Business Finance - Operations Management Week Two Assignment 2 Instructions

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Instructions

Assignment 2 of 2:

Nelson Fabricators sells a portable EKG machine. The sales manager requires a weekly forecast of the portable EKG machine so that he can schedule production. The manager uses exponential smoothing with α = 0.30.

Data template:   EKG Machines - Week 2 Assignment 2 template.xlsx

1. Forecast the number of machines at the end of week 17.

2. Calculate the bias and MAD. 

3. Recreate your forecast with α = 0.70. Compare the MAD to your previous answer. Which forecast is better?

4.  Using SOLVER, compute the forecast with the minimum MAD by changing α.  What characteristic of the data directly influences your optimal answer?  Briefly discuss the benefit of optimizing α.

Provide your solution and responses in the attached template, using ONLY the space provided.

Week Two Assignment 2

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EKGMachines-Week2Assignment2.xlsx

Sheet1

Nelson Fabricators -- portable EKG machines
Alpha (a) = 0.58 Note: Starting condition impacts solution. See SOLVER to verify.
Week Actual Production Forecast Error Abs Error
1 434 434 Assumption for initial conditions
2 613 434 -179 179
3 640 537 -103 103
4 531 596 65 65
5 758 559 -199 199
6 711 673 -38 38
7 790 695 -95 95
8 807 750 -57 57
9 646 783 137 137
10 714 704 -10 10
11 881 710 -171 171
12 746 808 62 62
13 702 772 70 70
14 945 732 -213 213
15 977 854 -123 123
16 750 925 175 175
17
Bias MAD
a = 0.3 (was =average(f7…f21)
a = 0.7 (was =average(f7…f21)
a = optimal
ANSWERS: There is an upward trend in the data, so a higher alpha is more responsive to this trend. (A trend-adjusted method would be even better.)
Optimization provides the alpha which mimizing your historical forecasting error, and therefore is assumed to provide the best future forecast (assuming the underlying conditions remain the same as before).

EKG Machines

Nelson Fabricators

Actual Production 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 434 613 640 531 758 711 790 807 646 714 881 746 702 945 977 750 Forecast 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 434 434 537 596 559 673 695 750 783 704 710 808 772 732 854 925 0

Week

Machines Produced

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