Components And Classification Of Dss 5j3k3y

DSS Components 1. Data Management Subsystem 2. Model Management Subsystem 3. Knowledge Management Subsystem 4. Interface Subsystem 5. The

Prepared By : Bhushan Phadke

1

Prepared By : Bhushan Phadke

2

Data Management

Model Management

Knowledge Management

Other Systems

Interface



DSS Components Prepared By : Bhushan Phadke

3

The Data Management Subsystem A data management system (DMS) is a computer program designed to manage a database (a large set of structured data), and run operations on the data requested by numerous clients. The DMS can be interconnected with the corporate data warehouse. Typical examples of DMS use include ing, human resources and customer 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 queries. •

Prepared By : Bhushan Phadke

4

The Model Management 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 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. Prepared By : Bhushan Phadke

5

Categories 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. Prepared By : Bhushan Phadke

6

The Knowledge Management 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 and semi-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 intelligent system (AI techniques)

Prepared By : Bhushan Phadke

7

Example: Knowledge Representation

Production Rule (IF..THEN..ELSE) Examples: ◦ IF your income is high THEN your chance of being audited by the IRS is high. ◦ IF your income is high THEN your chance of being audited by the IRS is high ELSE your chance for being audited is lower. ◦ IF your income is high OR your deductions are unusual THEN your chance of being audited by the IRS is high ELSE your chance for being audited is low. Prepared By : Bhushan Phadke

8

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

Prepared By : Bhushan Phadke

9

The



Managers Staff specialists Intermediary: 1.Staff assistant 2.Business (system) analyst 3.Group DSS Facilitator

Prepared By : Bhushan Phadke

10

Distinguishing DSS from Management 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.

Prepared By : Bhushan Phadke

11

Prepared By : Bhushan Phadke

12

Design and Construction of DSS

Construction of DSS with DSS Generators

Prepared By : Bhushan Phadke

13

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 Phadke

14

A DSS generator is a software package for developing the 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.

15

Prepared By : Bhushan Phadke

DSS Tools For construction of DSS application and creation of DSS generator is facilitated by Special s/w elements 1. Colour Graphics 2. Special Editors 3. Softwares 4. Random Number Generators

Prepared By : Bhushan Phadke

16

DSS softwares 1. Industry Oriented : for Hospitals for planning for Banks-portfolio Management Airlines-planning and control 2. Functional Areas Finance, HR, MKT, OM

Prepared By : Bhushan Phadke

17

Classification of DSS I. On Use level DSS is classified as 1. ive DSS, 2. Active DSS, and 3. Cooperative DSS

II.

On the conceptual level DSS is classified as 1. communication-driven DSS, 2. data-driven DSS, 3. document-driven DSS, 4. knowledge-driven DSS, and 5. model-driven DSS.

III

On System level DSS is classified as 1. enterprise-wide DSS and 2. desktop DSS

Prepared By : Bhushan Phadke

18

DSS classification On Use level 1.

2. 3.

A ive DSS : A ive DSS is a system that aids the process of decision making, but that cannot bring out explicit (clear) decision suggestions or solutions. An Active DSS: An active DSS can bring out explicit decision suggestions or solutions. A cooperative DSS : A cooperative DSS allows the decision maker (or its advisor) to modify, complete, or refine the decision suggestions provided by the system, before sending them back to the system for validation. The system again improves, completes, and refines the suggestions of the decision maker and sends them back to her for validation. The whole process then starts again, until a consolidated solution is generated.

Prepared By : Bhushan Phadke

19

DSS classification on conceptual level 1)

Communication driven Level DSS: A communication-driven DSS s 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. Document Driven DSS : A document-driven DSS manages, retrieves and manipulates unstructured information in a variety of electronic formats. Knowledge Driven DSS : A knowledge-driven DSS provides specialized problem solving expertise stored as facts, rules, procedures, or in similar structures.

3)

4)

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 s to aid decision makers in analyzing a situation, but they are not necessarily data intensive. Prepared By : Bhushan Phadke

20

DSS classification on System Level 1)

2)

Enterprise-wide DSS: Enterprise-wide DSS are linked to large data warehouses and serve many managers in a company. Desktop DSS: Desktop, single- DSS are small systems that reside on an individual manager's PC.

Prepared By : Bhushan Phadke

21