Chapter 4
Decision Support and Artificial
Intelligence
Brainpower for Your Business
Chapter Map
Introduction
n
People make decisions all
the time.
n
In a business environment,
managers regularly make complex decisions.
Introduction
Management Review à
Future successes will be
for those organizations that are
“Big on brain and small of mass”.
Introduction
The categories of
computer-aided decision support.
Decisions,
Decisions, Decisions
Decisions, Decisions, Decisions
Decisions, Decisions, Decisions
Decisions, Decisions, Decisions
How You
Make a Decision
Decisions, Decisions, Decisions
How You
Make A Decision
Step 1:
Intelligence
Find or
recognize a problem, need, or opportunity.
n This is the diagnostic phase of the decision making
n Involves the detection and interpretation of signs
t Consistent customer request for new feature or product
t Threat of new competition
t Declining sales
t Rising costs
t Offer from a company to handle your distribution needs
Decisions, Decisions, Decisions
How You
Make A Decision
Step 2: Design
Consider ways to solve the problem, fill the need, or
take advantage of an opportunity.
This is the phase where you would study all possible
solutions and develop those that are most interesting and feasible.
Decisions, Decisions, Decisions
How You
Make A Decision
Step 3:
Choice
Examine and weigh the merits of each solution, estimate the
consequences of each, and choose the best one.
n This is the prescriptive phase of the decision making.
n In this stage a course of action is prescribed and this
course of action could simply be to do nothing.
n Selection of best solution requires selection criteria such
as:
t Cost
t Ease of implementation
t Staffing requirements
t Timing
Decisions, Decisions, Decisions
How You
Make A Decision
Step 4: Implementation
Carry out the chosen solution, monitor the results,
and make adjustments as necessary.
The implementation of final solution is seldom enough
and will practically always need fine-tuning.
Decisions, Decisions, Decisions
Types of
Decisions You Face
Figure 4.3
Viewing Structured Versus
Nonstructured Decision Making as a Continuum
page 136
Decisions, Decisions, Decisions
Types of
Decisions You Face
n
If you want to decide which
cheese to by then the criteria would be based on:
t
Expiry date
t
Price
n
If you have to decide which
job offer is better to accept, then the criteria for your decision would be
based on:
t
Salary
t
Intrinsic motivation
t
Location
t
Company
t
Position
t
Benefits
t
Many other criteria
Decisions, Decisions, Decisions
Types of
Decisions You Face
n
In the cheese case, the
criteria are pretty straight forward, hence the decision making is rather
STRUCTURED.
n
In the case of the job
offer, the criteria are many and most are not straight forward and are
difficult to quantify, hence UN-STRUCTURED.
Decisions, Decisions, Decisions
Types of
Decisions You Face
Structured decision
Processes information in a specified way so that you
will always get the right answer.
n
Does not involve any
“feel” into the process
n
Does not require intuition
n
These types of decision
can be easily programmed
t
Fixed set of input
t
Same processing
t
Produce correct result
Decisions, Decisions, Decisions
Types of
Decisions You Face
Non-structured decision
One for which there may be several “right” answers and
there is no precise way to get a right answer.
n
No rules or criteria exist
that guarantee you a good solution.
n
Examples
t
To introduce a new product
line or not
t
To employ a new marketing
campaign
t
To change the corporate
image
Decisions, Decisions, Decisions
Types of
Decisions You Face
Recurring decision
One that happens repeatedly, and often periodically.
n
Usually use the same set
of rules each time.
Decisions, Decisions, Decisions
Types of
Decisions You Face
Nonrecurring decision
One that you make infrequently.
n
Or ad-hoc decision
n
May have different
criteria for determining the best solution each time
n
Example
t
Company merger
Decision Support Systems
Decision Support
Systems
Highly
flexible and interactive IT system that is designed to support decision making
when the problem is
not structured.
Decision Support Systems
n
A DSS is an alliance between
t you,
t the
decision maker and
t specialized
support provided by IT
Decision Support Systems
n
A DSS brings
t
Speed
t
Vast amounts of
information
t
Sophisticated processing
capabilities
Decision Support Systems
n
You bring the know-how in
the form of
t
Experience
t
Intuition
t
Judgment
t
Knowledge of relevant
factors
n
You must know the right
kind of questions to ask and how to process the information so you may get
useful answers from the IT.
