The ultimate tool in mid/top management aid, it's how huge business entities get driven efficiently & effectively.

1. WELCOME
ً ‫مرحبا‬

2. DECISION
SUPPORT
SYSTEMS (DSS)
Khaled A. Anter

3. Ground rules
 Start at 9:00 am, End at 2:00pm
 15 min. Breaks at 10:30am, 12:00pm
 Phones silent please
 No politics, No religions, No sports
 Share your experience
 Relax & have fun

4. WHO ARE YOU?
WHY ARE YOU
HERE?

5. Training Objectives
 Understanding the complexity of the decision
making process on the organizational state
 Exploring the history & development of DSS’s
 Types & classifications of DSS’s
 Components of a DSS
 Capabilities & benefits of a DSS
 Case studies

7. Understanding the complexity of the
decision
 What is a decision?
 What is it’s importance in management & to
business?
 How do you usually take your
personal/professional decisions?

8. Classical methods of decision
making
 Pros and cons (Rational decision making)
Plato and Benjamin Franklin.
 Simple prioritization.
 Elimination by Aspects “ Amos Tversky in
1972”.
 Consent to a person in authority or an "expert“.
 Flipism.
 Prayer, tarot cards, astrology, augurs, revelatio
n, or other forms of divination.

9. Classical methods of decision
making
 Taking the most opposite action compared to
the advice of mistrusted authorities.
 Opportunity cost.
 Bureaucratic (set up criteria for automated
decisions)
 Political (negotiate choices among interest
groups)
 Use of a structured decision making method.

13. Quick overview
History of DSS

14. History of DSS
 Carnegie Institute of Technology during the late
1950s and early 1960s.
 late 1980s, executive information
systems (EIS), group decision support
systems (GDSS), and organizational decision
support systems (ODSS) evolved from the single
user and model-oriented DSS.
 In 1987, Texas Instruments completed
development of the Gate Assignment Display
System (GADS).
 Beginning in about 1990, data
warehousing and on-line analytical

15. Taxonomies
 By relationship:
 Passive, active, and cooperative DSS.
 By mode of assistance:
 Communication-driven DSS, data-driven
DSS, document-driven DSS, knowledge-driven
DSS, and model-driven DSS.
 By scope:
 Enterprise-wide DSS and desktop DSS.

16. Components of a DSS
1. The database (or knowledge base),
2. The model (i.e., the decision context and user
criteria),
3. The user interface.

17. Development Frameworks
 DSS technology levels (of hardware and
software) may include:
 The actual application that will be used by the
user.
 Generator contains Hardware/software
environment that allows people to easily develop
specific DSS applications.
 Tools include lower level hardware/software.

18. Classification of DSS applications
(cont.)
 By frameworks:
 Text-oriented DSS
 Database-oriented DSS
 Spreadsheet-oriented DSS
 Solver-oriented DSS
 Rule-oriented DSS
 Compound DSS (most popular).

19. Classification of DSS applications
(cont.)
 By support given by DSS:
 Personal Support
 Group Support
 Organizational Support

20. Classification of DSS
applications
 DSS components may be classified as:
 Inputs: Factors, numbers, and characteristics to
analyze
 User Knowledge and Expertise: Inputs
requiring manual analysis by the user
 Outputs: Transformed data from which DSS
"decisions" are generated
 Decisions: Results generated by the DSS based
on user criteria

21. DSSs which perform
selected cognitive decision-making
functions and are based on artificial
intelligence or intelligent agents
technologies are called Intelligent Decision
Support Systems (IDSS)
IDSS

22. Benefits of DSS (cont.)
 Improves personal efficiency
 Speed up the process of decision making
 Increases organizational control
 Encourages exploration and discovery on the
part of the decision maker
 Speeds up problem solving in an organization
 Facilitates interpersonal communication

23. Benefits of DSS
 Promotes learning or training
 Generates new evidence in support of a
decision
 Creates a competitive advantage over
competition
 Reveals new approaches to thinking about the
problem space
 Helps automate managerial processes
 Create Innovative ideas to speed up the
performance

24. DSS Characteristics and
capabilities (cont.)
 Solve semi-structured & Unstructured
problems
 Support To Managers At All Levels
 Support Individual and groups
 Inter-dependence and Sequence Decision.
 Support Intelligence, Designee, Choice.
 Adaptable & Flexible
 Interactive and ease of use

25. DSS Characteristics and
capabilities
 Interactive and efficiency
 Human control the process
 Ease of development by end user
 Modeling and Analysis
 Data Access
 Stand alone Integration & Web Based
 Support Varieties Of Decision Process

26. EE-DSS Kansas Use Case EPA
Active Traffic Management DSS
Safe & Sound NHS DSS
Case studies

27. EE-DSS Kansas Use Case EPA
Case I

28. EE-DSS Kansas Use Case EPA
 A tool for detecting and documenting
exceptional air quality events that cause the
violation of the National Ambient Air Quality
Standard.
 This DSS gathers data from: NASA satellite
sensors, Navy Aerosol Analysis and
Prediction System, NAAPS.

29. EE-DSS Kansas Use Case EPA
 After the evidence has been gathered, the states
can flag an event to be reviewed,
 Analysts at the state level can examine events,
trends, and concentrations and sends the data
with justification to the regional EPA,
 Upon approval at the regional level, is then sent to
the federal EPA who can decide whether the
event can be classified as exceptional,
 The DSS is a tool that supports every level of the
process, from identifying candidate events to the
eventual determination of the exceptionality of the
event.

30. Safe & Sound NHS DSS
Case II

31. Safe & Sound NHS DSS
 A web based communication DSS for pooling
medical cases information & aiding the
decision making process for doctors &
patients.
 It’s user friendly interface: PDA “aka Paddie”
(personal digital assistant)

32. Active Traffic Management DSS
Case III

33. Active Traffic Management DSS
 A system that gathers data from traffic, satellite
monitors to prepare optimal traffic schemes on
German autobahns by PTV,
 User interface in road sign displays.

34. Last words

35. ANY
QUESTION?
Thank you