Review of selected software for sales forecasting and decision support systems

Reviews of Software and Books

REVIEW OF SELECTED SOFTWARE FOR SALES FORECASTING AND DECISION SUPPORT SYSTEMS

Essam Mahmoud University of North Texas

As a supplement to the special section on sales forecasting and decision support systems (DSS), we include some infor- marion and reviews about selected software for sales forecasting and DSS. First, we discuss the eight software packages we received for evaluation in the special section. Next, we evalu- ate the software in the light of criteria used by practitioners when selecting software for forecasting purposes. It should be clear that we are not endorsing or recommending any particular package. Rather, we are providing a review which might serve as the basis for an approach by which users might select software according to their own needs and resources.

1. Interactive Statistical Programs

The first package, Interactive Statistical Programs (ISP) is an ideal teaching tool to supplement other marketing software. ISP has two key characteristics in this context. Firstly, it was designed specifically to remove the computational burden of statistics from the users in order to enable them to concentrate on the statistical and forecasting concepts. Thus it is intended to provide students with a better understanding and apprecia- tion of statistical modeling, promoting the idea of statistics as a way of understanding and dealing with uncertainty instead of treating it as a black box. Secondly, ISP contains a section on forecasting and several teaching modules on forecasting which include time series, decomposition of a time series, exponential smoothing, linear regression, inferences in linear regression, autocorrelation, transformations and nonlinear relation- ships, and multiple regression.

ISP is available with English and French language commands. It is menu-driven, interactive and very "friendly." Such features make it attractive to marketing students who often approach concepts such as sales forecasting and modeling with apprehension of computational aspects and statistical con-

�9 1988, Academy of Marketing Science Journal of the Academy of Marketing Science Fall, 1988, Vol. 16, No. 3&4, 104-112 0092-0703&4188/1603-4-0104 $2.00

cepts. In developing ISP, the authors, Spyros Makridakis and Robert Winkler, have attempted to exploit the tremendous capabilities provided by today's computers to make forecasting and statistical concepts interesting and more understand- able to students. ISP includes examples and sets of data, chosen specifically to increase students' involvement and interest in the material to be learned. Certainly, some students are becom- ing more aware of the uncertainties in today's world and oftbe fact that some knowledge of forecasting and statistics can help them better understand and deal with these uncertainties. ISP would also be a useful addition to the marketing professor's software library because of the package's value in analyzing marketing research data. Students can learn about sampling, data handling, data transformations, plotting, and cross-tabulation, for example. A number of statistics and non-parametric statistics are included. Students can input their own data interactively or read it from different ASCII or Lotus files. ISP checks for appropriate inputs and provides the users with a message if such inputs are wrong. The extensive and successful classroom testing of ISP since 1981 contributes to the positive appeal of this "student-friendly" software for sales forecasting and statistical analysis.

2. AUTOCAST

AUTOCASTis a forecasting system forexponential smoothing methods. It is the outcome of extensive research by the author of the system, Everette S. Gardner, Jr.. Exponential smoothing has become widely used in practice, and is a valuable tool for short-term sales forecasting and inventory control. Empirical studies demonstrate that smoothing techniques are quite accurate compared with more complex forecasting methods. Among these studies is Makridakis et al. (1982) for 1001 time series. Based on Gardner's work in the Journal of Forecasting (1985), Management Science (1985), and The Handbook of Forecasting (1987) AUTOCAST was developed to address three distinct types of models: nonsea- sonal models, additive seasonal models, and multiplicative seasonal models. Each of the three models deals with different cases of parameter estimation: constant level, linear trend and nonlinear trend. Gardner's introduction of the damped trend to

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be used for longer-range forecasting has been shown to be a good method. AUTOCAST enables the users to input time series easily and to edit a particular series. The system analyses the time series and determines its structure and selects the appropriate model automatically. Thus, all smoothing parameters are selected by an automatic search algorithm to minimize either the mean absolute deviation or the mean squared error. However, the system enables users to preselect their own parameters if they would like to do so. The system also allows adjustment of forecasts when necessary, for example, in re- sponse to changing market conditions, and also permits the adjustment of the value of outliers if needed. AUTOCAST provides the opportunity to update all model parameters on a period by period basis. Data can be analyzed graphically and checking the autocorrelation of the residuals is possible also in this way. The system is menu driven and therefore easy to use. The user only presses certain functional keys. For example, AUTOCAST utility "F6" provides the automatic forecast and identifies the proper model.