Decision Support Systems
Figure 4.4
The Alliance Between You and a
Decision Support System
page 137
Decision Support Systems
Components
of a Decision Support System
n
A typical DSS has three components:
t Model
management
t Data
management
t User
interface management
Decision Support Systems
Components
of a Decision Support System
Figure 4.5
Components of a Decision Support
System page 138
Decision Support Systems
Components
of a Decision Support System
How do the components work together?
n
You tell the DSS using the
user interface management component which model to use
n
The model is found in the
model management component which you had instructed to use on a set of information
found in the data management component
n
So the model
t
Requests the information
from the data management component
t
Analyzes that information
t
Sends the results to the
user interface management component, hence back to you
Decision Support Systems
Components
of a Decision Support System
The Model
management
Consists of both the DSS models and the DSS model
management system.
t
A model is a
representation of some event, fact or situation to represent variables and
their relationships
t
The model you use in DSS
depend on the decision you are making and consequently the kind of analysis you
require such as:
"
What-if analysis
"
Optimization
Decision Support Systems
Components
of a Decision Support System
Data
management
Performs the function of storing and maintaining the
information that you want your DSS to use.
n
It consists of both the
DSS information and the DSS database management system
n
The information you use in
your DSS comes from one or more of the three sources:
t
Organizational information
t
External information
t
Personal information
Decision Support Systems
Components
of a Decision Support System
User
interface management
Allows you to communicate with the DSS.
n
Consists of the user
interface and the user interface management system
n
Allows you to combine your
know-how with the storage and processing capabilities of the computer
n
Through it you enter
t
Information
t
Commands
t
Models
n
Best user interface uses
your terminology and methods and is:
t
Flexible
t
Consistent
t
Simple
t
adaptable
Collaboration Systems
Collaboration system
A system that is designed specifically to
improve the performance of teams by supporting the sharing and flow of
information.
Figure 4.6
Collaboration Software
Connects People
page 141
Collaboration System
Collaboration software takes many forms with
t Many
combinations of features
t Varying
degrees of complexity
Collaboration System
Three types of collaboration systems are discussed in the book:
t Enterprise-wide
collaboration
t Supply
chain collaboration
t Web-based
collaboration
Collaboration System
Enterprise-wide
Collaboration
n
Lotus Notes and Microsoft Exchange are
types of integrated collaboration systems.
Collaboration System
Supply-Chain
Collaboration
n
Supply chain management means working with
your suppliers and distributors in all phases of planning, production, and
distribution.
Collaboration System
Web-Based
Collaboration
n
Web-based collaboration
tools use the power of the Internet to enable people to work together
effectively and efficiently.
n
The peer-to-peer
file-sharing feature is combined with the ability to create and edit documents
collaboratively, and to send and receive text and voice messages.
Geographic
Information Systems
Geographic Information Systems
Geographic information system (GIS)
A decision support system designed to work
with spatial information.
Geographic Information Systems
Spatial information
Is any information that can be shown in map
form, such as roads, the distribution of bald eagle populations, and the layout
of electrical lines.
Geographic Information Systems
Figure 4.7
Geographic Information Systems
page 144
Geographic Information Systems
n
Today GISs are helping businesses:
t Identify
the best site to locate a branch office
t Target
pockets of potential customers
t Reposition
promotions and advertising
t Determine
the optimal location of a new distribution outlet
Geographic Information Systems
Business Geography
A new type of information created when
businesses combine textual information with spatial information
Artificial Intelligence
Artificial Intelligence
Artificial Intelligence
Artificial intelligence (AI)
The science of making machines imitate human
thinking and behavior.
Artificial Intelligence
Robot
A mechanical device equipped with simulated human
senses and the capability of taking action on its own.
Artificial Intelligence
n
Who uses artificial intelligence?
t
Financial analysts to:
"
Manage assets
"
Invest in the stock market
"
Perform other financial
operations
Artificial Intelligence
n
Who uses artificial intelligence?
t
Hospitals:
"
For scheduling staff
"
Assigning beds to patients
"
Diagnose illnesses
"
Treat conditions and
illnesses
Artificial Intelligence
n
Who uses artificial intelligence?
t
Credit card companies
"
To detect credit card
fraud
t
Insurance companies
"
To ferret out fraudulent
claims
Artificial Intelligence
n
Artificial intelligent
systems that businesses today use most can be classified into the following
major categories
t
Expert systems
t
Neural networks
t
Genetic algorithms
t
Intelligent agents
Expert Systems
Expert Systems
Expert system
or knowledge-based system
Is an artificial intelligence system
that applies reasoning capabilities to reach a conclusion.
