CHAPTER 9 : Enabling the Organization – Decision Making
Decision making
growth by technology because people need to analyse large amounts of
information, moreover they need to make decision quickly. They must apply
sophisticated analysis techniques (modelling, forecasting) to make good
decision.
Model is
a simplified representation or abstraction of reality.
Transaction Processing Systems, basic business system that serves the
operational level.
Online transaction processing (OLTP), capturing of transaction and event
information using technology to process the information according to defined
business rules, store information, update existing information to reflect new
information.
Decision Support Systems, where models information to support managers and
business professionals during the decision-making process.
Executive Information System, a specialized DSS that support senior
level or top level executive within the organization.
Most EISs
offering the following:
Consolidation, involves aggregation of information and features simple
roll-ups to complex groupings of interrelated information. Eg: Data for
different sales representatives can be rolled up to an office level. Then state
level, then a regional sales level.
Drill-down, enables users to get details, and details of details,
of information. Eg. From regional representative at each office.
Slice-dice, looks at information from different perspectives.
Eg. One slice of information could display all product sales during a given
promotion, another slice could display a single product’s sales for all
promotions.
Digital dashboard, integrates information from multiple components
and presents it in a unified display.
Artificial Intelligence (AI), simulates human intelligence such as
ability to reason and learn. It can check info on competitor. Ultimate goal is
ability to build a system that can mimic human intelligence.
Four common
categories include:
Expert system, computerized advisory programs that imitate
reasoning processes of experts in solving difficult problem (playing chess).
Neural Network,
attempts to emulate the way the human brain work. Eg. Finance industry uses
neural network to review loan application and create patterns or profiles of
applications that fall into two categories: approved or denied.
Intelligent system is various commercial applications of artificial
intelligence, while Artificial
intelligent (AI) is simulates human intelligent such as the ability to
reason and learn. The goal is the ability to build system that can mimic human
intelligent.
Four Common
Categories of AI include:
Expert system, computerized that imitate the reasoning processes
of experts in solving difficult problems. Example, playing chess and diagnose
diseases.
Neural Network, emulate way the human brain works. Example,
industry use to review loan applications and create patterns or profiles of
applications that fall into two categories – approved or denied. Fuzzy
logic is mathematical method of handling imprecise or subjective
information. Example, washing machine determine by themselves how much water to
use or how long to wash.
Genetic Algorithm is an artificial intelligent system that mimics the
evolutionary, survival of the fittest process to generate increasingly better
solutions to problems. Example, business executives use genetic algorithm to
help them decide which combination of projects a firm should invest.
Intelligent Agent is special-purposed knowledge-based information
system that accomplishes specific tasks on behalf of its users, which is
multi-agent systems and agent-based modelling. Example, software will search
several retailer’s websites and provide a comparison of each retailer’s
offering including prive and availability.
Data-mining
software includes many forms of AI such as neural networks and expert system.
Common forms of analysis capabilities include:
Cluster analysis
Technique used
to divide information set into mutually exclusive group (be close even
different department). Example, consumer goods by content, brand-loyalty or
similarity.
Association detection
Reveals degree
to which variables are related and the nature and frequency of the
relationships in the information. Market basket analysis is analyse
such items as web sites and checkout scanner information to detect customer’s
buying behaviour.
Statistical analysis
Performs such
function as information correlations. Distributions, calculations, and variance
analysis. Forecast, prediction made on the basis of time-series information
which is time-stamped information collected at a particular frequency.
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