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
|
37
|
|
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
|
January
|
---
|
|
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.