quantative forecasting

8/9/2019 Quantative Forecasting

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OPERATIONS MANAGEMENT

O MP

By: ZAHID HUSSAIN


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Quantitative Methods of

Forecasting


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Demand ManagementQualitative Forecasting

MethodsSimle ! "eighted Moving

Average Forecasts

E#onential Smoothing

OB!"#I$!S


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Demand Management

A

B(4) C(2)

D(2) E(1) D(3) F(2)

De%endent De&and:

Raw Materials,

Component parts,

Sub-assemblies, etc.

Inde%endent De&and:

Finished Goods (how many

bikes to sell.

The coordination and control o all sources o demand

to use the producti!e system eiciently and to deli!er

product in time.


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Indeendent Demand$"hat a %rm can do to manage it&

". Can take an active ro'e to inluence demand by'(Pressuri)ing the sales *orce+(O,ering incentives to customer-(O,ering incentive to sales team.(/0 cut in rice

1(Other *actors li2e advertising etc

B. Can take a assive role and simplyrespond to demand by

'(Running at *ull caacit0+(Po3erless to change demand due to

advertising e#ense(-(Mar2et is %# in si)e

.(Other cometitive4 legal4 environmentalethical reasons(


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Methods o* Forecasting

"ll orecastin# methods can be di!ided into two broadcate#ories$

%Qua'itative%Quantitative(

&i!ision o orecastin# methods into 'ualitati!e and'uantitati!e cate#ories is based on the a!ailability o

historical time series data.

Many orecastin# techni'ues use past or historical

data in the orm o ti&e series." time series is simply

a set o obser!ations measured at successi!e points in

time or o!er successi!e periods o time.


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uan a ve e o s oForecasting

In*o on demand

! Production

DemandForecast *orOerations

Planningthes0stem

Product design,process design,

equipment,investment, capacity

planning

Schedulingthes0stem

Aggregate prod.Planning,

OperationsSchedules

5ontrollingthes0stem

Prod. Control,Inventory Control,

abor Control,Cost control

Outut o* Goods

! Services!SI"# $%&A"$ 'O(%CAS)I"# A"$ Prod. O Subs stem


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#i&e Series Mode's:% Based u%on assu&%tion that the future is a

function of %ast(

% )hat ha%%ened over a %eriod of ti&e and use aseries of %ast data to &a*e a forecast(

"asua' Mode's:% It incor%orate the varia+'es or factors that

&ight inf'uence the ,uantity +eing

forecast(% Factors 'i*e 'a-n &overs sa'es is inf'uenced +y factors

as ne- housing starts. advertising +udget. co&%etitor%rice(

uantitati!e orecastin# methods are used when

historical data on !ariables o interest are a!ailable.


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Quantitative forecasting &ethods fa''s in t-o

categories/( #i&e series &ode's% #rend %ro0ection 12ong ter&3% Deco&%osition &ethod 1Inter&ediate ter&3

% S&oothing &ethod 1Short ter&3!4%onentia' S&oothing

Naive forecasting

5( "asua' Mode'% 6egression 7 "orre'ation ana'ysis% !cono&etric &ode'% Si&u'ation &ode'% In%ut out%ut &ode'


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Naive A%%roach

!4a&%'e9

#he sa'e of a %roduct is / units in an8//(

)hat is the sa'es forecast of this %roductin Fe+8//;

So'ution9

#he sa'es forecast for the &onth of Fe+8//

-i'' +e / units of %roduct(


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Moving Average

% #o generate a forecast nu&+er ofhistorica' actua' data va'ues are used(

% It is +ased u%on the assu&%tion that the

&ar*et de&and -i'' stay fair'y steadyover ti&e(

Moving Average/4 sa'es three &onths ago3 ? i(e Su& of -eight


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Moving Average :

)eighted Moving average: !4a&%'e:Month Actual Sales - months 3eighted Moving Average

*an+- -

'eb+-

&ar+- /Apr+- 0 1/:/2:2-:3405 .00

&ay+- 7 1/:02:/2:3405 9 .//

*un+- /

*ul+- 0

Aug+- /-

Sep+- 8

Oct+- 8

"ov+- 0

$ec+- 9 1/:02:82:83405 8.00

)eight A%%'ied Ceriod

2ast &onth

5 #-o &onths ago

/ #hree &onths ago

?

an a e e o s o


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Moving Average :

)eighted Moving Average:!4a&%'e:A de%art&enta' stores &ay find that in a four &onth %eriod

the +est forecast is derived +y using the fo''o-ing data

of actua' sa'e and -eightage %ercent( Find the sa'es

forecast for fifth Month(

So'ution9

FE< (@1E3>( 1/E3>(513>(/1/3/ < G(E

FE < @1E3>1/E3>513


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QUESTIONSQUESTIONS

quantative forecasting

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