is the process of projecting the values of one or more variables into the future.
Forecasting
It can result in poor inventory and staffing decisions, resulting in part shortages, inadequate customer service, and many customer
Poor forecasting
in the length of time on which a forecast is based
Planning horizon
is the unit of measure for the time period used in a forecast.
Time bucket
is a set of observations measured at successive points in time or over successive periods of time.
Time series
is the underlying pattern of growth or decline in a time series.
Trend
are characterized by repeatable periods of ups and downs over short periods of time.
Seasonal patterns
Are regular pat terns in a data series that take place over long periods of time
Cyclical patterns
(sometimes called noise) is the unexplained deviation of a time series from a predictable pattern such as a trend, seasonal, or cyclical pattern.
Randomvariations
is a one-time variation that is explainable.
Irregularvariation
is the difference between the observed value of the time series and the forecast,
Forecasterror
MSE is probably the most commonly used measure of forecast accuracy. (Sometimes the square root of MSE is computed, this is called the
Rootmeansquareerror (RMSE)
is based on the assumption that the future will be an extrapolation of the past
Statiscal forecasting
is an average of the most recent "k" observations in a time series.
Moving average forecast
is a method for building a statistical model that defines a relationship between a single dependent variable and one or more independent variables, all of which are numerical
Regression analysis
A linear regression model with more than one independent variable is called
Multiple linear regressionmodel
relles upon opinions and expertise of people in developing forecasts.
Judgementalforecasting
is asking those who are close to the end consumer, such as salespeople, about the customers' purchasing plans.
Grassroot forecasting
consists of forecast- ing by expert opinion by gathering judgments and opinions of key personnel based on their experience and knowledge of the situation.
Delphimethod
provides a method for doing this by quantifying bias-the tendency of forecasts to consistently be larger or smaller than the actual values of the time series.