Exponential Smoothing

Period (t) 1 2 3 4 5 6 7 8 9

Actual Demand 11155 4593 2866 3095 7487 7580 3221 1947 2104

Forecast, alpha factor of 0.5 6000 8578 6585 4726 3910 5699 6639 4930 3439

ME - -3985 -3719 -1631 3577 1881 -3418 -2983 -1335

MAD - 3985 3719 1631 3577 1881 3418 2983 1335

MAPE - 87% 130% 53% 48% 25% 106% 153% 63%

Step 1:

Exponential smoothing formula: = ( α * the previous week demand) + ( (1 - α) * the previous week forecast)

C5 = (0.5*B4)+((1-0.5)*B5)

Step 2:

Mean error: = Actual Demand - Forecasted DemandC6 = C4-C5

Step 3:

Mean Absolute Deviation = ABS (Mean Error)C7 = ABS(C6)

Step 4:

Mean Absolute Percentage Error: = Mean Absolute Deviation / Actual Demand (format as a percentage to 1 decimal place)C8 = C7/C4

Step 5: Copy the formulas across to find the forecast, ME, MAD, MAPE until week 52.

Step 6: Move to sheet Exercise 2, using the tabs below

Use the exponential smoothing formula to calculate the forecast for week 2. Use an alpha factor

of 0.5.

Find the mean error, this is the difference between the actual demand and the demand

forecasted

Find the mean absolute deviation, this is the absolute difference between the actual demand

and the demand forecasted. Therefore all deviations are positive.

Find the mean absolute percentage error.

0.867515785

10 11 12 13 14 15 16 17 18 19 20 21 22

7184 2968 1845 1994 5190 1845 2222 2400 8723 4489 2800 3026 5855

2771 4978 3973 2909 2451 3821 2833 2527 2464 5593 5041 3921 3473

4413 -2010 -2128 -915 2739 -1976 -611 -127 6259 -1104 -2241 -895 2382

4413 2010 2128 915 2739 1976 611 127 6259 1104 2241 895 2382

61% 68% 115% 46% 53% 107% 27% 5% 72% 25% 80% 30% 41%

( α * the previous week demand) + ( (1 - α) * the previous week forecast)

0.868

Mean Absolute Deviation / Actual Demand (format as a percentage to 1 decimal place)

Copy the formulas across to find the forecast, ME, MAD, MAPE until week 52.

Correct

Use the exponential smoothing formula to calculate the forecast for week 2. Use an alpha factor

of 0.5.

Find the mean error, this is the difference between the actual demand and the demand

forecasted

Find the mean absolute deviation, this is the absolute difference between the actual demand

and the demand forecasted. Therefore all deviations are positive.

Find the mean absolute percentage error.

Correct

Correct

Correct

23 24 25 26 27 28 29 30 31 32

13118 5400 3370 3640 14710 6057 3778 2041 7671 6317

4664 8891 7146 5258 4449 9579 7818 5798 3920 5795

8454 -3491 -3776 -1618 10261 -3522 -4040 -3757 3751 522

8454 3491 3776 1618 10261 3522 4040 3757 3751 522

64% 65% 112% 44% 70% 58% 107% 184% 49% 8%

33 34 35 36 37 38 39 40 41

3941 4257 8238 14917 6142 3832 4140 13588 5595

6056 4999 4628 6433 10675 8408 6120 5130 9359

-2115 -742 3610 8484 -4533 -4576 -1980 8458 -3764

2115 742 3610 8484 4533 4576 1980 8458 3764

54% 17% 44% 57% 74% 119% 48% 62% 67%

42 43 44 45 46 47 48 49 50

3491 3770 9121 11745 4836 3017 3260 10033 4130

7477 5484 4627 6874 9310 7073 5045 4152 7093

-3986 -1714 4494 4871 -4474 -4056 -1785 5881 -2963

3986 1714 4494 4871 4474 4056 1785 5881 2963

114% 45% 49% 41% 93% 134% 55% 59% 72%

51 52

2577 278

5611 4094

-3034 -3816

3034 3816

118% 1373%

Exponential Smoothing and 3 Month Moving Average Exercise

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

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32

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34

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37

38

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ AK AL AM AN AO AP AQ AR AS AT AU AV AW AX AY AZ BA

