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Business Intelligence

Unit 1

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Decision Support

System

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•

Managers generate the informationthey need for more unstructuredtypes decisions in an interactive ,simulation-based process.

• !or Eg electronic spreadsheetsallo a Manager to pose a series ofhat-if "uestions and receive

interactive responses to such adhoc re"uests for information.

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Decision Support System

• # Decision Support System %DSS& is a computer-based 'nformation System that supports business ororganizational decision-making activities.

•   DSSs serve the management, operations, and

planning levels of an organization %usually mid andhigher management&

• 't helps to make decisions, hich may be rapidlychanging and not easily speci(ed in advance

%)nstructured and Semi-Structured decisionproblems&.

• Decision support systems can be either fullycomputerized, human or a combination of both.

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DSS by its characteristics

• DSS tends to be aimed at the less ell structured,underspeci(ed problem that upperlevel managers typically face*

• DSS attempts to combine the use of models or

analytic techni"ues ith traditional data access andretrieval functions*

• DSS speci(cally focuses on features hich makethem easy to use by non-computer people in an

interactive mode* and• DSS emphasizes +eibility and adaptability to

accommodate changes in the environment andthe decision-making approach of the user.

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• DSSs include knoledge-based systems.

• # properly designed DSS is an interactive softare-based

system intended to help decision makers compile usefulinformation from a combination of ra data, documents,and personal knoledge, or business models to identifyand solve problems and make decisions.

•  Typical information that a decision support application

might gather and present includes

• 'nventories of information assets %including legacy andrelational data sources, cubes, data arehouses,and data marts&,

•

omparative sales (gures beteen one period and thenet,

• /ro0ected revenue (gures based on product salesassumptions.

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History

•  The concept of Decision Support has evolved from tomain areas of research

• The theoretical studies of organizational Decision -Maing done at the arnegie 'nstitute of

 Technology during the late 1234s and early 1254s, andthe technical !or on Technology in the 1"#$s%

• DSS became an area of research of its on in the middle

of the 1264s, before gaining in intensity during the1274s.

• 'n the middle and late 1274s, a" Eecutive 'nformationSystems %E'S&, 8roup Decision support systems %8DSS&,and 9rganizational Decision Support Systems %9DSS&

evolved from the single user and model-oriented DSS.

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History

• 'n the 1264s DSS as described as :a computer-based system to aid Decision Making:.

•  'n the late 1264s the DSS movement startedfocusing on :interactive computer-based systems

hich help decision-makers utilize data bases andmodels to solve ill-structured problems:.

• 'n the 1274s DSS should provide systems :usingsuitable and available technology to improve

e;ectiveness of managerial and professionalactivities<

•  Toards the end of 1274s DSS faced a ne challengetoards the design of 'ntelligent =orkstations.

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• 'n 1276, Teas 'nstruments completeddevelopment of the 8ate #ssignment DisplaySystem %8#DS& for )nited #irlines.

• This decision support system is credited ithsigni(cantly reducing travel delays by aidingthe management of ground operations atvarious airports, beginning ith 9>?are

'nternational #irport in hicago and Stapleton#irport in Denver olorado.

• @eginning in about 1224, Data=arehousing and 9n-line #nalytical/rocessing %9A#/& began broadening therealm of DSS. #s the turn of the millenniumapproached, ne =eb-based analyticalapplications ere introduced.

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•  The advent of better reporting technologies hasseen DSS start to emerge as a critical component ofManagement Design.

• DSS also have a eak connection to the userinterface paradigm of hypertet. @oth the )niversityof Bermont /C9M'S system %for medical decisionmaking& and the arnegie Mellon 98FMS system

%for military and business decision making& eredecision support systems hich also ere ma0orbreakthroughs in user interface research.

• !urthermore, although hypertet researchers havegenerally been concerned ith information

overload, certain researchers, notably DouglasEngelbart, have been focused on decision makers inparticular.

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&omponents

• Design of Decision Support System

•  Three fundamental components of aDSS architecture are

1. The database %or knoledge base&,

G. The model %i.e., the decision contetand user criteria&, and

H. The user interface.

I. The users themselves

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De'elopmentframe!ors

• DSS systems are not entirely di;erent from othersystems and re"uire a structured approach. Such aframeork includes people, technology, and thedevelopment approach.

• The Early !rameork of Decision Support Systemconsists of four phases

1% Intelligence Searching for conditions that call fordecision.

