Decision support systems use analytical models, specialized databases, and interactive modeling to support semi-structured business decisions. They provide information and techniques to analyze specific problems through interactive inquiries and flexible reporting formats. Common applications include supply chain optimization, pricing analysis, and product quality improvement through statistical modeling.

1. Decision Support Systems

2. Decision Support in Business
2
Companies are investing in data-driven decision
support application frameworks to help them
respond to
Changing market conditions
Customer needs
This is accomplished by several types of
Management information
Decision support
Other information systems

3. Levels of Managerial Decision
Making
3

4. Information Quality
4
Information products made more valuable by
their attributes, characteristics, or qualities
Information that is outdated, inaccurate, or
hard to understand has much less value
Information has three dimensions
Time
Content
Form

5. Attributes of Information Quality
5

6. Decision Structure
6
Structured (operational)
The procedures to follow when decision
is needed can be specified in advance
Unstructured (strategic)
It is not possible to specify in advance
most of the decision procedures to follow
Semi-structured (tactical)
Decision procedures can be pre-specified,
but not enough to lead to the correct decision

7. Decision Support Systems
Management Information
Systems
Provide information about the
performance of the organization
Decision
support
provided
Information form
and frequency
Information
format
Periodic, exception, demand,
and push reports and
responses
Prespecified, fixed format
Information
processing
methodology
7
Information produced by
extraction and manipulation of
business data
Decision Support Systems
Provide information and
techniques to analyze
specific problems
Interactive inquiries and
responses
Ad hoc, flexible, and
adaptable format
Information produced by
analytical modeling of
business data

8. Decision Support Trends
8
The emerging class of applications focuses on
Personalized decision support
Modeling
Information retrieval
Data warehousing
What-if scenarios
Reporting

9. Business Intelligence Applications
9

10. Decision Support Systems
10
Decision support systems use the following to
support the making of semi-structured business
decisions
Analytical models
Specialized databases
A decision-maker’s own insights and judgments
An interactive, computer-based modeling
process
DSS systems are designed to be ad hoc,
quick-response systems that are initiated and
controlled by decision makers

11. Applications of Statistics and
Modeling
11
Supply Chain: simulate and optimize supply
chain flows, reduce inventory, reduce stock-
outs
Pricing: identify the price that maximizes
yield or profit
Product and Service Quality: detect quality
problems early in order to minimize them
Research and Development: improve
quality, efficacy, and safety of products and
services

12. Management Information
Systems
12
The original type of information system
that supported managerial decision making
Produces information products that support
many day-to-day decision-making needs
Produces reports, display, and responses
Satisfies needs of operational and tactical
decision makers who face structured
decisions

13. Online Analytical Processing
13
OLAP
Enables managers and analysts to examine
and manipulate large amounts of detailed and
consolidated data from many perspectives
Done interactively, in real time, with rapid
response to queries

14. Using Decision Support Systems
14
Using a decision support system involves an interactive analytical
modeling process
Decision makers are not demanding pre-specified information
They are exploring possible alternatives
What-If Analysis
Observing how changes to selected variables affect other
variables
Sensitivity Analysis
Observing how repeated changes to a single variable affect
other variables
Goal-seeking Analysis
Making repeated changes to selected variables until a chosen
variable reaches a target value
Optimization Analysis
Finding an optimum value for selected variables, given certain
constraints

15. Data Mining
15
Provides decision support through knowledge
discovery
Analyzes vast stores of historical business data
Looks for patterns, trends, and correlations
Goal is to improve business performance
Types of analysis
Regression
Decision tree
Neural network
Cluster detection
Market basket analysis

16. Market Basket Analysis
16
One of the most common uses for data mining
Determines what products customers
purchase together with other products
Results affect how companies
Market products
Place merchandise in the store
Lay out catalogs and order forms
Determine what new products to offer
Customize solicitation phone calls

17. Executive Information Systems
17
Combines many features of MIS and DSS
Provide top executives with immediate and
easy access to information
Identify factors that are critical to accomplishing
strategic objectives (critical success factors)
So popular that it has been expanded to
managers, analysis, and other knowledge
workers

18. Enterprise Information Portals
18
An EIP is a Web-based interface and integration
of MIS, DSS, EIS, and other technologies
Available to all intranet users and select
extranet users
Provides access to a variety of internal and
external business applications and services
Typically tailored or personalized to the user
or groups of users
Often has a digital dashboard
Also called enterprise knowledge portals

19. Enterprise Knowledge Portal
19

20. Expert Systems
20
An Expert System (ES)
A knowledge-based information system
Contain knowledge about a specific, complex
application area
Acts as an expert consultant to end users

21. Components of an Expert System
21
Knowledge Base
Facts about a specific subject area
Heuristics that express the reasoning
procedures of an expert (rules of thumb)
Software Resources
An inference engine processes the knowledge
and recommends a course of action
User interface programs communicate with
the end user
Explanation programs explain the reasoning
process to the end user

22. Components of an Expert System
22

23. Expert System Application
Categories
23
Decision Management
Loan portfolio analysis
Employee performance evaluation
Insurance underwriting
Diagnostic/Troubleshooting
Equipment calibration
Help desk operations
Medical diagnosis
Software debugging

24. Expert System Application
Categories
24
Process Monitoring/Control
Machine control (including robotics)
Inventory control
Production monitoring
Chemical testing

25. Benefits of Expert Systems
25
Captures the expertise of an expert or group of
experts in a computer-based information system
Faster and more consistent than an expert
Can contain knowledge of multiple experts
Does not get tired or distracted
Cannot be overworked or stressed
Helps preserve and reproduce the knowledge
of human experts

26. Limitations of Expert Systems
26
The major limitations of expert systems
Limited focus
Inability to learn
Maintenance problems
Development cost
Can only solve specific types of problems
in a limited domain of knowledge

27. Developing Expert Systems
27
Suitability Criteria for Expert Systems
Domain: the domain or subject area of the problem is
small and well-defined
Expertise: a body of knowledge, techniques, and
intuition is needed that only a few people possess
Complexity: solving the problem is a complex task
that requires logical inference processing
Structure: the solution process must be able to cope
with ill-structured, uncertain, missing, and conflicting
data and a changing problem situation
Availability: an expert exists who is articulate,
cooperative, and supported by the management and
end users involved in the development process

28. Development Tool
28
Expert System Shell
The easiest way to develop an expert system
A software package consisting of an expert
system without its knowledge base
Has an inference engine and user interface
programs

29. Knowledge Engineering
29
A knowledge engineer
Works with experts to capture the knowledge
(facts and rules of thumb) they possess
Builds the knowledge base, and if necessary,
the rest of the expert system
Performs a role similar to that of systems
analysts in conventional information systems
development

30. Information Management Agents
30
Search Agents – help users find files and
databases, search for information, and suggest
and find new types of information products,
media, resources
Information Brokers – provide commercial
services to discover and develop information
resources that fit business or personal needs
Information Filters – Receive, find, filter,
discard, save, forward, and notify users about
products received or desired, including e-mail,
voice mail, and other information media