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A business' lifecycle is directly impacted by it's ability to look at future probabilities. Forecasting and its many methods is one way of doing this. There are four classifications of forecasting, qualitative, time series analysis, casual relationships, and simulation. Using these types of forecasting a business will have a clearer perspective as to future changes to expect, industrial and consumer behaviors, and even potential shortage or influx of supplies or services.

Qualitative analysis is a subjective analysis that is bases off of qualitative traits. Essentially it consists of traits that do not involve measurements or numbers, but strictly based off observations and opinions. An example of a type of qualitative analysis is grass roots. Grass roots analysis is a high level forecast which has been compiled from many low level forecasts. Another example is market research. Market research sets out to collect, analyze, and interpret data in various ways in order to determine the nature of its customers and competitors , demand for its service or product, and any possible features the product may be lacking .A third example of qualitative analysis is the Delphi method. The Delphi method is an interactive set of well-defined procedures in which independent experts are asked to complete and return a questionnaire to a facilitator. After the questionnaire is returned, the facilitator provides an anonymous summary of the experts' findings. This promotes the participants into freely expressing their viewpoints and removes any pre-defined criteria.

A Time series analysis is an analysis of a sequence of measurements made at specific time intervals, such as quarterly, seasonal, cyclical, or even weekly. It's based on the principle that using past demand, one should be able to predict future demands. Examples of time series analysis include exponential smoothing, weighted moving average, and trend projections. Exponential smoothing