of Business Intelligence 187
A Preview of the Content of Chapters 5 through 9 187
The Origins and Drivers of Business Intelligence (BI) 188
The General Process of Intelligence Creation and Use 189
The Major Characteristics of Business Intelligence 192
Toward Competitive Intelligence and Advantage 195
The Typical Data Warehouse and Business Intelligence User Community 197
Successful Business Intelligence Implementation 198
France Telecom Business Intelligence 199
Structure and Components of Business Intelligence 201
Conclusion: Business Intelligence Today and Tomorrow 203
Resources, Links and the Teradata University Network Connection 203
References 205
Data Warehousing 206
Opening Vignette: Continental Airlines Flies High With Its Real-Time Data Warehouse 206
Data Warehousing Definitions and Concepts 209
Data Warehousing Process Overview 212
Data Warehousing Supports First American Corporation's Corporate Strategy 212
Data Warehousing Architectures 214
Data Integration and the Extraction, Transformation, and Load (ETL) Processes 222
Bank of America's Award-Winning Integrated Data Warehouse 223
Data Warehouse Development 226
Things Go Better with Coke's Data Warehouse 227
HP Consolidates Hundreds of Data Marts into a Single EDW 231
Real-Time Data Warehousing 238
Egg Plc Fries the Competition in Near-Real-Time 239
Data Warehouse Administration and Security Issues 243
Resources, Links, and the Teradata University Network Connection 244
End of Chapter Application Case Real-Time Data Warehousing at Overstock.com 249
References 250
Business Analytics and Data Visualization 253
Opening Vignette: Lexmark International Improves Operations with Business Intelligence 254
The Business Analytics (BA) Field: An Overview 256
Ben & Jerry's Excels with BA 257
Online Analytical Processing (OLAP) 261
TCF Financial Corp.: Conducting OLAP, Reporting, and Data Mining 266
Reports and Queries 266
Multidimensionality 269
Advanced Business Analytics 273
Predictive Analysis Can Help You Avoid Traffic Jams 274
Data Visualization 276
Financial Data Visualization at Merrill Lynch 279
Geographic Information Systems (GIS) 280
GIS and GPS Track Where You Are and Help You with What You Do 282
Real-time Business Intelligence Automated Decision Support (ADS), and Competitive Intelligence 284
Business Analytics and the Web: Web Intelligence and Web Analytics 289
Web Analytics Improves Performance for Online Merchants 291
Usage, Benefits, and Success of Business Analytics 292
Retailers Make Steady BI Progress 294
End of Chapter Application Case State Governments Share Geospatial Information 298
References 299
Data, Text, and Web Mining 302
Opening Vignette: Highmark, Inc., Employs Data Mining to Manage Insurance Costs 302
Data Mining Concepts and Applications 304
Data Help Foretell Customer Needs 306
Motor Vehicle Accidents and Driver Distractions 309
Data Mining to Identify Customer Behavior 310
Customizing Medicine 311
A Mine on Terrorist Funding 312
Data Mining Techniques and Tools 313
Data Mining Project Processes 325
DHS Data Mining Spinoffs and Advances in Law Enforcement 328
Text Mining 329
Flying Through Text 330
Web Mining 333
Caught in a Web 334
End of Chapter Application Case Hewlett-Packard and Text Mining 340
References 341
Neural Networks for Data Mining 343
Opening Vignette: Using Neural Networks To Predict Beer Flavors with Chemical Analysis 343
Basic Concepts of Neural Networks 346
Neural Networks Help Reduce Telecommunications Fraud 349
Learning in Artificial Neural Networks (ANN) 355
Neural Networks Help Deliver Microsoft's Mail to the Intended Audience 356
Developing Neural Network-Based Systems 362
A Sample Neural Network Project 367
Other Neural Network Paradigms 370
Applications of Artificial Neural Networks 372
Neural Networks for Breast Cancer Diagnosis 373
A Neural Network Software Demonstration 374
End of Chapter Application Case Sovereign Credit Ratings Using Neural Networks 380
References 381
Business Performance Management 383
Opening Vignette: Cisco and the Virtual Close 384
Business Performance Management (BPM) Overview 386
Strategize: Where Do We Want To Go? 388
Plan: How Do We Get There? 390
Monitor; How are we Doing? 392
Discovery-Driven Planning: The Case of Euro Disney 94
Act and Adjust: What Do We Need To Do Differently 395
Performance Measurement 398
International Truck and Engine Corporation 400
Business Performance Management Methodologies 402
Business Performance Management Architecture and Applications 409
Performance Dashboards 417
Dashboards for Doctors 419
Business Activity Monitoring (BAM) 421
City of Albuquerque Goes Real-time 422
End of Chapter Application Case Vigilant Information Systems at Western Digital 428
References 429
Collaboration, Communication, Group Support Systems, and Knowledge Management 431
Collaborative Computer-Supported Technologies and Group Support Systems 433
Opening Vignette: Collaborative Design at Boeing-Rocketdyne 434
Making Decisions in Groups: Characteristics, Process, Benefits, and Dysfunctions 436
Supporting Groupwork with Computerized Systems 439
How General Motors is Collaborating Online 440
Tools for Indirect Support of Decision Making 443
