dss

Decision Support System

Amit Kr Bhardwaj, LMTSOM, Thapar
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Decision Support Systems Concept
• DSS are interactive computer-based systems, which help
decision makers utilize data and models to solve unstructured
problems (Scott Morton, 1971).

• Decision support systems couple the intellectual resources of
individuals with the capabilities of the computer to improve the
quality of decisions. It is a computer-based support system for
management decision makers who deal with semi-structured
problems (Keen and Scott Morton, 1978).

Content-free expression
• There is no universally accepted definition of DSS
Umbrella term vs. narrow definition (specific technology)

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What is a DSS
• The term DSS refers to systems which support
the process of decision making.
• DSS may be defined as a “what-if” approach
that uses an information system to assist
management in formulating policies and
projecting the likely consequences of
decisions.

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• DSS supports the decision making process
rather than automating the decision making
process.
• DSS allows the decision maker to retrieve data
and test alternative solutions during the
process of decision making .
• DSS may be considered as an extension of
MIS.

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Objectives of DSS
• To save time and effort in decision making process.
• To help in processing the collected data and in producing a suggested
solution to a problem.
• To provide sophisticated and fast analysis of vast amount of data and
information.
• To provide support for decision maker at all management levels mainly in
semi-structured or unstructured situation by bringing together human
judgement and computerized information.
• To promote learning, which leads to new demands and refinement of
application.
• To provide efficient and effective solution of every complex problem.
• To check the impact of changes on the proposed solution with help of
“what-if” analysis
• To use the goal seeking analysis to find the value of the inputs necessary
to achieve a desired level of output .

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Characteristics of a DSS
• Provide rapid access to information
• Handle large amounts of data from different sources
• Provides report and preparation flexibility
• Offer both textual and graphical orientation
• Support drill-down analysis
• Perform complex, sophisticated analysis and comparison using
advanced s/w
• Support optimization, satisfying and heuristic approaches.
• Goal seeking analysis
• Simulation

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Capabilities of DSS
• Support for problem solving Phase
• Support for different decision frequencies
• Support for different problem structures
• Support for various decision-making levels

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Difference between DSS and MIS
MIS DSS
• MIS focuses on structured tasks and • DSS focuses on semi-structured
routine . tasks which require managerial
judgements
• MIS emphasis on data storage
• DSS emphasis on data
• In MIS, data is often accesses
manipulation
indirectly by managers
• In DSS, data is directly by managers
• MIS puts reliance on computer
experts • DSS puts reliance on manager’s
own judgement.
• MIS places emphasis on efficiency
of decision • DSS places emphasis on
effectiveness of decision
• MIS provides tactical information to
top management to take decisions. • DSS provides strategic information
• MIS are regular and recurring • The need for DSS can be irregular.

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Types of DSSs
• Data -oriented
• Model-oriented DSS

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Alter’s Classification of DSS Components

File Draw er Data Analysis
System s System s

Analysis Representational
Inform ation Models
System s

Optim ization
Suggestion Models
Models
Accounting
Models

Marakas: Decision Support
Systems, 2nd Edition © 2003, Chapter 1 - 10
Prentice-Hall

Data -oriented DSS

• DSS- database plays a vital role in structure of DSS, It provide the
data retrieval, analysis and presentation. Very often data from TPS
are collected in data warehouse and this data can be analyzed
with use of online analytical processing and datamining. Data
warehouse integrate multiple databases and other information
sources into a single repository or access point that is suitable for
direct querying, analysis or processing., whereas the datamining
(data mining is the process of finding correlations or patterns
among dozens of fields in large relational databases.) is refers to
extracting or ‘mining ‘ knowledge from large amount of data.

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File Drawer Systems
• They are the simplest type of DSS
• Can provide access to data items
• Data is used to make a decision
• ATM Machine
Use the balance to make transfer of funds
decisions

Data Analysis Systems
• Provide access to data
• Allows data manipulation capabilities
• Airline Reservation system
No more seats available
Provide alternative flights you can use
Use the info to make flight plans

Analysis Information Systems
• Information from several files are combined
• Some of these files may be external
• We have a true “data base”
• The information from one file, table, can be
combined with information from other files
to answer a specific query.

Model based DSSs
• Model based DSSs use some type of model to
perform ‘what-if’ and other kind of analysis
to make decisions. These systems include
activities such simulation, optimizing
scenario .this type of DSSs usually are
developed by persons with management
science background.

