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HiTek Computer Services repairs and services personal computers at its store, and it makes local service calls. It primarily uses part-time State University students as technicians. The company has had steady growth since it started. It purchases generic computer parts in volume at a discount from a variety of sources whenever they see a good deal. Thus, they need a good forecast of demand for repairs so that they will know how many computer component parts to purchase and stock, and how many technicians to hire. The company has accumulated data shown in the accompanying table for repair and service calls for the past 12 months.
In the following table, please calculate the forecast using smoothing constants (a) equal to 0.30.
Forecast, F(t+1)
Period
Month
Demand
a = 0.30
a = 0.50
1
January
37
2
February
40
37.00
3
March
41
38.50
4
April
39.75
5
May
45
38.37
6
June
50
41.68
7
July
43
45.84
8
August
47
44.42
9
September
56
45.71
10
October
52
50.85
11
November
55
51.42
12
December
54
53.21
13
---
53.61
The company has also calculated the exponential smoothing forecasts using smoothing constants (a) equal to 0.50 (provided above). What can you say about the responsiveness of the two forecasts? Which one is likely to be more responsive?
The company wants to compare the accuracy of these two different forecasts using MAD. Please compute MAD for (a) equal to 0.30 and (a) equal to 0.50 compared to the actual demand data. Which alpha provides a more accurate forecast? Describe why it might be more accurate.
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