UNIT –IV

 Decision Support System: Definitions of DSS

 Architecture of DSS
 Scope of DSS
 Characteristic and Capabilities of DSS
 Components of DSS
 Modules in DSS
 Classification of DSS
 DSS Tools
 DSS Generators
 Steps in Designing a DSS.

“A decision support system is a specialized kind of information system which is an interactive

system that supports in the decision making process of a manager in an organization especially in
semi-structured and unstructured situations. The system utilizes information, models and data
manipulation tools to help make decisions in semi-structured to unstructured situations.

Types of Decision Support Systems (DSS)

Data-Driven DSS take the massive amounts of data available through the company’s TPS and MIS
systems and cull from it useful information which executives can use to make more informed
decisions. They don’t have to have a theory or model but can “free-flow” the data. The first generic
type of Decision Support System is a Data-Driven DSS. These systems include file drawer and
management reporting systems, data warehousing and analysis systems, Executive Information
Systems (EIS) and Spatial Decision Support Systems. Business Intelligence Systems are also
examples of Data-Driven DSS.

Model-Driven DSS A second category, Model-Driven DSS, includes systems that use accounting and
financial models, representational models, and optimization models. Model-Driven DSS emphasize
access to and manipulation of a model. Simple statistical and analytical tools provide the most
elementary level of functionality. Some OLAP systems that allow complex analysis of data may be
classified as hybrid DSS systems providing modeling, data retrieval and data summarization
functionality. Model-Driven DSS use data and parameters provided by decision-makers to aid them
in analyzing a situation, but they are not usually data intensive.

Knowledge-Driven DSS The terminology for this third generic type of DSS is still evolving.
Currently, the best term seems to be Knowledge-Driven DSS. Adding the modifier “driven” to the
word knowledge maintains a parallelism in the framework and focuses on the dominant knowledge
base component. Knowledge-Driven DSS can suggest or recommend actions to managers. These
DSS are personal computer systems with specialized problem-solving expertise.

Document-Driven DSS A new type of DSS, a Document-Driven DSS or Knowledge Management

System, is evolving to help managers retrieve and manage unstructured documents and Web pages.
A Document-Driven DSS integrates a variety of storage and processing technologies to provide
complete document retrieval and analysis. The Web provides access to large document databases
including databases of hypertext documents, images, sounds and video.
Communications-Driven and Group DSS Group Decision Support Systems (GDSS) came first, but
now a broader category of Communications-Driven DSS or groupware can be identified. This fifth
generic type of Decision Support System includes communication, collaboration and decision
support technologies that do not fit within those DSS types identified. Therefore, we need to
identify these systems as a specific category of DSS.

Characteristics and Capabilities of DSS

1. DSS provide support for decision makers mainly in semi-structured and unstructured
situations by bringing together human judgment and computerized information.\
2. Support is provided for various managerial levels
3. Support is provided to individuals as well as to groups
4. DSS provide support to several interdependent and/or sequential decisions
5. DSS support all phases of the decision-making process:
6. DSS support a variety of decision-making processes and styles.
7. DSS are adaptive over time.
8. Users must feel at home with DSS
9. DSS attempt to improve the effectiveness of decision making rather than its efficiency.

Needs of DSS: - DSS have become necessary for today’s manager because of following reasons: -
Fast computation: - A decision maker can perform a large number of computations very quickly
and that too at a low cost with the help of computer support systems.
Enhanced productivity: - Decision support system can enhance the productivity of support staff
and also enable the group members to discuss the problems among themselves as a distance.
Better decisions: - Computer support system can help a decision-maker in arriving at a better
decision. For example, more alternatives can be evaluated, risk analysis be performed quickly,
and views of experts from different places can be collected quickly and at a lower cost.
Data transmission: - Sometimes the data, which may be stored at different locations, may be
required to be transmitted quickly from distant locations. Computer support system can
search, store, and transmitted the required data quickly and economically.

Components of DSS: - The main component of DSS is

1. Hardware
2. Software
Hardware: - Hardware is that parts of the computer system that can be touched. These are
tangible parts. Without hardware, software is nothing. Hardware is just like human body and
software is like soul in body. All input and output devices are hardware parts. For example
Mouse, Keyboard etc. are the parts of hardware.
There is no fixed hardware configuration for designing, developing, maintaining and executing
DSS. The hardware configuration for a DSS is mainly determined by:-
a) The size of the database
b) The DBMS package which one intends to use.
c) The type of model that are being used.
d) Ways in which reports/presentations are expected.
Software: - Software is a set of computer programs that are designed and develop to perform a
specific task. Software acts as a interface between the user and computer. Software can be
defined as a set of instructions written by a programme to solve a problem. It can be classified
as:-
e) Database Management Sub-System
f) Model Management Sub-system
g) Dialogue Management Sub-system

This is explained as below:-

a) Database Management Sub-system:- Normally there are two sources of data such as
internal source or external source. Database management system provides facilities for
organizing, storing and queering these data. It acts as an information bank. DBMS software
provides various facilities to modify and delete for database creation, manipulate the data
present in database, query the data in the database.
The architecture of a database management system includes External Schema, Conceptual
Schema, and Internal Schema.