Exponential Smoothing

Period (t) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52

Actual Demand 11155 4593 2866 3095 7487 7580 3221 1947 2104 7184 2968 1845 1994 5190 1845 2222 2400 8723 4489 2800 3026 5855 13118 5400 3370 3640 14710 6057 3778 2041 7671 6317 3941 4257 8238 14917 6142 3832 4140 13588 5595 3491 3770 9121 11745 4836 3017 3260 10033 4130 2577 278

Forecast 6000 7547 6660 5522 4794 5602 6195 5303 4296 3639 4702 4182 3481 3035 3681 3130 2858 2721 4521 4512 3998 3706 4351 6981 6507 5566 4988 7905 7350 6279 5007 5806 5960 5354 5025 5989 8667 7910 6686 5922 8222 7434 6251 5507 6591 8137 7147 5908 5114 6589 5852 4869

ME - -2954 -3794 -2427 2693 1978 -2974 -3356 -2192 3545 -1734 -2337 -1487 2155 -1836 -908 -458 6002 -32 -1712 -972 2149 8767 -1581 -3137 -1926 9722 -1848 -3572 -4238 2664 511 -2019 -1097 3213 8928 -2525 -4078 -2546 7666 -2627 -3943 -2481 3614 5154 -3301 -4130 -2648 4919 -2459 -3275 -4591

MAD - 2954 3794 2427 2693 1978 2974 3356 2192 3545 1734 2337 1487 2155 1836 908 458 6002 32 1712 972 2149 8767 1581 3137 1926 9722 1848 3572 4238 2664 511 2019 1097 3213 8928 2525 4078 2546 7666 2627 3943 2481 3614 5154 3301 4130 2648 4919 2459 3275 4591

MAPE - 64% 132% 78% 36% 26% 92% 172% 104% 49% 58% 127% 75% 42% 100% 41% 19% 69% 1% 61% 32% 37% 67% 29% 93% 53% 66% 31% 95% 208% 35% 8% 51% 26% 39% 60% 41% 106% 62% 56% 47% 113% 66% 40% 44% 68% 137% 81% 49% 60% 127% 1652%

Alpha Factor 0.3

-13516 160876 5023%

EXERCISE 2: Change the alpha factor to values between 0 and 1. Try to find the best alpha factor.

0

2000

4000

6000

8000

10000

12000

14000

16000

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52

Dem

an

d

Week

Actual Demand Forecast Linear (Forecast)

Exercise 2

Reflection:

Question 1a) Is exponential smoothing a good technique for using in the aerial simulation game?

Question 1b) Why? More react to recent changes rather than all past observation.

Question 2 What could you do to improve the accuracy of the forecast?

Is exponential smoothing a good technique for using in the aerial simulation game? No

Exponential Smoothing (monthly)

Period (t) 1 2 3 4 5 6 7 8

Actual Demand 21709 20235 14101 12014 15626 20949 27777 19807

Forecast 21661 21676 21244 19101 16975 16570 17884 20852

ME - -1441 -7143 -7087 -1349 4379 9893 -1045

MAD - 1440.723 7142.506 7086.795 1349.031 4379.099 9893.264 1044.715

MAPE - 7.1% 50.7% 59.0% 8.6% 20.9% 35.6% 5.3%

Alpha Factor 0.3

EXERCISE 4: Change the alpha factor to values between 0 and 1. Try to find the best alpha factor.

0

5000

10000

15000

20000

25000

30000

35000

1 2 3 4 5 6 7 8 9 10

De

man

d

Month

Actual Demand Forecast

9 10 11 12 13

31353 27702 21977 22858 17018

20538 23783 24958 24064 23702

10815 3919 -2981 -1206 -6684

10814.7 3919.29 2981.497 1206.048 6684.234

34.5% 14.1% 13.6% 5.3% 39.3%

Change the alpha factor to values between 0 and 1. Try to find the best alpha factor.

