REVIEWS OF SOFTWARE AND BOOKS

APPENDIX

INFORMATION ON THE DIFFERENT SOFTWARE PACKAGES CONTAINED IN THIS REVIEW MAY BE OBTAINED AS FOLLOWS:

1. ISP: Lincoln Systems Corporation

P. O. Box 391 Westford, MA 01886 (617) 692-3910

2. AUTOCAST: Levenbach Associates Managerial Computing Training & Support 103 Washington St., Suite 348 Morristown, NJ 07960

3. SMOOTH: True BASIC, Inc. Hanover, New Hampshire 03755

4.4CAST/2: Levenbach Associates

5. FORECAST MASTER: Scientific Systems

54 Cambridge Park Drive Cambridge, MA 02140 (617) 661-6364

6. PC SCA Statistical System: Scientific Computing Associates

P.O. Box 625 DeKalb, Illinois 60115

7. WISARD: SHADE Information Systems Inc. P.O. Box 19730 Green Bay, WI 54307-9730 (414) 432-6700

8. EXPERT CHOICE: Decision Support Software, Inc. 1300 Vincent Place McLean, Virginia 22101 (703) 442-7900 (Mary Ann Selly)

BOOK REVIEW THE MODERN FORECASTER, THE FORECASTING PROCESS

THROUGH DATA ANALYSIS

Reviewed by Essam Mahmoud

University of North Texas

The Modem Forecaster, The Forecasting Process Through Data Analysis.

By Hans Levenbach and James P. Cleary. (New York: Van Nostrand Reinhold Company, Inc., 1984,

537pp., $36.95, subject to change in 1988).

As the sub-title to The Modern Forecaster suggests, the focus of this book is on the process of forecasting and on the analysis of data during that process. The authors' approach to forecasting is managerially oriented, with an emphasis on the implementation of forecasting techniques and how they might be used to assist decision-making. They argue that "the success of a forecasting organization depends upon the extent to which traditional management philosophies and practices ,are applied to an unconventional business discipline" (p. 485). Hence they explain how to develop a management plan for forecasting with objectives and performance measurement. The emphasis is on the forecaster documenting his/her work at each stage of

the forecasting process to provide details of steps taken and assumptions made. This is a useful point which is not always made explicit. Levenbach and Cleary stress the documentation of the forecasting process from the standpoint of forecasting a s

a decision support tool: "the users of the forecast will... appreciate the additional documentation. Instead of simply having a set of numbers, they will have the kind of information they need to assist them in making decisions about their area of responsibility" (p. 39). There are also several references made concerning the presentation of forecasts to the users, empha- sizing that the forecaster's job does not end with the production of forecasts. In the discussion of forecasting tracking (p. 245), Levenbach and Cleary stress ongoing communication with management. They are clearly concerned with the practical aspects ,and the implementation of forecasting and not only the methodology. They write "the larger a firm, the more likely it is that a communications breakdown will occur and that the forecaster will not be aware of marketing decisions or other

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internal policy decisions by various field and staff groups" (p. 247).

This emphasis on practical implementation of forecasting is not surprising given the authors' backgrounds: Hans Leven- bach was Division Manager of the Analytical Support Center for AT&T, James Cleary is Division Controller of Marketing/ Sales for AT&T Information Systems. Their intention is to present different forecasting techniques in the context of the data available and the uses to which the techniques might be put, thus reducing the possibility of forecasting by mere mechanistic execution of computer programs. Levenbach and Cleary pay particular attention to software considerations for forecasting and also warn the reader to be wary of "automatic" forecasting methods and software programs.

The Modern Forecaster is a valuable text for continuing education programs in forecasting as well as graduate market- ing and management science courses in forecasting. The au- thors' style is lucid; the chapters are relatively short which permits readers to build knowledge about forecasting in a piecemeal fashion at the desired pace. The book reflects current views among forecasting researchers and therfore the title, "The Modem Forecaster," is indeed appropriate. For example, the authors stress the combination of forecasting techniques: "a basic principle is to utilize more than one projection technique.., the forecaster can be reasonably sure of avoiding biases which are inherent in any one projection technique or its use" (p. 35). They also acknowledge that "the degree of forecast precision for the projection techniques is not necessarily a direct function of the degree of sophistication" (p. 35).

