Turban, Aronson, and Liang
Decision Support Systems and Intelligent Systems,
Seventh Edition
Chapter 3
Decision Support Systems:
An Overview
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
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Decision Support Systems
• Systems designed to support
managerial decision-making in
unstructured problems
• More recently, emphasis has shifted
to inputs from outputs
• Mechanism for interaction between
user and components
• Usually built to support solution or
evaluate opportunities
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DSS
• A DSS is a methodology that supports
decision-making.
• It is:
– Flexible;
– Adaptive;
– Interactive;
– GUI-based;
– Iterative; and
– Employs modeling.
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Characteristics and
Capabilities of DSS (Figure 3.1)
1. Provide support in semi-structured and unstructured
situations, includes human judgment and
computerized information
2. Support for various managerial levels
3. Support to individuals and groups
4. Support to interdependent and/or sequential decisions
5. Support all phases of the decision-making process
6. Support a variety of decision-making processes and
styles
(more)
5
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
7. Are adaptive
8. Have user friendly interfaces
9. Goal: improve effectiveness of decision making
10. The decision maker controls the decision-making
process
11. End-users can build simple systems
12. Utilizes models for analysis
13. Provides access to a variety of data sources,
formats, and types
Decision makers can make better, more consistent
decisions in a timely manner
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Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson, 6th edition
Copyright 2001, Prentice Hall, Upper Saddle River, NJ
Business Intelligence
•
•
•
•
Proactive(Down to business and positive )
Accelerates decision-making
Increases information flows
Components of proactive BI:
– Real-time warehousing
– Automatic learning
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Components of DSS
• Subsystems:
– Data management
• Managed by DBMS
– Model management
– User interface
– Knowledge Management and
organizational knowledge base
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© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
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Data Management Subsystem
• Components:
– Database
– Database management system
– Data directory
– Query facility
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© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Database
• Interrelated data extracted from
various sources, stored for use by the
organization, and queried
– Internal data, usually from TPS
– External data from government
agencies, trade associations, market
research firms, forecasting firms
– Private data or guidelines used by
decision-makers
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Database Management System
•
•
•
•
•
•
Extracts data
Manages data and their relationships
Updates (add, delete, edit, change)
Retrieves data (accesses it)
Queries and manipulates data
Employs data dictionary
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• What are the major functions(capabilities)
of DBMS?
Storage, retrieval, and control are the three
basic functions. The DBMS manages the
database: organize, extract/access, modify,
delete, and catalogue data.
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Data Directory
• Catalog of all data
– Contains data definitions
– Answers questions about the availability
of data items
– Source
– Allows for additions, removals, and
alterations
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• Extraction ,Capture data from several sources,
filter them, summarize, condense, and reorganize
the data.
• the function of a query facility is to Provides the
basis for access to data. Accepts requests, checks
for feasibility, provides answers.
•
the function of a directory is a catalog of all data
in the database. It includes data definitions.
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Model Management Subsystem
• Components:
– Model base
– Model base management system
– Modeling language
– Model execution, integration, and
command processor
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Models
• Strategic models
– support top management's strategic
planning. For example, examination of
acquisitions, diversifications, and
mergers.
• Tactical models support mainly middle
management in resource allocation and
in control. For example, make or buy
decisions or devising a major promotion
plan.
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• Operational
– Supports daily activities
• Analytical
– Used to perform analysis of data
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Model Base Management System
• Functions:
– Model creation
– Model updates
– Model data manipulation
• Model directory:
– Catalog of models
– Definitions
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Model Management Activities
• Model execution
– Controls running of model
• Model command processor
– Receives model instructions from user
interface
– Routes instructions to MBMS or module
execution or integration functions
• Model integration
– Combines several models’ operations
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User Interface System
Data management
and DBMS
Knowledge-based
system
Model
management and
MBMS
User Interface Management System (UIMS)
Natural Language Processor
Input
Action
Languages
Based on Figure 3.6, Schematic
View of the User Interface
Users
Output
Display
Language
PC Display
Printers, Plotters
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User Interface Management
System
• GUI
• Natural language processor
• Interacts with model management
and data management subsystems
• Examples
– Speech recognition
– Display panel
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•
A user interface covers all aspects of
the communications between a user and
the MSS. Most of the power, flexibility, and
ease-of-use characteristic of MSS are
derived from this component. As it is the
part of the system that the user sees, to
him/her, it is the system.
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Knowledge-Based Management
System
• All decisions require reasoning
• Reasoning : the process by which new information
is obtained from existing data or information
• Knowledge base is where the “knowledge” of the
DSS is stored
• Knowledge can be represented as simple if-then
rules, heuristics, previous outcomes or information
that may have been programmed into the DSS by
the designer
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DSS Hardware
• De facto standard
• Web server with DBMS:
– Operates using browser
– Data stored in variety of databases
– Can be mainframe, server, workstation,
or PC
– Any network type
– Access for mobile devices
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DSS Classifications
• GSS v. Individual DSS
– Decisions made by entire group or by
lone decision maker
• Custom made v. vendor ready made
– Generic DSS may be modified for use
• Database, models, interface, support are
built in
• Addresses repeatable industry problems
• Reduces costs
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•
•
List the major components of DSS and
briefly define each of them.
The major components are:
–
–
–
–
Data management; includes a database and
its management system.
Model management; includes models and
their management system.
Knowledge base; includes artificial
intelligence enhancements to the other
components.
The user; he or she is the decision maker.
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•
List and describe the major classes of DSS
users.
The major classes of DSS users are:
Management (user, decision-maker) - looking for
more user-friendly systems that can do more
general analysis and aid in decision making.
Staff (intermediaries) - are looking for more detailedoriented system and are willing to use more
complex system. Staff acts as intermediary
between MSS and manager. Different
intermediaries:
Staff assistants have specialized knowledge about
management problems and some experience
with the decision support technology.
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An expert tool user is skilled in the application of
one or more types of specialized problem-solving
tools. The expert tool user performs the tasks the
problem solver does not have the technical skills
to do.
Business (system) analysts have a general
knowledge of the application area, a formal
business administration education, and
considerable skill in DSS construction tools.
Facilitator in GSS controls and coordinates the
software of group DSS.
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•
•
•
•
What types of support are provided by
DSS?
DSS provides:
In semistructured and unstructured
situations
Support by bringing human judgment and
computerized information together.
Support for various managerial levels,
ranging from top executives to line
managers.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
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• Support to individuals as well as groups,
since less structured problems sometimes
require several individuals from different
departments and organizational levels.
• Support to several interdependent and or
sequential decisions.
• Support in all phases of the decisionmaking process: intelligence, design,
choice, and implementation.
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