11 12 13

3 Month Moving Average

Period (t) 1 2 3 4 5 6 7 8 9 10

Actual History 11155 4593 2866 3095 7487 7580 3221 1947 2104 7184

3 month moving average - - - 6204.7 3518 4483 6054 6096 4249 2424

ME - - - -3110 3969 3097 -2833 -4149 -2145 4760

MAD - - - 3110 3969 3097 2833 4149 2145 4760

MAPE - - - 100% 53% 41% 88% 213% 102% 66%

182818 5697%

Step 1:Three month average: = (Month 1 Demand + Month 2 Demand + Month 3 Demand) / 3

E5 = SUM(B4:D4)/3

]

Step 2:

Mean error: = Actual Demand - Forecasted DemandE6 = E4 - E5

Step 3:

Mean Absolute Deviation = ABS (Mean Error)E7 = ABS(E6)

Step 4:Mean Absolute Percentage Error: = Mean Absolute Deviation / Actual Demand (format as a percentage to 1 decimal place)

E8 = E7/E4

Step 5: Copy the formulas across to find the forecast, ME, MAD, MAPE until week 52.

Find the average of the previous three months

Find the mean error, this is the difference between the actual demand and the demand

forecasted

Find the mean absolute deviation, this is the absolute difference between the actual

demand and the demand forecasted. Therefore all deviations are positive.

Find the mean absolute percentage error.

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

2968 1845 1994 5190 1845 2222 2400 8723 4489 2800 3026 5855 13118 5400 3370

3745 4085 3999 2269 3010 3010 3086 2156 4448 5204 5337 3438 3894 7333 8124

-777 -2240 -2005 2921 -1165 -788 -686 6567 41 -2404 -2311 2417 9224 -1933 -4754

777 2240 2005 2921 1165 787.7 685.7 6567 40.67 2404 2311 2417 9224 1933 4754

26% 121% 101% 56% 63% 35% 29% 75% 1% 86% 76% 41% 70% 36% 141%

(Month 1 Demand + Month 2 Demand + Month 3 Demand) / 3

Mean Absolute Deviation / Actual Demand (format as a percentage to 1 decimal place)

Copy the formulas across to find the forecast, ME, MAD, MAPE until week 52.

Find the average of the previous three months

Find the mean error, this is the difference between the actual demand and the demand

forecasted

Find the mean absolute deviation, this is the absolute difference between the actual

demand and the demand forecasted. Therefore all deviations are positive.

Find the mean absolute percentage error.

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

3640 14710 6057 3778 2041 7671 6317 3941 4257 8238 14917 6142 3832 4140 13588

7296 4137 7240 8136 8182 3959 4497 5343 5976 4838 5479 9137 9766 8297 4705

-3656 10573 -1183 -4358 -6141 3712 1820 -1402 -1719 3400 9438 -2995 -5934 -4157 8883

3656 10573 1183 4358 6141 3712 1820 1402 1719 3400 9438 2995 5934 4157 8883

100% 72% 20% 115% 301% 48% 29% 36% 40% 41% 63% 49% 155% 100% 65%

41 42 43 44 45 46 47 48 49 50 51 52

5595 3491 3770 9121 11745 4836 3017 3260 10033 4130 2577 278

7187 7774 7558 4285 5461 8212 8567 6533 3704 5437 5808 5580

-1592 -4283 -3788 4836 6284 -3376 -5550 -3273 6329 -1307 -3231 -5302

1592 4283 3788 4836 6284 3376 5550 3273 6329 1307 3231 5302

28% 123% 100% 53% 54% 70% 184% 100% 63% 32% 125% 1907%

Aerials demand data:

Period Previous Year Current Year1 11155 12500

2 4593 5200

3 2866 3600

4 3095 4800

5 7487 6000

6 7580 8500

7 3221 4700

8 1947 3200

9 2104 3200

10 7184 7600

11 2968 3300

12 1845 2400

13 1994

14 5190

15 1845

16 2222

17 2400

18 8723

19 4489

20 2800

21 3026

22 5855

23 13118

24 5400

25 3370

26 3640

27 14710

28 6057

29 3778

30 2041

31 7671

32 6317

33 3941

34 4257

35 8238

36 14917

37 6142

38 3832

39 4140

40 13588

41 5595

42 3491

43 3770

44 9121

45 11745

46 4836

47 3017

48 3260

49 10033

50 4130

51 2577

52 278