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Decision Support Systems
Overview
Dr Sherif Kamel
Department of Management
School of Business, Economics and Communication
Decision Support Systems
 Systems designed to support managerial decision-making in
unstructured problems
 Increasing emphasis shifting to inputs from outputs
 Mechanism for interaction between user and components
 Usually built to support solution or evaluate opportunities
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Decision Support Systems
 A DSS is a methodology that supports decision-making
 The methodology is…
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flexible
adaptive
Interactive
GUI-based
Iterative and
employs modeling
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS Definition
 Little (1970) defines DSS as a “model-based set of
procedures for processing data and judgments to assist a
manager in his decision-making”
 Alter (1980) defines DSS by contrasting them with traditional
electronic data processing (EDP)
 Moore and Chang (1980) defines DSS as extendible systems
capable of supporting ad hoc data analysis and decision
modeling, oriented toward future planning and used at
irregular and unplanned intervals
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS v EDP
Dimensions
DSS
EDP
Use
Active
Passive
User
Line and staff
management
Clerical
Goal
Effectiveness
Mechanical efficiency
Present and future
Past
Flexibility
Consistency
Time Horizon
Objective
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
What is a DSS application?
 DSS application is usually built to…
 support the solution of a certain problem…or….
 evaluate an opportunity
 It could be used by a simple user through a PC interface or
collectively by a group of people through web-based
applications
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Case: DSS Application
Reducing Inventories and Improving Performance
 Cambar Company is distributing industrial, electrical and
electronic supplies (half a million products represent the
inventory)
 Objective = how to reduce inventory without compromising
customer service (decisions were mainly based on intuition
leading to overstock and carrying additional costs)
 Need is to improve accuracy of demand forecasts (key to
inventory reduction)
 What needs to be done?
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Case: DSS Application
Reducing Inventories and Improving Performance
 Steps to follow:
 Analyzing demand data and identifying order rules
 Develop, test and deploy a prototype for inventory-planning and
management system
 Developing a model whereby…
 Business information is saved
 Model based on data on the data server built on the application server
 Approximating lead time demand and rationalize the ordering process
which also affects the service level associated
 Optimizing the model at the optimization and simulation server, results
are captured at the application server which are then sent to the web
server in the form of reports
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Multi-tiered Architecture
 Incorporating optimization, simulation and other models into
Web-based DSS
Optimization
Simulation
Server
Web
Browser
Web
Server
Data
Warehouse
DBMS
Application
Server
Data
Server
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS Characteristics
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
What is Business Intelligence?
 BI is a collection of technical and process innovations across
the data warehousing and business intelligence space
 Proactive BI focus on accelerating decision-making by
leveraging its infrastructure to produce timely, relevant and
useful information
 BI helps the continuous increase in information flow with
business related implications through better decision making
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Components of DSS
1. Data management subsystem
 It includes a database that contains relevant data for the situation
and is managed by a database management system (DBMS)
application
 Connected to the corporate data warehouse (with decision making
data) accessed via database web server
2. Model management subsystem
 Software package that includes financial, statistical, management
science, quantitative models providing the analytical capabilities
called model base management system (MBMS) usually runs on
application server
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Components of DSS
3. User interface subsystem
 Users communicate and interact with the DSS
 Interaction between users (decision-makers) and computing
 Web browser provides a user-friendly and easy interface
4. Knowledge-based management subsystem
 Support subsystem providing intelligence for decision makers
 Known as organizational knowledge base
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Building Blocks of DSS
DBMS
MBMS
KBMS
(optional)
User
Interface
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Schematic view of DSS
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
1. Data Management Subsystem
A.
B.
C.
D.
DSS Database
Database management system
Data directory
Query facility
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Structure of Database Management System
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
A. DSS Database
 Interrelated data extracted from various sources, stored for
use by the organization, and queried
 Internal data, usually from TPS
 External data from government agencies, trade associations, market
research firms, forecasting firms
 Private data or guidelines used by decision-makers
 Could also share DBMS with other systems
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
B. Database Management System
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Database is created, accessed and updated by a DBMS
Most DSS are built with a standard relational database
Captures and extracts data for inclusion in a DSS database
Updates (add, delete, edit, change) data records and files
Manages data and their relationships
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
C. Data Directory
 Catalog of all data
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Contains data definitions
Answers questions about the availability of data items
Source
Meaning
Allows for additions, removals, and alterations
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
D. Query Facility
 Retrieves and accesses data
 Queries and manipulates data
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
2. Model Base Management Subsystem
A.
B.
C.
D.
E.
Model base
Modeling language (tools)
Model base management system
Model directory
Model execution, integration, and command processor
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
A. Model Base
 Model base contains routine and special statistical, financial,
forecasting, management science, quantitative models that
provide the analysis capabilities in a DSS
 Models are divided into 4 main categories
 Strategic – supporting top management decisions
 Tactical – used primarily by middle management to allocate
resources
 Operational – supporting daily activities
 Analytical – used to perform analysis of data
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
B. Modeling Language (tools)
 Models are usually customized because DSS mainly focus
on semi-structured and unstructured problems
 Example: C++, OLAP, Java, Excel
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
C. Model Base Management System
 Functions of the model-base management system include:
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Model creation using programming languages
Model updates and changes
Model data manipulation
Generation of new routines
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
D. Model Directory
 Catalog of models including all the models and other
software in the model based (it does the same function as is
data directory in the database)
 Definitions (to demonstrate the capabilities and functions of
the model)
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
E. Model Execution, Integration, Command
Processor
 Model execution
 Controls running of model
 Model command processor
 Receives model instructions from user interface
 Routes instructions to MBMS or module execution or integration
functions
 Model integration
 Combines several models’ operations
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
3. User Interface Subsystem
 Combines all aspects of communication between a user and
the DSS
 Dealing with factors related to ease of use, accessibility and
human-machine interactions (web-browser have been
recognized as the most effective)
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
User Interface Management System
 GUI
 Natural language processor
 Interacts with model management and data management
subsystems
 Examples
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Speech recognition
Display panel
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
4. Knowledge-Based Management System
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Expert or intelligent agent system component included
Complex problem solving capabilities
Enhances operations of other components
May consist of several systems
Mainly text-oriented DSS
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
User in DSS
 User represents the decision maker
 Individual or group
 Human interaction with DSS is key (capabilities are important
for DSS success)
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS Hardware
 Web server with DBMS:
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Operates using browser
Data stored in variety of databases
Can be mainframe, server, workstation, or PC
Any network type
Access could be through mobile devices
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS Classifications
 Text-oriented DSS
 Information is often stored in textual format and must be accessed
by decision makers
 Documents are electronically created, revised and accessed
 Web-based documents is an example
 Database-oriented DSS
 Mainly reflecting elements of report generation and query
capabilities
 Usually of large volume, descriptive and rigidly structured
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
DSS Classifications
 Spreadsheet-oriented DSS
 Allowing the use of spreadsheet as a modeling tool for DSS analysis
 Most common end-user DSS
 Manipulation of data and the creation of multiplicity of scenarios
 Solver-oriented DSS
 Algorithm of procedure written to solve a specific problem
 Economic order quantity procedure for calculating an optimal ordering
quantity
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang
Web and DSS
 Web technologies
 Internet, intranets, extranets
 Enterprise software
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Knowledge management (KM)
Enterprise resource planning (ERP)
Customer relationship management (CRM)
Supply chain management (SCM)
Copyright © 2006 Sherif Kamel
Copyright © 2001-2006 Turban, Aronson and Liang