b) Model Management Sub-system:- A model presents the relationship between various

parameters of the system. It gives a mathematical description of reality. The model builder
provides a structured framework for developing models by helping decision makes. The
model builder also contains model dictionary consistencies in the definitions user of models.
A model management subsystem provides the following: -

1. A model base management system which helps in the creation of models and
maintenance of the same.
2. An external interface which permits a user to choose a model to be executed and
provides facilities for entering data.
3. An interface to the database.
c) Dialogue Management Sub-system:- This acts as the gateway for the user to communicate
with the DSS. It provides menus and icons for the user to communicate effectively with the
system. It converts the queries given by the user into forms which the other subsystems can
recognize and execute. It keeps a track of activities that are being performed.

The major activities of a Dialogue management subsystem are to:

1. Provides menus and icons for the user to communicate effectively with the system.
2. Provide necessary on-line context sensitive help to various kinds of users.
3. Convert the queries given by the user into forms which the other subsystems can
recognize and execute.
4. Keep track of the activities that are being performed.
Advantages of Decision Support Systems (DSS)
1. Time savings
2. Enhance effectiveness
3. Improve interpersonal communication
4. Competitive advantage
5. Cost reduction
6. Increase decision maker satisfaction
7. Promote learning
8. Increase organizational control

Disadvantages of Decision Support Systems (DSS)

1. Monetary cost.
2. Overemphasize decision making.
3. Assumption of relevance
4. Transfer of power.
5. Unanticipated effects.
6. Obscuring responsibility.
7. False belief in objectivity.
8. Status reduction.
9. Information overload.

Classification of DSS
(i) Fie Drawer Systems :- This is a system which provide the user with organized
information regarding specific demands. This system provides on-line information. This
is very useful system for decision making.

(ii) Data Analysis Systems: - These decision systems are based on comparative
analysis and makes use of a formula. The cash flow analysis, inventory analysis and
personnel inventory systems are examples of the analysis systems. This use of simple
data processing tools and business rules are required to develop that system.

(iii) Information Analysis System: - In this system the data is analyzed and the
information reports are generated. The decision makers use these reports for
assessment of the situation for decision-making. The sales analysis, accounts receivables
system, market research analysis are examples of such systems

(iv) Accounting Systems: - These systems are not necessarily required for decision making
but they are desirable to keep track of the major aspects of the business. These systems
account items such as cash, inventory, and personnel and so on.

(v) Model Based Systems: - These systems are simulation models or optimization models
for decision making. It provides guidelines for operation or management. The product
decision mix decisions, material mix, job scheduling rules are the examples. It is the
most important type of DSS.
 (vi) Solver Oriented DSS: - It is performing certain computations for solving a particular
type of problem. The solver could be economic order quantity procedure for calculating
an optimal ordering quantity.
vii) Suggestion System: - There are used for operational purposes. They give suggestion
to the management for a particular problem. This model helps in making required
collection of data before taking a suitable decision.

viii) Compound DSS: - It is a system that includes two or more of the above five basic
structures explained above. It can be built by using a set of independent DSS, each
specializing in one area.

ix) Text oriented DSS: - A Text oriented DSS supports a decision maker by electronically
keeping trade of textual represented information that have a bearing on decision. It
allows documents to be electronically created, revised and viewed as needed. The
information technologies such as documents emerging, hypertext and intelligent agents
can be incorporated into this type.

DSS Architecture

Organizations are decision-driven. The success or failure of each decision impacts a company’s
strategy directly or indirectly. If organizational decision making is aligned with the right kind of
artificial intelligence system, chances are that the performance of the organization will improve to a
great extent.
The alignment of human intellect with computerized decision support systems has become
essential for rapid, more appropriate and agile decision making. Given the pace of change and
continuous economic turbulence, it’s become vital to combine strategy, human cognition and
technology. And this is why computerized decision support systems have become an integral part of
organizational decision making.
This means that each organization needs to build some sort of IT infrastructure to support decision
making. Though they realize its importance and also put a lot of effort in building one to fulfill their
needs. However, in some organizations, a DSS is built in an inept and incompetent manner. The
design process is shortened and is carried out in a hasty manner.
While this is understandable because of the cut throat competition, ever changing business
environment and economically unstable setting, but companies need more time to gather creative
inputs, work on design and infrastructure of a DSS along with DSS analysts and programmers and
identify potential security and networking issues. This will help in building a strong, more
appropriate and highly effective decision support system.
Unless each component of a DSS is carefully designed and developed, it’s impossible to create
a standalone computer system to support decision making. This requires equal involvement of
decision makers and DSS analysts, designers and programmers. Each of the DSS architecture
components requires a careful approach and stanch support from all the parties.

How are DSS architecture, network and security interrelated ?

DSS architecture, network and security are interconnected. The study of DSS architecture involves
obtaining an in-depth understanding about how a user is going to interact with the system and how
information will flow from one point to another. DSS network is concerned about how hardware is
organized, how data is distributed throughout the system, how DSS components are connected and
whether the information is fed/accessed using internet, extranet or intranet.

