Presentation on Decision Support Systems.

1. DECISION SUPPORT
SYSTEMS

2. WHAT IS DECISION MAKING?
• A selection process, concerned with selecting the best type of alternative
• The thought process of selecting a logical choice from the available options
• The process by which managers respond to opportunities and threats
• It leads to commitment. The commitment depends upon the nature of the
decision whether short term or long term.

3. MANAGERS AND DECISION MAKING
• It is very difficult for managers to make good decisions without valid, timely
and relevant information:
 Number of alternatives to be considered is increasing
 Many decisions are made under time pressure

4. DECISION PROCESS
• Decision makers go through a fairly systematic process:
Act on it
Review It
Define the
“Process or Problem”
Develop Alternative
Courses of Action
Select
The “Best” One

5. THE NATURE OF DECISIONS
• Information systems can support decision-making levels.
• These include the three levels of management activity.
 Strategic management
 Tactical management
 Operational management

6. INFORMATION REQUIREMENTS BY
MANAGEMENT LEVEL
Strategic
Management
Tactical
Management
Operational
Management

7. TYPES OF DECISIONS
• The decision fall into one of the following categories:
 Structured Decisions
 Unstructured
 Semi-Structured

8. STRUCTURED DECISIONS
• Structured decisions are repetitive and routine problems for which standard
solutions exist
• Ex: finding an appropriate inventory level, finding an optimal investment
strategy

9. UNSTRUCTURED DECISIONS
• Unstructured decisions are non-routine and complex.
• We cannot specify some procedures to make a decision
• Ex: expanding the business, moving operations to foreign countries.
• IS must provide a wide range of information products to support these types
of decisions at all levels of the organization

10. SEMI-STRUCTURED DECISIONS
• Semi-structured decisions fall between structured and unstructured
decisions
• It requires a combination of standard procedures and individual judgment.
• Ex: annual evaluation of employees, trading bonds, setting marketing
budgets for consumer products.

11. WHAT IS DSS?
• A decision support system is a computer application that analyzes business
data and presents it so that users can make business decisions more easily.
• It is an informational application.
• Typical information that a decision support application might gather and
present would be:
 Comparative sales figures between one week and the next
 Projected revenue figures based on new product sales assumptions
 The consequences of different decision alternatives, given past
experience in a context that is described

12. DSS ARCHITECTURE
• Three fundamental components of a DSS architecture are:
• the database (or knowledge base),
• the model (i.e., the decision context and user criteria), and
• the user interface
The users themselves are also important components of the architecture.

13. TYPES OF MODELS
• DSS software is a collection of software tools that are used for data analysis
or a collection of mathematical and analytical models.
• There can be 3 different types of modeling software for DSSs:
 Statistical models
 Optimization models
 Forecasting models

14. STATISTICAL MODELING
• Statistical modeling software can be used to help establish relationships
such as relating product sales to differences in age, income or other factors
between communities.
• Ex: SPSS.

15. OPTIMIZATION MODELS
• Optimization models often using Linear Programming (LP) determine the
proper mix of products within a given market to maximize profit.

16. FORECASTING MODELS
• The user of this type of model might supply a range of historical data to
project future conditions and sales that might result from those conditions.
• Companies often use this software to predict the action of competitors.

17. CAPABILITIES OF DSS
• Using a DSS involves 4 basic types of analytical modeling activities:
 What-if analysis
 Sensitivity analysis
 Goal-seeking analysis
 Optimization analysis

18. WHAT-IF ANALYSIS
• What-If analysis is used to determine what some of the possible changes
could be on a theoretical solution.
• Observing how changes to selected variables affect the other variables.
• E.g. What if we cut advertising by 10%?What would happen to sales?

19. SENSITIVITY ANALYSIS
• Sensitivity analysis is the study of how different variables effect one and
other, when change occurs.
• Observing how repeated changes to a single variables affect other variables.
• E.g: Let's cut advertising by $1000 repeatedly so we can see its relationship
to sales.

20. GOAL-SEEKING ANALYSIS
• Compiles all of the given data and determines what inputs are required to
reach specific goals.
• Making repeated changes to selected variables until a chosen variable
reaches to a target value.
• E.g. Let's try increase in advertising until sales reach to target

21. OPTIMIZATION ANALYSIS
• To find the optimum value for one or more target variables, given certain
constraints.
• Finding an optimum value for selected variables, given certain constraints.
• E.g. What's the best amount of advertising to have, our budget and choice of
media?

22. CHARACTERISTICS OF DSS
• Improved decision making through better understanding of the businesses
• An increased number of decision alternatives examined
• The ability to implement ad hoc analysis
• Faster response
• Improved communication
• More effective teamwork
• Better control
• Time and costs savings

23. THANKYOU