Ch.4 Forecasting

Forecasting

The art and science of predicting future events.

Economic forecasts

Planning indicators that are valuable in helping organizations prepare medium- to long-range forecasts.

Technological forecasts

Long-term forecasts concerned with the rates of technological progress.

Demand forecasts

Projections of a company’s sales for each time period in the planning horizon.

Quantitative forecasts

Forecasts that employ mathematical modeling to forecast demand.

Qualitative forecasts

Forecasts that incorporate such factors as the decision maker’s intuition, emotions, personal experiences, and value system.

Jury of executive opinion

A forecasting technique that uses the opinion of a small group of high-level managers to form a group estimate of demand.

Delphi method

A forecasting technique using a group process that allows experts to make forecasts. three different types of participants in the Delphi method: decision makers, staff personnel, and respondents.

Sales force composite

A forecasting technique based on salespersons’ estimates of expected sales.

Market survey

A forecasting method that solicits input from customers or potential customers regarding future purchasing plans.

Time-series

A forecasting technique that uses a series of past data points to make a forecast.

Naive approach

A forecasting technique that assumes that demand in the next period is equal to demand in the most recent period.

Moving-average

A forecasting method that uses an average of the n most recent periods of data to forecast the next period.

Exponential smoothing

A weighted-moving-average forecasting technique in which data points are weighted by an exponential function.

Smoothing constant

The weighting factor used in an exponential smoothing forecast, a number greater than or equal to 0 and less than or equal to 1.

Mean absolute deviation

(MAD) A measure of the overall forecast error for a model.

Mean squared error

(MSE) The average of the squared differences between the forecasted and observed values.

Mean absolute percent error

(MAPE) The average of the absolute differences between the forecast and actual values.

Trend projection

A time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

Seasonal variations

Regular upward or downward movements in a time series that tie to recurring events.

Cycles

Patterns in the data that occur every several years.

Linear regression analysis

A straight-line mathematical model to describe the functional relationships between independent and dependent variables.

Standard error of the estimate

A measure of variability around the regression line—its standard deviation.

Coefficient of correlation

A measure of the strength of the relationship between two variables.

Coefficient of determination

A measure of the amount of variation in the dependent variable about its mean that is explained by the regression equation.

Multiple regression

An associative forecasting method with more than one independent variable.

Tracking signal

A measurement of how well a forecast is predicting actual values.

Bias

A forecast that is consistently higher or consistently lower than actual values of a time series.

Adaptive smoothing

An approach to exponential smoothing forecasting in which the smoothing constant is automatically changed to keep errors to a minimum.

Focus forecasting

Forecasting that tries a variety of computer models and selects the best one for a particular application.

Stagger chart

A short-term rolling forecast that is easily prepared, discussed, and evaluated.