CHAPTER 3: DECISION SUPPORT SYSTEMS: AN OVERVIEW

Decision Support Systems and Intelligent Systems, 7th

Learning Objectives 

Understand possible decision support system (DSS) configurations

Understand the key differences and similarities between DSS and business intelligence (BI) systems

Describe DSS characteristics and capabilities Understand the essential definition of DSS Understand DSS components and how they

integrate

ReviewDefinitions of DSS

DEF1: DSS as extendible systems capable of supporting ad hoc data analysis and decision modeling, oriented toward future planning, and used at irregular, unplanned intervals.

DEF2: DSS as a computer-based system consisting of three interacting components:

1-a language system (a mechanism to provide communication between the user and other components of the DSS),

2-a knowledge system (a repository of problem domain knowledge embodied in DSS as either data or procedures),

3-and a problem-processing system (a link between the other two components, containing one or more of the general problem-manipulation capabilities required for decision making).

DEF3:DSS is situations where a 'final' system can be developed only through an adaptive process of learning and evolution."

DSS Configurations  

The configuration of decision support systems depends on the nature of the management-decision situation and the specific technologies used for support

These technologies are assembled from four basic components Data Models User interface Knowledge (optional)

these components are assembled defines their major capabilities and the nature of the support provided.

DSS configuration has the following characteristics: It supports individual members and an entire team. It is used repeatedly and constantly. It has three major components: data, models. and a

user interface. It uses subjective(based), personal, and objective data. It is used in the private sector. It helps the user to make faster, smarter, better

decisions.

DSS Configurations  

DSS Application And BI

A DSS application is an approach (or methodology) for supporting decision-making.

It uses an interactive, flexible, adaptable CBIS especially developed for supporting the solution to a specific nonstructured management problem.

It uses data, provides an easy user interface, and can incorporate the decision-maker's own insights

(e.g., a scheduling system for a specific company) CBIS=Computer Based information system

DSS Application and BI

Business intelligence (BI) is a collection of technical and process innovations across the data warehousing and business intelligence space

Business 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(Online Analytical Processing )/DSS.

Predictive analytics A business analytical approach toward forecasting (e.g., demand, problems, opportunities) that is used instead of simply reporting data as they occur

DSS Characteristics and Capabilities 

Components of DSS 

1-Data management subsystem Consists, generally, of database that contains relevant data

for the situation and is managed by software called DBMS which can be connected with the corporate data warehouse

2-Model management subsystem Consists of financial, statistical, management science or

other quantitative models that provides the DSS system analytical capabilities

3-User interface subsystem The component of a computer system that allows

bidirectional communication between the system and its user

Components of DSS 

4-Knowledge-based management subsystem (optional) The knowledge-based management subsystem can support

any of the other subsystems or act as an independent component

Organizational knowledge base An organization’s knowledge repository 

Data Management Subsystem  

1. The Database: is a collection of interrelated data organized to meet the needs and structure of an organization and can be used by more than one person for more than one application

Internal data come mainly from the organization’s transaction processing system

External data include industry data, market research data, census data, regional employment data, government regulations, tax rate schedules, and national economic data

Private data can include guidelines used by specific decision makers and assessments of specific data and/or situations

Data Management Subsystem  

Data organization: fully integrated DSS database vs. separate database Data extraction: the process of capturing data from several sources,

synthesizing them, summarizing them, determining which of them are relevant, and organizing them, resulting in their effective integration

2. Database management system (DBMS) software for establishing, updating, and querying (e.g., managing) a database

Extracts data Manages data and their relationships Updates (add, delete, edit, change) Retrieves data (accesses it)

3. Directory  a catalog of all the data in a database or all the models in a model base

4. Query Facility the (database) mechanism that accepts requests for data, accesses them, manipulates them, and queries them 

Data Management Subsystem  

The Model Management Subsystem

Five main parts in The Model Management Subsystem

1. Model base A collection of preprogrammed quantitative models (e.g., statistical, financial, optimization) that provide analysis capabilities

five categories of models in the model base Strategic models Tactical models Operational models Analytical models Model building blocks and routines

The ability to invoke, run, change, combine and inspect models is a KEY DSS capability

The Model Management Subsystem

Strategic models:    Models that represent problems for the strategic level (i.e., executive level) of management

Tactical models:   Models that represent problems for the tactical level(planned) (i.e., midlevel) of management 

Operational models:  Models that represent problems for the operational level of management

Analytical models:  Mathematical models into which data are loaded for analysis 

Model building blocks and routines: Preprogrammed software elements that can be used to build computerized models. For example, a random-number generator can be employed in the construction of a simulation model 

The Model Management Subsystem

2. Modeling tools (Modeling language)

3. Model base management system: MBMS software has six main functions

Model creation, using programming languages, DSS tools and/or subroutines, and other building blocks

Generation of new routines and reports Model updating and changing Model data manipulation Model execution Model integration

The Model Management Subsystem

4. Model directory

Catalog of all the models and other software in the model base. It includes:

Model definition Model’s Main function Answers of questions about the availability of and

capability of the models

5. Model command Processor: accepts and interprets the instruction, and routes them from the user interface component to the MBMS

User Interface (Dialog) Subsystem 

User interface:  The component of a computer system that allows bidirectional communication between the system and its user. Most important component in any DSS!!Why?

User interface management system (UIMS)  The DSS component that handles all interaction between users and the system

DSS user interfaces access is provided through Web browsers including: Voice input and output Portable devices Direct sensing devices

Knowledge-Based Management Subsystem  

Advanced DSS are equipped with a component called a knowledge-based management subsystem that can supply the required expertise for solving some aspects of the problem and provide knowledge that can enhance the operation of other DSS components

The User  

The person faced with a decision that an MSS is designed to support is called the user, the manager, or the decision maker

MSS has two broad classes of users: managers and staff specialists Staff specialists use the system much more frequently

than manager and tend to be more detail-oriented Staff analysts are often intermediaries between

managers and the MSS

The User  

Intermediary   A person who uses a computer to fulfill requests made by other people (e.g., a financial analyst who uses a computer to answer questions for top management)

Staff assistant  An individual who acts as an assistant to a manager Expert tool user A person who is skilled in the application of one

or more types of specialized problem-solving tools Business (system) analysts  An individual whose job is to analyze

business processes and the support they receive (or need) from information technology

Facilitators (in a group support systems GSS)  A person who plans, organizes, and electronically controls a group in a collaborative computing environment

DSS Hardware  

Hardware affects the functionality and usability of the MSS The choice of hardware can be made before, during, or after

the design of the MSS software Major hardware options:

Organization’s servers Mainframe computers with legacy DBMS, Workstations Personal computers Client/server systems

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 Download DSS software Use DSS applications provided by the company Buy online from application service providers (ASPs) 

DSS Hardware  

DSS Classifications  

Alter’s output classification: based on the Degree of action implication ( conclusion )of system

out-puts" or the extent to which system outputs can directly support the decision

Seven Categories Data

File drawer systems Data analysis systems

Data or models Analysis information systems

Models Accounting models Representational models Optimization models Suggestion models

DSS Classifications  

Holsapple and Whinston’s classification classify DSS into the following six frameworks

Text-oriented DSS Database-oriented DSS Spreadsheet-oriented DSS Solver-oriented DSS Rule-oriented DSS

DSS Classifications  

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(habit or frequent) nature

Ad hoc DSS    A DSS that deals with specific problems that are usually neither predictable nor recurring

Personal support Group support Organizational support