UNIT 6. Decision Support System

8/7/2019 UNIT 6. Decision Support System

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Unit 6

DECISIONSUPPORT SYSTEM


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Decision Support System

Decision Support System (DSS) refers to a class of systems thatsupports the process of decision making. The emphasis is onsupport rather than on automation of decisions.

DSS are interactive information systems, that rely on an integratedset of user-friendly hardware & software tools to produce & presentinformation to support management in decision making process.

DSS assists management in decision making by combining data,sophisticated analytical models and user-friendly software into asingle powerful system that supports semi-structured or

unstructured decision-making.

While MIS is considered for structured decisions, DSS is consideredmore useful for decisions at tactical/strategic levels, which involvescomplex decisions


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Decision Support System Components

The DSS has three basic components:

1) The Database

2) The Modelbase- Behavioral Model- Management Science Model

- Operations Research Model

3) The DSS Software System


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1. DATABASE : The DSS Database is a collection of current or historical

data from a number of applications or groups. It uses live organizationaldata so that decisions could be taken based upon actual conditions. Thedatabase has access to data from both internal & external sources.

2. MODELBASE : A Model is an abstract representation that shows thecomponents or relationships of a phenomenon. DSS uses 3 types of models:

Behavioral Model : Here the focus is on studying/understanding thebehavior/trends amongst variables.E.g. Trend analysis, Forecasting, Co-relation, Regression

Management Science Model : These models are build on Principles of Management, management Accounting & Econometrics.E.g. Budgetary systems, Cost Accounting, Inventory Management etc



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Operations Research Model : These are basically mathematical

models. These models represents real life problems in terms of variables and parameters expressed in algebraic equation forms.E.g. Linear Programming, Material Requirement planning etc.

3. DSS SOFTWARE : It permits easy interactions between the usersof the system and the DSS database & modelbase. It managesthe creation, storage and retrieval of models in the modelbaseand integrates them with the data in the DSS database.The DSS software also provides a graphic, easy to use, flexibleuser interface that supports the interaction between the usersand the DSS.



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Desirable Characteristics of Decision Support System

DSS should aid the decision maker in decision makingDSS should be able to address semi/un-structured decision makingsituationsDSS should support decision makers particularly at tactical/strategiclevelsDSS should be able to create general purpose models, simulationcapabilities and other analytical tools available to a decision maker DSS should be readily adapted to meet information requirementsfor any decision environmentDSS should provide mechanism to enable rapid response to adecision makers request for informationDSS should be flexible to accommodate variety of managementstylesDSS should facilitate communication between/among various levelsof decision makingDSS should have in-built flexibility and ability to evolve as user sophistication grows


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The Decision Support System Approach and CoreCapabilities


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MIS-Decision Support System - Comparison


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Structure of Decision Support Systems


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Fundamental DSS Programme Structure

1) Dialogue Management : Users interfaces with the Dialogue

Management components, which is a set of programmes thatmanages the user interface and translates the users request intocommands for the other 2 components. It has 3 sub parts:a) User Interface b) Dialogue Control c) Request Translator

2) Model Management : It maintains & executes models of business activity. Examples of such models are spreadsheets,financial models & simulation models. It is used to create, storeand modify models and to cause them to be involved.

3) Database Management : It performs 2 functions:It stores & manipulates the database as directed by either theModel Management or the Dialogue Management component.It maintains an interface with data sources that are external to theDSS i.e. Enterprise data, External data sources and other DSSapplications.


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Group Decision Support Systems (GDSS)

DSS is designed for and used more by individual decision maker.

However, it was felt that in todays complex business environment, decisionmakers generally work in groups because it leads to a better groupunderstanding of the problems and leads to better solutions.

Hence the DSS application was expanded to facilitate Group DecisionEnvironment and the DSS for a group came to be known as GroupDecision Support System (GDSS).

Under the GDSS environment, the members of the group utilizes the DSS

as a group and the user-interface is expanded to include the computerswhich are suitably connected/networked. In this way, under GDSS,members of a group can communicate using their computers with DSS or with other members of the group to facilitate optimal decision making.


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What is GDSS ?

According to De Sanctis and Gallupe, GDSSis an interactive computer-based system thatfacilitates the solution of unstructured

problems by a set of decision-makers workingtogether as a group.