(%Design Developing and analyzing possiblealternative actions of solution.

)%&hoice Selecting a course of action among those.

*%Implementation #dopting the selected course of

action in decision situation.

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DSS Technology +e'els ,of hard!are and soft!are may include.

•  This is the part of the application that allos thedecision maker to make decisions in a particularproblem area. The user can act upon that particularproblem.

• 8enerator contains ?ardaresoftare environment that

allos people to easily develop speci(c DSSapplications. This level makes use of case tools orsystems such as rystal, #nalytica and iThink.

•  Tools include loer level hardaresoftare. DSSgenerators including special languages, functionlibraries and linking modules

• #n iterative developmental approach allos for the DSSto be changed and redesigned at various intervals. 9ncethe system is designed, it ill need to be tested and

revised here necessary for the desired outcome.

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&lassi/cation

•  There are several ays to classify DSS applications. Jotevery DSS (ts neatly into one of the categories, but may bea mi of to or more architectures.

•   DSS is classi(ed into the folloing si frameorks

1. tet-oriented DSS,G. database-oriented DSS,

H. spreadsheet-oriented DSS,

I. solver-oriented DSS,

3. rule-oriented DSS,

5. compound DSS.

•. # compound DSS is the most popular classi(cation for aDSS. 't is a hybrid system that includes to or more of the(ve basic structures described

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•

 The support given by DSS can beseparated into three distinct,interrelated categories

•

 /ersonal Support,•  8roup Support, and

• 9rganizational Support.

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DSS components may be classi(ed

as

• Inputs. !actors, numbers, andcharacteristics to analyze

• User 0no!ledge and

2pertise. 'nputs re"uiring manualanalysis by the user

• 3utputs. Transformed data from

hich DSS :decisions: are generated• Decisions. Cesults generated by the

DSS based on user criteria

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• DSSs hich performselected cognitive decision-making

functions and are based on arti(cialintelligence or intelligentagents technologies are called 'ntelligentDecision Support Systems %'DSS&

•  The nascent (eld of Decisionengineering treats the decision itself as anengineered ob0ect, and applies engineering

principles such as Design and Kualityassurance to an eplicit representation ofthe elements that make up a decision.

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4roup Decision Support

System

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Time56lace 7rame!or 

• Same TimeSame /lace

 – decision room

• Same TimeDi;erent /lace – telephone conferencing, video

conferencing

• Di;erent TimeSame /lace – pro0ectteam rooms, shared oLces

• Di;erent TimeDi;erent /lace – email, ork+o management systems

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8roup Decision SupportSystems %8DSS&

• 8roup Support Systems %8SS&

• Electronic Meeting Systems

• ollaborative omputing

• Evolved as information technology researchersrecognized that technology could bedeveloped for supporting meeting activities

 – 'dea generation

 – onsensus building – #nonymous ranking

 – Boting, etc.

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Important &haracteristicsof a 4DSS

• Specially Designed 'nformationSystem

• 8oal of Supporting Groups ofDecision Makers

• Easy to Aearn and )se

•

May be designed for one type ofproblem or for manyorganizational decisions

• Designed to encourage group

activities

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 Three Aevels of 8DSSSupport

• @ased on DeSanctis and 8allupe

 – Aevel 1 /rocess Support

 – Aevel G Decision-making Support – Aevel H Cules of order

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Aevel 1 /rocess Support

• Supports the basic communicationprocess beteen participants – electronic messaging

 – netork linking the /s – public screen

 – anonymous input of votes and ideas

 – solicitation of ideas or votes

 – summary and display of ideas andopinions

 – format for an agenda

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Aevel G Decision-MakingSupport

• Decision Modeling and 8roup Decision Techni"ues aimed at reducing )ncertaintyand that occur in the group decisionprocess

• adds capabilities for modeling anddecision analysis – planning and (nancial models

 –

decision trees – probability assessment models

 – resource allocation models

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Aevel H Cules of 9rder

• Cule of order ensures that the group involved inthe group meeting can conduct its business ina ay that is both fair and e;ective.

• haracterized by machine-induced groupcommunication patterns

• ontrol the pattern, timing, or content ofinformation echange

•

Special softare containing rules of order isadded – rules determining the se"uence of speaking, the

appropriate response, or voting rules

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8roupare Technologies

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4roup!are technologies

• 8roupare is de(ned as any softare that enablesgroup collaboration over a netork.

