Chapter 4, Problem 3.2Q

Summary Introduction

Case summary/Introduction: TSC is a small business dedicated to sell Photostat copy of original to university students. It also offers a range of service like passport photos, self-service copy machines, packaging and shipping. A university instructor shares his original documents before the semester starts. A manager at TSC is forecasting demand of documents. He usually estimated two-third of student’s enrollment.

Characters in the case:TSC Company.

Adequate Information: A university instructor shares his original documents before the semester starts. A manager at TSC is forecasting demand of documents. He usually estimated two-third of student’s enrollment.

Interpretation:Comparison of methodology with rule of thumb.

Explanation of Solution

Rule of thumb means that a course pack production batch size should be two-thirds the size of the reported enrollment.

Comparison can be done by using Mean Square Error.

There are different courses for students in which a number of students are enrolled. However, numbers produced are the Photostat copies of original documents which are required by university students. In case, a student requires a copy of document, number 1 symbol is used for calculation and 0 is used for no requirement.

Numbers produced	No. enrolled	Optional? (1=Yes, 0=No)	Forecast (Traditional)	Error	Error^2	Forecast (regression)	Error	Error^2
101	220	1	146.67	-45.67	2085.44	89.62	-11.39	129.62
95	210	1	140.00	-45.00	2025.00	82.63	-12.38	153.14
176	200	0	133.33	42.67	1820.44	160.13	-15.87	251.95
81	100	0	66.67	14.33	205.44	90.23	9.23	85.14
36	38	0	25.33	10.67	113.78	46.89	10.89	118.57
38	40	0	26.67	11.33	128.44	48.29	10.29	105.82
195	450	1	300.00	-105.00	11025.00	250.39	55.38	3067.50
159	400	1	266.67	-107.67	11592.11	215.44	56.43	3184.91
96	120	0	80.00	16.00	256.00	104.21	8.21	67.35
40	42	0	28.00	12.00	144.00	49.69	9.69	93.80
244	310	0	206.67	37.33	1393.78	237.02	-6.98	48.76
238	280	0	186.67	51.33	2635.11	216.05	-21.95	481.93
46	50	0	33.33	12.67	160.44	55.28	9.28	86.06
50	50	0	33.33	16.67	277.78	55.28	5.28	27.85
88	100	0	66.67	21.33	455.11	90.23	2.23	4.96
190	350	1	233.33	-43.33	1877.78	180.49	-9.52	90.54
25	25	0	16.67	8.33	69.44	37.80	12.80	163.89
300	360	0	240.00	60.00	3600.00	271.97	-28.03	785.85
251	300	0	200.00	51.00	2601.00	230.03	-20.97	439.87
231	280	0	186.67	44.33	1965.44	216.05	-14.95	223.59
101	250	1	166.67	-65.67	4312.11	110.59	9.58	91.87
91	250	1	166.67	-75.67	5725.44	110.59	19.59	383.57
37	40	0	26.67	10.33	106.78	48.29	11.29	127.40
201	250	0	166.67	34.33	1178.78	195.08	-5.92	35.08
180	220	0	146.67	33.33	1111.11	174.11	-5.89	34.73
33	35	0	23.33	9.67	93.44	44.79	11.79	139.05
34	35	0	23.33	10.67	113.78	44.79	10.79	116.47
77	150	1	100.00	-23.00	529.00	40.69	-36.32	1318.78
243	300	0	200.00	43.00	1849.00	230.03	-12.97	168.30
62	120	1	80.00	-18.00	324.00	19.72	-42.29	1788.02
49	120	1	80.00	-31.00	961.00	19.72	-29.29	857.61
48	50	0	33.33	14.67	215.11	55.28	7.28	52.95
20	20	0	13.33	6.67	44.44	34.31	14.31	204.69
MSE (Average)					1848.35			452.41

Conclusion

The value of MSE clearly shows that the regression forecast is better than the traditional forecast as traditionally, more than 33% of the copies were wasted and at present, error is less, which implies less wastage of copies.