The system is supported with an easy manual which includes detailed examples. AUTOCAST runs on the IBM PC/ XT/AT, all models of COMPAQ computers and most of the IBM PC compatibles, with a minimum of 256K in RAM, DOS 2.0 or higher, and two disk drives are required. Either a color or a black and white graphics monitor can be used.

3. SMOOTH

SMOOTH is software developed by Victor McGee to deal with smoothing techniques for forecasting. The system con- sists of 15 models based on the work of Pegels (1969) and Gardner (1985). SMOOTH includes damped trend and Robert Brown's linear trend models. Like AUTOCAST, SMOOTH is a friendly system and is a menu-driven package. It enables the user to either enter a file through the option K (KEYBOARD) within the DATA Menu or through an existing file. The data entry process is very easy and is well defined before data input begins. The system also allows the identification of whether it is monthly, annual, quarterly or other non-seasonal data. The user can either specify the parameters or let the system search for the optimal parameters that minimize the mean squared error (MSE), and then can observe the process of minimization and the optimal parameters on the screen. SMOOTH'S option utilities allow the selection of the data points to which the model can be fitted and the number of forecasts ahead that need to be generated. The graphical capabilities of SMOOTH are good. They show the actual time series alone, the forecasted values, the time series and the forecast together, and the error. SMOOTH provides an output summary or detailed output as well as specific outputs through the output menu. Hence, there are opportunities to compare models selected and tested. The system writes all the results on a file and provides the output in comparative form which enables the user to judge which model is the best.

SMOOTH is an extremely useful package for teaching forecasting and exponential smoothing. A feature that contributes to its pedagogical value is that it provides useful information about model structure and the trend and seasonal factors incorporated in the time series. Another pragmatic feature is that the system calculates eight different accuracy measures for each model. This indeed enables users to judge carefully the accuracy of a model given the advantages and disadvantages of

some of the accuracy measures. SMOOTH also provides the user with an autocorrelation function. Nevertheless, one can rely on the graph of the error term and observe the normality of the error term.

The system's help utilities are advantageous, permitting a user to leam about the model to be used. SMOOTH also allows the user to transform the time series by either adding, subtract- ing or multiplying a constant or using an algorithm, etc.

SMOOTH runs on IBM PCs and compatibles.

4. 4CAST/2

4CAST/2 is a forecasting system which can read up to seventeen variables and is designed to provide the users with the opportunity to use a variety of forecasting techniques. These are moving averages, exponential smoothing (single exponential, double exponential, Holt-Winters, adaptive smoothing, damped trend smoothing), decomposition method, turning point analysis, curve fitting, and linear regression. The system also provides the users with the capabilities of using autocorrelation analysis (simple autocorrelation, cross corre- lation and partial autocorelation).

Users can read 16 data files and can work with them one after the other during a given session. The system is menu- driven and like the other software discussed is user friendly. The system's main functions are file manipulation, forecast, graphics, review and series. For example, the forecast sub- menu allows the user to select the forecasting model required. Very specific steps must be followed in order to identify a forecast and the system recognizes the variable(s) to he forecasted. Users must choose the type of procedure to be applied for a particular variable or time series. The system then permits users to choose the parameters or the system will determine them. Graphical capabilities enable users to plot time series and change the scale of their graphs as well as plot two variables together. Accuracy measures included are mean error, mean absolute error, menu absolute percentage error, mean squared error, and Theil's U statistic. However, certain steps are required if the users wish to see the calculation of a particular forecasting accuracy measures(s). The system is available for IBM PC, XT/AT or close compatibles. Users are advised to do practice sessions in order to become familiar with the system. The user may obtain more familiarity by using the manual's examples or The Modem Forecaster by Hans Leven- bach and James P. Cleary (1984).