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Accounting Models
• Use internal accounting data
• Provide accounting modeling capabilities
• Can not handle uncertainty
• Use Bill of Material
– Calculate production cost
– Make pricing decisions

Representational Model
• Can incorporate uncertainty
• Uses models to solve decision problem using
forecasts
• Can be used to augment the capabilities of
Accounting models
• Use the demand data to forecast next years
demand
• Use the results to make inventory decisions.

Optimization Systems
• Used to estimate the effects of different
decision alternative
• Based on optimization models
• Can incorporate uncertainty
Assign sales force to territory
Provide the best assignment schedule

Suggestion Systems
• A descriptive model used to suggest to the
decision maker the best action
• A prescriptive model used to suggest to the
decision maker the best action
• May incorporate an Expert System
• Use the system to recommend a decision
• Ex: Applicant applies for personal loan

Information from Datamining
• Association: correlation relationship
• Sequence: time series analysis
• Classification and prediction
• Clustering

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Elements of DSS

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Elements of DSS
• USERS
• Databases
• DSS software- DBMS, MMS(Model
Management Software)
• Model base: Optimization models, Forecasting
Models and Sensitivity analysis models

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Architecture of DSS

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Working of DSS

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Applications of DSS
• DSSs support unstructured and semi-
structured decisions
• DSS support different decision frequencies.
• DSS support different problems structures
• DSS support various decision making levels

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Advantages of DSS
• As DSS reduces the time and efforts in collecting and analysis of
data for different sources, a large number of alternatives can be
evaluated .
• As modelling and forecasting is made easy by DSS, managers gets
more insights into business processes. Thus, it enables a thorough
quantitative analysis in a very short time. Even major changes in a
scenario can be evaluated objectively in a timely manner.
• DSS makes it possible to explain to others the basis for arriving at a
particular conclusion.
• DSS allows the decision makers to interact in a natural manners due
to the careful design of the interface.
• Cost saving
• Improve managerial effectiveness
• Support of individual/ groups
• Use and control rests with the user and not with the EDP dept.
• Flexible and adaptive.
• Improve the effectivenessKrof the LMTSOM, Thapar
Amit Bhardwaj, decisions.
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Tools of DSSs
• Material Requirement Planning (MRP) is method for ordering and
maintaining materials stocks cost effectively.
• Linear Programming: PERT, CPM
• Queuing Theory
• Descriptive statistics
• Correlation analysis
• Variance analysis
• Network analysis
• Transportation problems
• Maximum flow or distance
• Regression analysis
• Multi dimensional scaling
• Dynamic programming
• Probability theory

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GROUP DSS
• The DSS approach has resulted in better decision making for
all levels of individual users.
• However, Many DSS approaches and techniques are not
suitable for a group decision-making environment.
• Although not all workers and managers are not involved in
committee meetings and group decision- making sessions,
some tactical and strategic-level managers spend more than
half their decision-making time in group settings.
• Such managers need assistance with group decision making.

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• A Group Support System( GSS), Also called a
group decision support system and a
computerized collaborative work system,
consists of most of the elements in DSS, plus
s/w to provide effective support in group
decision-making settings

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Characteristics of a GDSS that
Enhance Decision Making
• Special Design
• Ease of use
• Flexibility
• Decision-Making Support
• Anonymous Input
• Reduction of Negative Group Behavior
• Parallel Communications
• Automated recordkeeping
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GSS software
• GSS s/w, often called groupware or workgroup
s/w, helps in joint group scheduling,
communication, and management.
• Eg s/w from Autodesk is helping design the
1776’ tall Freedom Tower to replace the twin
towers of World Trade Center in New York city

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In addition to groupware, GSSs use
a number of tools
• Email and Instant Messaging
• Videoconferencing
• Group Scheduling
• Project Management
• Document sharing

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GSS Alternatives
• Decision room
• The local area decision network
• Teleconferencing
• Wide area decision network

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Advantages of GDSS

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Limitation of GDSS

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Components of GDSS
• Hardware
• Software
• People

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GDSS software includes
• Electronics questionnaires
• Electronics brainstorming tool
• Idea organiser
• Tools for voting and setting priorities.
• Policy formulation tool
• Group dictionaries
•

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Example of DSS in Accounting system
• Budgeting models
• Cost analysis model
• Break even analysis
• Evaluation of funds and investment
• Cash and funds flow model for budegting

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• Manoratty na sidhayanti karayani, Suptasay
sihangasay mukhe mriga na nivsanti
• Hardwork is the key of Success. Never
compromised with hardwork,

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