•  These technologies have the potential to increasecollaboration at a distance hile reducing the cost of

travel and the time knoledge orkers aste intransit.

4roup!are pro'ides

• +eible communication structures %connecting peoplein ne ays&,

• increased communication speed,

•  increased ork performance and productivity,

• organizational memory capability, etc.

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2amples of 4roup!areTechnologies include.

• Shared authoring tools such as MS 38ce applications %=ord,Ecel, etc.& hich include common ord processing programs,graphics programs and sound-editing facilities. Many stand-alone applications can be considered as groupare if they canaccess and modify a document on the eb or a common server

• E-mail systems such as MS 3utloo 2press, support multipletet-based communications and is the most often usedgroupare 9nline forums are real-time, tet-based systems thatallo group posting and response to tet messages. They areself-archiving, in that the se"uence of tet-based conversationsinvolving dozens or even hundreds of contributors is maintainedfor revie by others

• 'nstant messaging such as 93+ messenger, is a groing formof groupare that allos knoledge orkers orking aay fromtheir desks to echange short items of information

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• Screen sharing allos a user ith the appropriate accessprivileges to connect to and take control of a remote /. 't ispopular in training and troubleshooting situations here asupport person can sho the trainee at a remote site ho toperform an operation and then atch as the trainee attempts todo the operation

• lectronic !hiteboard provides a virtual hiteboard draingspace that enables multiple collaborators to take turns atauthoring and modifying hand-dran graphics or simply by

posting a slide for a presentation. They are used in con0unctionith other products, such as videoconferencing hich is the real-time, multi-ay broadcasting of video and audio

• :ideoconferencing such as Sype conferences; allo real-time, multi-ay broadcasting of video and audio, usingtelephone lines for audio and the 'nternet or other netorks forthe video channels

• Multimodal conferencing supports real-time group sharing ofan electronic hiteboard, a tet forum, audio, and multiple-channel video and audio.

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4roup!are 

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?

•  Tools %hardare, softare, processes& thatsupport person-to-person collaboration

•  This can include e-mail, bulletin boards,conferencing systems, decision supportsystems, video and ork+o systems,etcN

• Some common groupare acronyms – 4roup Support Systems ,4SS

 – 4roup Decision Support Systems ,4DSS – lectronic Meeting Systems ,MS

 – Bulletin Board Systems ,BBS

 – 4roup &ollaboration Systems ,4&S – &omputer-Supported &ooperati'e

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4roup!are and +e'els of&ollaboration

• 8roupare can be divided into three categories depending on thelevel of collaboration

1% &ommunication can be thought of as unstructured interchange ofinformation. # phone call or an 'M hat discussion are eamples ofthis.

(% &onferencing %or collaboration level, as it is called in the academicpapers that discuss these levels& refers to interactive ork toard ashared goal. @rainstorming or Boting are eamples of this.

)% &o-ordination refers to comple interdependent ork toard ashared goal. # good metaphor for understanding this is to thinkabout a sports team* everyone has to contribute the right play at

the right time as ell as ad0ust their play to the unfolding situation -but everyone is doing something di;erent - in order for the team toin. That is comple interdependent ork toard a shared goalcollaborative management.

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lectronic &ommunication Tools

• Electronic communication tools send messages, (les,data, or documents beteen people and hencefacilitate the sharing of information. Eamples include

• Synchronous conferencing

• #synchronous conferencing• E-mail

• !aing

• Boice mail

•

=ikis• =eb publishing

• Cevision control

l t i & f i

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lectronic &onferencingTools

•Electronic conferencing tools facilitate the sharing of information, but in a more interactiveay. Eamples include

•'nternet forums %also knon as message boards or discussion boards& O a virtualdiscussion platform to facilitate and manage online tet messages

•9nline chatO a virtual discussion platform to facilitate and manage real-time tetmessages

•

'nstant Messaging• Telephony O telephones allo users to interact

•Bideoconferencing O netorked /s share video and audio signals

•Data conferencing O netorked /s share a common hiteboard that each user canmodify

•#pplication sharing O users can access a shared document or application from theirrespective computers simultaneously in real time

•Electronic meeting systems %EMS& O originally these ere described as :electronic meetingsystems,: and they ere built into meeting rooms. These special purpose rooms usuallycontained video pro0ectors interlinked ith numerous /s* hoever, electronic meetingsystems have evolved into eb-based, any time, any place systems that ill accommodate:distributed: meeting participants ho may be dispersed in several locations.

