Pharma Sales Forecasting

8/18/2019 Pharma Sales Forecasting

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SALES FORECASTING

HARSHALKOTHARI


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Sales forecasting is an importantassessment tool that helps toRegularly take the pulse of yourcompany get tips on e ecti!esales forecasting "ith helpsform a professional speakerauthor an# $usiness consultant"ho has $een a real estate$roker % professional insurance

salesperson an# &nancialplanner'


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Real(Time )eman

+I)EO


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,ury of E-ecuti!e opinion .etho#

)elphi .etho#

The sales force Estimation .etho#

Time series Analysis .etho#

Popular Method of SalesForecasting


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There are t"o steps in this metho#/igh ranking e-ecuti!es estimate pro$a$le

salesAn a!erage estimate is calculate#In the 0ury of e-ecuti!e opinion metho# of salesforecasting% appropriate managers "ithin the

organi1ation assem$le to #iscuss their opinionson "hat "ill happen to sales in the future'

This metho# com$ines managerial e-perience"ith statistical kno"le#ge'

,ury of E-ecuti!e opinion


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This is a 2uick an# easy "ay to turn out a forecast' This is a "ay to pool the e-perience an# 0u#gement of "ell informe# people' This may $e the only feasi$le approach if the

company is so young that it has not yetaccumulate# the e-perience to use otherforecasting metho#s'

This metho# may $e use# "hen a#e2uate salesan# market statistic are missing %or "hen these&gure ha!e not yet $een put into the form re2uire#for more sophisticate# forecasting metho#s'

Companies using the 0ury of e-ecuti!eopinion metho# #o so for one or more offour reason 3


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.ainframe computer forecasting is #one $ycon#ucting a series of meetings $et"een thet"o mainframe analysts at a company% theSer!ice #irector% an# a Research Operationsanalyst' Typically% three or four meetings arere2uire# in or#er to arri!e at a forecastconsensus' In $et"een meetings% theforecasts are e-amine# $y colleagues% $oth#omestic an# a$roa#% for fee#$ack an#reaction'

EXAMPLE 3


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Se!eral yea rs ago researchers at the Ran# corporation

#e!elope# a techni2ue for pre#icting the future that iscalle# )elphi te chni 2ue

)elp hi metho# also gathers e!aluates an# summari1ese-pert opinions as the $asis for a forecast $ut theproce#ure is more formal than that for the 0ury of e-ecuti!eopinion metho#

)elphi .etho#


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)ecision .akersSta Respon#ents

Steps in the )elphi metho#

Steps 4( !arious E"perts are as#ed to ans$er% independentl&and in $riting% a series of 'uestions a(out the future ofsales or $hate)er other area is (eing forecasted*

STEP + , A su--ar& of all the ans$ers is then prepared* .oe"pert #no$s% ho$ an& other e"pert ans$ered the 'uestions*

Three Types of 6articipants


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STEP / , 0opies of su--ar& are gi)en to theindi)idual e"perts $ith the re'uest that the& -odif&their original ans$ers if the& thin# it necessar&*

STEP 1 , Another su--ar& is -ade of these-odi2cations% and copies again are distri(uted to thee"perts* This ti-e% ho$e)er% e"pert opinions thatde)iate signi2cantl& fro- the nor- -ust (e 3usti2ed

in $riting*

STEP 4 , A third su--ar& is -ade of the opinions and 3usti2cations% and copies are once again distri(utedto the e"perts* 5usti2cation in $riting for all ans$ers

is no$ re'uired*

STEP 6 , The forecast is generated fro- all of theopinions and 3usti2cations that arise fro- step 4*


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The Sales Force .etho# is a sa les forecastingtechni2ue that pre#icts future sales $y

analy1ing the opinions of sales p eople as agr o up

Sales Force Estimation.etho#


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A sales forecast is an estimate of sales in #ollars orphysical unit in future perio# un#er a particular marketingprogram an# assume set of economic an# other factor out

si#e the unit for "hich the forecast is ma#e'

The Sales Force .etho# is a sales forecasting techni2uethat pre#icts future sales $yanaly1ing the opinions of sales people as

a group'Salespeople continually interact "ith customers%an# from this interaction they usually#e!elop a knack for pre#ictingfuture sales'


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Not greatly #i erent in principle from the simple pro0ection of past

sales is time series analysis a statistical proce#ure for stu#yinghistorical sales #ata

This proce#ure in!ol!es isolating an# measuring four chief types ofsales !ariations long term tren#s cyclical changes seasonal !ariationsan# irregular 7uctuations

One #ra"$ack of time series analysis is that it is #i8cult to 9: call theturns::

e Series analysis .etho#


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The time series analysis metho# 6re#icts the future sales$y analy1ing

The historical relationship $et"een sales An# time'

Time Series analysis

in!ol!es


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Many businesses prepare their sales forecast on the basis of pastsales.

Time series analysis involves breaking past sales down into fourcomponents

(1)The trend: Are sales growing flat or in decline.

(!) "easonal or cyclical factors. "ales are affected by swings in generaleconomic activity (e.g. increases in the disposable income ofconsumers may lead to increase in sales for products in a particularindustry). "easonal and cyclical factors occur in a regular pattern

(#) $rratic events% these include strikes fads war scares and other

disturbances to the market which need to be isolated from past salesdata in order to be able to identify the more normal pattern of sales

(&) 'esponses: the results of particular measures that have been takento increase sales (e.g. a ma or new advertising campaign).


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For a goo# of this see R' ;' .iller an# ) '<?(4>S'@' .ullick an# )')' Smith% 9:ho" toChoose the Right Forecasting Techni2ue::/ar!ar# ;usiness Re!ie" * 6age no ==(B*

Reference


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Pharma Sales Forecasting