Qualitative forecasting methods

Qualitative forecasting methods are usually based on subjective judgments and past historical data are not needed. They are most useful for new products or services. Section 2.3 discusses in detail the various qualitative forecasting methods. 

Quantitative forecasting methods require historical data that are accurate and consistent. They assume that past represents the future, namely, history will tend to repeat itself. Most quantitative methods fall in the category of time series analysis and are discussed in detail in Section 2.4. 

These methods are based on subjective opinions obtained from company executives and consumers. These methods are ideally suited for forecasts where there are no past data or past data is not reliable due to the changes in environment (e.g., peacetime data on spare part needs for military aircrafts are not useful for forecasts during war time). Qualitative methods are commonly used for strategic decisions where long-term forecasts are necessary. The qualitative approaches vary in sophistication from scientifically conducted consumer surveys to intuitive judgments from top executives. Quite frequently qualitative methods are also used as supplements to quantitative forecasts. In a 1994 survey of forecasting in practice, 78% of top 500 companies responded that they always or frequently used qualitative methods for forecasting (Sanders and Manrodt, 1994). 

A brief review of the most commonly used qualitative methods is given in the following text. For a detailed discussion of qualitative methods, the reader is referred to the textbook by Lilien et al. (2007). 

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Currently, the landslide hazard spatial prediction methods can be divided into qualitative methods and quantitative methods. As we all know qualitative forecasting method mainly depends on the subjective experience and the predicted accuracy of qualitative methods is lower than it of quantitative methods. So the qualitative methods have been gradually replaced by the quantitative methods. Quantitative models can be divided into statistic analysis models, deterministic models, probabilistic model, fuzzy information optimization processing and neurd network models. 

Qualitative Qualitative forecasting methods are primarily subjective and rely on human judgment. They are most appropriate when little historical data are available or when experts have market intelligence that may affect the forecast. Such methods may also be necessary to forecast demand several years into the future in a new industry. 

The success of a manufacturing supply chain depends on its ability to accurately forecast customer demands and produce in time to meet those demands. This chapter is divided into two parts. Part 1 (Demand Forecashng) discusses the commonly used forecasting methods (both qualitative and quantitative) used in industry. It also includes a discussion of available forecasting software and real-world applications of forecasting methods. 

Explain the differences between qualitative and quantitative forecasting methods. Which method is applicable under what conditions ... 

However, the computational effort increases rapidly with the number of atoms involved and reaches such prohibitive levels that the chemist s desire to have, on theoretical grounds, a reasonably accurate forecast of molecular interactions and chemical reactivity has so far proved unrealizable. It is hence necessary to resort to approximate methods which yield at least qualitative indications and a rough prediction of the phenomenology involved. 

For long-term (>1 year) and medium-term (6 months to a year) forecasting, most firms preferred qualitative methods, in particular, executive committee consensus. 

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