171eModern Forecaster is third in a series of three books on forecasting which includes The Beginning Forecaster and The Professional Forecaster. Much reference is made in The Modem Forecaster to topics, details and examples covered in the other two texts. The authors omit, however, an explanation of exactly how the three texts relate to one another. This would have been helpful, especially to the reader who is not familiar with the other texts.

The authors' presentation of forecasting as a process is a valuable notion. There are several processes discussed, for example, in addition to a general process of how to forecast, the authors include a process of how to manage the function of forecasting to increase the likelihood of good forecasting performance, a procedure for making a turning point analysis, the process for analyzing residuals, etc. While the "process theme" is well developed, in a teaching situation it will require considerable interpretation by the instructor. For example, at the beginning of Chapter 4, the authors write "this chapter deals with the final phase of the forecasting process." The description of that final phase, however, does not fit with the process described on p. 8 when the process is first introduced. This could be a little confusing, especially for undergraduate students who often prefer clearly "packaged" texts. Neverthe- less the book is much more likely to be used as a graduate-level text book or as a supplementary reference book.

Furthermore, on the whole, The Modern Forecaster is well- organized and has summaries and "useful reading" sugges- tions at the ends of each chapter. There are also checklists at the ends of many chapters, for example: "Multiple Regression Checklist," "Forecasting Tracking Checklist," "Demand Analysis Checklist" and "ARIMA Forecasting Checklist."

Suck checklists could be most helpful in implementing fore- casting techniques. From a pedagogical viewpoint, Appendix B contains a number of data series which can be used with the twelve computer workshops" which are included at the ends of several chapters. These provide students with hands-on expe- rience and, like the book as a whole, are focused on understand- ing and interpreting data. Levenbach and Cleary explain that their concern in the workshops is with the reasoning behind the analysis rather than with the "best" forecasting model. This reasoning appears to reflect the philosophy of the entire book. The last chapter of each section of the text also includes "problems" to be solved.

The text as a whole, and, in particular, Chapters 5-7, make a much needed contribution to the forecasting literature in the explanation of data analysis. Levenbach and Cleary recognize that good forecasting depends on good data. They propose that data analysis can be applied not only in developing the forecast but also can be used very effectively in presenting the results of a study to management. Levenbach and Cleary deal with data quality, graphical displays of data, and the analysis of the distribution of data, the latter being an important step often overlooked in forecasting.

In an introductory text in forecasting, it is noteworthy that the authors give considerable coverage to robust techniques. For example, in the discussion of data analysis, they describe robust estimates of location such as the trimmed mean and the Huber M - estimator. In Chapter 16 they discuss a robust alternative for analyzing the demand for residential extension telephones.

The forecasting methods explained in The Modern Fore- caster are grouped as follows. First is an introductory meth- odological section covering exponential smoothing models, seasonal adjustment and cycle forecasting, and regression models. This is followed by detailed sections on the econom- etric approach to forecasting and on the Box-Jenkins approach to forecasting. The discussion of econometric methods focuses on the demand analysis process and the estimation of demand elasticities. The organization of the chapters and of the mate- rial in each chapter is always presented in the following format: the reason for selecting a method, how to use the method, what the problems in using a method are, and ways to cope with them. For example, in Chapters 10 and 21 respectively, the authors ask why a forecaster might consider building regres- sion models and ARIMA (autoregressive integrated moving average) models. Also, they write: "forecasters must be aware of the pitfalls and advantages of any quantitative forecasting method before applying it in practice" (p. 280).

Levenhach and Cleary enhance the descriptions of the methods with detailed examples. One illustrative data set, "the telecommunicatiorrs example," is introduced in Chapter I and is used throughout the book. Other detailed examples used include one for the pooling of cross-sectional and time-series data. Expanded examples for modeling univariate ARIMA time series deal with main telephone gain data, U.S. housing starts, the Federal Reserve Board index of industrial produc- tion, and nonfarm employment.