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GDSS Components

The GDSS components are similar to that of theDSS components. The GDSS has three basiccomponents as follows:

1) HARDWARE

2) SOFTWARE

3) PEOPLE AND PROCEDURE


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GDSS Components1) HARDWARE

- Input/Output Devices- Audio/Visual Instruments- Electronic Display Board Screens- Computer Equipments- Conferencing Infrastructure- Network Systems enabling the linking of different sites/locations

and participants to each other

2) SOFTWARE- Database and DBMS- Modeling Capabilities- Dialogue Management with Multiple-user Access- Specialized Application Programmes to facilitate group access

3) PEOPLE AND PROCEDURE- Trained Facilitator/s- Decision Making Participants- Support Staff - Laid Down Procedures and Modus Operandi


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GDSS Configuration


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The GDSS Features

a) Anonymous inputs without identifying the sourceof inputs to enable group decision makers toconcentrate on the merits of the input withoutconsidering who gave it.

b) Parallel communication/s to enable every groupmember to address issues or makecomments/suggestions simultaneously.

c) Automated record keeping by anonymouslyrecording each comment that is entered into thePC by the group member, for future review andanalysis.


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Factors in GDSS Success

a) Improved pre-planningb) Increased participationc) Open, collaborative meeting(s) atmosphere

d) Criticism-free idea generatione) Setting priorities and making decisionsaccordingly

f) Documentation/Record keeping of meetingsg) Access to external information, if and when

required


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Executive Information System/Executive SupportSystem (EIS/ESS)

EIS/ESS is a specialized DSS that includes all hardware, software, dataprocedures and people used to assist senior/top level executives within anorganization.

EIS is a computer based system that serves the information needs of TopExecutives by providing capabilities like:1) Exception Reporting 2) Critical Success Factors identification3) Drill Down capabilities

EIS/ESS has emerged in response to the emerging dynamic situationwhere the Top Executives are bombarded with huge amount of data,effectively leading to Information Overload with the resultantunderstandable confusions and dilemma.

EIS/ESS is developed to support decision making at senior level includingmembers of the Board of Directors, Chief Executive Officer (CEO), Chief Operating Officer (COO), Chief Finance Officer (CFO) etc.


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Why EIS/ESS ?According to Watson and others, EIS/ESS has become imperative due to certaininternal and external factors as enumerated below:

A) INTERNAL FACTORS- Need for timely information- Need for improved communication- Need for access to operational data

- Need for rapid status updates on various business activities- Need for access to corporate database- Need for more accurate information- Need for ability to identify historical trends

B) EXTERNAL FACTORS

- Increased and intensifying global competition- Rapidly changing business environment- Need to be more pro-active- Need to access external database- Increasing Government regulations


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EIS/ESS Characteristics

The characteristics can be divided into three categories:

1. Informational Characteristics2. User-Interface/Orientation Characteristics3. Managerial/Executive Characteristics

1. Informational Characteristics:

- Flexibility and ease of use- Provides timely information with short response time and quick

retrieval- Provides correct information- Provides relevant information- Provides validated information


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EIS/ESS Characteristics

2. User-Interface/Orientation Characteristics:

- Contains sophisticated self-help, user friendly interfaces includingGraphic User Interface (GUI)

- Facilitates access from many places- Provides secure, reliable and confidential access and access

procedure- Is customized to suit the management style of individual executives

3. Managerial/Executive Characteristics

- Provides support for defining overall Vision, Mission and Strategy

as it has strategic/futuristic orientation- Provides support for Strategic Management Strategic Planning /

Organizing / Control / Staffing etc)- Can help with situations that have a high degree of risk/uncertainty


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EIS/ESS Capabilities

a) It provides access to aggregated / macro / global informationb) It enables to use external data extensivelyc) It enables to address ad hoc queries/analysisd) It incorporates graphics and text in the same display to provide

better viewe) It shows trends, ratios and deviations

f) It provides access to historical and also the latest datag) It highlights problem indicators and supports open-ended problem

explanation with written interpretationsh) It is organized around critical success factors and provides

Management by Exception reportsi) The information can be presented in a hierarchical structure,

thereby facilitating detailed information at various levels, along withDrill Down capabilities.

j) It filters, compresses and tracks critical data and also provideforecasting capabilities


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EIS/ESS Benefits

1. Facilitates the attainment of organizational objectives2. Facilitates access to information by integrating many sources of data and provide broad, highly aggregated information.

3. Improves the user productivity by enabling more effectivedecision making

4. Allows the anticipation of problems/opportunities and facilitates

pro-active rather than a re-active response.5. Increases communication capability and quality6. Facilitates better Strategic Planning and Control7. Facilitates finding the cause of a problem in a Root-Cause

Analysis mode rather than Fix-It mode8. Meets the needs of the executives in time-effective and time-

efficient manner 9. The EIS/ESS provides competitive advantage


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Expert Systems - DefinitionAn Expert System is a computer Programme that represents and copiesknowledge of some specialist in a specific area that has successfully been

solved by human experts with a view to solving problems or giving advice.

