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A large health maintenance organization (HMO) was created as a result of a corpo

ID: 3156304 • Letter: A

Question

A large health maintenance organization (HMO) was created as a result of a corporate merger two years ago. To help in preparing a staffing plan, the operations manager needs to develop a forecast for the Number of Lawsuits for Month 25. Following is the Number of Lawsuits for the past 24 months.

Month

Number of Lawsuits

Month

Number of Lawsuits

Month

Number of Lawsuits

1

16

9

51

17

63

2

25

10

56

18

57

3

16

11

67

19

48

4

24

12

45

20

55

5

38

13

53

21

61

6

46

14

61

22

51

7

54

15

55

23

56

8

52

16

69

24

53

   

Calculate your forecast results to one (1) decimal place (xx.x).

a) Make a forecast for the Number of Lawsuits for Month 25 using the moving average, weighted moving average and exponential smoothing forecasting methods on the following basis:

For the moving average, use a four-period moving average

For the weighted moving average, use a two-period weighted moving average with a weight of 0.70 for the most recent period and the appropriate weight for second most recent period.

For exponential smoothing, using an = 0.25, and the forecast for the Number of Lawsuits for Month 15 is 57.

b)From the results of a), which method provides the better forecast for Month 25? Why? Your selection criteria must be based on one of the numerical evaluation methods we used in our related homework problem using the forecast results for Month 19 through Month 24. Only saying “it is the easier method” is not acceptable.

Month

Number of Lawsuits

Month

Number of Lawsuits

Month

Number of Lawsuits

1

16

9

51

17

63

2

25

10

56

18

57

3

16

11

67

19

48

4

24

12

45

20

55

5

38

13

53

21

61

6

46

14

61

22

51

7

54

15

55

23

56

8

52

16

69

24

53

Explanation / Answer

(a)

(1) For the moving average, use a four-period moving average

      

(3)

For exponential smoothing, using an = 0.25,

t = 1
s1 = x0
s1 = 16

t = 2
st = xt - 1 + (1 - )st - 1
s2 = x2 - 1 + (1 - )s2 - 1
s2 = 0.25(x1) + (1 - 0.25)s1
s2 = 0.25(x1) + (0.75)s1
s2 = 0.25(25) + (0.75)16
s2 = 6.25 + 12
s2 = 18.25

t = 3
st = xt - 1 + (1 - )st - 1
s3 = x3 - 1 + (1 - )s3 - 1
s3 = 0.25(x2) + (1 - 0.25)s2
s3 = 0.25(x2) + (0.75)s2
s3 = 0.25(16) + (0.75)18.25
s3 = 4 + 13.6875
s3 = 17.6875

t = 4
st = xt - 1 + (1 - )st - 1
s4 = x4 - 1 + (1 - )s4 - 1
s4 = 0.25(x3) + (1 - 0.25)s3
s4 = 0.25(x3) + (0.75)s3
s4 = 0.25(24) + (0.75)17.6875
s4 = 6 + 13.265625
s4 = 19.265625

t = 5
st = xt - 1 + (1 - )st - 1
s5 = x5 - 1 + (1 - )s5 - 1
s5 = 0.25(x4) + (1 - 0.25)s4
s5 = 0.25(x4) + (0.75)s4
s5 = 0.25(38) + (0.75)19.265625
s5 = 9.5 + 14.44921875
s5 = 23.94921875

t = 6
st = xt - 1 + (1 - )st - 1
s6 = x6 - 1 + (1 - )s6 - 1
s6 = 0.25(x5) + (1 - 0.25)s5
s6 = 0.25(x5) + (0.75)s5
s6 = 0.25(46) + (0.75)23.94921875
s6 = 11.5 + 17.9619140625
s6 = 29.4619140625

t = 7
st = xt - 1 + (1 - )st - 1
s7 = x7 - 1 + (1 - )s7 - 1
s7 = 0.25(x6) + (1 - 0.25)s6
s7 = 0.25(x6) + (0.75)s6
s7 = 0.25(54) + (0.75)29.4619140625
s7 = 13.5 + 22.096435546875
s7 = 35.596435546875

t = 8
st = xt - 1 + (1 - )st - 1
s8 = x8 - 1 + (1 - )s8 - 1
s8 = 0.25(x7) + (1 - 0.25)s7
s8 = 0.25(x7) + (0.75)s7
s8 = 0.25(52) + (0.75)35.596435546875
s8 = 13 + 26.697326660156
s8 = 39.697326660156

t = 9
st = xt - 1 + (1 - )st - 1
s9 = x9 - 1 + (1 - )s9 - 1
s9 = 0.25(x8) + (1 - 0.25)s8
s9 = 0.25(x8) + (0.75)s8
s9 = 0.25(51) + (0.75)39.697326660156
s9 = 12.75 + 29.772994995117
s9 = 42.522994995117

t = 10
st = xt - 1 + (1 - )st - 1
s10 = x10 - 1 + (1 - )s10 - 1
s10 = 0.25(x9) + (1 - 0.25)s9
s10 = 0.25(x9) + (0.75)s9
s10 = 0.25(56) + (0.75)42.522994995117
s10 = 14 + 31.892246246338
s10 = 45.892246246338

t = 11
st = xt - 1 + (1 - )st - 1
s11 = x11 - 1 + (1 - )s11 - 1
s11 = 0.25(x10) + (1 - 0.25)s10
s11 = 0.25(x10) + (0.75)s10
s11 = 0.25(67) + (0.75)45.892246246338
s11 = 16.75 + 34.419184684753
s11 = 51.169184684753

