[2] Decision Making, Systems and Support

7/24/2019 [2] Decision Making, Systems and Support

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ITS 583 Business

Intelligence

Decision Making,Systems andSupport


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Learning ObjectivesO Understand the need for comuteri!ed suort ofmanagerial decision ma"ing

O Understand an earl# frame$or" for managerialdecision ma"ing

O Learn the concetual foundations of the decisionsuort s#stems %&SS'

O &escribe the concet of $or" s#stems and itsrelationshi to decision suort

O List the major tools of comuteri!ed decisionsuort

O Understand the major issues in imlementingcomuteri!ed suort s#stems


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Business (ressures

)esonsesSuort *odel


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Organi!ational

)esonsesO Be )eactive+ ,nticiative+ ,dative+ and

(roactive

O *anagers ma# ta"e actions+ such asO -mlo# strategic lanning

O Use ne$ and innovative business models

O )estructure business rocesses

O (articiate in business alliances

O Imrove cororate information s#stems

O Imrove artnershi relationshis

O -ncourage innovation and creativit# .cont./


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*anagers actions+

continuedO Imrove customer service and relationshisO *ove to electronic commerce %e0commerce'

O *ove to ma"e0to0order roduction and on0demandmanufacturing and services

O Use ne$ IT to imrove communication+ dataaccess %discover# of information'+ andcollaboration

O )esond 1uic"l# to cometitors2 actions %eg+ in

ricing+ romotions+ ne$ roducts and services'O ,utomate man# tas"s of $hite0collar emlo#ees

O ,utomate certain decision rocesses

O Imrove decision ma"ing b# emlo#ing anal#tics


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4losing the Strateg#

aO One of the major objectives of

comuteri!ed decision suort is to

facilitate closing the ga bet$eenthe current erformance of anorgani!ation and its desirederformance+ as e6ressed in itsmission+ objectives+ and goals+ and

the strateg# to achieve them


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*anagerial &ecision

*a"ingO *anagement is a rocess b# $hichorgani!ational goals are achieved b# usingresources

O Inuts7 resources

O Outut7 attainment of goals

O *easure of success7 oututs inuts

O *anagement &ecision *a"ing

O &ecision ma"ing7 selecting the best solutionfrom t$o or more alternatives


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*int!berg2s 9:

*anagerial )olesInterpersonalInterpersonal1. Figurehead

2. Leader

3. Liaison

InformationalInformational

4. Monitor5. Disseminator

6. Spokesperson

DecisionalDecisional7. Entrepreneur8. Disturan!e hand"er

#. $esour!e a""o!ator

1%. &egotiator


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&ecision0*a"ing St#leO &ecision0ma"ing st#les of users are

categori!ed as either

O ,nal#tic orO ;euristic

b# (rentice


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,nal#tic &ecision

*a"ingO )elies on information that is s#stematicall# ac1uired and

s#stematicall# evaluated to narro$ alternatives and ma"e achoice

O Use methodical+ ste0b#0ste rocedures to ma"e decisions

O ?alue 1uantitative information and the models thatgenerate and use it

O Use mathematics to model roblems and algorithms tosolve them

OThe# see" otimal rather than comletel# satisf#ingsolutions

OThe# use decision techni1ues such as grahing+ robabilit#models+ and mathematical techni1ues to ensure a sounddecision0ma"ing rocess


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;euristic &ecision

*a"ingO , heuristic decision ma"er ma"es

decisions $ith the aid of guidelines

$hich are not necessaril# aliedconsistentl# or s#stematicall#

O It is e6erienced0based

O Learn b# acting+ use trial and error to

@nd solutions+ and rel# on commonsense to guide them


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,nal#tic and ;euristic

&ecision *a"ing


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&ecision *a"ing

(rocessO *anagers usuall# ma"e decisions b# follo$inga four0ste rocess %a"a the scienti@caroach'

9 &e@ne the roblem %or oortunit#'

> 4onstruct a model that describes the real0$orld roblem

3 Identif# ossible solutions to the modeledroblem and evaluate the solutions

A 4omare+ choose+ and recommend a otentialsolution to the roblem


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&ecision ma"ing is

dicult+ becauseOTechnolog#+ information s#stems+ advancedsearch engines+ and globali!ation result in moreand more alternatives from $hich to choose

O overnment regulations and the need for

comliance+ olitical instabilit# and terrorism+cometition+ and changing consumer demandsroduce more uncertaint#+ ma"ing it more dicultto redict conse1uences and the future

O Other factors are the need to ma"e raiddecisions+ the fre1uent and unredictable changesthat ma"e trial0and0error learning dicult+ and theotential costs of ma"ing mista"es


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Ch# Use 4omuteri!ed

&SSO 4omuteri!ed &SS can facilitate decision

via7

O Seed# comutations

O Imroved communication andcollaboration

O Increased roductivit# of grou members

O Imroved data management

O Overcoming cognitive limitsO Dualit# suortE agilit# suort

O Using CebE an#$here+ an#time suort


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, &ecision Suort

Frame$or" %b# or# and Scott0*orten+ 9GH9'


