1. B. Information Technology (IS) CISB434: Decision Support Systems
Chapter 4:
An Overview of DSS Concepts, Methodologies & Technologies

2. Learning Objectives
Examine the possible decision support system (DSS) configurations
Describe the DSS characteristics and capabilities

3. Learning Objectives Describe the components and structure of DSS
Data Management Subsystem
Model Management Subsystem
User Interface (Dialog) Subsystem
Knowledge-based Management Subsys-tem
User

4. Learning Objectives
Explain the unique role of the user in DSS versus MIS
Describe DSS hardware and software platforms
Examine important DSS classifications

5. An Overview of DSS Concepts, Methodologies & Technologies
DSS Configurations

6. DSS Configurations Introduction
Decision support can be provided in many different configurations
These configurations depend on
the nature of the management-decision situation, and
the specific technologies used for support

7. DSS Configurations Introduction
These technologies are assembled from four basic components
Data
Models
User interface
Knowledge (optional)

8. DSS Description DSS Application
A DSS program is build for a specific purpose
e.g. a scheduling system for a company
Typically built to
support the solution of a problem
evaluate an opportunity
An approach (or methodology) for sup-porting decision making

9. DSS Description DSS Application
A DSS supports all phases of decision making
may include a knowledge component
Can be used by a single user on a PC
Can be Web-based for use by many people at several locations

10. DSS Application Architecture

11. An Overview of DSS Concepts, Methodologies & Technologies
DSS Characteristics & Capabilities

12. Characteristics & Capabilities

13. Characteristics & Capabilities
Business analytics
The application of models directly to business data
It involves using DSS tools, especially models, in assisting decision makers
It is essentially OLAP/DSS
Predictive analytics
A business analytical approach toward forecasting
e.g., demand, problems, opportunities
that is used instead of simply reporting data as they occur

14. Characteristics & Capabilities
Support for decision makers
mainly in semi-structured and unstruc-tured situations
by bringing together human judgment and computerized information
Support for all managerial levels
ranging from top executives to line managers
Support for individuals and groups
Support for interdependent and/or se-quential decisions
Support in all phases of the decision-making process
Support for a variety of decision-making processes and styles 12

15. Characteristics & Capabilities
DSS are flexible
users can add, delete, combine, change, or rearrange basic elements
DSS can be readily modified to solve other similar problems
User-friendliness
strong graphical capabilities
a natural language interactive human–machine interface can greatly increase the effectiveness of DSS
Improved effectiveness of decision making
e.g. accuracy, timeliness 12

16. Characteristics & Capabilities
Decision maker has complete control over all steps of decision-making
End users are able to develop and modify simple systems by themselves
Models are generally utilized to analyze decision- making situations
models enable experimentation 12

17. Characteristics & Capabilities
Access is provided to a variety of data sources, formats, and types
Can be employed as a standalone tool
used by a decision maker in one location
or distributed throughout an organization or in several organizations along the supply chain
Can be integrated with other DSS and/ or applications
can be distributed internally and externally
using networking and Web technologies 12

18. An Overview of DSS Concepts, Methodologies & Technologies
Components of DSS

19. Components of dss Data Management Subsystem Model Management Subsystem
User Interface (Dialog) Subsystem
Knowledge-based Management Subsys-tem
User

20. Components of DSS

21. Data Management Subsystem
Components of DSS
Data Management Subsystem

22. Components of DSS Data Management Subsystem23

23. Components of DSS Data Management Subsystem
The data management subsystem is composed of
DSS database
DBMS
Data directory
Query facility 23 24

24. Data Management Subsystem The DSS Database
Internal Data come mainly from the organization’s Transaction Processing System (TPS)
Private Data can include
guidelines used by some decision makers
assessments of specific data and/or situations
External Data includes
industry data
market research data
census data
regional employment data
government regulations
tax rate schedules
national economic data 24

25. Data Management Subsystem Data Organization
Data for DSS can be
entered directly into models
extracted directly from larger databases e.g. Data Warehouse
Can include multimedia objects
OODBs in XML used in m-commerce

