Describe at least three qualitative forecasting techniques and the advantages and disadvantages of each 4.. Describe averaging techniques, trend and seasonal techniques, and regression
Trang 2You should be able to:
1 List the elements of a good forecast
2 Outline the steps in the forecasting process
3 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 accuracy
7 Compare two ways of evaluating and controlling forecasts
8 Assess the major factors and trade-offs to consider when
choosing a forecasting technique
Trang 3Forecast – a statement about the future
value of a variable of interest
We make forecasts about such things as
weather, demand, and resource availability
Forecasts are an important element in making
informed decisions
Trang 4∑ − ×
=
100 Actual
Forecast Actual
t t
n
= Actual t Forecast t
MAD
t t
1
Forecast
Actual MSE
−
−
= ∑
n
MAD weights all errors evenly
MSE weights errors according
to their squared values
MAPE weights errors according to relative error
Trang 5Forecasts that project patterns identified in
recent time-series observations
observations taken at regular time intervals
can be estimated from past values of the
time-series
Trang 6These Techniques work best when a series
tends to vary about an average
Averaging techniques smooth variations in the
data
They can handle step changes or gradual
changes in the level of a series
Techniques
1 Moving average
2 Weighted moving average
3 Exponential smoothing
Trang 7Technique that averages a number of the
most recent actual values in generating a
forecast
average moving
in the periods
of Number
1 period
in value Actual
average moving
period MA
period for time
Forecast
where
MA
1
1
=
−
=
=
=
=
=
−
= −
∑
n
t A
n
t F
n
A F
t n t
n
i
i t n
t
Trang 8The most recent values in a time series are
given more weight in computing a forecast
The choice of weights, w, is somewhat arbitrary
and involves some trial and error
etc , 1 period
for value actual
the ,
period for
value actual
the
etc.
, 1 period
for weight ,
period for
weight
where
) (
) (
) (
1 1
1 1
−
=
=
−
=
=
+ + +
=
−
−
−
−
−
−
t A
t A
t w
t w
A w
A w
A w
F
t t
t t
n t n t t
t t
t t
Trang 9A weighted averaging method that is based
on the previous forecast plus a percentage of
the forecast error
period previous
the from sales
or demand Actual
constant Smoothing
=
period previous
for the Forecast
period for
Forecast
where
) (
1 1
1 1
1
=
=
=
− +
=
−
−
−
−
−
t
t t
t t
t t
A
F
t F
F A
F F
α
α
Trang 10A simple data plot can reveal the existence
and nature of a trend
where
F t = Forecast for period t
a = Value of F t at t = 0
b = Slope of the line
t = Specified number of time periods from t = 0
Trang 11Slope and intercept can be estimated from
historical data
b = n∑ty −∑t∑y
n∑t2 −( ) ∑t 2
a = ∑y −b∑t
where
Trang 12The trend adjusted forecast consists of two
components
Smoothed error
Trend factor
TAFt +1 = S t + T t
where
S t = Previous forecast plus smoothed error
T t = Current trend estimate
Trang 13Alpha and beta are smoothing constants
ability to respond to changes in trend
Trang 14Regression - a technique for fitting a line to
a set of data points
Simple linear regression - the simplest form of
regression that involves a linear relationship
between two variables
The 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)
Trang 15organizations will be to take advantage of future
opportunities and reduce potential risks
A worthwhile strategy is to work to improve short-term
forecasts
Accurate up-to-date information can have a significant
effect on forecast accuracy:
Reduce the time horizon forecasts have to cover
Sharing forecasts or demand data through the
supply chain can improve forecast quality