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1

**Forecasting**

The art and science of predicting future events.

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2

**Economic forecasts**

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

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3

**Technological forecasts**

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

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4

**Demand forecasts**

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

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5

**Quantitative forecasts**

Forecasts that employ mathematical modeling to forecast demand.

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6

**Qualitative forecasts**

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

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7

**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.

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8

**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.

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9

**Sales force composite**

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

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10

**Market survey**

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

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11

**Time-series**

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

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12

**Naive approach**

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

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13

**Moving-average**

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

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14

**Exponential smoothing**

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

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15

**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.

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16

**Mean absolute deviation**

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

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**Mean squared error**

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

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**Mean absolute percent error**

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

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19

**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.

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**Seasonal variations**

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

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21

**Cycles**

Patterns in the data that occur every several years.

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22

**Linear regression analysis**

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

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23

**Standard error of the estimate**

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

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**Coefficient of correlation**

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

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**Coefficient of determination**

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

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**Multiple regression**

An associative forecasting method with more than one independent variable.

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**Tracking signal**

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

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**Bias**

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

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**Adaptive smoothing**

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

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**Focus forecasting**

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

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31

**Stagger chart**

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

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