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Overview

Decision Support Systems (DSS) are a specific class of computerized informationsystem that supports business and organizational decision-making activities. Aproperly designed DSS is an interactive software-based system intended to helpdecision makers compile useful information from raw data, documents, personal

knowledge, and/or business models to identify and solve problems and makedecisions.

A DSS supports all phases of decision making and may include a knowledgecomponent

A DSS can be used by a single user on a PC or can be Web-based for use bymany people at several locations

Typical information that a decision support application might gather and presentwould be:

Accessing all of your current information assets, including legacy andrelational data sources, cubes, data warehouses, and data marts

Comparative sales figures between one week and the next Projected revenue figures based on new product sales assumptions The consequences of different decision alternatives, given past experience in

a context that is described

Decision Making as a Component of Problem Solving

Solution Types

Optimization model

Finding the best solution

Satisfying model

Finding a good - but not necessarily the best -

solution to a problem

Heuristics

Commonly accepted guidelines or procedures

that usually find a good solution

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Characteristics

Handles large amounts of data from different sources

Provides report and presentation flexibility

Offers both textual and graphical orientation

Supports drill down analysis Performs complex, sophisticated analysis and comparisons using advanced

software packages

Supports optimization, satisfying, and heuristic approaches

Performs different types of analyses

What-if analysis

Makes hypothetical changes to problem and observes impact on

the results

Simulation

Duplicates features of a real system

Goal-seeking analysis Determines problem data required for a given result

Capabilities of a DSS Supports

Problem solving phases

Different decision frequencies

Solves

Highly structured problems

Straightforward problems, requiring known facts and

relationships. Semi-structured or unstructured problems

Complex problems wherein relationships among data are not

always clear, the data may be in a variety of formats, and are

often difficult to manipulate or obtain

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Components of a DSS

Components of a Modular DSS System

DSS Software System and its logical links with other systems

Advantages

TPSExternal

Data

DSS

Databas

e

DSS Software

System

Models

OLAP Tools

Data Mining Tools

User

InterfaceUser

Online Analytical Processing

It supports multidimensional

analysis, enabling users to view

same data in different ways u

multiple dimensions. Each aspe

feature represents a diffe

dimension which provides

analyses of same data in diffe

way to obtain different view to

same output.

Models

Financial

Statistical

analysis

Graphical

Model management softwar

(MMS)

Coordinates the use of mode

Model base

Provides decision makers wit

access to a variety of modeand assists them in decisio

Dialogue manager

Allows decision makers to

easily access and manipulate

Data Mining Tools

Data mining is more discoveries

driven. This provides insights into

corporate data that cannot be

obtained with OLAP, by finding

hidden patterns and behavior.

These patterns and rules are

used to guide decision making

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Less expensive than custom approaches or real systems.

Faster to construct than real systems

Less risky than real systems

Provides learning experience (trial and error)

Future projections are possible

Can test assumptions Disadvantages

Assumptions about reality may be incorrect

Accuracy of predications often unreliable

Requires abstract thinking

Executive Support System (ESS) Characteristics

A specialized DSS that includes all the hardware, software, data,

procedures, and people used to assist senior-level executives within

the organization Tailored to individual executives

Easy to use

Drill down capabilities

Support the need for external data

Help with situations with high degree of uncertainty

Futures orientation (predictions, forecasting)

Linked with value-added business processes

Capabilities

Support for

defining overall vision strategic planning

strategic organizing and staffing

strategic control

crisis management

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Operations Support System (OSS)

Operations Support System (OSS) performs

management, inventory, engineering, planning,

and repair functions for tele-communicationsservice providers and their networks.

For traditional telecom service providers,

Operations Support Systems (OSSs) were

mainframe-based systems designed to support

telephone company staff members to automate

their daily jobs such as order processing, line

assignment, line testing and billing, etc. The

complementary term Business Support Systems

(BSS) is a newer term and typically refers to

"business systems" dealing with customers,

supporting processes such as taking orders,

processing bills, and collecting payments. The two

systems together are often abbreviated BSS/OSS or simply B/OSS. B/OSS plays a critical role to support operations

of a service provide and its increasing business services including voice, data, VOIP and multi-media.

Functions of an OSS solution may include the following components:

Order processing, accounting, billing and cost management

Network inventory, service provision, design and assign

Network discovery and reconciliation, trouble and fault management, capacity management

Network elements, asset and equipment management, field service management

Most of the Operation Support Systems are designed based on the Telecommunications Management Network

(TMN) model. To better define OSS and BSS for future business and technology development, the Tele-Management

Forum is working on a newer model to replace the aging TMN. This new model is called TOM (Telecoms Operations

Map) or eTOM (enhanced Telecom Operations Map).

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Additional Capabilities of DSSBusiness analytics

The application of models directly to business data. Business analytics

involves using DSS tools, especially models, in assisting decision makers. It is

essentially OLAP/DSS. See also business intelligence (BI).

Predictive analyticsA business analytical approach toward forecasting (e.g., demand, problems,

opportunities) that is used instead of simply reporting data as they occur

The key characteristics and capabilities of DSS

Support for decision makers, mainly in semi structured and

unstructured situations, by bringing together human judgment and

computerized information

Support for all managerial levels, ranging from top executives to line

managers

Support for individuals as well as groups Support for interdependent and/or sequential decisions

Support in all phases of the decision-making process

Support for a variety of decision-making processes and styles

DSS are flexible, so users can add, delete, combine, change, or rearrange

basic elements; DSS can be readily modified to solve other, similar problems

User-friendliness, strong graphical capabilities, and a natural language

interactive humanmachine interface can greatly increase the effectiveness

of DSS

Improved effectiveness of decision making

The decision maker has complete control over all steps of the decision-

making process in solving a problem

End users are able to develop and modify simple systems by

themselves

Models are generally utilized to analyze decision-making situations

Access is provided to a variety of data sources, formats, and types

Can be employed as a standalone tool used by an individual decision

maker in one location or distributed throughout an organization and in

several organizations along the supply chain

Can be integrated with other DSS and/or applications, and it can be

distributed internally and externally, using networking and Web technologies

DSS Hardware Portability has become critical for deploying decision-making capability in the

field, especially for salespersons and technicians

The power and capabilities of the World Wide Web have a dramatic impact on

DSS

Communication and collaboration

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Download DSS software

Use DSS applications provided by the company

Buy online from application service providers (ASPs)

Classification of DSS AIS SIGDSS classification for DSS

Communications-driven and group DSS (GSS)

Data-driven DSS

Document-driven DSS

Knowledge-driven DSS, data mining, and management ES applications

Model-driven DSS

Compound DSS

Holsapple and Whinstons classification

Text-oriented DSS

Database-oriented DSS

Spreadsheet-oriented DSS Solver-oriented DSS

Rule-oriented DSS

Alters output classification

Data

File drawer systems

Data analysis systems

Data or models

Analysis information systems

Models

Accounting models

Representational models

Optimization models

Suggestion models

Other DSS categories

Institutional DSS

A DSS that is a permanent fixture in an organization and has

continuing financial support. It deals with decisions of a recurring

nature

Ad hoc DSS

A DSS that deals with specific problems those are usually neither

anticipated nor recurring Personal support

Group support

Organizational support

Group support system (GSS)

Information systems, specifically DSS, which support the collaborative

work of groups

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Custom-made systems versus ready-made systems