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, &ecision SuortFrame$or" cont

O &egree of Structuredness %Simon+ 9GHH'

O &ecision are classi@ed as

O ;ighl# structured %a"a rogrammed'

O Semi0structured

O ;ighl# unstructured %ie+ non0rogrammed'

OT#es of 4ontrol %,nthon#+ 9G5'

O Strategic lanning %to0level+ long0range'

O *anagement control %tactical lanning'

O Oerational control


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Structured vs

Unstructured (roblemsWell-structured Problems Unstructured Problems

Definition 'an e des!ried (ith a high degree o)completeness

'annot e des!ried (ith a high degree o)completeness

'an e so"*ed (ith a high degree o)certainty

'annot e reso"*ed (ith a high degree o)certainty

E+perts usua"", agree on the !orre!tionso"ution

E+perts o)ten disagree aout the estso"ution

Educational goal LE-$& / $E-S/& / CORRECTS/L0/&S

LE-$& / '/&S$0' -&DDEFE&DREASONABLES/L0/&S

Complexity $anges )rom *er, simp"e to *er, !omp"e+ $anges )rom *er, simp"e to *er, !omp"e+

Examples $e!on!i"ing a !ompan,s ank a!!ount Estimating the sum o) )uture !ash )"o(s)rom the use o) "ong"i*ed assets

'a"!u"ating the !apita" gain on the sa"e o) aui"ding

udging the adeua!, o) an argumentpromoting a redu!tion in the !apita" gainsta+ rate

Relatively simple - 'ompute straight"ine depre!iation nterpret a !ompan,s !urrent ratio

Relatively complex - '"assi), a "ease as !apita" or operating on!ea"" ne!essar, )a!ts are assem"ed

repare operating udget )or ne+t 5 ,ears


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SimonJs &ecision0

*a"ing (rocess


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4omuter Suort for

Structured &ecisionsO Structured roblems7 encountered reeatedl#+have a high level of structure

O It is ossible to abstract+ anal#!e+ and classif#them into seci@c categories

O eg+ ma"e0or0bu# decisions+ caital budgeting+resource allocation+ distribution+ rocurement+ andinventor# control

O For each categor# a solution aroach is

develoed K/ *anagement Science


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*anagement Science

,roachO ,lso referred to as Oeration )esearchO In solving roblems+ managers should follo$ the

@ve0ste *S aroach

9 &e@ne the roblem

> 4lassif# the roblem into a standard categor#%'

3 4onstruct a model that describes the real0$orldroblem

A Identif# ossible solutions to the modeledroblem and evaluate the solutions

5 4omare+ choose+ and recommend a otentialsolution to the roblem


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,utomated &ecision

*a"ingO , relativel# ne$ aroach to suortingdecision ma"ingO ,lies to highl# structures decisions

O ,utomated decision s#stems %,&S'

%or decision automation s#stems'

O ,n ,&S is a rule0based s#stem that rovides asolution to a reetitive managerial roblem in aseci@c area

O eg+ simle0loan aroval s#stem


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,utomated &ecision

*a"ingO ,&S initiall# aeared in the airline industr#called revenue %or #ield' management %orrevenue otimi!ation' s#stems

O d#namicall# rice tic"ets based on actual

demandOToda#+ man# service industries use similar

ricing models

O ,&S are driven b# business rulesM


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,utomated &ecision0*a"ing Frame$or"


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4omuter Suort for

Unstructured &ecisionsO Unstructured roblems can be onl# artiall#suorted b# standard comuteri!ed1uantitative methods

OThe# often re1uire customi!ed solutions

OThe# bene@t from data and informationO Intuition and judgment ma# la# a role

O 4omuteri!ed communication and collaborationtechnologies along $ith "no$ledge

management is often used


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4omuter Suort for

Semi0structured(roblemsO Solving semi0structured roblems ma# involve a

combination of standard solution roceduresand human judgment

O *S handles the structured arts $hile &SS deals

$ith the unstructured artsO Cith roer data and information+ a range of

alternative solutions+ along $ith their otentialimacts


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4oncet of &ecision

Suort S#stems4lassical &e@nitions of &SS4lassical &e@nitions of &SS

Interactive comuter0based s#stems+ $hich heldecision ma"ers utili!e data and models to solve

unstructured roblemsN - Gorry and Scott-Morton,1971

&ecision suort s#stems coule the intellectualresources of individuals $ith the caabilities of thecomuter to imrove the 1ualit# of decisions It is a

comuter0based suort s#stem for managementdecision ma"ers $ho deal $ith semistructuredroblems - Keen and Scott-Morton, 1978


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&SS as an Umbrella

TermOThe term &SS can be used as an umbrella termto describe an# comuteri!ed s#stem thatsuorts decision ma"ing in an organi!ation