ES is a highly specialized computer systems capable of using that element of a human specialists knowledge and reasoning that can be formulated into aset of facts and Heuristic Rules.

ES copies human expertise in a Narrow Domain to solve Specific

Problems in a Well Defined Area.

An ES is a computer Programme that:a) Reasons with domain-specific knowledge that is logical as well as numericalb) User domain-specific methods that are heuristic as well as following

procedures that are algorithmic (certain)c) Performs well in the problem aread) Explains or make understandable both what it knows and the reasons for its

answerse) Retains flexibility


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Expert Systems Components


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Expert Systems - Capabilities

a) Capturing of Expertise

b) Codifying the Expertise

c) Duplicating and Transferring the Expertise

d) Saving the Human Experts Time

e) Saving on Maintenance and Updating of theKnowledge Base


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Expert Systems - Characteristics

a) Ability to explain their reasoning or suggesteddecisions

b) Ability to display Intelligence behaviorc) Ability to draw conclusions from complex

relationshipsd) Ability to provide Portable Knowledgee) Ability to deal with certaintyf) Not widely used or tested, due to difficulty of

useg) Limited to relatively narrow problemsh) Inability to deal with Mixed Knowledgei) Difficulty to maintain


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Expert Systems - Applications

Aerospace Technology (NASA)Airline/Civil Aviation (Scheduling/Routing)Banking and Finance (Credit Card Limits)CriminologyEducationFood Industry

Health Care Management (Diagnosing Blood Infections)Geological Data Analysis and interpretation for oil explorationdrilling sitesPersonnel ManagementSecurity Analysis/Portfolio ManagementTax PlanningForeign Exchange ManagementTrouble Shooting Telephone NetworkConfiguring Computer SystemsQuality Control and Monitoring


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Expert Systems - Limitations

An ES is based on a narrow range of codified domain, they maynot be able to tackle multi-dimensional problems.Due to narrow range of knowledge incorporated in the ES, theytypically do not respond well to situations outside their range of expertise.Typically ES may not be able to make available common senseknowledge and broad-ranging contextual information/s.ES typically lack human self-awareness and self-analysis tool.Introspection is not available as ES also happen to be non-self-referral systems.If a problem is not specific and has not been solved previously byan expert, then the problem is not considered suitable for theExpert Systems implementations.

- ES are capable of performing only within a specific, logic orientedrealm of expertise, as computers basically only have MEMORYand not, necessarily, INTELLIGENCE !


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Artificial Intelligence (AI) - Introduction

AI is a branch of computer science concerned with the study andcreation of computer systems that exhibit some form of humanintelligence:

1. Systems that learn new concepts and tasks2. Systems that can reason & draw useful conclusions about the

world around us

3. Systems that can understand natural languages4. Systems that perform other types of activities that require human

types of intelligence.

AI is a branch of computer science that is concerned with the

automation of intelligent behavior.

AI is a series of related technologies that attempt to reproducehuman behavior including thinking, speaking, feeling & reasoning.


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Natural V/s Artificial Intelligence

Attributes NaturalIntelligence

Artificial

IntelligenceAbility to use sensors (eyes, ears, touch, smell) High Low

Ability to be creative and imaginative High Low

Ability to learn from past experiences High Low

Ability to be adaptive High Low

Ability to afford the cost of acquiring intelligence High Low

Ability to use a variety of information sources High High

Ability to acquire a large amount of externalinformation

High High

Ability to make complex calculations Low HighAbility to transfer information Low High

Ability to make a series of calculations, rapidly andaccurately

Low High


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Pre-requisites of AI

Understand what is Common SenseUnderstand Facts and relationships among FactsBe able to manipulate Qualitative dataBe able to deal with exceptions and discontinuityBe able to interface with humans in a Free-FormatfashionBe able to deal with new situations based on previous

learning


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AI ONION MODEL

Heuristic

Search

Modeling &Representationof knowledge

CommonSenseReasoning

& Logic

AILanguages& Tools

Natural Language Processing

Computer Visio n

Expert Systems

Problem Solvin

g &

Planning


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AI - Applications

Manufacturing/Production Planning and SchedulingProject ManagementFactory ManagementSales, Distribution and Field ServicesDiagnosis and Trouble ShootingFinancial ManagementCurrency/Interest Rate SWAPsPortfolio ManagementAsset Liability ManagementReading/Interpreting FinancialsCriminologyGeology (Potential Drilling/Oil Exploration Sites)

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UNIT 6. Decision Support System

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