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Sample Coursework Paper on Operations and Supply Chain Strategy

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Sample Coursework Paper on Operations and Supply Chain Strategy
Qn.2. (a) Calculate the forecasts for periods 7 through 11 using moving average models with n = 2, n = 4, and n = 6

Period

Demand

Moving Average

N=2

N=4

N=6

1

40

 

 

 

2

33

 

 

 

3

56

 

 

 

4

43

 

 

 

5

23

 

 

 

6

45

 

 

 

7

38

36.5

43

40

8

40

44.5

38.75

39.7

9

29

49.5

41.75

40.8

10

40

33

37.25

36.3

11

 

34

36.5

35.8

 

(b) Calculating bias and MAD for each set of forecasts

For N=2

Period

Demand

Moving Average

Deviation

Absolute Deviation

7

38

36.5

2.5

2.5

8

40

44.5

4.5

4.5

9

29

49.5

-20.5

20.5

10

40

33

7

7

=34.5

MAD== 8.63

For N=4

Period

Demand

Moving Average

Deviation

Absolute Deviation

7

38

43

5

5

8

40

38.75

1.2

1.2

9

29

41.8

-12.8

12.8

10

40

37.3

2.7

2.7

=52.7

MAD== 13.2

For N=6

Period

Demand

Moving Average

Deviation

Absolute Deviation

7

38

40

2

2

8

40

39.7

0.3

0.3

9

29

40.8

-11.8

11.8

10

40

36.3

3.7

3.7

=17.8

MAD== 4.45

Qn.8. Using a three and four week moving average to forecast sales for each of the weeks (4 through 9) and (5 through 9) respectively

Week

Rental

3-Week Moving Average

4-Week Moving Average

1

1202

 

 

2

1503

 

 

3

1444

 

 

4

1254

1383

 

5

1609

1400.3

1350.8

6

1499

1435.7

1452.5

7

1689

1454

1451.5

8

1555

1599

1512.8

9

 

1581

1588

  Comparing the forecasts of these two methods using Mean Absolute Deviation (MAD)
For 3-Week Moving Average

Week

Rental

Moving Average

Deviation

Absolute Deviation

4

1254

1383

-129

129

5

1609

1400.3

208.7

208.7

6

1499

1435.7

63.3

63.3

7

1689

1454

235

235

8

1555

1599

-44

44

=680

MAD== 136

For the 4-Week Moving Average

Week

Rental

Moving Average

Deviation

Absolute Deviation

5

1609

1350.8

258.12

258.12

6

1499

1452.5

46.5

46.5

7

1689

1451.5

237.5

237.5

8

1555

1512.8

42.2

42.2

=584.4

MAD== 146.1

Qn.12. Calculating the monthly usage index and finding the total pallets for the fifth year with the use of a simple linear regression

Year

1

2

3

4

Usage Index(monthly)

Jan

1484

1482

1792

1902

1665

Feb

1394

1400

1586

1722

1525.5

March

1552

1548

1770

1876

1686.5

Apr

1796

1864

2110

2218

1997

May

2060

2198

2408

2548

2303.5

Jun

2214

2446

2652

2844

2539

July

2330

2580

2606

2972

2622

Aug

2432

2698

2872

3110

2778

Sep

2416

2682

2946

3208

2813

Oct

2262

2592

2906

3200

2740

Nov

1942

2132

2340

2806

2305

Dec

1566

1802

2046

2418

1958

 

Finding the total pallets used in the fifth year by linear regression

Month (X)

Monthly Usage Index(Y)

XY

X2

1

1665

1665

1

2

1525.5

3051

4

3

1686.5

5059.5

9

4

1997

7988

16

5

2303.5

11517.5

25

6

2539

15234

36

7

2622

18354

49

8

2778

22224

64

9

2813

25317

81

10

2740

27400

100

11

2305

25355

121

12

1958

23496

144

TOTAL

78

186661

650

AVERAGE

6.5

15555.1

54.17

 

The dependent variable here is time (X)

B=  , let n=1

A=Average for Y-B (Average for X)

B= =287.17

A=2244.4-(287.17×6.5) = 377.71

Y=A+BX, Y=377.71+287.17X   but if X=5

Y=377.71+ (5×287.17) = 1813.56

Average monthly forecasts for year 5 is 1813.56 and total forecasts would be 1813.56×12 which is 21762.77

Monthly forecasts in the fifth year is as shown below

Year

5

Jan

1987.3

Feb

1675.2

March

2530

Apr

2475

May

1907

Jun

2865

July

2498

Aug

2469

Sep

2097

Oct

2551

Nov

2312

Dec

2158

TOTAL

21762.77

AVERAGE

1813.56

 

 

 

 

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