5. FORECAST MASTER

FORECAST MASTER is a multivariate time series forecasting system consisting of exponential smoothing (simple, Holt's, adaptive, and Winter's smoothing models), Box-Jen- kins, Bayesian Vector Autoregression, curve fitting and State Space forecasting. The system is menu-driven with the functions summarized making it easy to select a particular forecasting method or any other functions such as a graph or data editing. FORECAST MASTER enables users to read data files from a different environment and create new files. Users must define the variables and then define the forecasting procedure required. The system can read up to 15 variables. Users define the time series and generate the forecast by answering certain questions displayed on the screen.

It is possible to check the validity of the model by examining the autocorrelation function and by applying model diagnos-

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tics such as residual analysis, the autocorrelation of the residual, and summary statistics such as the mean, standard deviation, R, and Durbin-Watson statistic. FORECAST MASTER also provides some help through diagnostic analysis to identify stationafity.

FORECAST MASTER does require effort from the user at the beginning to understand the steps that must be followed. The system uses mostly Basic language concepts and the user should he familiar with this language's commands.

FORECAST MASTER requires an IBM PC, XT, or AT or compatible machine with at least 512 K of memory. The Intel 8087 or 80287 numerical data processor chip although not required is highly recommended.

6. PC SC Statistical System

The PC SCA Statistical System is a statistical system that provides a wide range of statistical inferences (analysis) such as: plots and histograms, regression analysis, analysis of vari- ance, cross tabulation, nonparametric statistics, and forecasting and time series analysis (exponential smoothing: single, double, Holt's, Winter's; and Box-Jenkins). The system is suitable for both students and professionals. The system ranges from nine to nineteen diskettes depending on the features and the type of users. The necessary hardware is 512 KB RAM or more and a hard disk.

Users are required to read the supplementary documentation for the PC SCA Statistical System carefully before run- ning the system in order to be familiar with all the commands. Users must follow particular instructions as well as being familiar with many commands. The system is available for mainframe computers with the instructions for the mainframe being similar to those for the PC version. There are three manuals available: a reference manual for fundamental capabilities, a reference manual for forecasting and time series analysis, and supplemental documentation for the PC SCA system. Like ISP, this system is suitable for an educational environment. Students are able to understand the methodology of implementing forecasting, stage by stage. Successful use of the system necessitates users being familiar with each forecasting method and the manual's instructions.

7. WISARD

WISARD is a menu-driven system which allows the user to select data entry, a forecast procedure, printing, graphics, or a batch process. For example, data entry would allow the user to access another specific menu, "Data Entry Menu," and then choose to edit an existing series or group of series, create a new one or group or delete series. WISARD uses a composite model based on linear regression, single exponential smoothing and double exponential smoothing to provide forecast values. It allows users to exchange data with Lotus 1-2-3, to apply forecasting in a simple fashion. The WISARD forecasting system requires an IBM PC, XT or AT or a true compatible operating under PC or MS-DOS, and a minimum of 256K of memory and one 360K, 5 1/4" floppy diskette drive. WISARD is also available for the HP-150 touch screen personal computer operating under MS-DOS.

