Write a note on revenue forecasting with reference to any industry which you like the most.

Forecasting revenue is one the biggest challenges for the business modeller. The first problem is producing a meaningful and useful definition of the market place. In the telecommunications, information technology and media sectors, for instance, there is such a high degree of convergence that it is becoming increasingly difficult to distinguish between the separate markets. Modellers may also have incomplete or inaccurate data The different approaches to forecasting can be classified in several ways. A useful classification is as follows: i) Extrapolation techniques: Extrapolation techniques, like, time series analysis, implicitly assume that the past will be a reasonable predictor of the future. This assumption may be valid for mature and stable businesses, like the water and gas utilities. However, many industry sectors are experiencing rising levels of structural change. The use extrapolative techniques for these sectors may provide poor results. ii) Causative techniques: Causative techniques, such as, multiple regression, attempt to comprehend the basic relationships that determine the dynamics of a market. This understanding, combined with a set of assumptions about the future, provides the basis for the forecast. Because the underlying relationships are often estimated from historical data, these techniques are useful when only small, incremental changes in assumptions are expected in the future. iii) Judgmental techniques: Modellers may often be asked to produce a forecast for a new product or market where there are no available historic data. In these cases, forecasting can become judgmental and highly subjective. Although the forecasts can be refined through studying the results of market research and by examining the experiences of similar or related products in other markets and countries, the task of forecasting becomes more like an art than a science. In practice, majority of modellers depend on a blend of all three techniques. They may establish the current market trends through time series analysis, and attempt to understand market dynamics through multiple regression methods. This understanding will then be combined with their belief of how these relationships might develop in the future to produce a forecast.