The manager of a small health clinic would like to use exponential smoothing to
ID: 382290 • Letter: T
Question
The manager of a small health clinic would like to use exponential smoothing to forecast demand for laboratory services in the facility. However, she is not sure whether to use a high or low value of. To make her decision, she would like to compare the forecast accuracy of a high and low on historical data. She has decided to use an =0.7 for the high value and =0.1 for the low value. Given the following historical data, which do you think would be better to use? (Round answers to 2 decimal place, e.g. 15.25)
Using
provides a better historical fit based on the MAD criterion.
Week Demand(lab requirements) 1 337 2 345 3 332 4 378 5 362 6 351
Explanation / Answer
Following table calculates values of Absolute Deviations under both types of forecast methods.
It is to be noted :
Absolute deviation = Absolute difference between Forecast value and demand value
Ft = alpha.At-1 + ( 1 – alpha ) x Ft-1
Ft, Ft-1 = Forecast for period t and t-1
At-1 = Actual demand for period t-1
Alpha = Exponential smoothing factor ( can be either 0.7 and 0.1)
WEEK
DEMAND
Forecast( alpha = 0.7)
Absolute deviation
Forecast ( alpha = 0.1)
Absolute deviation
1
337
337.00
0.00
337.00
0.00
2
345
337.00
8.00
337.00
8.00
3
332
342.60
10.60
337.80
5.80
4
378
335.18
42.82
337.22
40.78
5
362
365.15
3.15
341.30
20.70
6
351
362.95
11.95
343.37
7.63
SUM =
76.52
82.91
Sum of Absolute deviation values for alpha = 0.7 will be 76.52
Hence, MAD for alpha = 0.7 = 76.52/6 = 12.75
Sum of Absolute deviation values for alpha = 0.1 wlll be 82.91
Hence, MAD for alpha = 0.1 will be = 82.91 /6 = 13.81
FORECAST USING ALPHA = 0.1
FORECAST USING ALPHA = 0.7
Since MAD for forecast using 0.7 is less than MAD for forecast using ALPHA = 0.1, forecast using alpha of 0.7 is preferable
WEEK
DEMAND
Forecast( alpha = 0.7)
Absolute deviation
Forecast ( alpha = 0.1)
Absolute deviation
1
337
337.00
0.00
337.00
0.00
2
345
337.00
8.00
337.00
8.00
3
332
342.60
10.60
337.80
5.80
4
378
335.18
42.82
337.22
40.78
5
362
365.15
3.15
341.30
20.70
6
351
362.95
11.95
343.37
7.63
SUM =
76.52
82.91
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