31
4
CHAPTER
Forecasting
D
ISCUSSION
Q
UESTIONS
1.
Qualitative models
incorporate subjective factors into the
forecasting model. Qualitative models are useful when subjective
factors are important. When quantitative data are difficult to ob
tain, qualitative models may be appropriate.
2.
Approaches are qualitative and quantitative. Qualitative is
relatively subjective; quantitative uses numeric models.
3.
Shortrange (under 3 months), mediumrange (3 to 18 months),
and longrange (over 18 months).
4.
The steps that should be used to develop a forecasting
system are:
(a) Determine the purpose and use of the forecast
(b) Select the item or quantities that are to be forecasted
(c) Determine the time horizon of the forecast
(d) Select the type of forecasting model to be used
(e) Gather the necessary data
(f) Validate the forecasting model
(g) Make the forecast
(h) Implement the results
(i) Evaluate the results
5.
Any three of: sales planning, production planning and budget
ing, cash budgeting, analyzing various operating plans.
6.
There is no mechanism for growth in these models; they are
built exclusively from historical demand values. Such methods
will always lag trends.
7.
Exponential smoothing
is a weighted moving average where
all previous values are weighted with a set of weights that decline
exponentially.
8.
MAD, MSE, and MAPE are common measures of forecast
accuracy. To find the more accurate forecasting model, forecast
with each tool for several periods where the demand outcome is
known, and calculate MSE, MAPE, or MAD for each. The
smaller error indicates the better forecast.
9.
The
Delphi technique
involves:
(a) Assembling a group of experts in such a manner as to pre
clude direct communication between identifiable members
of the group
(b) Assembling the responses of each expert to the questions
or problems of interest
(c) Summarizing these responses
(d) Providing each expert with the summary of all responses
(e) Asking each expert to study the summary of the responses
and respond again to the questions or problems of interest.
(f) Repeating steps (b) through (e) several times as necessary
to obtain convergence in responses. If convergence has
not been obtained by the end of the fourth cycle, the re
sponses at that time should probably be accepted and the
process terminated—little additional convergence is
likely if the process is continued.
10.
A time series model predicts on the basis of the assumption
that the future is a function of the past, whereas a causal model
incorporates into the model the variables of factors that might
influence the quantity being forecast.
11.
A time series is a sequence of evenly spaced data points with the
four components of trend, seasonality, cyclical, and random variation.
12.
When the smoothing constant,
D
, is large (close to 1.0),
more weight is given to recent data; when
D
is low (close to 0.0),
more weight is given to past data.
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 Spring '11
 AK

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