Quantative Forecasting
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Transcript of 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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uan a ve e o s oForecasting
#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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uan a ve e o s oForecasting
Quantitative forecasting ðods fa''s in t-o
categories/( #i&e series &ode's% #rend %ro0ection 12ong ter&3% Deco&%osition ðod 1Inter&ediate ter&3
% S&oothing ðod 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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uan a ve e o s oForecasting
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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uan a ve e o s oForecasting
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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uan a ve e o s oForecasting
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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uan a ve e o s oForecasting
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