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&ollaborati'e Management ,coordination Tools

• ollaborative management tools facilitate and manage groupactivities. Eamples include

• lectronic calendars %also called timemanagement softare& O schedule events and automaticallynotify and remind group members

• 6ro@ect management systems O schedule, track, and chartthe steps in a pro0ect as it is being completed

• 3nline proo/ng O share, revie, approve, and re0ect ebproofs, artork, photos, or videos beteen designers,customers, and clients

•

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• nterprise Boomaring O collaborativebookmarking engine to tag, organize, share, andsearch enterprise data

• 6rediction Marets O let a group of peoplepredict together the outcome of future events

• 2tranet Systems %sometimes also knon as>pro0ect etranets>& O collect, organize, manage

and share information associated ith the deliveryof a pro0ect %e.g. the construction of a building&

• Social Soft!are Systems O organize socialrelations of groups

• 9nline SpreadsheetsO collaborate and sharestructured data and information

• &lient 6ortals O interact and share informationith your clients in a private online environment

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@ene(ts of 8DSS

• supports parallel generation of ideas

• supports larger groups

• rapid and easy access to eternalinformation

• parallel computer discussion

• anonymous input

• automatic documentation of thegroup meetings

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4roup!are,&ollaborati'e soft!are

• ollaboration, ith respect toinformation technology, seems tohave several de(nitions. Some are

defensible but others are so broadthey lose any meaningful application.

• )nderstanding the di;erences in

human interactions is necessary toensure the appropriate technologiesare employed to meet interaction

needs.

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&ollaborati'e Soft!are

• ollaborative softare helps facilitate the action-orientedteam !oring together o'er geographic distances byproviding tools that help communication, collaboration and theprocess of problem solving by providing the team ith acommon means for communicating ideas and brainstorming.

• #dditionally; collaborati'e soft!are may support pro@ectmanagement functions; such as tas assignments; time-management ith deadlines and shared calendars.

•  The artifacts, the tangible evidence of the problem solvingprocess, including the (nal outcome of the collaborative e;ort,

typically reCuire documentation and archi'ing of theprocess itself; and may in'ol'e archi'ing pro@ect plans;deadlines and deli'erables%

h i i hi h h

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 The primary ays in hich humansinteract in an organization

• Conversational interaction is an echange of information beteento or more participants here the primary purpose of the interaction isdiscovery or relationship building. There is no central entity aroundhich the interaction revolves but is a free echange of informationith no de(ned constraints generally focused on personal

eperiences. ommunication technology such as telephones, instantmessaging, and e-mail are generally suLcient for conversationalinteractions.

• Transactional interaction involves the echange of transactionentities here a ma0or function of the transaction entity is to alter therelationship beteen participants. The transaction entity is in a

relatively stable form and constrains or de(nes the ne relationship.9ne participant echanges money for goods and becomes a customer. Transactional interactions are most e;ectively handled by transactionalsystems that manage state and commit records for persistent storage.

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• 'n Collaborative Interactions the main function ofthe participants> relationship is to alter a collaboration

entity %i.e., the converse of transactional&. Thecollaboration entity is in a relatively unstable form.

• Eamples include the

•  development of an idea,

• the creation of a design,

• the achievement of a shared goal. Therefore, realcollaboration technologies deliver the functionality formany participants to augment a common deliverable.

• Cecord or document management,

•  threaded discussions,

•  audit history, and other mechanisms designed tocapture the e;orts of many into a managed contentenvironment are typical of collaboration technologies.

@ th d d di id

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@y method used e can divideollaborative Softare into

• =eb-based collaborative tools

• Softare collaborative tools

@ d di id

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@y area served e can dividecollaborative softare into

• Fnoledge management tools

• Fnoledge creation tools

• 'nformation sharing tools

• ollaborative pro0ect managementtools

& ll b ti 6 @ t

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&ollaborati'e 6ro@ectManagement Tools

• &ollaborati'e pro@ect management tools ,&6MT arevery similar to collaborative management tools %MT&ecept that MT may only facilitate and manage a certaingroup activities for a part of a bigger pro0ect or task,

•  hile /MT covers all detailed aspects of collaborationactivities and management of the overall pro0ect and itsrelated knoledge areas.