O -g+ an organi!ation $ide "no$ledge

management s#stemE a decision suort s#stemseci@c to an organi!ational function %mar"eting+@nance+ accounting+ manufacturing+ lanning+S4*+ etc'


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&SS as a Seci@c

,licationO In a narro$ sense &SS refers to a rocess forbuilding customi!ed alications forunstructured or semi0structured roblems

O 4omonents of the &SS ,rchitecture

O &ata+ *odel+


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;igh0Level ,rchitecture

of a &SS


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T#es of &SSOT$o major t#es7O *odel0oriented &SS

O &ata0oriented &SS

O-volution of &SS into Business IntelligenceO Use of &SS moved from secialist to managers+

and then $homever+ $henever+ $herever

O -nabling tools li"e OL,(+ data $arehousing+ data

mining+ intelligent s#stems+ delivered via Cebtechnolog# have collectivel# led to the termbusiness intelligenceP %BI' and business anal#ticsP


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The &SSBI 4onnectionOFirst+ their architectures are ver# similar

because BI evolved from &SS

OSecond+ &SS directl# suort seci@cdecision ma"ing+ $hile BI rovidesaccurate and timel# information+ andindirectl# suort decision ma"ing

OThird+ BI has an e6ecutive and strateg#

orientation+ eseciall# in its B(* anddashboard comonents+ $hile &SS+ incontrast+ is oriented to$ard anal#sts


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The &SSBI 4onnection

contOFourth+ most BI s#stems are constructed $ithcommerciall# available tools and comonents+$hile &SS is often built from scratch

OFifth+ &SS methodologies and even some tools

$ere develoed mostl# in the academic $orld+$hile BI methodologies and tools $eredeveloed mostl# b# soft$are comanies

OSi6th+ man# of the tools that BI uses are alsoconsidered &SS tools %eg+ data mining andredictive anal#sis are core tools in both'


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The &SSBI 4onnection

contO,lthough some eole e1uate &SS $ithBI+ these s#stems are not+ at resent+ thesameO some eole believe that &SS is a art of BIQone

of its anal#tical tools

O others thin" that BI is a secial case of &SS thatdeals mostl# $ith reorting+ communication+ andcollaboration %a form of data0oriented &SS'

O BI is a result of a continuous revolution and+ assuch+ &SS is one of BI2s original elements

O *SS K BI andor &SS

or #s em e$ o


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or #s em e$ o&ecision Suort %,lter+

>::A'O dro the $ord s#stemsP from &SS

O focus on decision suortP

use of an# lausible comuteri!ed or

noncomuteri!ed means for imroving decisionma"ing in a articular reetitive or nonreetitivebusiness situation in a articular organi!ationP

O Cor" s#stem7 a s#stem in $hich humanarticiants andor machines erform a business

rocess+ using information+ technolog#+ andother resources+ to roduce roducts andorservices for internal or e6ternal customers


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-lements of a Cor"

S#stem9 Business rocess ?ariations in the rocess

rationale+ se1uence of stes+ or methods used forerforming articular stes

> (articiants Better training+ better s"ills+ higherlevels of commitment+ or better real0time ordela#ed feedbac"

3 InformationBetter information 1ualit#+ informationavailabilit#+ or information resentation

A Technolog# Better data storage and retrieval+

models+ algorithms+ statistical or grahicalcaabilities+ or comuter interaction

00/


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-lements of a Cor"

S#stem cont5 (roduct and services Better $a#s to evaluate

otential decisions

4ustomersBetter $a#s to involve customers in

the decision rocess and to obtain greater clarit#about their needs

H Infrastructure *ore eRective use of sharedinfrastructure+ $hich might lead to imrovements

8 -nvironment Better methods for incororatingconcerns from the surrounding environment

G Strateg# , fundamentall# diRerent oerationalstrateg# for the $or" s#stem


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*ajor Tool 4ategories

for *SS

Source7 Table 9ASource7 Table 9A


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;#brid %Integrated'

Suort S#stemsOThe objective of comuteri!ed decision suort+regardless of its name or nature+ is to assistmanagement in solving managerial ororgani!ational roblems %and assess oortunities

and strategies' faster and better than ossible$ithout comuters

O -ver# t#e of tool has certain caabilities andlimitations B# integrating several tools+ $e canimrove decision suort because one tool can

rovide advantages $here another is $ea"

OThe trend is therefore to$ards develoing

h#brid %integrated' suort s#stem


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;#brid %Integrated'

Suort S#stemsOT#e of integrationO Use each tool indeendentl# to solve diRerent

asects of the roblem

O Use several loosel# integrated tools This mainl#

involves transferring data from one tool to anotherfor further rocessing

O Use several tightl# integrated tools From theuser2s standoint+ the tool aears as a uni@ed

s#stemO In addition to erforming diRerent tas"s

in the roblem0solving rocess+ tools cansuort each other

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[2] Decision Making, Systems and Support