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INTRODUCTION TO DSS….
SUBJECT NAME : DECISION SUPPORT SYESTM.
SUBJECT CODE : GE5B_12.
STUDENT NAME : RAHUL MODAK.
UNIV ROLL NO : 22601221182
UNIV REG NO : 212261001210182
DEPARTMENT : B.C.A
SEMESTER : 3

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Characteristics and Capabilities of DSS
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
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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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DSS Components
1. Data Management Subsystem
2. Model Management Subsystem
3. Knowledge-based (Management) Subsystem
4. User Interface Subsystem
5. The User

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DSS Components
User
User Interface
DBMS MBMS
KBS3
KBS2
KBS1

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Types of decision support systems
Decision support systems can be broken down into
categories, each based on their primary sources of
information.
Data-driven DSS
A data-driven DSS is a computer program that makes
decisions based on data from internal databases or
external databases. Typically, a data-driven DSS uses
data mining techniques to discern trends and patterns,
enabling it to predict future events. Businesses often use
data-driven DSSes to help make decisions about
inventory, sales and other business processes. Some are
used to help make decisions in the public sector, such as
predicting the likelihood of future criminal behavior.
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Model-driven DSS
Built on an underlying decision model, model-driven
decision support systems are customized according to a
predefined set of user requirements to help analyze
different scenarios that meet these requirements. For
example, a model-driven DSS may assist with scheduling or
developing financial statements.
Communication-driven and group DSS
A communication-driven and group decision support system
uses a variety of communication tools -- such as email,
instant messaging or voice chat -- to allow more than one
person to work on the same task. The goal behind this type
of DSS is to increase collaboration between the users and
the system and to improve the overall efficiency and
effectiveness of the system.

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Knowledge-driven DSS
In this type of decision support system, the data that
drives the system resides in a knowledge base that is
continuously updated and maintained by a knowledge
management system. A knowledge-driven DSS provides
information to users that is consistent with a company's
business processes and knowledge.
Document-driven DSS
A document-driven DSS is a type of information
management system that uses documents to retrieve
data. Document-driven DSSes enable users to search
webpages or databases, or find specific search terms.
Examples of documents accessed by a document-driven
DSS include policies and procedures, meeting minutes
and corporate records.

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Fast:
DSS is a fast method for taking decisions. Computers give us
results fast. The data we need is displayed on the screen within
a few minutes. We have to just take decisions overselves after
getting data from the computer software.
Automation:
If you want to reward any customer then you don’t need to
worry. The software will know which consumer buy most of
the company products and you will give them a 50% discount
on their next purchase. So it automates the process of decision
making.
Advantages of a decision support system (DSS):
Efficient:
It is an efficient method. There are fewer chances that
computerized data may be wrong. Computers always extract the
data that we feed to them. If we feed relevant data then it will
output data that is accurate. (more)

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Training:
If we have all the data available on our desk then deciding by
top management is easy. They make decisions in no time. First,
they get data from a single click. For example, the CEO of
Samsung want to know how many sales of a specific model of
mobile is sold in December, then he will get information from
the computer software. If he wants to know which Samsung
mobile model has most of the sales in last year then he will
know by doing a couple of clicks from the computer. It is noted
that the data is only available to the CEO and top management
of the company. So they don’t need extra training.
Communication:
The top company authority gets accurate data from the
computerized software. The company CEO and managerial staff
communicate with each other and make decisions. They have
all the statement ready from the software and they have to only
say yes or no to the statements.

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Low cost:
If we use the old method of organizing and processing the data
then it consumes a lot of manpower. We just get data from
relevant authorities and input it into our software. We also get
data from doing little research in any field. For example, if we
want to construct a building then we get information from real
estate agents about cost, time, structure, maps and then we
input in computer software and get the results about total cost,
and time duration.
Satisfaction:
If you make a random decision without any valid data in front of
you then you will be not confident in your decision. But if you
first see the data and then make a decision then you get
satisfaction with your decisions.

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Disadvantages of a decision support system (DSS):
Limited skills:
If the management of the company gets all the data
prepared by the system then they don’t do any research by
themselves. I mean they will do less mental things. Their
brain will become limited. Their skills will be not polished.
Blame computer:
If any staff make mistake then he will directly blame the
computer. He will tell that his computer is not working that
is why I am not giving a result.
Machine dependent:
All the data is kept in the computer machine. So the CEO will
be bound to the machine. He cannot decide without
investigating data from the machine.
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Wrong information:
If the computer system is given the wrong data input then the
results will also be not correct. The computer does not know if the
data is right or wrong. The computer is dependent on us. If we feed
the right data it will show the right result and if we make mistakes
and feed wrong data to the computer then obviously it will show us
the wrong result.
Overconfidence:
The management of the company becomes overconfidence. They
know all the data and take decisions upon data. But they don’t
know that they are doing clerical work. They are making fewer self-
decisions and they are most of the time fetching data from the
machine.
Wrong coding of software:
Sometimes the software is not coded correctly. The software may
get errors and shows wrong results. I mean it will show errors
which you try to fetch data. So the IT staff of the company have to
make sure that software works well before handling it to
management staff.

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Organizations use decision support systems in several
different contexts, including the following:
•GPS routing. GPS route planning is an example of a
typical DSS. It compares different routes, taking into
account factors such as distance, driving time and cost.
The GPS navigating system also enables users to choose
alternative routes, displaying them on a map and providing
step-by-step instructions.
•ERP dashboards. ERP (enterprise resource planning)
dashboards can use a decision support system to visualize
changes in production and business processes, monitor
current business performance against set goals and identify
areas for improvement. ERP dashboards let business
owners see a snapshot of their company's most important
numbers and metrics.
DECISION SUPPORT SYSTEM EXAMPLES
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•Clinical decision support system. A clinical decision
support system (CDSS) is a software program that uses
advanced decision-making algorithms to help physicians
make the best medical decisions. Healthcare
professionals often use these to interpret patient records
and test results, and to calculate the best treatment plan.
CDSS in healthcare can help providers identify
abnormalities during specific tests, as well as monitor
patients after certain procedures to determine if they are
having any adverse reactions.
•Crop-planning. Farmers use DSS to help them
determine the best time to plant, fertilize, and
reap their crops. Bayer Crop Science has applied
analytics and decision-support to every element of
its business, including the creation of “virtual
factories” to perform “what-if” analyses at its corn
manufacturing sites.