• #nother ma0or di;erence is that MT may include socialsoftare, Document Management System %DMS& and

)ni(ed ommunication %)&•  hile /MT mostly considers business or corporate

related goals ith some kind of social boundaries mostcommonly used for pro0ect management.

& ll b ti @ t

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&ollaborati'e pro@ectmanagement tools ,&6MT

• /MT facilitate and manage social or group pro0ect basedactivities.

• Eamples include

• Electronic calendars

• /ro0ect management systems

• Cesource Management

• =ork+o systems

• Fnoledge management

• /rediction markets

• Etranet systems• Social softare

• 9nline spreadsheets

• 9nline artork proo(ng, feedback, revie and approval tool

& ll b ti M t

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&ollaborati'e ManagementTools ,&MT

• 'n addition to most /MT eamples, MT also includes

• ?C and e"uipment management

•  Time and cost management

• 9nline chat

• 'nstant messaging

•  Telephony

• Bideoconferencing

• =eb conferencing

• Data conferencing• #pplication sharing

• Electronic Meeting Systems %EMS&

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• Synchronous conferencing

• E-mail

• !aing

• voice mail

•

=ikis• =eb publishing

• Cevision control

• harting• Document-centric collaboration

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• Document retention

• Document sharing

• Document repository

• Evaluation and survey

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8roup Decision Making

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• Many of the decisions in today>s orkplace are madeby groups of individuals

•  8roups bring many advantages to the choice process – Multiple source of knoledge and eperience – # ider variety of prospectives – /otential synergy associated ith collaborative

activity

• Some times too many decision makers result in eithera bad decision or no decision at all.

• 4roup in term of decision maing can be de/nedas .  a collective entity that is independent of theproperties of its members.

• Multiparticipant decision maer ,MDM& #nactivity conducted by a collective entity composed ofto or more individuals and characterised in terms ofboth the properties of the collective entity and of its

individual members

8roup Decision Making

lassi(cation of Multi-participant

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• Decision structure, to types

 – ollaborative• 8roup decision structure !ormal

participants and multiple decision maker –

Jegotiation decisions – Ma0ority decisions

 – Joncollaborative• Team decision structure !ormal participants

and single decision maker – Jegotiation decisions

 – Ma0ority decisions

• 'ndividual decision structure

p pDecision -Making structures

" i ti Net k

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• The structure of an MDM is primarily based onthe interaction and flow of communication amongthe various members.

• Communication can be thought as any means bywhich information is transmitted to one or moremembers of the MDM.

• Basic Types of Networks Structures1. heel Network 

!. "hain Network 

#. "ircle Network 

$. "ompletely "onnected Network 

"ommunication Networks

"lassification of networks according to centrality

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• %ighly "entralised – They are efficient to routine and recurring decisions. – They tend to strengthen the leadership position of the

central members. – They tend to result in a stable set of interactions among the

 participants. – They tend to produce lower average levels of satisfaction

among the participants.

• %ighly Decentralised – They tend to produce higher average levels of satisfaction

among participants. – They facilitate nonroutine or nonrecurring decisions. – They promote innovation and creative solutions.

"lassification of networks according to centrality

,actors used in determining Decision Structure

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1. The importance of the &uality of the decision.

!. The e'tent to which the decision maker possess the knowledge ande'pertise to make the decision.

#. The e'tent to which potential participants have the necessary information.

$. The degree of structuredness of the problem conte't.

(. The degree to which the acceptance or commitment is critical tosuccessful implementation.

). The probability of acceptance of an autocratic decision.

*. The degree of motivation among the participants to achieve theorganisational goals.

+. The degree of potential conflicts among the participants over a preferredsolution.

,actors used in determining Decision Structure

2roblems with 3roup Decisions

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1.Size – The most widely studied and conse&uential component of

group decision making.

 – Studies show that as the si-e of a group increasesindividual satisfaction tends to decrease.

/s the si-e increases the less active members tend to

 become noticeably less productive.

  0ogic suggests that the management of an MDMre&uiring consensus or maority is easier when the si-e issmall.

2roblems with 3roup Decisions

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E;ects related to MDM %Management DM& size

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 – 2articipant interaction tends to decrease as si-e increase.

 – /ffective or emotional relationships tend to decrease as si-eincreases.

 –

"entral dominant leadership tend to increase as si-e increases.

 – "onflicts is resolved with political rather than analyticalsolutions as si-e increases.