t = 12
st = xt - 1 + (1 - )st - 1
s12 = x12 - 1 + (1 - )s12 - 1
s12 = 0.25(x11) + (1 - 0.25)s11
s12 = 0.25(x11) + (0.75)s11
s12 = 0.25(45) + (0.75)51.169184684753
s12 = 11.25 + 38.376888513565
s12 = 49.626888513565

t = 13
st = xt - 1 + (1 - )st - 1
s13 = x13 - 1 + (1 - )s13 - 1
s13 = 0.25(x12) + (1 - 0.25)s12
s13 = 0.25(x12) + (0.75)s12
s13 = 0.25(53) + (0.75)49.626888513565
s13 = 13.25 + 37.220166385174
s13 = 50.470166385174

t = 14
st = xt - 1 + (1 - )st - 1
s14 = x14 - 1 + (1 - )s14 - 1
s14 = 0.25(x13) + (1 - 0.25)s13
s14 = 0.25(x13) + (0.75)s13
s14 = 0.25(61) + (0.75)50.470166385174
s14 = 15.25 + 37.85262478888
s14 = 53.10262478888

t = 15
st = xt - 1 + (1 - )st - 1
s15 = x15 - 1 + (1 - )s15 - 1
s15 = 0.25(x14) + (1 - 0.25)s14
s15 = 0.25(x14) + (0.75)s14
s15 = 0.25(55) + (0.75)53.10262478888
s15 = 13.75 + 39.82696859166
s15 = 53.57696859166

t = 16
st = xt - 1 + (1 - )st - 1
s16 = x16 - 1 + (1 - )s16 - 1
s16 = 0.25(x15) + (1 - 0.25)s15
s16 = 0.25(x15) + (0.75)s15
s16 = 0.25(69) + (0.75)53.57696859166
s16 = 17.25 + 40.182726443745
s16 = 57.432726443745

t = 17
st = xt - 1 + (1 - )st - 1
s17 = x17 - 1 + (1 - )s17 - 1
s17 = 0.25(x16) + (1 - 0.25)s16
s17 = 0.25(x16) + (0.75)s16
s17 = 0.25(63) + (0.75)57.432726443745
s17 = 15.75 + 43.074544832809
s17 = 58.824544832809

t = 18
st = xt - 1 + (1 - )st - 1
s18 = x18 - 1 + (1 - )s18 - 1
s18 = 0.25(x17) + (1 - 0.25)s17
s18 = 0.25(x17) + (0.75)s17
s18 = 0.25(57) + (0.75)58.824544832809
s18 = 14.25 + 44.118408624607
s18 = 58.368408624607

t = 19
st = xt - 1 + (1 - )st - 1
s19 = x19 - 1 + (1 - )s19 - 1
s19 = 0.25(x18) + (1 - 0.25)s18
s19 = 0.25(x18) + (0.75)s18
s19 = 0.25(48) + (0.75)58.368408624607
s19 = 12 + 43.776306468455
s19 = 55.776306468455

t = 20
st = xt - 1 + (1 - )st - 1
s20 = x20 - 1 + (1 - )s20 - 1
s20 = 0.25(x19) + (1 - 0.25)s19
s20 = 0.25(x19) + (0.75)s19
s20 = 0.25(55) + (0.75)55.776306468455
s20 = 13.75 + 41.832229851341
s20 = 55.582229851341

t = 21
st = xt - 1 + (1 - )st - 1
s21 = x21 - 1 + (1 - )s21 - 1
s21 = 0.25(x20) + (1 - 0.25)s20
s21 = 0.25(x20) + (0.75)s20
s21 = 0.25(61) + (0.75)55.582229851341
s21 = 15.25 + 41.686672388506
s21 = 56.936672388506

t = 22
st = xt - 1 + (1 - )st - 1
s22 = x22 - 1 + (1 - )s22 - 1
s22 = 0.25(x21) + (1 - 0.25)s21
s22 = 0.25(x21) + (0.75)s21
s22 = 0.25(51) + (0.75)56.936672388506
s22 = 12.75 + 42.702504291379
s22 = 55.452504291379

t = 23
st = xt - 1 + (1 - )st - 1
s23 = x23 - 1 + (1 - )s23 - 1
s23 = 0.25(x22) + (1 - 0.25)s22
s23 = 0.25(x22) + (0.75)s22
s23 = 0.25(56) + (0.75)55.452504291379
s23 = 14 + 41.589378218535
s23 = 55.589378218535

t = 24
st = xt - 1 + (1 - )st - 1
s24 = x24 - 1 + (1 - )s24 - 1
s24 = 0.25(x23) + (1 - 0.25)s23
s24 = 0.25(x23) + (0.75)s23
s24 = 0.25(53) + (0.75)55.589378218535
s24 = 13.25 + 41.692033663901
s24 = 54.942033663901

month number of Lawsuits four period moving average 1 16 2 25 3 16 4 24 5 38 20.25 6 46 25.75 7 54 31 8 52 40.5 9 51 47.5 10 56 50.75 11 67 53.25 12 45 56.5 13 53 54.75 14 61 55.25 15 55 56.5 16 69 53.5 17 63 59.5 18 57 62 19 48 61 20 55 59.25 21 61 55.75 22 51 55.25 23 56 53.75 24 53 55.75
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