forecasting mcgraw-hill/irwin copyright © 2012 by the mcgraw-hill companies, inc. all rights...
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Forecasting
McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
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You should be able to:1. List the elements of a good forecast2. Outline the steps in the forecasting process3. Describe at least three qualitative forecasting
techniques and the advantages and disadvantages of each
4. Compare and contrast qualitative and quantitative approaches to forecasting
5. Describe averaging techniques, trend and seasonal techniques, and regression analysis, and solve typical problems
6. Explain three measures of forecast accuracy7. Compare two ways of evaluating and controlling
forecasts8. Assess the major factors and trade-offs to consider when
choosing a forecasting technique
3-2Student Slides
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Forecast – a statement about the future value of a variable of interestWe make forecasts about such things as
weather, demand, and resource availabilityForecasts are an important element in making
informed decisions
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n
100
Actual
ForecastActual
MAPE t
tt
n
tt ForecastActualMAD
2
tt
1
ForecastActualMSE
n
MAD weights all errors evenly
MSE weights errors according to their squared values
MAPE weights errors according to relative error
3-4Student Slides
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Forecasts that project patterns identified in recent time-series observationsTime-series - a time-ordered sequence of
observations taken at regular time intervalsAssume that future values of the time-series
can be estimated from past values of the time-series
3-5Student Slides
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These Techniques work best when a series tends to vary about an averageAveraging techniques smooth variations in the
dataThey can handle step changes or gradual
changes in the level of a seriesTechniques
1. Moving average2. Weighted moving average3. Exponential smoothing
3-6Student Slides
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Technique that averages a number of the most recent actual values in generating a forecast
average moving in the periods ofNumber
1 periodin valueActual
average moving period MA
period for timeForecast
where
MA
1
1
n
tA
n
tF
n
AF
t
n
t
n
iit
nt
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The most recent values in a time series are given more weight in computing a forecastThe choice of weights, w, is somewhat
arbitrary and involves some trial and error
etc. ,1 periodfor valueactual the , periodfor valueactual the
etc. ,1 periodfor weight , periodfor weight
where
)(...)()(
1
1
11
tAtA
twtw
AwAwAwF
tt
tt
ntntttttt
3-8Student Slides
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A weighted averaging method that is based on the previous forecast plus a percentage of the forecast error
period previous thefrom salesor demand Actual
constant Smoothing=
period previous for theForecast
periodfor Forecast
where
)(
1
1
111
t
t
t
tttt
A
F
tF
FAFF
3-9Student Slides
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A simple data plot can reveal the existence and nature of a trend
Linear trend equation
Ft a btwhere
Ft Forecast for period t
aValue of Ft at t 0
bSlope of the line
t Specified number of time periods from t 0
3-10Student Slides
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Slope and intercept can be estimated from historical data
bn ty t yn t 2 t
2
ay b tn
or y bt
where
n Number of periods
y Value of the time series
3-11Student Slides
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The trend adjusted forecast consists of two componentsSmoothed errorTrend factor
TAFt+1 St Ttwhere
St Previous forecast plus smoothed error
Tt Current trend estimate
3-12Student Slides
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Alpha and beta are smoothing constantsTrend-adjusted exponential smoothing has
the ability to respond to changes in trend
TAFt+1 St Tt St TAFt + At TAFt Tt Tt 1 TAFt TAFt 1 Tt 1
3-13Student Slides
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Regression - a technique for fitting a line to a set of data pointsSimple linear regression - the simplest form of
regression that involves a linear relationship between two variablesThe object of simple linear regression is to obtain
an equation of a straight line that minimizes the sum of squared vertical deviations from the line (i.e., the least squares criterion)
3-14Student Slides
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The better forecasts are, the more able organizations will be to take advantage of future opportunities and reduce potential risks A worthwhile strategy is to work to improve short-term
forecastsAccurate up-to-date information can have a
significant effect on forecast accuracy:PricesDemandOther important variables
Reduce the time horizon forecasts have to cover Sharing forecasts or demand data through the
supply chain can improve forecast quality
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