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CHAPTER 3
DECISION SUPPORT
SYSTEMS CONCEPTS,
METHODOLOGIES,
AND TECHNOLOGIES:
AN OVERVIEW
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
Learning Objectives
 Describe the components and structure of
each DSS component: the data management
subsystem, the model management
subsystem, the user interface (dialog)
subsystem, the knowledge-based
management subsystem, and the user
 Explain Internet impacts on DSS and vice
versa
Learning Objectives
 Explain the unique role of the user in DSS versus
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management information systems (MIS)
Describe DSS hardware and software platforms
Understand important DSS classifications
Become familiar with some DSS application areas
and applications
Understand important, current DSS issues
DSS Configurations
 Decision support can be provided in many
different configurations。
 These configurations depend on the nature of
the management-decision situation and the
specific technologies used for support
DSS Configurations
 These technologies are assembled from four
basic components (each with several
variations and are typically deployed over the
Web)
 Data
 Models
 User interface
 Knowledge (optional)
DSS Description
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DSS application
A DSS program built for a specific purpose
(e.g., a scheduling system for a specific
company)
Business intelligence (BI)
A conceptual framework for decision
support. It combines architecture, databases
(or data warehouses), analytical tools, and
applications
DSS Description

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A DSS is an approach(or methodology)for
support decision making, it also supports all
phases of decision making and may include
a knowledge component
A DSS can be used by a single user on a PC
or can be Web-based for use by many
people at several locations
DSS Characteristics
and Capabilities
Decision Support And Business
Intelligence System /turban著/2005年
DSS Description
Decision Support And Business
Intelligence System /turban著/2005年
DSS Characteristics
and Capabilities

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/DSS. See also business intelligence
(BI).
DSS Characteristics
and Capabilities

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
 The key characteristics and capabilities of DSS
 Support for decision makers, mainly in semistructured
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，DSS
support virtual teams through collaborative web tools

