1. Supporting Decision Making
Chapter 10
Supporting Decision Making
McGraw-Hill/Irwin
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.

2. Learning Objectives
Identify the changes taking place in the form and use of decision support in business
Identify the role and reporting alternatives of management information systems
Describe how online analytical processing can meet key information needs of managers
Explain the decision support system concept and how it differs from traditional management information systems

3. Learning Objectives
Explain how the following information systems can support the information needs of executives, managers, and business professionals
Executive information systems
Enterprise information portals
Knowledge management systems
Identify how neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents can be used in business

4. Learning Objectives
Give examples of several ways expert systems can be used in business decision-making situations

5. Structured (operational) Unstructured (strategic)
Decision Structure
Structured (operational)
Procedures can be specified in advance
Unstructured (strategic)
Not possible to specify procedures in advance
Semi-structured (tactical)
Decision procedures can be pre-specified, but not enough to lead to the correct decision
Structured (operational)
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

6. Provides decision support through knowledge discovery
Data Mining
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

7. Market Basket Analysis
One of the most common uses for data mining
Determines what products customers purchase together with other products
Other uses
Cross Selling
Product Placement
Affinity Promotion
Survey Analysis
Fraud Detection
Analyze Customer Behavior
Consider some of the typical applications of MBA:
• Cross Selling. Offer the associated items when customer buys any items from
your store.
• Product Placement. Items that are associated (such as bread and butter, tissues
and cold medicine, potato chips and beer) can be put near each other. If
the customers see them, it has higher probability that they will purchase them
together.
• Affinity Promotion. Design the promotional events based on associated products.
• Survey Analysis. The fact that both independent and dependent variables of market basket analysis are nominal (categorical) data type makes MBA very useful to analyze questionnaire data.
• Fraud Detection. Based on credit card usage data, we may be able to detect certain purchase behaviors that can be associated with fraud.
• Customer Behavior. Associating purchase with demographic, and socio economic data (such as age, gender, and preference) may produce very useful results for marketing.

8. Executive Information Systems (EIS)
Combines many features of MIS and DSS
Provides immediate and easy information
Identifies critical success factors
Features
Customizable graphical user interfaces
Exception reports
Trend analysis
Drill down capability
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

9. Benefits of Expert Systems
Captures human experience in a computer-based information system
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
Benefits of Expert Systems
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
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

10. Knowledge Engineering
A knowledge engineer
Works with experts to capture the knowledge they possess
Facts and rules of thumb
Builds the knowledge base
if necessary, the rest of the expert system
Similar role to systems analysts
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
10-10

11. Neural Networks
Modeled after the brain’s mesh-like network of interconnected processing elements (neurons)
Interconnected processors operate in parallel and interact with each other
Allows the network to learn from the data it processes
Computing systems modeled after the brain’s mesh-like network of interconnected processing elements (neurons)
Interconnected processors operate in parallel and interact with each other
Allows the network to learn from the data it processes

12. Genetic algorithm software
Uses Darwinian, randomizing, and other mathematical functions
Simulates an evolutionary process, yielding increasingly better solutions to a problem
Used to model a variety of scientific, technical, and business processes
Useful when thousands of solutions are possible

13. Virtual reality is a computer-simulated reality
Virtual Reality (VR)
Virtual reality is a computer-simulated reality
Fast-growing area of artificial intelligence
Originated from efforts to build natural, realistic, multi-sensory human-computer interfaces
Relies on multi-sensory input/output devices
Creates a three-dimensional world through sight, sound, and touch
Telepresence
Using VR to perform a task in a different location
Current applications of virtual reality
Computer-aided design
Medical diagnostics and treatment
Scientific experimentation
Flight simulation
Product demonstrations
Employee training
Entertainment

14. Software robots or bots
Intelligent Agents
Software surrogate for an end user or a process that fulfills a stated need or activity
Uses built-in and learned knowledge base to accomplish tasks
Software robots or bots
Software surrogate for an end user or a process that fulfills a stated need or activity
Uses built-in and learned knowledge base to make decisions and accomplish tasks in a way that fulfills the intentions of a user
Also called software robots or bots
Interface Tutors – observe user computer operations, correct user mistakes, provide hints/advice on efficient software use
Presentation Agents – show information in a variety of forms/media based on user preferences
Network Navigation Agents – discover paths to information, provide ways to view it based on user preferences
Role-Playing – play what-if games and other roles to help users understand information and make better decisions

15. Types of Intelligent Agents
User Interface Agents
Interface Tutors
Presentation Agents
Network Navigation Agents
Role-Playing Agents
Information Management Agents
Search Agents
Information Brokers
Information Filters
User Interface Agents
Interface Tutors – observe user computer operations, correct user mistakes, provide hints/advice on efficient software use
Presentation Agents – show information in a variety of forms/media based on user preferences
Network Navigation Agents – discover paths to information, provide ways to view it based on user preferences
Role-Playing – play what-if games and other roles to help users understand information and make better decisions
Information Management Agents
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 , voice mail, and other information media