Demand Forecasting
The below given data represents the sales of an industry, plot the values in the graph and discuss the constant rate of change, constant percentage rate of change, statistical curve fitting and Graphic curve fitting.
Period 
Year 
Quarter 
Sales Proceeds in million $ 
1 
2005 
I 
1000 
2 
II 
1100 

3 
III 
1400 

4 
IV 
1200 

5 
2006 
I 
1300 
6 
II 
1500 

7 
III 
1100 

8 
IV 
1400 

9 
2007 
I 
1600 
10 
II 
1800 

11 
III 
1700 

12 
IV 
1900 
Solution
(A) Graphic Curve Method
With the above data of quarterly figures of sales proceeds for the years 2005, 2006 and 2007, it is necessary to forecast sales of the industry in the last quarter of 2008. The data shows that quarterly sales of the industry are usually enhancing.
But for making forecast of future sales we have to identify a more accurate gauge of the quarterly increase in sales. For this reason, one way is to fit a line to the provided data graphically so that it depicts the trend in the data as accurately as feasible.
For using trend line for forecasting reasons we have to measure its incline which tells us the quarterly enhancement in the sales of the industry.
Presume the incline of line so fitted is 36. Now, with the sales of $1900 in the last quarter of the year 2007, the sales of first quarter of the year 2008 would be 1900 + 36 = 1936.
In the second quarter it will be 1900 + 36 + 36 = 1972 and in the third quarter it will be 1900 + 36 +36 + 36 = 2008 and finally the last quarter would be 1900 + 36 + 36 + 36 + 36 = 2044 million dollars.
Alternatively, the future sales proceeds at mere future period can be anticipated by expanding the graphically constructed trend line to that point of period.
(B) Statistical Curve Fitting
There is a restriction of the graphical curve fitting to anticipate future demand. The accurateness is based on how much good fit curve is sketched by the analyst. A more correct skill to sketch a good fit curve to the sales data is the use of statistical method.
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