CHAPTER
NINE:ENABLING THE ORGANIZATION
Reason
for Growth of Decision Making Information System
1.
People need to analyze large amounts of information :- improvement in
technology itself, innovations in communication, and globalisation have
resulted in a dramatic increase in the alternatives and dimension people need
to consider when making a decision or appraising an opportunity.
2.
People must make decision quickly :- time is of the essence and people simply
do not have time to sift through all the information manually.
3.
People must apply sophisticated analysis technique such as modelling and
forecasting to make good decision :- information system substantially reduce
the time required to perform this sophisticated analysis technique.
4.
People must protect the corporate asset of organizational information :-
information systems offer the security required to ensure organization
information remains safe.
Model
- a simplified representation or abstraction of reality.
Transaction
Processing System
Ø Moving up through the organizational pyramid
users move from requiring transactional information to analytical information
Ø
Transaction processing system – the basic business system that serves
the operational level (analysis) in an organization
Ø 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
Ø Online analytical processing (OLAP) – the
manipulation of information to create business intelligence in support of
strategic decision making
Decision
support systems
Ø Decision support system (DSS) – models information
to support managers and business professionals during the decision-making
process
Ø 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
Goal-seeking
analysis – finds the inputs necessary to achieve a goal such as a desired level
of outputs
Executive
information system
Ø Executive information system (EIS) – A
specialized DSS that supports senior level executives within the organization
Ø 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 information
- Slice-and-dice – looks at information
from different perspectives
Ø Interaction between a TPS and an EIS
Ø Digital dashboard – integrates information
from multiple components and presents it in a united display
Artificial
intelligence (AI)
Ø The ultimate goal of AI is the ability to
build a system that can mimic human intelligence
Ø Intelligent system – various commercial
applications of artificial intelligence
Ø Artificial intelligence (AI) – simulates
human intelligence such as the ability to reason and learn
Four most common categories of AI include;
1. Expert system – computerized advisory
programs that imitate the reasoning processes of experts in solving difficult
problems
2. Neural network – attempts to emulate the
way the human brain works
Fuzzy logic – a mathematical method of
handling imprecise or subjective information
3. Genetic algorithm – an artificial
intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem
4. Intelligent agent – special-purposed
knowledge-based information system that accomplishes specific tasks on behalf
of its users
Data
Mining
Ø Data-mining software includes many forms of
AI such as neutral networks and expert systems
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