DSS Insight Cases

The DSS Insight features that begin each chapter are mini-cases that describe actual decision situations and the DSSs devised to help decision makers in those situations. These cases cut across a diverse collection of organizations, industries, functional areas of management, and decision needs. They have been selected to help students develop a more professional sense of decision making and its challenges. They also help students develop a practical sense of computer-based decision support, which should benefit their own hands-on DSS development efforts.

Each case illustrates important concepts discussed in the chapter that it introduces. Questions at the end of a chapter give students a chance to apply what they have learned in the chapter to an analysis of the case. We have found that these questions make an effective basis for class discussions about the subject matter just covered. We have also found that the case content can be usefully referenced during the lecture coverage of subsequent chapters to help illustrate new concepts as they are introduced.

Specifically, DSS Insight cases might be used as follows:

1. Before lecturing on the chapter, give a thumbnail sketch of what the case is about.
2. Lecture on the chapter's content.
3. In preparation for discussion of the case, each student should read it carefully, put himself/herself in the position of a decision maker or DSS developer, note key issues they faced, and note how they were (or could have been) resolved. Each student should be prepared to respond to the case questions at the end of the chapter.
4. Discuss the case and responses to selected questions. For the first one or two chapters, discussions are led by the instructor. Each subsequent case discussion is led by a student or small group of students (or by the instructor, if desired). The discussion leader may pose some questions other than those in the textbook.
5. In lecturing on the chapter that follows, refer back to the most recent case(s) for examples that illustrate new concepts being introduced.

Benefits of actively using DSS Insight cases include generating higher student involvement in learning, promoting clear thinking and insights about DSS-related concepts introduced in the chapter, encouraging the application and synthesis of what has been learned, and helping to exercise and improve student communication skills.

Unlike traditional case study instruction, analysis of a DSS Insights case is not trying to find proper recommendations for (or solutions to) particular decision problems. Instead, it aims to help students appreciate the DSS role in yielding such recommendations or solutions. It is possible to combine these two aims into a different kind of case consisting of a traditional case narrative, except that some facts and methods normally described there are accessible via a DSS provided to the students. Rather than having everything laid out neatly in a written narrative, students must gather, store, organize, and analyze relevant knowledge with the DSS. The DSS could range from a browser gateway into the World Wide Web to an IFPS-based system. In any case, it would be the students' partner in knowledge acquisition and derivation. Such a case may be devised as a continuum rather than a snapshot (as in the traditional case method). That is, new knowledge and problems relevant to the decision can become available over the course of a quarter or semester. The net result could be an added touch of realism for the traditional case method. This approach may work well not only in a DSS or knowledge management course, but also in a subsequent business capstone course.

Larger DSS Cases

Larger cases are provided at the ends of Parts I-IV. These are intended to help students appreciate how concepts introduced in prior chapters can be applied to real-world situations. The first of these is a traditional case. Students can use the classroom to present, justify, and discuss their answers to the case questions. This exercise helps them tie together a variety of important concepts introduced in the first four chapters.

The other three cases also help tie together concepts, but in the context of students developing their own DSSs. In effect, these are customized cases that evolve as students work on their projects. Students can use the classroom to relay and discuss their experiences in building DSSs. The textbook's case descriptions pose a series of guidelines for organizing students' consideration of their own customized DSS development cases as they unfold. The case descriptions also present samples of what other students have done in creating their own customized cases.

We suggest that students be required to submit a written proposal outlining what they intend to accomplish in their projects. An instructor can provide written feedback on the proposal (e.g., indicating that it needs to be beefed up, it is too ambitious in places, that certain parts deserve particular emphasis). If there is sufficient class time, students may be asked to give brief presentations about their proposed projects. What students learn by listening to others' proposals may help them to do better with their own development projects.

The Part II case shows some sample proposals and gives a set of issues students may consider in preparing their proposals. The Part III case shows some samples of project documentation that is submitted to the instructor at the end of the course. Appendix G provides related details. It also summarizes the kinds of topics that could be addressed in an interim report. The Part IV case is similar to that of Part III, except it deals with artificially intelligent decision support systems. Appendix H provides related details. We recommend that in addition to documenting their projects, students be allocated some class time to demonstrate the DSSs they have developed. Samples appear in the Decision Suppotr System Case Demonstration Video.

We have found that a good approach to identifying applications for project development is to let students choose their own (e.g., based on their own interests and experiences). This seems to enhance their motivation. We have also found that projects can be successful either as individual student projects or as group projects. For a class size of 10 or fewer, individual projects are workable. For larger classes, however, group projects tend to be more appropriate in order to keep the total number of projects in the 6-10 range. Group size in the 2-4 range is generally appropriate. We are inclined to let students form their own groups based on common backgrounds and application interests. A group's grade for its work is attributed to each of its members, or alternatively it may be influenced by group members' confidential assessments of the degree of contribution by each of the other members.