Decision Support Systems For Business Intelligence
    by Vicki L. Sauter


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. 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 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 do 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 has that knowledge about decision making been translated into specific DSS needs; (c) what forms of business intelligence needs are associated with the problem or the environment; (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 decision support systems 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 decision support systems 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.


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 over-focus 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 Cold Fusion. Most IS 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 MIS. Someday, these options will be feasible and will be 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, however, 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 needed 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. 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 decision support systems. 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 tradeoffs 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 decision support systems 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 applications descriptions, war stories and advice from practitioners. Still others provide a link to a variety of instructors (both academic and non-academic) on the topic.

I strived to provide support for the class from a variety of different perspectives. You can see the information at Further, there is information at the end of every chapter about the kinds of materials found in support of that chapter; 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

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



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 lead 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 Hofer, 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 and 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 Susanna Steitz-Filler editor of the Second Edition. They each believed in this project long before I did, continued to have faith in it when mine wore thin, and were willing to stand by decisions because they believed them to be right. I could not have produced this book without them. In addition, I want to thank my style editors, Elisa Adams and XXXX, 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), whose who made me laugh when I really needed it, and whose courage made me appreciate everything more.


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