 – Despite the disadvantages when the si-e of the MDM increasesin certain situations such as &uantitative udgment in statisticsthe larger the membership of the MDM the more likely it is thatthe results of the udgment must be made.

E;ects related to MDM %Management DM& size

/roblems ith 8roup Decisions

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!. 3roupthink4 a mode of thinking that people engage in when

they are deeply involved in a cohesive in5group.

 – The more friendly and cooperative the members of agroup the greater the likelihood that independent criticalthinking will be suspended in deference to group norms.

• 6nfavourable outcomes associated with 3roupthink 1. Tends to prevent a complete open5mind analysis of opportunities in

the development of obectives.

!. %olds back a meaningful search for information and tends to bias any

searches toward a self fulfilling selectivity.#. 0imits the participant7s ability to appraise possibilities associated

with the cost of failure.

$. Tends to eliminate the formation of incident of fallback position.

/roblems ith 8roup Decisions

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MDM Support Technologies

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 – Tools used in MDM environment to support the processesand activities related to the decision making process.

 – 6sual group meeting description .

 –  New technologies and telecommunications

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The four basic levels of MDM technology4

1. 8rganisational Decision Support System =ODSS>4 / comple'system of computer based technologies5 including those thatfacilitate communication5 that provides support for decisionmakers.

!. 3roup Support Systems =GSS>4 / collective of computer basedtechnologies used to aid MDM in identifying and addressing

 problems opportunities and issues.

#. 3roup Decision support System =GDSS>4/ collective ofcomputer based technologies designed to support the activitiesand processes related to MDM.

$. Decision Support System =DSS>4 a computer program underthe control of one or more persons that provides staff withinorganisations with support tools capable of enhancing theresults of the decision making process.

MDM Support Technologies

3ains and 0osses /ssociated with MDM /ctivities

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Some of the Gain1. "ollective has greater knowledge than a single participant.

!. /llows for synergistic results.

#. ;nteraction stimulates the generation of knowledge.

$. 2articipants can improve individual performance through

learning from others.

Some of the Losses(. "an block the production of ideas.

). "an produce information overload much faster.*. ?elative collection of speaking time is reduced with MDM si-e

+. ;ncrease opportunities of socialising over goal focus.

3ains and 0osses /ssociated with MDM /ctivities

Types of MDM Support Technologies

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Types by features offered in support of the multi-participant decision-making activities:

1. ?educe communication barriers.

!. ?educe uncertainty and noise.

#. 8rgani-e decision process.

 Types of MDM Support Technologies

Types of MDM Support Technologies

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Types by technology used:

1. @lectronic boardroom.

!. Teleconference room.

#. 3roup network.

$. ;nformation centre .

(. "ollaboration laboratory.

). Decision room.

Types of MDM Support Technologies

"ollaborative Support Technologies

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Groupare: / particular type of MDM support technology

specifically focused on issues related to collaborative

 processes among people. Aou can think of it as a tool that

when deployed and used appropriately positively affects

that way people communicate with each other resulting in

an improvement in the way people work.

Current market leaders of Groupare: – 0otus Notes

 – Microsoft @'change – 8racle 8ffice – 3roupise – Team 8ffice

"ollaborative Support Technologies

8 f t th t h l l

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• 8roupare refers to programs that help peopleork together collectively hile located remotelyfrom each other. /rograms that enable realtime collaboration are called synchronousgroupare.

• 8roupare services can include the sharing ofcalendars; collecti'e !riting; e-mail

handling; shared database access;electronic meetings !ith each person ableto see and display information to others;and other acti'ities%

•  Sometimes called collaborative softare,groupare is an integral component of a (eld ofstudy knon as omputer-Supportedooperative =ork or S=.

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• 8roupare is often broken don intocategories describing hether or not ork

group members collaborate in realtime %synchronous groupare andasynchronous groupare&.

• Some product eamples of groupare

include Aotus Jotes and Microsoft Echange,both of hich facilitate calendar sharing, e-mail handling, and the replication of (lesacross a distributed system so that all userscan vie the same information.

• Electronic :face-to-face: meetings arefacilitated by )-See Me and MicrosoftJetMeeting.

