FROM THE BOOKSHELF

ANDREW RUPPEL, Feature Editor, McIntire School of Commerce, University of Virginia

Decisions, Decisions, Decisions...

by Andrew Ruppel, McIntire School of Commerce, University of Virginia

New decision-making titles appearing this season include cases, case studies, and the use of spreadsheet models as part of their content. Decision science and quantitative methods instructors should find the titles described below as worthy choices for use in their courses.

QUANTITATIVE BUSINESS ANALYSIS CASEBOOK
Bodily, Carraway, Frey, Pfeiffer
Irwin, 1996, 279 pages.

This set of 52 cases (covering 34 enterprises, if you omit the multi-parts and the exercise sets) emphasizes decision analysis topics, with risk issues at the top of the list. The cases, all class-tested and real-company based, are provided in strict alphabetic order and average five pages in length, with the longest (in two parts) at 19 pages. Particularly important to the evaluation of case materials are the companion teaching notes. Good teaching notes help the instructor increase the effectiveness of the learning experience, save preparation time, and often provide different viewpoints on what constitutes a useful managerial answer. One quick indication of the thoroughness of the authors (all Darden faculty) in putting together their excellent instructor's manual is the page-ratio: two pages of notes, on average, for every page of case material. Each case note follows a standard format: case synopsis, teaching objectives, assignment suggestions, author's own analysis, and, guidance on conducting the case class session, including questions to prod the students. The manual also includes a matrix that classifies the cases by functional area (marketing and operations dominate), QM topic (LP is only modestly represented), and whether the case stresses methodology or reinforcement of managerial application (the split is one-third, two-thirds, respectively). The authors provide course outlines for use of the material in masters (and advanced undergraduate) plus executive programs. Also, they offer sample exam formats for nine of the cases. Case data in spreadsheet file formats are available as well.

An expanded version of the material is to be published by Irwin as Text and Cases in Quantitative Business Analysis. It will have 14 chapters organized in sections covering decision analysis and consequence evaluation, forecasting, and optimization. Two appendices will deal with Bayesian revision and spreadsheet modeling. The expanded version would appear to compete with the four-volume series in managerial decision analysis by Messrs. Schliefer and Bell, published by Course Technology last year. The titles by this pair of Harvard B-School authors address separately: Data Analysis, Regression, and Forecasting; Decision Making under Certainty; Decision Making under Uncertainty; and Risk Management. Hence, they offer four volumes of text plus cases, whereas the Darden authors assemble their coverage in one volume, while at the same time offering the cases in a stand-alone paperback. One can learn more about the authors, as well as search the full Darden Case Bibliography, at their Web site: http://www.darden.virginia. edu.

Making Hard Decisions: An Introduction to Decision Analysis (2nd ed.)
Robert Clemen
Duxbury, 1996, 664 pages.

The following comments are based on the author's guide to his revision, which appear on his Web page at http://www.fuqua.duke.e du/~clemen/

The reader is referred there for more detail, including a complete table of contents and a "hyper-preface." (While perusing Clemen's Web pages, interested browsers may wish to scan the pages he and Bob Nau maintain for the recently formed Decision Analysis Society, a subdivision of one of DSI's friendly competitorsțINFORMS.) The principal change from the first edition, says author Clemen, was to incorporate and reflect the material from Ralph Keeney's Value-Focused Thinking book. Seven of the chapters from the first edition have been rewritten or amplified in some way. On average, three case studies appear at the end of each chapter; many of these case studies address decision situations beyond the corporate arena. Three major sections follow the introductory chapter: Modeling Decisions, Modeling Uncertainty, and Modeling Preferences. The book is targeted for advanced undergraduates and masters students in business and in public policy but does not require a mathematical background beyond algebra and probability. Various software packages are covered, e.g., DPL. This is optionally available with the text, in student-edition form; no data disk is offered, however. Spreadsheet modeling is also emphasized. An annotated reading list is provided at the end of the book along with probability tables and answers to selected exercises. Instructor's manual available.

Strategic Decision Making: Multi-objective Decision Making with Spreadsheets.
Craig Kirkwood
Duxbury, In press, 345 pages.

This book will be issued as a paperback, so that it could be used in a course along with another book, such as Robert Clemen's Making Hard Decisions. In focusing on decisions (tactical as well as strategic) with tradeoffs among multiple, competing objectives, the basic approach is to use preference/utility theory, including subjective probabilities. However, the emphasis is not on the theory but on its practical application. Microsoft Excel is used to carry out computations. The book has a total of nine chapters and four appendices. After the introductory chapter, author Kirkwood (at Arizona State) discusses structuring objectives (Ch.2), developing alternatives (Ch.3) and multi-objective value analysis (Ch.4). Chapters 5 and 6 address uncertainty. Chapter 7 (the longest) brings the previous material together in a treatment of multiple objectives and uncertainty. A final chapter presents multi-attribute preference theory at the level of Keeney and Raiffa's Decisions with Multiple Objectives. This enables the book to be used for more advanced discussions, but it is not necessary to pursue this chapter in making practical use of the methods in the book. There is also a stand-alone chapter on resource allocation, which combines preference analysis methods with optimization using Microsoft Excel Solver. End-of-book appendices deal with a case study of consulting engagement, scenario development, probability elicitation, and interdependent uncertainties.

The only prerequisite for much of the book is elementary algebra. The primary audience is advanced undergraduate or masters students in business or engineering. Most of the examples and exercises are business-oriented, but with a technology component. (An instructor's manual, with answers to all exercises, will be available.) The book is also suitable for self-study. Exercises and examples address the types of decision problems that MBA graduates or engineers are likely to see at early to mid-point stages in their careers. However, the book takes a theory-based approach so that the methods will continue to be useful to readers throughout their careers. Author Kirkwood feels that with the flattening of contemporary organizations, more of their members will be engaging in decision making, particularly that involving trade-offs.

Also Forthcoming....

Multiple Objective Decision Making
Mollaghasemi and Pet-Edwards
IEEE Computer Society
Scheduled for June 1996.

This brief volume recaps various methods, available software, and gives application examples. It would appear to be more useful as technical briefing material than as a course text.