Expert Systems
Components
of an Expert System
n
Expert systems are good
for
t
Diagnostic problems:
Problems requiring an answer to the question “what’s wrong?” correspond to the
intelligence phase of decision making and
t
Prescriptive problems:
Problems that require an answer to the question “what to do?” and correspond to
the choice phase of decision making.
Expert Systems
Components
of an Expert System
Figure 4.9
Traffic-Light Expert System Rules
page 149
Expert Systems
Components
of an Expert System
n
An expert system is
usually built for a specific application area called domain:
t Accounting
t Medicine
t Process control
t Human resource management
t Financial management
t Production
t
Forestry management
Expert Systems
Components
of an Expert System
n
An expert system combines
t Information
types,
t People,
and
t IT
components.
Expert Systems
Components
of an Expert System
n
Information types include:
t Domain expertise
"
The reasoning process that will solve the
problem.
t “Why”
information.
t Problem
facts.
Expert Systems
Components of an Expert System
Figure 4.8
Developing and Using an Expert System
page 150
Expert Systems
Components
of an Expert System
n
People
t
Domain expert
"
provides the domain
expertise in the form of problem-solving strategies.
t Knowledge engineer
"
IT specialist who formulates the domain
expertise into an expert system.
t
Knowledge worker or user
"
that’s you.
Expert Systems
Components
of an Expert System
n
IT Components
t Knowledge base
"
stores the rules of the
expert system.
t
Knowledge acquisition
"
used to enter the rules.
t
Inference engine
"
takes the problem facts and
searches the knowledge base for rules that fit.
t
User interface
"
used to run the
consultation.
Expert Systems
What
Expert Systems Can and Can’t Do
n
An expert system can:
t
Reduce errors
t
Improve customer service
t
Reduce costs
n
An expert system can’t:
t
Use common sense
t
Automate all processes
Neural Networks
Neural Networks
Neural network
(often called an artificial neural network or ANN)
an artificial intelligence system that is
capable of finding and differentiating patterns.
Neural Networks
n A NN simulates the human
ability to classify things without taking prescribed steps leading to the solution
n
A NN can learn by example
n
A NN can adapt to new
concepts and knowledge
n
NN are widely used for
visual pattern and speech recognition systems
n
A PDA probably uses NN to
decipher your handwriting
Neural Networks
n NN are used for many other
applications such as
t
In airports to detect
bombs
t
In police departments to
identify corruption
t
In medicine to
"
Check for drug interaction
"
Detect anomalies in tissue
samples
"
Heart attacks
Neural Networks
n In business NN are used
t Security
trading
t Fraud
detection
t Real
estate appraisal
t Evaluating
loan applications
t Target
marketing
Neural Networks
Types of
Neural Networks
n
Self-organizing neural network - finds patterns and
relationships in vast amounts of data by itself.
n
Back-propagation neural network - a neural network trained by someone.
Neural Networks
Inside a
Neural Network
Figure 4.11
The Layers of a Neural Network
page 155
Neural Networks
Inside a Neural Network
n NNs attempt to mimic the human brain
n They consist of three layers of a virtual
neuron
t Input
layer
t Hidden
layer
t Output
layer
Neural Networks
Inside a Neural Network
n
Advantages of a neural
network
t
Can learn and adjust to new
circumstances on their own
t
Lend themselves to massive
parallel processing
t
Can function without
complete and well structured information
t
Can cope with huge volumes
of information with many dependent variables
t
Can analyze nonlinear relationships
in information
Neural Networks
Inside a Neural Network
n
The biggest problem with NN
t The
hidden layers are hidden
Genetic Algorithms
Genetic Algorithms
Genetic algorithm
An artificial intelligence system that
mimics the evolutionary, survival-of-the-fittest process to generate
increasingly better solutions to a problem.
Genetic Algorithms
n
Genetic algorithms are
artificial intelligence software capable of following trial-and-error processes
leading to the evolution of a good result.
n
In other words, genetic
algorithms are optimizing systems such that they find the combination of inputs
that give the best outputs.
