Topic 2 Demand Forecasting Models I(1)

8/11/2019 Topic 2 Demand Forecasting Models I(1)

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Time Period Demand

1 84

2 81

3 89

4 90

5 996 106

7 127

8 117

9 127

10 103

11 96

12 96

13 86

14 101

15 10916

1 2 3 4 5 6

60

70

80

90

100

110

120

130

140

Dema

Ti

Demand


2/26


3/26

Time Period Demand Last Period Forecast

1 84

2 81 84

3 89 81

4 90 89

5 99 90

6 106 99

7 127 106

8 117 127

9 127 117

10 103 127

11 96 103

12 96 96

13 86 96

14 101 86

15 109 101

16 109

Comment:This method is the navie method of forecast with maximum errors

its a short term forecast(not feasable)

0

20

40

60

80

100

120

140

Quantity


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Last Period Forecast

Demand

Last Period Forecast

Time Period


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6/26

Make Col D +ve Column F /Column B

3 3.70# 3.70#

8 8.99# 6.35#

1 1.11# 4.60#

9 9.09# 5.72#

7 6.60# 5.90#

21 16.54# 7.67#

10 8.55# 7.80#10 7.87# 7.81#

24 23.30# 9.53#

7 7.29# 9.30#

0 0.00# 8.46#

10 11.63# 8.72#

15 14.85# 9.19#

8 7.34# 9.06#

MD MPE

9.5 9.06#

st error can be 0 ,it doesnt mean yor forecast is corr

Column ! running

average

"soluteForecast Error

"solute PercentError

Mean "solutePercent Error

(MPE)


7/26

Col D running total Col F running total Col # / Col $

MD

-3 3 3.0 -1.00

5 11 5.5 0.91

6 12 4.0 1.50

15 21 5.3 2.86

22 28 5.6 3.93

43 49 8.2 5.27

33 59 8.4 3.9243 69 8.6 4.99

19 93 10.3 1.84

12 100 10.0 1.20

12 100 9.1 1.32

2 110 9.2 0.22

17 125 9.6 1.77

25 133 9.5 2.63

ect, ha!ent met the demand acta""y

Col F runningaverage

CumulativeForecast Error

Cumulative"solute

Forecast ErrorTracking%ignal


8/26

Time Period Demand

1 84

2 813 89 82.5

4 90 85.0 8.!

5 99 8".5 8#.!

6 106 ".5 "2.!

7 127 $02.5 "8.%

8 117 $$#.5 $$0.!

9 127 $22.0 $$#.!

10 103 $22.0 $2%.!

11 96 $$5.0 $$5.!

12 96 "".5 $08.!13 86 "#.0 "8.%

14 101 "$.0 "2.!

15 109 "%.5 ".%

16 $05.0 "8.!

&E'!E 100.7 101.0 101.7

M##MM 81.0 82.5 84.7

M*#MM 127.0 122.0 123.7

Two PeriodMoving Average

Forecast

Three PeriodMoving Average

Forecast

Fore

cast

1 2 3 4 5 6 7 8 9 10 11

0

20

40

60

80

100

120

140

Moving Av

Time Period

Quantity(units)


9/26

$ 2 % 5 # ! 8 " $0 $$ $20.0

20.0

0.0

#0.0

80.0

$00.0$20.0

$0.0

Moving Ave

Time Period

Demand/


10/26

8#.0

8".8

"#.0

$05.5

$$2.%

$$".%

$$8.5

$$0.8$05.5

"5.%

".8

"8.0

102.6

86.0

119.3

Four PeriodMoving Average

Forecast

12 13 14 15 16

rage Forecasts

Demand

Moving average

(Demand)

Moving average

(Demand)


11/26

$% $ $5 $#

rage

&emand

Two 'eriod (ovin) *vera)e+orecast

Three 'eriod (ovin) *vera)e+orecast

+our 'eriod (ovin) *vera)e+orecast


12/26

Time Period Demand

1 84 eig,ts

2 81 t-. is 01

3 89 t-1 is 0.

4 90 85.# t-2 is 035 99 8!."

6 106 ".%

7 127 $00.!

8 117 $$5.$

9 127 $$!.8

10 103 $2

11 96 $$%

12 96 $0.%

13 86 "!.

14 101 "$15 109 "5.5

16 $02

T,ree-4eriod 5eig,ted

moving average 6orecast

1 2 3 4 5 6 7 8 9 10 11 12 13

0

20

40

60

80

100

120

140

3-Period Weighted A

Periods

Demand/Forecast


13/26

14 15 16

erage

Demand

!ree"#eriod $eig!ted moving

average %orecast


14/26

Time Period Demand

1 24

2 26

3 22 25.0 25.04 25 2. 22.#

5 19 2.5 2.5

6 31 2%. 20.$

7 26 2." 28.8

8 18 25.$ 2#.#

9 29 2%.! $".!

10 24 2.8 2!.$

11 30 2.# 2.#

12 23 25.! 28."

