WELCOME

مرحبا

DECISION SUPPORT SYSTEMS (DSS)

Khaled A. Anter

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

WHO ARE YOU?

WHY ARE YOU HERE?

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

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?

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, re

velation, or other forms of divination.

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.

Quick overview

History of DSS

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 processing (OLAP)

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.

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.

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.

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).

Classification of DSS applications (cont.)

By support given by DSS: Personal Support Group Support Organizational Support

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

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

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

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

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

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

EE-DSS Kansas Use Case EPAActive Traffic Management DSSSafe & Sound NHS DSS

Case studies

EE-DSS Kansas Use Case EPA

Case I

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.

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.

Safe & Sound NHS DSS

Case II

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)

Active Traffic Management DSS

Case III

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.

Last words

ANY QUESTION?

Thank you