POM-QM
Q
FORECASTING
Prepared by: Hanife Demiralp
Source: POM-QM for Windows
V i 3
Version
FORECASTING
z Time
Series:
Suppose that data is given in the following
table and forecast the demand for the week of
February 14.
We are using (n=2) 2
weekk moving
i average
Absolute Percentage
g
Error = |Error| \ Demand
After 2 week (n=2)
we have forecast in
third week.
Error is =
Demand - Forecast
Example 2: Weighted Moving
Average
Forecast for week 7 is
(0.6*120) +
(0 4*110)=116
(0.4
110) 116
Forecast the demand
for the week February
14
Example 3: Exponential
Smoothing
Value for smoothing
constant, alpha, is 0.5
You can enter any
number
b iin thi
this column
l
for forecast. If you
enter no number,
starting forecast is
taken as starting
demand.
Forecast the demand
for the week of
February 14
Example 4: Exponential
smoothing
thi
with
ith trend
t
d
If beta is 0, single
g
exponential smoothing
is performed. If beta is
positive exponential
smoothing with trend is
performed
Forecast values
Error is =
Demand – Adjusted
Forecast
Example 5: Trend Analysis
Line that fits the data best is: y=104.33 +
1.857*x