8. EXPERT CHOICE

E X P E R T CHOICE is a useful tool for marketing managers and marketing researchers involved in a wide variety of deci-

sion tasks (strategic planning, marketing, new product devel- opment, product life cycle analysis, capital acquisitions, investment analysis and time allocation) in various public and private sector organizations. Decision makers can also apply EXPERT CHOICE to analyze a :sales forecast, especially a long term forecast, and its linkage with both investment and capital acquisitions, for example. Hence, EXPERT CHOICE is not a forecasting package which allows a user to select different forecasting methods. Instead it is a valuable supplement to other forecasting software. The forecast values must be input to EXPERT CHOICE. The system also allows users to incorporate information from spreadsheet models or word processing files. With EXPERT CHOICE marketers can test different decision alternatives and provide insights as to which alternative would be most appropriate according to different factors related to the problem. In other words, the EXPERT CHOICEmodel organizes the various factors of aproblem into an upside-down tree structure (DSS, Inc. 1986). The tree is upside-down because it branches downward from the goal. Intermediate levels represent the decision criteria and at the bottom of the tree are the "leaves" which represent the altema- tives of choice. EXPERT CHOICE is based on theory developed by one of the system designers, Thomas L. Saaty.

EXPERT CHOICE enables users to compare and combine cert,-dn factors to obtain priorities for the alternatives at the bottom of the tree. The system presents decision makers with a meaningful (ratio scale) measure of the differences between the alternatives.

Decision makers can use the EXPERT CHOICE system to build their own models which are most suitable to their needs. For example, a manager could design a forecasting model incorporating the factors related to the forecast such as an increase in price, a special event, promotions, advertising, market share, economic conditions (interest rate, consumer price index, etc.), seasonal factors and so on. Modifying the EXPERT CHOICE system to meet one's own needs is not simple, however, and requires very careful reading of the manual. Nevertheless, the ability to modify the system is valuable for the forecasting function. Using EXPERT CHOICE, marketing managers can combine the different sales forecasts of independent individuals or can combine quantitative and qualitative forecasts.

EXPERT CHOICE is available for the IBM PC, XT or AT with DOS 2.1 or greater, 320kb memory, two double-sided disk drives, or one hard disk, and graphics adaptor.

Choice Criteria for Forecasting Software

Forecast software users face the problem of how to select the proper software to match their needs. The literature provides some guidelines for the evaluation and selection of software for DSS. The most relevant literature to the topic of this review is that concerning the selection of statistical and forecasting packages (for example, see Francis and Heiberger 1975, Muller 1980, Levitan 1981, Mahmoud 1983, Keen and Woodm an 1984). In particular, Mahmoud (1983) and Malhotra et al. (1987) indicate some criteria that users might consider when choosing software. Mahmoud (1987a) surveyed the forecasting practices in 1986 of a random sample of 200 of the FORTUNE 500 firms. In their responses to a mail question- naire, managers indicated their perceptions of the relative

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TABLE 1 Rank of Criteria Considered in Selecting Forecasting Software

Criteria Mean score ~ # of Responses

1. Accuracy 4.3 67

2. Compatibility with existing software 4.2 67

3. Data handling, ease of data entry 4.1 67

4. Ease of output interpretation 3.9 66

5. Graphical capabilities 3.8 60

6. Vendor reputation 3.7 59

7. Documentation 3.7 59

8. Vendor maintenance 3.5 57

9. Ability to identify data patterns 3.5 52

10. Cost 3.2 49

11. Multiple modes 3.2 40

12. Testing opportunities 3.1 43

13. Combining forecasts 2.5 27

14. Portability 2.1 23

~Perceived importance of each criterion w~ts measured on a five point scale where "one" represented "not important at all" and "five" represented "very important."

importance of a number of choice criteria for forecasting software. The results are shown in Table 1. Accuracy, compatibility, and data handling are perceived to be the three most important criteria. Cost, testing opportunity, and combining forecasts appear to be less importanl. We now discuss the software reviewed above in terms of some of the criteria listed in Table 1.

