Components and Classification of Dss

DSS ComponentsDSS Components

1. Data Management Subsystem2. Model Management Subsystem3. Knowledge Management Subsystem4. User Interface Subsystem5. The User

Prepared By : Bhushan Phadke 1


Data

ManagementModel

Management

Knowledge

Management

User Interface

User

Other

Systems

DSS Components

The Data Management Subsystem The Data Management Subsystem

A data management system (DMS) is a computerprogram designed to manage a database (a large setof structured data), and run operations on the datarequested by numerous clients. The DMS can beinterconnected with the corporate data warehouse.Typical examples of DMS use include accounting,human resources and customer support systems.

Some of the capabilities of DMS in a DSS are:

• Captures/extracts data for inclusion in a DSS database.

• Interrelates data from different sources.

• Performs complex data manipulation tasks based on user queries.


The Model Management The Model Management

Subsystem Subsystem

The model base management system (MBMS) is a computer program that includes financial, statistical, management science or other quantitative models that provide the system’s analytical capabilities and appropriate software management. Usually, the models are customized using modeling languages (programming tools).

Some of the capabilities of MBMS in a DSS are:

• Allows user to manipulate the models so they can conduct experiments and sensitivity analyses ranging from ‘what-if” to goal seeking.

• Catalogs and displays the directory of models for use by several individuals in the organization.


Categories of ModelsCategories of Models

� Optimization

◦ get the highest level of goal attainment from a given set of resources.

� Heuristics◦ "rules of thumb" to arrive at satisfactory solutions.

� Simulation◦ predict behavior of a system over time.

� Sensitivity analysis◦ change inputs or parameters and look at model results.

◦ 2 approaches:

� What-if analysis – forward solution approach.

� Goal seeking – backward solution approach.


The Knowledge Management The Knowledge Management

Subsystem Subsystem

Many unstructured and even semi-structured problems are so complex that their solutions require expertise. This can be provided by an expert system or other intelligent system.

Some of the capabilities of KMS in a DSS are:

• Provides expertise in solving complex unstructured andsemi-structured problems

• What models to use, how, and interpreting results

• Reasoning, handling uncertainty and learning from data

• Expertise provided by an expert system or other intelligentsystem (AI techniques)


Example: Knowledge RepresentationExample: Knowledge Representation

� Production Rule (IF..THEN..ELSE) Examples:

◦ IF your income is highTHEN your chance of being audited by the IRS is high.

◦ IF your income is highTHEN your chance of being audited by the IRS is highELSE your chance for being audited is lower.

◦ IF your income is high OR your deductions are unusualTHEN your chance of being audited by the IRS is highELSE your chance for being audited is low.


The User Interface (Dialog) The User Interface (Dialog)

Subsystem Subsystem

User interface (of a computer program) refers to the graphical, textual and auditory information the program presents to the user, and the control sequences (such as keystrokes with the computer keyboard, movements of the computer mouse, and selections with the touch screen) the user employs to control the program.


The User The User

� Managers

� Staff specialists

� Intermediary:1.Staff assistant2.Business (system) analyst3.Group DSS Facilitator


Distinguishing DSS from Distinguishing DSS from

Management Science and MISManagement Science and MIS

� DSS is a problem solving tool and is

frequently used to address ad hoc and

unexpected problems.

� DSS evolve as they develop.


Design and Construction of DSSDesign and Construction of DSS


Construction of DSS with DSS Generators

� DSS application can be constructed with DSS generators with DSS tools

� DSS Generators :� It is a package of software used to build DSS application.

� eg. IBM,s GADS (Geodata Analysis and Display System) which displays a map showing the location of equipment, machines, inventories and materials. Shows workloads by territoty.

� Useful for police patrolling

� Other s/ws – Excell, Lotus 1-2-3, Quattro, Focus


Prepared By : Bhushan Phadke15

� A DSS generator is a software package for developing the user interface and in some cases a model, rules or a database schema for a DSS.

� A DSS generator is used to create a specific DSS.

� Sprague and Carlson (1982) identified "two basic objectives of the DSS Generator:

1. To permit quick and easy development of a wide variety of specific DSS; and

2. 2. The Generator must be flexible and adaptive enough to facilitate thei terative design process by which Specific DSS can respond quickly to changes".

ADSS generator is a software "package" that provides a set of capabilities to build specific DSS quickly and easily.

DSS ToolsDSS Tools


� For construction of DSS application and creation of DSS generator is facilitated by Special s/w elements1. Colour Graphics2. Special Editors3. Softwares4. Random Number Generators

DSS DSS softwaressoftwares


1. Industry Oriented : for Hospitals for planningfor Banks-portfolio ManagementAirlines-planning and control

2. Functional AreasFinance, HR, MKT, OM

Classification of DSSClassification of DSSI. On Use level DSS is classified as

1. Passive DSS,2. Active DSS, and3. Cooperative DSS

II. On the conceptual level DSS is classified as1. communication-driven DSS,2. data-driven DSS,3. document-driven DSS,4. knowledge-driven DSS, and5. model-driven DSS.

III On System level DSS is classified as1. enterprise-wide DSS and2. desktop DSS


DSS classification DSS classification On Use level On Use level

1. A Passive DSS : A passive DSS is a system that aids theprocess of decision making, but that cannot bring outexplicit (clear) decision suggestions or solutions.

2. An Active DSS: An active DSS can bring out explicitdecision suggestions or solutions.

3. A cooperative DSS : A cooperative DSS allows thedecision maker (or its advisor) to modify, complete, orrefine the decision suggestions provided by the system,before sending them back to the system for validation.The system again improves, completes, and refines thesuggestions of the decision maker and sends them backto her for validation. The whole process then startsagain, until a consolidated solution is generated.


DSS classification on conceptual level

1) Communication driven Level DSS: A communication-driven DSS supports more than one person working on a shared task.

eg. integrated tools like Microsoft's NetMeeting or Groove .

2) Data-driven DSS : A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.

3) Document Driven DSS : A document-driven DSS manages, retrieves and manipulates unstructured information in a variety of electronic formats.

4) Knowledge Driven DSS : A knowledge-driven DSS provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures.

5) Model Driven DSS:A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by DSS users to aid decision makers in analyzing a situation, but they are not necessarily data intensive.


DSS classification on System LevelDSS classification on System Level

1) Enterprise-wide DSS: Enterprise-wide DSS are linked to large data warehouses and serve many managers in a company.

2) Desktop DSS: Desktop, single-user DSS are small systems that reside on an individual manager's PC.


Components and Classification of Dss

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