Business forecasting is the process of estimating future business conditions by analyzing past business data. It is used to predict sales; customer and/or market size, stability and makeup; employee and salary information; website traffic; inventory; and risk. Business forecasting is an important tool for management, as it provides the basis for many business decisions. All businesses use forecasting to some extent, whether to anticipate the needs of their customers, determine whether to launch a new product line or control inventories and supply chains. Budgets and production plans are simple forms of forecasting that have always been used by businesses. Forecasting based on systematic procedures is increasingly becoming an important function within major corporations and even small businesses. The number of companies that have hired forecasters rose substantially beginning at the end of the 20th century.
Forecasting is particularly important for businesses with long production cycles. The longer it takes to source raw materials, prepare them for production, manufacture the products, market and sell them, the more the overall economy can change. Fluctuations in price, consumer attitude and the availability of raw materials can impact these enterprises significantly. Forecasting helps to protect businesses against loss by predicting such fluctuations and anticipating how to respond to them in advance.
Business forecasting is not an exact science. Forecasters can reach the same conclusions using different data and different methods, and many times forecasts prove accurate for reasons other than those on which the forecasts were based. Business success or failure is often affected not just by economic trends, but also by human behavior, which is considered very difficult to predict.
Forecasting can be done on a macro level, in which major economic trends — even a simple evaluation of better or worse economic conditions — are accounted for. Most forecasting, however, seeks to provide more specific information. Yet the more detailed the forecast, the less accuracy can be guaranteed. Forecasts are classified as external — those that consider the factors outside the individual business, such as changes in the tax code, or internal — forecasts that account only for aspects within the domain of the individual firm, such as employee pensions.
Business forecasting relies on data. Businesses are inundated with data of all kinds, which can easily be collected and stored thanks to the increase in point-of-sale data from retailers, data mining and data warehousing. Many companies have also developed computer software that supports business forecasting, especially SAS, SAP and Oracle. Data mining looks for information that has predictive value in mass quantities of data. Forecasting feeds this information into analytical models, such as classification, association and regression, to discover trends and retrieve details that can direct future planning. Forecasters analyze this data and try to convert it into knowledge about the company, industry and overall economy. Forecasts based on that knowledge, rather than simply on doing what was done in the past, are considered more accurate and more useful.
Forecasting methods can be qualitative or quantitative in nature. Qualitative forecasting tries to produce a common, general prediction, usually for the short term. Businesses usually use market research to generate such qualitative projections. They may also use what is known as the Delphi Method, in which experts in relevant fields are polled about their expectations for the future.
Econometric models are quantitative methods that look at relationships among different variables to assess how changes in one factor, such as interest rates, can affect other factors in an economic equation. This type of method helps forecasters predict future events by identifying cause-and-effect patterns in the relationships.
Other quantitative methods include the Time-Series Method, which bases predictions on past information, such as the history of recessions. This method is used to forecast events that are consistent and unfold slowly. Using econometric models, forecasters try to create mathematical equations that will account for the known variables in a way that points to future patterns.