Business Finance - Operations Management Week Two Assignment 2 Instructions

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29.07.2026
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WeekTwoAssignment2InstructionsHM.docx
EKGMachines-Week2Assignment2.xlsx

WeekTwoAssignment2InstructionsHM.docx


Turnitin™
This assignment will be submitted to Turnitin™.
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

image1.png

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

oleObject1.bin

image1.emf

image2.png

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

Week

Machines Produced

oleObject1.bin

image1.emf

image2.png

WeekTwoAssignment2InstructionsHM.docx


Turnitin™
This assignment will be submitted to Turnitin™.
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

image1.png

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

Week

Machines Produced

oleObject1.bin

image1.emf

image2.png

WeekTwoAssignment2InstructionsHM.docx


Turnitin™
This assignment will be submitted to Turnitin™.
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

image1.png

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

Week

Machines Produced

oleObject1.bin

image1.emf

image2.png

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