Sales Forecasting

Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgemental methods. Usage can differ between areas of application: for example, in hydrology, the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period.
Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts. In any case, the data must be up to date in order for the forecast to be as accurate as possible.
Although quantitative analysis can be very precise, it is not always appropriate. Some experts in the field of forecasting have advised against the use of mean square error to compare forecasting methods.
Forecasting involves the use of information at hand to make statements about the likely course of future events. In technical terms, conditional on what one knows, what can one say about the future? Forecasting techniques include uni-variant, multi-variant, and qualitative analysis. Time series used to forecast future trends include exponential smoothing, ARIMA (Autoregressive Integrated Moving Average) and trend analysis. Multi-variant prediction methods include multi regression model, econometrics, and state space. Delphi marketing research, situational analysis, and historical analogue belong to qualitative methodologies. These forecasting methods forecast trends over different time horizons. There are significant differences in time length being