DSS Characteristics
and
Capabilities
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
DSS Characteristics
and Capabilities
 User-friendliness, strong graphical capabilities, and a
natural language interactive human–machine 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
DSS Characteristics
and Capabilities
 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
Components of DSS
Decision Support And Business
Intelligence System /turban著/2005年
Components of DSS
 Database management system (DBMS)
Software for establishing, updating, and querying
(e.g., managing) a database
 Data warehouse
A physical repository where relational data are
organized to provide clean, enterprise-wide data in a
standardized format
 Database
The organizing of files into related units that are then
viewed as a single storage concept. The data in the
database are generally made available to a wide
range of users
Components of DSS
 Model management subsystem
 Model base management system (MBMS)
Software for establishing, updating, combining, and so
on (e.g., managing) a DSS model base
 User interface
The component of a computer system that allows
bidirectional communication between the system
and its user
Components of DSS
 Knowledge-based management subsystem
 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 ,knowledge may
be provided via web server, many artificial intelligence
methods have been implemented in web develop
system such as JAVA。
Data Management Subsystem
 The data management subsystem is composed of”
 DSS database
 DBMS
 Data directory
 Query facility
Data Management Subsystem
Decision Support And Business
Intelligence System /turban著/2005年
Data Management Subsystem
 The Database
 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
In large organizations that use extensive amounts of
data , such as WAL-MART , AT&T and American
Airlines data warehouse and used when needed。
 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
Data Management Subsystem
 Database management system (DBMS)
 Software for establishing, updating, and querying
(e.g., managing) a database
 Query Facility
The (database) mechanism that accepts requests for
data, accesses them, manipulates them, and queries
them
 Directory
A catalog of all the data in a database or all the
models in a model base
Data Management Subsystem
 Key database and database management system
issues
 Data quality
A key issue in data management，and if your data
management is poor the data cannot be trusted , and
therefore neither can any analysis based on them 。
Data Management Subsystem
 Data integration
Data and information are all over the place in most
organization。When it comes time to develop any
enterprise system，or even a single DSS，data must
be gathered from disparate sources and integrated
into that single version of the truth。
 Scalability
Key issues and important new directions discussed
include the internet as the main driving force for
applications especially across the enterprise
Data Management Subsystem
- Data security
one key issue that DBMS is supposed to handle by its
very nature is data security
The Model Management Subsystem
Decision Support And Business
Intelligence System /turban著/2005年
The Model Management Subsystem
 Model base
A collection of preprogrammed quantitative models
(e.g., special statistical, financial, optimization,
forecasting, management science and other
quantitative models that provide the analysis
capabilities) organized as a single unit。
The Model Management Subsystem
 Four categories of models with the model base
 Strategic models
 Tactical models
 Operational models
 Analytical models
The Model Management Subsystem
 Strategic models
It is used to support top manager’s strategic planning
responsibilities。Models that represent problems for
the strategic level (i.e., executive level) of management
 Tactical models
It is used mainly by middle managers to assist in
allocating and controlling the organization’s resources。
Models that represent problems for the tactical level
(i.e., midlevel) of management。
The Model Management Subsystem
 Operational models
It is used to support the day-to-day working activities
of the organization。Models that represent
problems for the operational level of management
 Analytical models
It is used to perform analysis on data 。
Mathematical models into which data are loaded for
analysis
The Model Management Subsystem
 Model building blocks and routines
 Model building blocks
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
 Model components for building DSS
At higher level than building blocks, it is important to consider the
different types of models and solution methods needed in the
DSS 。
 Modeling tools
It is often necessary to customize models, using programming
tools and languages 。
The Model Management Subsystem
 Model base management system: MBMS software
has four 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
The Model Management Subsystem
 Model directory
 Model execution is the process of controlling the actual
running of the model
 Model integration involves combining the operations of
several models when needed
 A model command processor is used to accept and
interpret modeling instructions from the user interface
component and route them to the MBMS, model
execution, or integration functions
User Interface (Dialog) Subsystem
 User interface
The component of a computer system that allows
bidirectional communication between the system
and its user.
 User interface management system (UIMS)
The DSS component that handles all interaction
between users and the system
User Interface (Dialog) Subsystem
 The user interface process
 Object
A person, place, or thing about which information is
collected, processed, or stored
 Graphical user interface (GUI)
An interactive, user-friendly interface in which, by using
icons and similar objects, the user can control
communication with a computer
User Interface (Dialog) Subsystem
Decision Support And Business
Intelligence System /turban著/2005年
User Interface (Dialog) Subsystem
 DSS user interfaces access is provided through Web
browsers including:
 Voice input and output
 Portable devices
 Direct sensing devices
User Interface (Dialog) Subsystem
 DSS developments
 Parallel processing hardware and software technologies
have made major inroads in solving the scalability issue
 Web-based DSS have made it easier and less costly to
make decision-relevant information and model-driven
DSS available to users in geographically distributed
locations, especially through mobile devices
User Interface (Dialog) Subsystem
 DSS developments
 Parallel processing hardware and software technologies
have made major inroads in solving the scalability issue
 Web-based DSS have made it easier and less costly to
make decision-relevant information and model-driven
DSS available to users in geographically distributed
locations, especially through mobile devices
User Interface (Dialog) Subsystem
 DSS developments
 Artificial intelligence continues to make inroads in
improving DSS
 Faster, intelligent search engines
 Intelligent agents promise to improve the interface in areas
such as direct natural language processing and creating facial
gestures
 The development of ready-made (or near-ready-made)
DSS solutions for specific market segments has been
increasing
User Interface (Dialog) Subsystem
 DSS developments
 DSS is becoming more embedded in or linked to most EIS
 GSS improvements support collaboration at the
enterprise level
 Different types of DSS components are being integrated
more frequently
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
The User
 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 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
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
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Communication and collaboration
Download DSS software
Use DSS applications provided by the company
Buy online from application service providers (ASPs)
DSS Classifications
 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
DSS Classifications
 Holsapple and Whinston’s classification
 Text-oriented DSS
 Database-oriented DSS
 Spreadsheet-oriented DSS
 Solver-oriented DSS
 Rule-oriented DSS
DSS Classifications
 Alter’s output classification
 Data
 File drawer systems
 Data analysis systems
 Data or models
 Analysis information systems
 Models
 Accounting models
 Representational models
 Optimization models
 Suggestion models
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 nature
 Ad hoc DSS
A DSS that deals with specific problems that are usually
neither anticipated nor recurring
DSS Classifications
 Other DSS categories
 Personal support
 Group support
 Organizational support
 Group support system (GSS)
Information systems, specifically DSS, that support the
collaborative work of groups
 Custom-made systems versus ready-made systems