1. The following tabulations are actual sales of units for six months and a starting forecast in January.
Calculate forecasts for the remaining five months using simple exponential smoothing with ? = .20.
Also, calculate MAD for the forecasts.
Month
January
February
March
April
May
June

Demand F
100 80
94
106
80
68
94

2. Assume that your stock of sales merchandise is maintained based on the forecast demand. If the
distributor’s sales personnel call on the first day of each month, compute your forecast sales by each
of the three methods requested here.
Month
Actual
June
140
July
180
August
170
a. Using a simple three-month moving average, what is the forecast for September?
b. Using a weighted moving average, forecast for September (Use the following weights: 0.2, 0.3, and
0.5)
c. Using a simple exponential smoothing and assuming the forecast for June had been 130, forecast
sales for September with alpha = 0.30
3. Assume an initial starting forecast of 300 units, a trend of 8 units, an alpha of 0.30 and a delta of 0.40.
If actual demand turned out be 288, calculate the forecast for the next period.
4. Historical demand for a product is as follow:
Demand
Apr
May
Jun
Jul
Aug
Sep

60
55
75
60
80
75

Using Least Square Method (Simple regression), forecast for October.

5. The following table shows the past 2 years of quarterly sales information for Rauniar Chips. Assume
that there are both trend and seasonal factors and that seasonal cycle is one year. Use trend
projection with seasonal variation method for forecast quarterly sales for the next year.
Quarter
I
II
III
IV

Sales
160
195
150
140

Quarter
V
VI
VII
VIII

Sales
215
240
205
190