To conclude, The Modern Forecaster is a very practical introductory text in forecasting. The positioning of the text, with its emphases on process, data analysis, hands-on leaming, and its excellent use of illustrations, recommends it to practi- tioners as well as students. For those who are seeking a

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forecasting text that is somewhat different from the traditional text, The Modern Forecaster may be an ideal choice.

Essam Mahmoud BCIS Department University of North Texas

REFERENCES

Levenbach, H., and J. P. Cleary. 1981. Tile Beginning Forecaster. Belmont, CA: Lifetime Learning Publications.

Cleary, J. P., and H. Levenbach. 1982. The Professional Forecaster. Belmont, CA: Lifetime Learning Publications.

BOOK REVIEW THE HANDBOOK OF FORECASTING:

A MANAGER'S GUIDE

Reviewed by Gillian Rice

The Handbook of Forecasting A Manager's Guide, Second Edition.

Edited by Spyros Makridakis and Steven C. Wheelwright,

(New York: John Wiley & Sons, Inc., 1987, 638 pp, $58.50).

The Handbook of Forecasting has four themes. These are: forecasting applications in organizations; methodological developments; illustrative case examples; and a focus on current issues in forecasting. Combined in one text, these themes contribute to a comprehensive discussion of forecast- ing. The editors, Spyros Makridakis and Steven Wheelwright have included chapters written by some of the foremost au- thorities in the discipline, for example: Scott Armstrong, Robert Fildes, Everette Gardner, Hans Levenbach, Steven McNees, and Robert Winkler.

The emphasis in The Handbook of Forecasting is on how to put forecasting into practice. Makridakis writes "to be useful, forecasting must improve planning, strategy, or decision making" (p. 611). His opinion reflects the primary message of the Handbook. Hence, the coverage on forecasting applica- tions in organizations is extensive. The first several chapters discuss managerial needs for forecasting for various functions such as sales, operations planning and control, capacity plan- ning, financial decisions, and strategic planning. Writers explain issues of organizational design and how to integrate forecasting and decision making. In noting that this area of forecasting has been relatively neglected, Fildes comments that "the aspect that has been best researched is the forecasting methods themselves" (p. 51). Nevertheless, these methods have not been widely adopted and according to Fildes, "...the slow adoption of quantitative forecasting techniques can per- haps be explained only by reference to an often ill-developed MIS" (p. 153). Various contributors to the text put forward nu- merous suggestions as to how to remedy this situation. For example, Armstrong argues that "rather than giving extensive concem to the forecasts, the manager should concentrate on the

forecasting process" (p. 597). Mabert and Showalter suggest that a forecasting system "should be tailored to the specific setting and linked into other organizational activities like marketing plans and the data collection systems" (p. 490). Mahmoud emphasizes the evaluation of forecasts which ap- pears to be one of the most problematic areas in forecasting implementation. Nevertheless, he suggests that the difficulties can be minimized with "understanding of the state of the art of forecasting techniques, awareness of the most important find- ings, the availability of different accuracy measures and their uses, the availability of reliable data bases...and the availability of good computer forecasting systems" (p. 520). The Hand- book of Forecasting makes a valuable contribution to a manager's knowledge of such issues. For example, with respect to data bases, Davidson and Prusak provide advice on selecting and using external data sources and forecasting services to support a forecasting strategy.

The second theme of The Handbook of Forecasting deals with methodological developments. Forecasting methods are not treated extensively, however, and only seventeen percent of the text is devoted explicitly to methodology. Six chapters deal with smoothing methods, ARIMA (autoregressive inte- grated moving average) models, decomposition methods, econometric methods, judgmental and Bayesian forecasting, and Lewandowski's method. The emphasis throughout is on practice rather than theory. For example, Gardner describes his chapter as a "working reference on exponential smooth- ing." The title of Pack's chapter is: "A practical overview of ARIMA models for time series forecasting." It is surprising that such a comprehensive text omits any detailed coverage of combining forecasting techniques when research has shown that combining separate forecasts can improve forecast accu- racy. Yet, Lewandowski in Chapter 16 presents an integrated approach to medium- and long-term sales forecasting which involves the combination of extrapolative and explicative variables into a single model. The model, known as "the marketing mix system" represents a pioneering effort to de- velop "a realistic system that can be used by practicing manag-

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