Videoconferencing Is Ready for Prime Time 446
Integrated Groupware Suites 448
NetMeeting Provides a Real-Time Advantage 449
Direct Computerized Support for Decision Making: From Group Decision Support Systems (GDSS) to Group Support Systems (GSS) 452
Eastman Chemical Boosts Creative Processes and Saves {dollar}500,000 with Groupware 456
Products and Tools for GDSS/GSS and Successful Implementation 458
Emerging Collaboration Tools: From VoIP to Wikis 462
Collaborative in Planning, Design, and Project Management 465
CPFR Initiatives at Ace Hardware and Sears 468
Creativity, Idea Generation, and Computerized Support 469
End of Chapter Application Case Dresdner Kleinwort Wasserstein Uses Wiki for Collaboration 475
References 476
Knowledge Management 478
Opening Vignette: Siemens Knows What It Knows Through Knowledge Management 479
Introduction to Knowledge Management 481
Cingular Calls on Knowledge 485
Organizational Learning and Transformation 486
Knowledge Management Activities 488
Approaches to Knowledge Management 490
Texaco Drills for Knowledge 492
Information Technology (IT) in Knowledge Management 495
Knowledge Management System (KMS) Implementation 500
Portal Opens the Door to Legal Knowledge 502
Knowledge Management: You Can Bank on It at Commerce Bank 504
Roles of People in Knowledge Management 507
Online Knowledge Sharing at Xerox 510
Ensuring the Success of Knowledge Management Efforts 513
The British Broadcasting Corporation Knowledge Management Success 514
How the U.S. Department of Commerce Uses an Expert Location System 515
When KMS Fail, They Can Fail in a Big Way 518
End of Chapter Application Case DaimlerChrysler EBOKs with Knowledge Management 524
References 526
Intelligent Systems 531
Artificial Intelligence and Expert Systems 533
Opening Vignette: Cigna Uses Business Rules to Support Treatment Request Approval 534
Concepts and Definitions of Artificial Intelligence 535
Intelligent Systems Beat Chess Grand Master 535
The Artificial Intelligence Field 537
Automatic Speech Recognition in Call Centers 542
Agents for Travel Planning at USC 544
Basic Concepts of Expert Systems (ES) 545
Applications of Expert Systems 549
Sample Applications of Expert Systems 549
Structure of Expert Systems 552
How Expert Systems Work: Inference Mechanisms 555
Problem Areas Suitable for Expert Systems 558
Development of Expert Systems 560
Benefits, Limitations, and Success Factors of Expert Systems 564
Expert Systems on the Web 567
Banner with Brains:Web-Based ES for Restaurant Selection 568
Rule-Based System for Online Student Consulation 568
End of Chapter Application Case Business Rule Automation at Farm Bureau Financial Services 573
References 574
Advanced Intelligent Systems 575
Opening Vignette: Improving Urban Infrastructure Management in the City of Verdun 576
Machine-Learning Techniques 577
Case-Based Reasoning (CBR) 580
CBR Improves Jet Engine Maintenance, Reduces Costs 585
Genetic Algorithm Fundamentals 587
Developing Genetic Algorithm Applications 592
Genetic Algorithms Schedule Assembly Lines at Volvo Trucks North America 593
Fuzzy Logic Fundamentals 595
Natural Language Processing (NLP) 598
Voice Technologies 601
Developing Integrated Advanced Systems 605
Hybrid ES and Fuzzy Logic System Dispatches Trains 607
End of Chapter Application Case Barclays Uses Voice Technology to Excel 611
References 612
Intelligent Systems over the Internet 614
Opening Vignette: Netflix Gains High Customer Satisfaction from DVD Recommendation 615
Web-Based Intelligent Systems 617
Intelligent Agents: An Overview 629
Characteristics of Intelligent Agents 622
Why Use Intelligent Agents? 624
Classification and Types of Intelligent Agents 626
Internet-Based Software Agents 629
Fujitsu(Japan) Uses Agents for Targeted Advertising 635
Wyndham Uses Intelligent Agents in Its Call Center 637
Agents and Multiagents 637
The Semantic Web: Representing Knowledge for the Intelligent Agents 641
Web-Based Recommendation Systems 647
Amazon.com Uses Collaborative Filtering to Recommend Products 648
Content-Based Filtering at Euro Vacations.com 653
Managerial Issues of Intelligent Agents 654
End of Chapter Application Case Spartan Uses Intelligent Systems to Find the Right Person and Reduce Turnover 659
References 660
Implementing Decision Support Systems 663
System Development and Acquisition 665
Opening Vignette: Osram Sylvania Thinks Small, Strategizes Big to Develop the HR Infonet Portal System 666
What Types of Support Systems Should You Build? 668
The Landscape and Framework of Management Support Systems Application Development 670
Development Options for Management Support System Applications 673
Prototyping: A Practical Management Support System Development Methodology 681
Criteria for Selecting an Management Support System Development Approach 687
Third-Party Providers of Management Support System Software Packages and Suites 689
Floriculture Partnership Streamlines Real-Time Ordering 692
Connecting to Databases and Other Enterprise Systems 693
The Rise of Web Services, XML, and the Service-Oriented Architecture 695
Lincoln Financial Excels by Using Web Services 696
