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During recent years a number of techniques have been developed to aid in the forecasting of corporate sales, individual product demand, economic indicators, and other related series. These techniques have included classical time series analysis, multiple regression and adaptive forecasting procedures. As a result of these developments, the individual company and decision maker is faced with the task of selecting the forecasting technique that is most appropriate for his situation. This article reports research conducted at INSEAD on how simulation can be used to compare and evaluate alternative forecasting techniques for a specific application.

This article presents a study of revenue forecasting in a Florida municipal government. Seven techniques, including the budget officers' judgmental approach, time series models, a deterministic model, and an optimized model, are employed with franchise and utility receipts in the Town of Davie. The authors found that simple time series models outperformed deterministic models and the judgmentally derived forecasts of local officials. Consistent with prior research, findings here suggest that the time series models are not only accurate, but also easy to implement and readily comprehensible by local officials.

As soon as the words “planning” and “control” are mentioned, the word “forecasting” is sure to follow. Next come several important questions: Should forecasting be the special domain of experts, or become a management tool? Can management obtain accurate and mathematically valid projections without investing in special hardware or software? The answer is that the basic tools required to prepare sound forecasts are readily available in most companies today.

The main scope of the paper is to demonstrate the capabilities of PYTHIA forecasting platform, to compare time series forecasting techniques, which were used to forecast mortgage loans in UK, and to show how PYTHIA can be useful for a bank.

The paper outlines the methods used to forecast the time series data, which are included in PYTHIA. Theta, the time‐series used to forecast average mortgage loan prices, were grouped in: all buyers – average loan prices in UK; first‐time buyers – average loan prices in UK; and home‐movers – average loan prices in UK. The case of all buyers – average loan prices in UK, was presented in detail.

After the comparison of the methods, the best forecasts are produced by WINTERS and this is maybe due to the fact that there is seasonality in the data. The Theta method comes next in the row and generally produces good forecasts with small mean absolute percentage errors. In order to tell with grater certainty which method produces the most accurate forecasts we could compare the rest error statistics provided by PYTHIA too.

The paper presents the PYTHIA forecasting platform and shows how it can be used by the managers of a Bank to forecast mortgage loan values. PYTHIA can provide the forecasts required by practically all business situations demanding accurate predictions. It is designed and developed with the purpose of making the task of managerial forecasting straightforward, user‐friendly and practical. It incorporates a lot of knowledge and experience in the field of forecasting, modeling and monitoring while fully utilizing new capabilities of computers and software.

This paper examines four underlying trends in the changing business environment relating to information technology and geographic, functional and sectorial integration. It discusses three required changes in management focus needed to reach global profitability from product inception to promotion. The skills required for this change are listed by functional area, although the techniques are predominantly cross‐cultural. This paper explains the steps needed to move from a traditional firm to a globally competitive network and the cultural barriers to building consumer‐focused extended‐value chains. Finally it discusses ways in which business school education can promote strategic thinking about profitability and heighten awareness of the potential gains from cooperative inter‐firm partnerships.

Consumer researchers are interested in the degree to which global convergence is occurring along with various consumer behaviour dimensions and to what extent the consumption patterns in different parts of the world are becoming similar. With increasing internationalisation and cultural cross‐fertilisation, the industrialised societies of the world are converging in many ways. Shifts in alcoholic beverage consumption patterns in Europe over the past 50 years may represent a case in point. As traditional cultural boundaries become blurred, consumer preferences for wine appears to be driven less by long‐standing local and regional traditions, and more by growing acceptance of a wider choice. The disparity of wine consumption among the 12 countries studied has also decreased. Other powerful forces are likely to accelerate the pace of convergence in the future.

Forecasts of demand for innovative, high‐technology products in the 1980s have usually erred on the high side, often by as much as 50 percent or more. Business decisions based on those inflated forecasts have sometimes spelled disaster: empty plants, layoffs, even bankruptcy. This article examines the problem of overoptimistic forecasting in the high‐technology arena, offers reasons for this bias, and suggests some action recommendations which can be applied by high‐tech decision makers to make forecasts more realistic. These recommendations include getting to know your market better, developing forecasting judgment, and finally, applying a “deflator” of up to 30–50 percent to forecasts that involve an abnormally high level of risk.

The value of strategic planning is a continuing topic for debate. As evidence mounts that many business strategies are poorly conceived and badly implemented, the debate has a renewed sense of urgency. What is most disquieting is the growing disenchantment of key participants in the process.