One of the most important criteria is accuracy. In this context, it is advisable to select a system that is well tested and whichprovides information about the models used and how the forecast is determined. Further desirable information includes details conceming numerical stability, the way in which the optimal parameters are delermined ,and the ability of the system to identify outliers. The accuracy can be judged by evaluating the approaches used to obtain forecasts. For ex- ,ample, ISP provides information about the torecast models :end the approach followed so users can check forecasts manually to test the accuracy of the system. Based on the information given by the software, the same manual checking procedure would be possible with SMOOTH, PC SCA, and AUTOCAST. However, 4CAST/2, FORECAST MASTER and W1SARD provide users with less detail about the model used. It is therefore more difficult to test the accuracy of these software packages.

Also concerning the accuracy criterion, it is preferable to use a sales forecasting system which includes several different accuracy measures. Empirical research has revealed that certain accuracy meztsures are more suitable for certain appfica- tions (Makridakis et al. 1983, Mahrnoud 1987b). SMOOTH h;ts advantages in this context as it includes eight accuracy measures: the other software reviewed provides between three and six accuracy measures.

Having software that is compatible with other software, (the criterion ranked second in Table 1), can save a user consider- able time. Such a feature provides the opportunity of reading files created by different systems ,and not having to reenter data. For example, ISP, AUTOCAST, 4CAST/2, SMOOTH, FORECAST MASTER and EXPERT CHOICE can read from different environments such as Lotus 1-2-3 and from ASCII files. However, it is also valuable if the system can both read from and write to different environments so that the results of sales Iorecasts may be incorporated easily in the marketing executive's final report developed using a spreadsheet package. AUTOCAST and 4CAST/2 are being updated to include this feature.

As can be seen from the preceding comments about compatibility, the latter is closely linked with data handling capabilities and the ease of data entry, the third criterion in Table 1.

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Forecasting efficiency can certainly be improved with the use of software that can read from other software and databases. Also, some systems, such as ISP, AUTOCAST, FORECAST MASTER and PC SCA, can alert users to the presence of oufliers so that the user can then check whether these data points are due to misentry or unusual events. Other systems may provide such information implicitly through autocorrelation or graphical analyses.

Graphical capabilities in the software are useful in testing forecasting models' performance at both the fitted and forecasted phases. Software which shows the actual data compared with the fitted and forecasted models' performance are the most valuable. ISP, 4CAST/2, SMOOTH, AUTOCAST, PC SCA, and FORECAST MASTER have graphical capabilities. Some systems are more developed than others in terms of high resolution graphics. For example, SMOOTH provides the users with better graphical capabilities in the four graphs it illustrates simultaneously on one screen (the actual time series, the forecast, the time series and the forecast together, and the error, separately).

A significant factor in forecasting success is the ability to identify the data pattern of the original series either by using a plotting function or statistical inferences such as decomposing the time series. The forecaster can then observe the most important components of a series and is therefore in a position to select the best model. All the software reviewed, except EXPERT CHOICE, have the feature to enable a forecaster to follow this procedure. Note, however, that while EXPERT CHOICE contains forecasting capabilities, it does not purport to be a forecasting software package, per se.

Documentation and help utilities are also important software choice criteria. Some systems are much easier to use because of the nature of the accompanying documentation and the simplicity of the instructions and/or because of an on- screen help utility. Other systems require a careful reading of the manual before the software can be used. Systems that are easy to use without more than a cursory look at the manual are ISP, SMOOTH, AUTOCAST and WISARD. Systems that necessitate users studying the manual first include 4CAST/2, PC SCA, FORECAST MASTER, and EXPERT CHOICE.

The criterion of multiple modes (batch, interactive) is seen as relatively less important by the survey respondents (Mahmoud, 1987a; see also Table 1) and has a mean score of 3.2. This feature could be especially useful, however, in cases where a manager needs to forecast the sales of a group of products with similar trend patterns. Batch processing would considerably improve the efficiency of completing such a task. AUTOCAST has this capability.