26. Data Management Subsystem Data Extraction (ETL)
The process of
capturing data from several sources
synthesizing, summarizing
determining which of them are relevant
and organizing them
resulting in their effective integration 24

27. Data Management Subsystem Database Management System
A database is created, accessed and updated by a DBMS
Software for establishing, updating, and querying e.g. managing a database
record navigation
data relationships
report generation 24

28. Data Management Subsystem Query Facility
The (database) mechanism that
accepts requests for data
accesses
manipulates
and queries data
Includes a query language
e.g. SQL 24

29. Data Management Subsystem Data Directory
A catalog of all the data in a database or all the models in a model base
Contains
data definitions
data source
data meaning
Supports addition and deletion of new entries

30. Data Management Subsystem Key DB & DBMS Issues
Data quality
Managers feel they do not get the data they need – 54% satisfied
Poor quality data leads to poor quality information
waste
lost opportunities
unhappy customers

31. Data Management Subsystem Key DB & DBMS Issues
Data integration
For DSS to work, data must be integrated from disparate sources
Data sources must be mapped into a set of metadata

32. Data Management Subsystem Key DB & DBMS Issues
Scalability
Volume of data increases dramatically
e.g. from 2001 – 2003, size of largest TPS DB increase two-fold (11 – 20 terabytes)
Needs new storage and search techno-logies

33. Data Management Subsystem Key DB & DBMS Issues
Data security
data must be protected from unauthorized access through security measures
tools to monitor database activities
audit trail

34. Model Management Subsystem
Components of DSS
Model Management Subsystem

35. Components of DSS Model Management Subsystem23

36. Components of DSS Model Management Subsystem
The Model Management Subsystem is composed of the following elements
Model Base
MBMS
Modeling Language
Model Directory
Model Execution, Integration & Command Processor 37

37. Model Management Subsystem Model Base
A collection of preprogrammed quanti-tative models
e.g., statistical, financial, optimization
Organized as a single unit
Provides analysis capabilities for DSS 37

38. Model Management Subsystem Model Base
Four categories of models with the model base
Strategic models
Tactical models
Operational models
Analytical models 37

39. Model Management Subsystem Categories of Models
Strategic Models
Models that represent problems for the strategic level
i.e. executive level of management
developing corporate objectives
forecasting sales target
Tactical Models
Models that represent problems for the tactical level
i.e. mid-level management
allocates and controls resources
labour requirement planning
sales promotion planning

40. Model Management Subsystem Categories of Models
Operational Model
Models that represent problems for the operational level of management
Supports day-to-day working activities
manufacturing targets
e-commerce transaction acceptance
approval of personal loans
Analytical Models
Mathematical models into which data are loaded for analysis
statistical
management science
data mining algorithms
Integrated with other models, e.g. strategic planning model

41. Model Management Subsystem Model Building Blocks & Routines
Preprogrammed software elements that can be used to build computerized models
e.g. curve- or line-fitting routine
regression analysis
Model components for building DSS
Modeling tools

42. Model Management Subsystem Model Base Management System
MBMS software has four main functions
Model creation
using programming languages
DSS tools and/or subroutines
and other building blocks
Generation of new routines and reports
Model updating and changing
Model data manipulation 37

43. Model Management Subsystem Model Directory
Similar to database directory
A catalog of all models and other soft-ware in the model base
model definitions
functions
availability and capability 37

44. Model Management Subsystem Model Execution, Integration
the process of controlling the actual run-ning of the model
Model integration
involves combining the operations of several models when needed 37

45. Model Management Subsystem Model Command Processor
A model command processor
accepts and interpret modeling instruc-tions from the user interface component
and route them to
the MBMS
model execution or integration functions 37

46. Model Management Subsystem Some DSS Questions
Which models should be used for what situations?
Cannot be done by MBMS
What method should be used to solve a problem in a specific model class?
highly dependent on the knowledge com-ponent