# 8DSS Eample

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p

Bideo onferencing

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Groupware system

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Groupware system

!i @ i

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!ive @asic group processes

communication

co-operation co-ordination

learning byknowledge

sharing

social interactionteam building

ynamic 8roup 'nteraction model

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Outcomes

3rganisationaoutcomes

4roup 'itality

Indi'idualre!ards

Processes

communication

cooperation coordination

learningsocialinteraction

Indi'idual interpretation and performance

rganisational en'ironment &hanges in organisational setting

mergingstructures

Groupcharacteristics

Technology

6ersons Tas 

7ormalstructur

e

Ce+ectionAearning

#ppropriation

Aifecycles

4roup

&ulture

Group 

6hysicalsetting

@ i / i i l

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@asic /rinciples

•  The e;ectiveness of a group can be epressed in terms ofthree types of outcomes, i.e. %"uality and "uantity of the &products, indi'idual re!ardsE and 'itality of thesocial relations.

• E;ectiveness depends on the "uality of the individual

preformance and si group processes, hich have to match•  The "uality of the group processes depends on the support

of si conditions, and on the interaction ith theenvironment.

•  The si aspects of the contet-of-use have to (t to each

other.• 8roups develop and tools become adopted and adapted to,

through interaction processes and feedback.

S)//9CT P M#T? P #D#/T#T'9J

Aessons learned %1&

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Aessons learned %1&

1. 8roupare is part of a social system. Design not for a tool assuch but for a ne socio-technical setting.

G. Design for several levels of interaction, i.e. for user friendlyhuman computer interaction, ade"uate interpersonalcommunication, group co-operation and organisationalfunctioning.

H. Design in a participative ay, i.e. users and possibly otherstakeholders should be part of the design process from thebeginning.

I. #nalyse carefully the situation of the users. Success ofcollaboration technology depends on the use and the users, noton the technology. 'ntroduction should match their skills and

abilities, and also their attitudes, otherise resistance isinevitable.

3. #nalyse carefully the contet, since success of collaborationtechnology depends on the (t to that contet. The more a nesetting deviates from the eisting one the more time, energyand other resources should be mobilised to make it a success.

Aessons learned %G&

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Aessons learned %G&

5. 'ntroduce the ne system carefully. #pply proper pro0ectmanagement, (nd a champion, try a pilot, inform peopleintensively

6. Train and support end-users etensively

7. Measure success conditions and success criteria before,

during and after the development process. 9nly in thisay you can learn for future developments.

2. /lan for a long process of introduction, incorporation,evaluation and adaptation. 8roupare is not a "uick (.

14. Despite careful preparations groupare is appropriated

and adapted in unforeseen ays. Feep options open forne ays of orking ith the groupare, because thismay result in creative and innovative processes.

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2pert Systems

• 'n arti(cial intelligence, an 2pert system is a computersystem that emulates the decision making ability of a

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system that emulates the decision-making ability of ahuman epert.

•  Epert systems are designed to solve comple problems

by reasoning about knoledge, represented primarilyas ifFthen  rules rather than throughconventional procedural code%

•  The (rst epert systems ere created in the 1264s andthen proliferated in the 1274s.

• Epert systems ere among the (rst truly successfulforms of #' softare.

9n 2pert System is divided into to sub-systems

• The Inference ngine applies the rules to the knon

facts to deduce ne facts. 'nference engines can alsoinclude eplanation and debugging capabilities.

• The 0no!ledge Base hich represents facts and rules.

t S t t

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• 2pert Systems are computer programsthat are derived from a branch of computer

science research called ArtifcialIntelligence ,9I%

• #'>s scienti(c goal is to understandintelligence by building computer programsthat ehibit intelligent behavior.

• 't is concerned ith the concepts andmethods of symbolic inference, or

reasoning, by a computer, and ho theknoledge used to make those inferencesill be represented inside the machine.

#' th t hi E t A l

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• #' programs that achieve Epert-Aevelcompetence in solving problems in task

areas by bringing to bear a body ofknoledge about speci(c tasks arecalled Knowledge-based  or ExpertSystems%

• 9ften, the term 2pert Systems isreserved for programs hose knoledgebase contains the no!ledge used by

human e2perts, in contrast toknoledge gathered from tetbooks ornon-eperts.

• More often than not, the to terms,

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• Epert Systems %ES& and

•  Fnoledge-@ased Systems %F@S&,

are used synonymously.•  Taken together, they represent the most

idespread type of #' application. The area ofhuman intellectual endeavor to be captured in anepert system is called the task domain.

• Task  refers to some goal-oriented, problem-solving activity.

•  Domain refers to the area ithin hich the task isbeing performed.