None of the software reviewed contains an integral feature for combining forecasts. While it is possible to combine forecasts using EXPERT CHOICE, it is necessary to input the forecasts separately; thus EXPERT CHOICE is an aid to a forecasting package in the marketing decision support system. At present, however, it appears that managers are not very concerned about the capability of software to perform the function of combining forecasts. In the survey (Mahmoud 1987a), the choice criterion "combining forecasts" received a mean importance score of only 2.5 (see Table 1). Nevertheless, this may change in the near future with more managers de-

manding the function and more forecasting software providing it. Studies reported in the literature have shown that combining forecasts leads to improved forecasting accuracy, a goal of all forecasters (for example, see Makridakis et al. 1983, Makri- dakis and Winkler 1983, Mahmoud 1984).

Upon reading this review and analysis of forecasting software and choice criteria, it should be noted that the relative importance of a particular criterion will vary from one organization to another. Thus, for example, some criteria may be weighted differently depending on the knowledge of the user and the level of technology currently available.

REFERENCES

Francis, T. and R. M, Hieberger. ! 975. "The Evolution of Statistical Program Packages: The Beginning." in Proceedings of Computer Science and Statistics: 8th Annual Symposium on the Interface edited by J. W. France, Los Angeles, CA: UCLA

Gardner, Everette S. Jr. ! 985. "Exponential Smoothing: The State of the Art." Journal of Forecasting 4: 1-28.

.. 1985. "Forecasting Trends in Time Series." Manage- ment Science 31 : 1237-1246.

.. 1987. "Smoothing Methods for Short-term Planning and Control" in The Handbook of Forecasting A Manager's Guide edited by Spyros Makridakis and Steven C. Wheelwright. New York: John Wiley & Sons, Inc.

Keen, P. G. W. and L. A. Woodman. 1984. "What to do with all those micros." Harvard Business Review Sept.-Oct.: 142-150.

Levenbach, Hans and James P. Cleary. 1984. The Modern Forecaster: The Forecasting Process through Data Analysis. New York: Van Nostrand Reinhold Company, Inc.

Levitan, Laurence. 1981. "Getting the Most out of Application Software Packages." lnfo Systems 4: 68-72.

Mahmoud, Essam. 1983. "An Evaluation of Selected Computer Packages for Forecasting." Paper presented at the Third International Symposium on Forecasting, Philadelphia.

. 1984. "Accuracy in Forecasting: A Survey." Journal of Forecasting 3 (April-June): 139-160.

. 1987a. "Report on a Survey of the Use of Forecasting Methods and Software in Large Firms." Working Paper, University of North Texas.

. 1987b. "The Evaluation of Forecasts." in The Handbook of Forecasting: A Manager's Guide edited by Spyros Makridakis and Steven C. Wheelwright. New York: John Wiley & Sons, Inc.

Makridakis, Spyros et al. ! 982. '~l'he Accuracy of Extrapolation (time series) Methods: Results of a forecasting competition." Journal of Forecasting I: 111-153.

, S. Wheelwright and V. McGee. 1983. Forecasting Methods and Applications, Second Edition. New York: John Wiley & Sons, Inc.

and R. Winkler. 1983. "Averages of Forecasts: Some Empirical Results." Management Science 29: 987-995.

Malhotra, Naresh K., Armen Tashchian and F_.ssam Mahmoud. 1987. ' ~ e Integration of Microcomputers in Marketing R~seareh and Decision Making." Journal of the Academy of Marketing Science 15: 69-82.

Muller, Mervin E. 1980. "Aspects of Statistical Computing: What Packages For the 1980's Ought To Do." The American Statistician 34 (3).

Pegels, Carl C. 1969. "Exponential Forecasting: Some New Variations." Management Science 12:311-315.

Decision Support Software (DSS), Inc. 1986. EXPERT CHOICE Software Manual. McLean, VA: DSS, Inc.

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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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Documents

Review of selected software for sales forecasting and decision support systems