47. User Interface (Dialog) Subsystem
Components of DSS
User Interface (Dialog) Subsystem

48. Components of DSS User Interface (Dialog) Subsystem
The component of a computer system that allows bidirectional communication bet-ween the system and its user
Managed by User Interface Management System (UIMS)
The DSS component that handles all inter-action between users and the system 23

49. User Interface (Dialog) Subsys. The User Interface Process
Object
A person, place, or thing about which information is collected, processed, or stored
Graphical User Interface (GUI)
An interactive, user-friendly interface in which, by using icons and similar objects, the user can control communication with a computer

50. User Interface (Dialog) Subsys. The User Interface Process23

51. User Interface (Dialog) Subsys. DSS User Interfaces
DSS user interfaces access is provided through Web browsers including
Voice input and output
Portable devices
Direct sensing devices

52. User Interface (Dialog) Subsys. DSS Developments
Parallel processing hardware and soft-ware technologies have made major inroads in solving the scalability issue
Web-based DSS
easier and less costly to make decision-relevant information
model-driven DSS available to users in geographically distributed locations
especially through mobile devices

53. User Interface (Dialog) Subsys. DSS Developments
Artificial intelligence continues to make inroads in improving DSS
faster, intelligent search engines
intelligent agents promise to improve the interface in areas such as
direct natural language processing
creating facial gestures

54. User Interface (Dialog) Subsys. DSS Developments
The development of ready-made DSS solutions for specific market segments has been increasing
DSS is becoming more embedded in or linked to most EIS

55. User Interface (Dialog) Subsys. DSS Developments
GSS improvements support collabora-tion at the enterprise level
Different types of DSS components are being integrated more frequently

56. Knowledge-Based Management Subsystem
Components of DSS
Knowledge-Based Management Subsystem

57. Components of DSS Knowledge-Based Mngt Subsystem
Advanced DSSs are equipped with a Knowledge-based Management Sub-system
supplies required expertise for solving some aspects of the problem
provides knowledge that can enhance the operation of other DSS components 23

58. Components of DSS Knowledge-Based Mngt Subsystem
Knowledge components provided by
Expert Systems
Neural Network
Intelligent Agents
Fuzzy Logic
Case-Based Reasoning
etc.

59. An Overview of DSS Concepts, Methodologies & Technologies
Role of Users

60. The User
The person faced with a decision that an MSS is designed to support is called
user
manager, or
decision maker

61. The User Differences in users Provides the human intellect
cognitive preferences
abilities
ways of arriving at a decision
Provides the human intellect
expertise in guiding the development and use of a DSS

62. The User MSS has two broad classes of users
Staff Specialists use the system much more frequently than manager
tend to be more detail-oriented
e.g. production planners
Staff Analysts are often intermediaries between managers and the MSS

63. The User Intermediary
A person who uses a computer to fulfill requests made by other people
e.g. a financial analyst who uses a com-puter to answer questions for top manage-ment
Staff Assistant s
An individual who acts as an assistant to a manager
Expert Tool Users
A person who is skilled in the application of one or more types of specialized problem-solving tools

64. The User Intermediary Business (System) Analysts
One who analyzes business processes and the support they receive (or need) from information technology
Facilitators (in a GSS)
One who plans, organizes, and controls a group in a collaborative computing envi-ronment

65. An Overview of DSS Concepts, Methodologies & Technologies
DSS Hardware

66. DSS Hardware
Hardware affects the functionality and usability of the MSS
The choice of hardware can be made before, during, or after the design of the MSS software
Major hardware options
Organization’s servers
Mainframe computers with legacy DBMS
Workstations
Personal computers
Client/Server systems

67. DSS Hardware
Portability has become critical for deploying decision- making capability in the field, especially for salespersons and technicians
The power and capabilities of the World Wide Web have a dramatic impact on DSS
Communication and collaboration
Download DSS software
Use DSS applications provided by com-pany
Buy online from Application Service Pro-viders

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