User-Developed Management Support System 697
End-User Development Using Wikis 697
Management Support System Vendor and Software Selection 700
Putting Together an Management Support System 701
End of Chapter Application Case A Fully Integrated MSS for Sterngold: An Old Dental Manufacturer Adopts New IT Tricks 705
References 706
Integration, Impacts and the Future of Management Support Systems 708
Opening Vignette: Elite Care Supported by Intelligent Systems 709
Systems Integration: An Overview 711
Types of Management Support System Integration 715
Integration with Enterprise Systems and Knowledge Management 720
The Impacts of Management Support Systems: An Overview 725
Management Support Systems Impacts on Organizations 726
Management Support Systems Impacts on Individuals 730
Automating Decision Making and the Manager's Job 731
Issues of Legality, Privacy, and Ethics 733
Intelligent and Automated Systems and Employment Levels 737
Robots 738
Other Societal Impacts of Management Support Systems and the Digital Divide 739
The Future of Management Support Systems 742
End of Chapter Application Case An Intelligent Logistics Support System 747
References 748
Online Material
Enterprise Systems 751
Knowledge Acquisition, Representation, and Reasoning 752
Online Files
Representative Decision Support Tools
Decision Support Technologies and the Web
Emerging Technologies That May Benefit Decision Support
Additional References
Teradata University Network
Online Files
The MMS Running Case
Web Sources for Decision-Making Support Sampler
Further Reading
Online Files
Databases
Major Capabilities of the UIMS
Ad Hoc Visual Basic DSS Example
Further Reading on DSS
Online Files
Influence Diagrams
Links to Spreadsheet-Based DSS Excel Files in Chapter 4
Spreadsheet-Based Economic Order Quantity Simulation Model
Waiting Line Modeling (Queueing) in a Spreadsheet
Linear Programming Optimization: The Blending Problem
Lindo Example: The Product-Mix Model
Lingo Example: The Product-Mix Model
The Goal Programming MBI Model
Links to Excel Files of Section 4.9
Table of Models and Web Impacts
Model Base Management
Additional References
BI Preview Chapter Online Files
The General Process of Intelligence Creation and Use as Reflected in Continental Airline Case
BI Governance
The BI User Community
An Action Plan for the Information Systems Organization
Online Files
Capabilities of EIS
SAP Analytics
Trends in Visualization Products for Decision Support
Virtual Realty Visualization
Competitive Intelligence on the Internet
Cabela's
Online Files
Data Mining
Online Files
Heartdisease.sta
Creditrisk.xls
Movietrain.xls
Movietest.xls
Statistica Coupon
Online Files
Portfolio of Options
Rolling Forecasts and Real-Time Data
Effective Performance Measurement
Six Sigma Roles
Problems with Dashboard Displays
Online Files
Seven Sins of Deadly Meetings and Seven Steps to Salvation
Whiteboards
Internet Voting
GroupSystems Tools for Support of Group Processes
Collaboration in Designing Stores
Online Files
Leveraging Knowledge through Knowledge Management Systems
Online Files
Intelligent Systems
Internet-Based Intelligent Tutoring Systems
Automating the Help Desk
Assignment ES
Online Files
Steps in the CBR Process
Automating a Help Desk with Case-Based Reasoning
Automatic Translation of Web Pages
Online Files
Guidelines for a "Think Small, Strategize Big" Implementation
Project Management Software
Utility Computing
Agile Development and Extreme Programming (XP)
A Prototyping Approach to DSS Development
IBM's WebSphere Commerce Suite
XML, Web Services and Service-Oriented Architecture
The Process of Selecting a Software Vendor and an MSS Package
Online Files
An Active and Self-Evolving Model of Intelligent DSS
Cookies and Spyware
A Framework for Ethical Issues
A Hybrid Intelligent System
Online Tutorials
Systems
Forecasting
Text Mining Project
Statistica Software Project
References 748
Glossary 751
Index 763
New interesting book: Rethinking Development Economics or Media Economics
Intellectual Property Law for Engineers and Scientists
Author: Howard B Rockman
An excellent text for clients to read before meeting with attorneys so they'll understand the fundamentals of patent, copyright, trade secret, trademark, mask work, and unfair competition laws.
This is not a "do-it-yourself" manual but rather a ready reference tool for inventors or creators that will generate maximum efficiencies in obtaining, preserving and enforcing their intellectual property rights. It explains why they need to secure the services of IPR attorneys.
Coverage includes employment contracts, including the ability of engineers to take confidential and secret knowledge to a new job, shop rights and information to help an entrepreneur establish a non-conflicting enterprise when leaving their prior employment.
Sample forms of contracts, contract clauses, and points to consider before signing employment agreements are included.
Coverage of copyright, software protection, and the Digital Millennium Copyright Act (DMCA) as well as the procedural variances in international intellectual property laws and procedures.
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