DECISION MAKING
•
Reasons
for the growth of decision-making information systems
– People need to analyze large amounts of
information
– People must make decisions quickly
– People must apply sophisticated analysis
techniques, such as modeling and forecasting, to make good decisions
– People must protect the corporate asset of
organizational information
·
Model – a simplified representation or abstraction of reality
TRANSACTION
PROCESSING SYSTEM
•
Transaction processing system - the basic business system that serves the
operational level (analysts) in an organization
•
Online transaction processing (OLTP) – the capturing of transaction and event
information using technology to (1) process the information according to
defined business rules, (2) store the information, (3) update existing
information to reflect the new information
•
Online analytical processing (OLAP) – the manipulation of information to create
business intelligence in support of strategic decision making
DECISION SUPPORT
SYSTEM
•
Decision support system (DSS) – models information to support managers and
business professionals during the decision-making process
•
Three
quantitative models used by DSSs include:
1.
Sensitivity analysis – the study of the impact that changes in
one (or more) parts of the model have on other parts of the model
2.
What-if analysis – checks the impact of a change in an
assumption on the proposed solution
3.
Goal-seeking analysis – finds the inputs necessary to achieve a
goal such as a desired level of output
EXECUTIVE INFORMATION
SYSTEM
•
Executive information system (EIS) – a specialized DSS that supports senior
level executives within the organization
•
Most EISs
offering the following capabilities:
– Consolidation – involves the aggregation of information
and features simple roll-ups to complex groupings of interrelated information
– Drill-down
– enables users to get details,
and details of details, of information
– Slice-and-dice – looks at information from different perspectives
ARTIFICIAL
INTELLIGENCE
•
Intelligent system – various commercial applications of
artificial intelligence
•
Artificial intelligence (AI) – simulates human intelligence such as the
ability to reason and learn
•
Four most
common categories of AI include:
•
Expert system – computerized advisory programs that
imitate the reasoning processes of experts in solving difficult problems.
Example robot.
•
Neural Network – attempts to emulate the way the human
brain works. Example California police.
•
Fuzzy logic – a mathematical method of handling imprecise or subjective
information
•
Genetic algorithm – an artificial intelligent system that
mimics the evolutionary, survival-of-the-fittest process to generate
increasingly better solutions to a problem. Example to determine fiber optic by
telecommunication
•
Intelligent agent – special-purposed knowledge-based
information system that accomplishes specific tasks on behalf of its users.
Example Ford Motor Co. Balance with cost and demands.
•
Multi-agent
systems
•
Agent-based
modeling
DATA MINING
•
Common
forms of data-mining analysis capabilities include:
–
Cluster
analysis
–
Association
detection
–
Statistical
analysis
CLUSTER ANALYSIS
•
Cluster analysis – a technique used to divide an
information set into mutually exclusive groups such that the members of each
group are as close together as possible to one another and the different groups
are as far apart as possible
•
CRM
systems depend on cluster analysis to segment customer information and identify
behavioral traits
ASSOCIATION DETECTION
•
Association detection – reveals the degree to which variables
are related and the nature and frequency of these relationships in the
information
– Market
basket analysis – analyzes such
items as Web sites and checkout scanner information to detect customers’ buying
behavior and predict future behavior by identifying affinities among customers’
choices of products and services
STATISTICAL
ANALYSIS
•
Statistical analysis – performs such functions as information
correlations, distributions, calculations, and variance analysis
– Forecast – predictions made on the basis of
time-series information
– Time-series
information – time-stamped
information collected at a particular frequency
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