Genetic Algorithms
n Genetic algorithms use three concepts of evolution:
t
Selection — survival of the fittest.
t Crossover — combining portions of good outcomes in the hope of creating
an even better outcome.
t
Mutation — randomly trying
combinations and evaluating the success (or failure) of the outcome.
Genetic Algorithms
n
Who uses genetic
algorithms?
t
They are used by business executives
to help them decide which combination of projects a firm should invest in.
t
They are used by
investment firms to help then in trading choices and associated decisions.
t
Used in the garment
industry to help them solve the problem of laying out the pieces of the garment
and cutting fabric in a way that leaves as little waste as possible.
t
Used to determine the
optimal configuration of fiber optic cable in a network that may include as
many as 100,000 connection points.
Genetic Algorithms
Intelligent Agents
Intelligent Agents
Intelligent agent
Software that assists you, or acts on your
behalf, in performing repetitive computer-related tasks.
Intelligent Agents
n
Four types of intelligent agents include:
t
Buyer agents or shopping
bots
t
User or personal agents
t
Monitoring-and-surveillance
or predictive agents
t
Data-mining agents
Intelligent Agents
Buyer
Agents
Buyer agent
or shopping bot
an intelligent agent on a Web site that helps the customer find products
and services.
Intelligent Agents
Buyer
Agents
n
Types of filtering include:
t Collaborative filtering
- a method of placing you in an affinity group of people with the same
characteristics.
t Profile filtering
- requires that you choose terms or enter keywords.
Intelligent Agents
Buyer
Agents
n
Types of filtering
continued:
t
Psychographic filtering -
anticipates your preferences based on the answers you give to a questionnaire.
t
Adaptive filtering - asks you
to rate products or situations and also monitors your actions over time to find
out what you like and dislike.
Intelligent Agents
User
Agents
n
User
agents (sometimes called personal agents) - intelligent agents that take action on your
behalf.
Intelligent Agents
Monitoring-and-Surveillance
Agents
n
Monitoring-and-surveillance
agents (also called predictive agents) - observe and report on equipment.
Intelligent Agents
Data-Mining
Agents
n
Data-mining
agent - operates in a data warehouse discovering
information.
Intelligent Agents
Components
of an Intelligent Agent
n
Autonomy - act without your
telling them every step to take.
n
Adaptivity - discovering, learning,
and taking action independently.
n
Sociability -
conferring with other agents.
Closing Case Study One
Using
Neural Networks To Categorize People
n
Using neural network software,
businesses now have the ability to look for patterns in their customer
information.
n
How accurate is it for a
business to predict the future behavior of customers on the basis of past
behavior?
Closing Case Study Two
Decision
Support and Artificial Intelligence in Health Care
n
Good health care is based
largely on good information.
n
How can DSS and AI be used
to track symptoms, treatment, and outcomes that require the collection and
maintenance of a huge amount of qualitative and quantitative information?
Summary
Student
Learning Outcomes
n Define decision support system, list its components, and
understand its applications.
n Define collaboration systems along with their features and
uses.
n Define geographic information systems and state how they differ
from other decision support tools.
Summary
Student
Learning Outcomes
n
Define artificial intelligence and list the
different types that are used in business.
n
Define expert systems, and the type of
problems to which they are applicable.
n
Define neural networks, their uses, and the
major strength and weaknesses.
Summary
Student
Learning Outcomes
n
Define genetic algorithms and list the
concepts on which they are based, and the types of problems they solve.
n
Define intelligent agents, list the four types,
and identify the types of problems they solve.
Summary
Assignments
& Exercises
n
Make a GIS
n
Collaboration Work
n
Choose a Financing Option
n
Which Software Would You Use?
Real Hot
Electronic Commerce
Finding
Investment Opportunities on the Internet
n
Learning about Investing
n
Researching the Company
behind the Stock
n
Finding other Sources of
Company Financials
n
Making Trades Online
n
Retrieving Stock Quotes
Visit the Web to Learn More
www.mcgrawhill.ca/college/haag
n
Learning about Investing
n
Researching the Company
behind the Stock
n
Finding other Sources of
Company Financials
n
Making Trades Online
n
Retrieving Stock Quotes