While DSS architecture is concerned about conception of the structure, model and behavior of a
system which is to be developed, networking is all about connection between the components –
software and hardware.

Security is central to any computer software system and a DSS is no exception to the rule. A virus
attack, a hacking attempt or information leakage can cause damage to the system as well as the
organization. As a decision support system contains secret information, it needs to be 100% safe
and secure. It’s also necessary for safeguarding employee and customer data.

Let’s take a close look at these components.

DSS Architecture
There are four fundamental components of DSS architecture:
 User Interface
 Database
 Model (context or situation representation)
 Knowledge
User Interface
In the previous article, we learnt what it takes to design and build an effective user interface design.
Since it’s a full-fledged subject of study, we looked at the prerequisites of a good user interface
design, concerns pertaining to dialogue development, flexibility, mode of feeding information,
interface design rules and factors influencing the success of a user interface design.
The Database
Next, comes the database. It serves as the storehouse of information. It contains:
i. Personal/internal information – details collected from within the organization, from
employees, customers. It may include ideas, your own thoughts, experiences and
insights.
ii. External information – information collected from outside sources, like independent
researches, internet, government organizations, etc.
A DSS accesses information directly from the database, depending upon your needs and type of
decision you are making. A decision support system architecture scheme focuses on
iii. Type of database required for a particular decision making system model
iv. Who’s responsible for different types of databases
v. How to maintain accuracy and security of database
Model
This component of DSS architecture takes care of:
vi. DSS model and
vii. DSS model management system
While a model is a representation of context, a situation or an event, a DSS model management
system stores and maintains DSS models.
A model makes an important component of DSS architecture because it allows you to carry out a
particular type of data analysis that you need for a particular kind of decision-making. For example,
you need to understand what happens if you change a particular variable. A spreadsheet-based
model will help you conduct what-if analysis.
A model management system just stores and manages DSS models. But it doesn’t help you decide
the best model for a decision type. Decision makers can use their expertise to decide the model for
resolving a particular model.

Knowledge
This element of DSS architecture provides information about the relationship among data, which is
too complex. It manages the knowledge and provides decision makers with alternative solutions of
a problem. It also sends signals to decision makers when there is any mismatch between forecasted
and actual results.
What Does a DSS Architecture Scheme Address ?
A well defined DSS architecture scheme addresses:
 A problem definition that a DSS is expected to resolve
 The objectives of a DSS
 Components of a DSS and connection between them
 Development and maintenance schedule
 Skills, tools, funds and other support required for DSS development
 Anticipated enhancements
 Project participants and their roles
DSS Networking
A decision support system is connected to various computers (workstations), databases and
servers. This connection is important for a DSS to work; however, this can give rise to a number of
networking and computing issues.
Also, the increasing trend of internet-based DSS system may add to the intensity of networking and
security issues. In this section, we’re going to learn about basic networking concepts and related
issues.
DSS architecture is based on the physical connection among its various components as well
hardware. And the way in which components or systems are networked define how information
flows. However, before we discuss this in detail, let’s understand what a network is and how it can
be established:
Network: A network is an assortment or a group of computers that are connected with each other
or in a specific way, in order to communicate with each other. This connection facilitates the sharing
of information among the connected computer systems.
To communicate among the connected systems requires:
 An agreement upon language of communication
 Unique identifier for each host/networked computer
 Physical connection, such as modem or Ethernet
 A network protocol (rules and formats for information sharing)
 A technology for information sharing (LAN, Internet, Remote Access Dialup Servers and
private Integrated Services Digital Networks (ISDN)
Designing and Building a Decision
Support System
A lot goes into designing and building a decision support system. It works as a
support system only after it is fed intelligence during its development. Developing a
DSS is a complex process and thus, takes longer. It goes repetitively through three
stages - inputs, activities and outputs during each phase of system development
lifecycle. You provide an input, carry out the desired activity and measure the
output. You move further, if it produces the right output or else you come back to
the input phase and make adjustments.

A DSS framework design and development goes through these stages:

1. Intelligence

At this stage, the objective is to search for problems/situations/conditions that

call for decision.
 You, as a business, are expected to identify and define the problem context
for which support is required. You must define the objectives and available
resources, so that the outcomes generated meet your expectations.

2. Design

This stage deals in analyzing all possible actions, along with the
determination of system design and system construction.

System design includes determination of components, platform, function

libraries and special languages while system structure is about deciding the
prototype approach. This stage also includes identifying hardware
requirements. The development starts here.

3. Choice

Once you shortlist and analyze all possible courses of actions in step 2, now is
the time to choose the best from among them, depending upon your business
objectives and results generate.

4. Implementation

This is the final stage where testing, evaluation, adjustments and deployment
take place. However, this is the final product but this can be tweaked, refined
and upgraded basis your activities and requirements.
When developing a custom DSS, these are important factors that must be kept in
mind:

 Data management functions

 Available hardware platforms

 User interface

 Compatibility with other applications

 Cost

A decision support system helps improve your bottom line, only if it’s customized to
your specific needs and is implemented correctly.