- Evaluate the loss on sales and unused capacity
Compare the simulated prospective sales with the simulated capacity. For example, dur-
ing week 1, the loss on unused capacity = 1.10(3375 - 3250) = $137.50, given the data
from Table 32. Likewise, during week 4, loss on lost sales = 2.40(3350 - 3325) = $60.00. - Determine the average weekly losses
Total the computed losses obtained in step 7, and divide by 10 to obtain the following av-
erage weekly values:
Loss on unused capacity $68.75
Loss on forfeited sales 90.00
Total $158.75If more trucking facilities are procured, the forfeited sales will be reduced, but the un-
used capacity will be increased. The optimal number of trucks to be purchased is that for
which the total loss is a minimum.
LINEAR REGRESSION APPLIED TO
SALES FORECASTING
A firm had the following sales for 5 consecutive years:
Year Sales, $000
19AA 348
19BB 377
19CC 418
19DD 475
19EE 500In 19FF, the firm decided to expand its production facilities in anticipation of future
growth, and therefore it required a forecast of future sales. Apply linear regression to dis-
cern the sales trend. What is the projected sales volume for 19JJ?
Calculation Procedure:
- Plot a scatter diagram for the given data
Regression analysis is applied where a causal relationship exists between two variables,
although the relationship is obscured by the influence of random factors. The problem is
to establish the relationship on the basis of observed data. Here we assume that the sales
volume is a linear function of time.
Consider the annual sales income to be a lump sum received at the end of the given
year, and plot the sales data as shown in Fig. 36. The aggregate of points is termed a scat-
ter diagram. This diagram will be replaced by a straight line that most closely approaches
the plotted points; this straight line is called the regression line, or line of best fit.