FORECASTING Flashcards
The process of using historical data to predict future events
Forecasting
Forecasts that use subjective inputs such as opinions from consumer surveys, sales staff,managers, executives, and experts.
Judgemental
uses historical data assuming the future will be like the past (quantitative)
Time Series
uses explanatory variables to predict the future
Associative model
Managers and staff complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast
delphi method
Opinions of managers and staff
executive opinions
With personal contact with customers
sales force
The opinions of market
Consumer surveys
A time-ordered sequence of observations taken at regular intervals over time
time series forecast
long-term movement in data
trend
short-term regular variations in data
seasonality
caused by unusual circumstances
irregular variations
caused by chance
random variations
*Simple to use
*Virtually no cost
*Easily understandable
*Cannot provide high accuracy
naive forecast
wave like variations lasting more than one year
cycle
assumes an average is a good estimator of future behavior
simple moving average
puts more weight on recent data and less on past data.
weighted moving average
is a technical indicator that assigns a greater weighting to the most recent data points, and less weighting to data points in the distant past.
weighted moving average
is obtained by multiplying each number in the data set by a predetermined weight and summing up the resulting values.
weighted moving average
is a measure of the performance.
alpha
is an amount/percentage given to increase or decrease the importance of an item
weight
It is a sophisticated weighted averaging method that is relatively easy to use and understand.
EXPONENTIAL SMOOTHING
It is a weighted averaging method based on previous forecast plus a percentage of the forecast error.
EXPONENTIAL SMOOTHING
The smoothing constant represents the percentage of forecast error.
EXPONENTIAL SMOOTHING
A method that uses measurable, historical data observations, to make forecasts by calculating the weighted average of the current period’s actual value and forecast, with a trend adjustment added in.
ADJUSTED EXPONENTIAL SMOOTHING
