CHAPTER 4 Flashcards
(33 cards)
The art and science of predicting future events.
Forecasting
Planning indicators that are valuable in helping organizations prepare medium- to long-range forecasts.
Economic forecasts
Long-term forecasts are concerned with the rates of technological progress.
Technological forecasts
Projections of a company’s sales for each time period in the
planning horizon.
Demand forecasts
The forecast is the only estimate of demand until actual demand becomes known. True or false?
True
Forecasting follows seven basic steps:
(1) Determine the use of the forecast;
(2) Select the items to be forecasted;
(3) Determine the time horizon of the
forecast;
(4) Select the forecasting model(s);
(5) Gather the data needed to make
the forecast;
(6) Make the forecast;
(7) Validate and implement the results.
Forecasts that employ mathematical modeling to forecast demand.
Quantitative forecasts
Forecasts that incorporate such factors as the decision
maker’s intuition, emotions, personal experiences, and value system.
Qualitative forecast
—Takes the opinion of a small group of high-level
managers and results in a group estimate of demand
Jury of executive opinion
—Uses an interactive group process that allows experts to make
forecasts
Delphi method
Based on salespersons’ estimates of expected sales.
Sales force composite
Solicits input from customers or potential customers regarding
future purchasing plans
Market survey
Uses a series of past data points to make a forecast.
Time series
—Assumes that demand in the next period is equal to demand in
the most recent period.
Naive approach —
Uses an average of the n most recent periods of data to forecast the next period
Moving average
A weighted-moving-average forecasting technique in
which data points are weighted by an exponential function.
Exponential smoothing
The weighting factor, a, used in an exponential smoothing forecast, a number between 0 and 1
Smoothing constant
A measure of the overall forecast error for a
model.
Mean absolute deviation (MAD)
The average of the squared differences between
the forecast and observed values.
Mean squared error (MSE
The average of the absolute differences
between the forecast and actual values, expressed as a percentage of actual
values
Mean absolute percent error (MAPE)
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.
Trend projection and regression analysis
Trend projection
—Regular upward or downward movements in a time series
that tie to recurring events
Seasonal variations
Patterns in the data that occur every several years
Cycles
A straight-line mathematical model to describe the
functional relationships between independent and dependent variables.
Linear-regression analysis