13 25.2 2.2

Exponential SmoothingForecast with alpha = 0!

Exponential SmoothingForecast with alpha = 0"

1 2 3 4 5 6 7 8 9 10 11 12

0&0

5&0

10&0

15&0

20&0

25&0

30&0

35&0

!"onentia# $moothing

Time Period

Demand/Forecast


15/26

,-* ,-*

2 2 +or ex/onential smoothin(-*) o to data analsis and select ex/onential smo

2. 2. 1elect the demand coloumn

2%."2 2%."2 the value of alfa is iven in dam/in factor

2.$%# 2.$%# if alfa is .2 then dam/in factor is 0.8

2%.$088 2%.$088 out /ut rane is the couloun where ou want forecast

2.#8!0 2.#8!0

2.""#% 2.""#%

2%.55"!$ 2%.55"!$

2.#!!# 2.#!!#

2.5$82$ 2.5$82$

25.#$5! 25.#$5!

13

Demand

'#onentia *moot!ing Forecast $it!

a#!a + 0&2

'#onentia *moot!ing Forecast $it!

a#!a + 0&8


16/26

othin


17/26

l4,a 01

Period Demand

1 102 11 $0.00

3 9 $0.204 11 "."#

5 10 $0.$!

6 8 $0.$%

7 12 ".!$

8 9 $0.$!9 10 "."%

10 11 "."5

11 20 $0.$#12 11 $2.$%

13 9 $$."0

14 11 $$.%2

15 10 $$.2#16 9 $$.0$

17 11 $0.#018 4 $0.#8

19 10 ".%520 11 ".8

l4,a 07

Period Demand

1 10

2 11 $0.0

3 9 $0.84 11 ".

5 10 $0.!

6 8 $0.$

7 12 8.

8 9 $$.%9 10 ".5

10 11 "."11 20 $0.8

12 11 $8.213 9 $2.

E84onential

%moot,ing

Forecast

E84onential

%moot,ing

Forecast

1 2 3 4 5 6

0

5

10

15

20

25

!

)a#ue

10

15

20

25

!"on


18/26

14 11 ".!

15 10 $0.!16 9 $0.$

17 11 ".218 4 $0.#

19 10 5.%20 11 ".$

1 2 3 4 5 6 7 8 9

0

5


19/26

7 8 9 10 11 12 13 14 15 16 17 18 19 20

onentia# $moothing (A#"ha % &')

,ct-a Forecast

Data Point

s/ie in demand

di/ in demand

ntia# $moothing (A#"ha % &'*)

Demand

'#onentia *moot!ing Forecast


20/26

10 11 12 13 14 15 16 17 18 19 20


21/26

$"%ha 01

Period Demand

1 10 ,-*2 11 $0

3 9 $0.24 11 "."#

5 10 $0.$#8

6 8 $0.$%

7 12 ".!0!52

8 9 $0.$##0$#9 10 "."%28$28

10 11 "."#2502

11 20 $0.$5!000$"212 21 $2.$25#00$5%#

13 19 $%."0080$22"

14 22 $."20%80"8%

15 18 $#.%%#%0!2!8#16 20 $#.##"05822"

17 21 $!.%%52%##58%18 19 $8.0#8$8"%2#!

19 20 $8.2555$#$%20 21 $8.#0%#$$#"$

E84onential

%moot,ing

Forecast

1 2 3 4 5 6 7 8

0

5

10

15

20

25

!"on

D

)a#ue


22/26

9 10 11 12 13 14 15 16 17 18 19 20

ntia# $moothing (A#"ha % &')

,ct-a Forecast

ta Point

sustained increase in demand

low al/ha means slow reaction time


23/26

$"%ha 07

Period Demand

1 10 ,-*2 11 $0.00

3 9 $0.804 11 ".%#

5 10 $0.#!

6 8 $0.$%

7 12 8.%

8 9 $$.2"9 10 ".#

10 11 ".8"

11 20 $0.!812 21 $8.$#

13 19 20.%

14 22 $".2"

15 18 2$.#16 20 $8.#"

17 21 $".!18 19 20.!5

19 20 $".%520 21 $".8!

E84onential

%moot,ing

Forecast

1 2 3 4 5 6 7

0

5

10

15

20

25

!"on

P

)a#ue


24/26

9 10 11 12 13 14 15 16 17 18 19 20

ntia# $moothing (A#"ha % &'*)

,ct-a Forecast

riod

same trend as /revious sheet

hiher al/ha sees faster reaction to increase in trend


25/26

Month Actual Demand

$ $2

2 $!

% 20

$"

5 2

# 2$

! %$8 28

" %#

$0

1 2 3 4 5 6 7 8 9 100

5

10

15

20

25

30

35

40

%() + 2&55 . 10&3611111111

,ct-a Deman

Linear (,ct-a

Demand)

Month

A

ctua#Demand


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d

Date post:	02-Jun-2018
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Topic 2 Demand Forecasting Models I(1)

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