•

 Typical tasks are Diagnosis, /lanning, Scheduling,on(guration and Design.

•  #n eample of a task domain is aircraft crescheduling,

The Building Blocs of 2pert

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g pSystems

• Every epert system consists of to principal parts• the knoledge base* and

•  the reasoning, or inference, engine.

• The knowledge base of epert systems contains both

• !actual and

•

?euristic knoledge.• Factual knowledge is that knoledge of the task domain that is idely

shared, typically found in tetbooks or 0ournals, and commonly agreedupon by those knoledgeable in the particular (eld.

• Heuristic knowledge is the less rigorous, more eperiential, more 0udgmental knoledge of performance. 'n contrast to factual

knoledge, heuristic knoledge is rarely discussed, and is largelyindividualistic. 't is the knoledge of good practice, good 0udgment,and plausible reasoning in the (eld. 't is the knoledge that underliesthe :art of good guessing.:

• Knowledge representation formalizes and

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g porganizes the knoledge. 9ne idely usedrepresentation is the production rule, or

simply rule.•   # rule consists of an I7 part and a THG part

%also called a condition and an action&.

•  The '! part lists a set of conditions in some logical

combination.•  The piece of knoledge represented by the

production rule is relevant to the line of reasoningbeing developed if the '! part of the rule is

satis(ed* conse"uently, the T?EJ part can beconcluded, or its problem-solving action taken.

• Epert systems hose knoledge is represented inrule form are called rle-based systems.

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•  The  problem-solving model , or paradigm, organizesand controls the steps taken to solve the problem.

• 9ne common but poerful paradigm involves chainingof I7-THG rules to form a line of reasoning.

• 'f the chaining starts from a set of conditions andmoves toard some conclusion, the method iscalled !orward c"aining.

• 'f the conclusion is knon %for eample, a goal to beachieved& but the path to that conclusion is not knon,then reasoning backards is called for, and the methodis backward c"aining.

•  These problem-solving methods are built into programmodules called in!erence engines or inference

 procedures that manipulate and use knoledge in theknoledge base to form a line of reasoning.

omponents of an Epert

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2pert System

System

User

)ser'nterface

Fnoledge@ase

'nferenceEngine

• #s Epert Systems evolved, many ne

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#s Epert Systems evolved, many netechni"ues ere incorporated into

various types of 'nference Engines. Someof the most important of these ere

1% Truth Maintenance. Truth maintenancesystems record the dependencies in a

knoledge-base so that hen facts arealtered dependent knoledge can bealtered accordingly. !or eample, if thesystem learns that Socrates is no longerknon to be living, it ill revoke theassertion that Socrates is mortal.

(% Hypothetical easoning. 'n

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(% Hypothetical easoning. 'nhypothetical reasoning, the

Fnoledge @ase can be divided upinto many possible vies, akaorlds.

•.  This allos the 'nference Engine to

eplore multiple possibilities inparallel. 'n this simple eample, thesystem may ant to eplore the

conse"uences of both assertions,hat ill be true if Socrates is livingand hat ill be true if he is notQ

•  Though an epert system consists primarily of a

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knoledge base and an inference engine, a couple ofother features are orth mentioning reasoning ith

uncertainty, and eplanation of the line of reasoning.• Fnoledge is almost alays incomplete and

uncertain. To deal ith uncertain knoledge, a rulemay have associated ith it a condence factor or aeight.

•  The set of methods for using uncertain knoledge incombination ith uncertain data in the reasoningprocess is called reasoning with uncertainty .

• #n important subclass of methods for reasoning ith

uncertainty is called :fuzzy logic,: and the systemsthat use them are knon as :fuzzy systems.:

• 7uzzy +ogic. 9ne of the (rst etensions of simplyi l t t k l d l t

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using rules to represent knoledge as also toassociate a probability ith each rule. So, not toassert that Socrates is mortal but to assertSocrates may be mortal ith some probabilityvalue. Simple probabilities ere etended in somesystems ith sophisticated mechanisms foruncertain reasoning and combination of

probabilities.• 3ntology &lassi/cation. =ith the addition of

9b0ect classes to the Fnoledge @ase a ne typeof reasoning as possible. Cather than reasonsimply about the values of the 9b0ects, the system

could also reason about the structure of theob0ects as ell. 'n this simple eample Man canrepresent an 9b0ect lass and C1 can be rede(nedas a rule that de(nes the class of all men.

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