Using Information Systems for Decision Making

finickyontarioAI and Robotics

Oct 29, 2013 (3 years and 5 months ago)

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Using Information

Systems for

Decision Making

LEARNING GOALS


Discuss the problems associated with
management decision making.


Explain the decision
-
making process.


Describe decision support systems.


Explain how group decision support systems work.


Describe executive information systems.


Discuss artificial intelligence technologies and their
applications.

Decision Making Today


Business decisions are increasingly difficult to
make


Dramatic increase in the internal business data
available to managers


Managers must keep current on vast amounts of
data resources on the Internet


Globalization


The speed of commerce


The increased number of business choices
available


Group decision making

Internet Architecture


A brief History of the internet


written by some of the people who were
there at the start



Hobbes’ internet timeline v7.0



Today’s Internet


Thousands of networks


Connected by legal agreements and
commercial contracts


Uses TCP/IP protocol


Internet service providers (ISPs)

Roadblocks to Good Decision
Making


Human cognition


Our mental ability to comprehend and understand
something


Human perception


Difficulty isolating problems


Tend to think of only narrow range of possible
solution


Human bias


Tendency to shape responses based on
stereotypes, memory, and current position

How to Overcome the
Roadblocks


Decision support systems (DSS) are one tool


A computer
-
based system that supports and
improves human decision making


Helps analyze complex problems


Process vast amounts of analytical data


Group decision support systems (GDSS)


Tool for supporting team decision making


Executive information system (EIS)


Computer
-
based system that supports the decision
-
making processes of senior managers

The Decision
-
Making Process


Simon’s model of the decision
-
making
process


Intelligence


Design


Choice


Intelligence Phase


Scan the environment for a problem.


Determine if decision
-
maker can solve
the problem.


Within scope of influence


Fully define the problem by gathering
more information about the problem.



Design Phase


Develop a model of the problem.


Determine type of model.


Verify model.


Develop and analyze potential
solutions.

Choice Phase


Select the solution to implement.


More detailed analysis of selected
solutions might be needed.


Verify initial conditions.


Analyze proposed solution against real
-
world constraints.

Problem
Structure


Structured problems


Unstructured problems


Semi
-
structured problems

Decision Support Systems


Major components


Data management system


Internal and external data sources


Model management system


Typically mathematical in nature


User interface


How the people interact with the DSS


Data visualization is the key


Graphs


Charts


Geographic information systems (GIS)


Modeling Tools and Techniques


Simulation


Computerized model of the problem


Used to examine proposed solutions and their
impact


Sensitivity analysis


Determine how changes in one part of the model influence
other parts of the model


What
-
if analysis


Manipulate variables to see what would happen in given
scenarios


Goal
-
seeking analysis


Work backward from desired outcome

Groups Decision Support Systems


Having multiple participants in the
decision process adds potential
problems


Production blocking


Evaluation apprehension


Social loafing


Group think


GDSS tools contain special tools to
overcome these problems


GDSS Tools


Brainstorming tools


Commenter tools


Categorizing tools


Idea
-
ranking tools


Electronic
-
voting tools


Group facilitator

Executive Information Systems


Computer
-
based tool that specifically
helps
top
-
level

management make
strategic decisions


Processes both
internal

and
external

data


Presents data in summary form


Drill
-
down

is a key feature


gives the
manager the ability to see more details
when needed


Artificial Intelligence (AI)


Field of study that explores the
development of computer systems that
behave like humans


Strong AI


create a computer that can
think like a human


Weak AI


develop computers and
programs that employ
thinkinglike

features

Expert Systems


AI systems that codify
human expertise

in a
computer system


Main goal is to transfer knowledge from one
person to another


Wide range of subject areas


Medical diagnosis


Computer purchasing


Whale watching


Knowledge engineer elicits the expertise from the
expert and encodes it in the expert system

Expert Systems Components


Knowledge base


Inference engine


User interface


Explanation system

Other Artificial Intelligence
Technologies


Neural networks


use software to simulate
the neural working of the human brain


Intelligent agents (
bots
)


autonomously
handle tasks for humans and act on user’s
behalf


Genetic algorithms


Computer instructions
that create a population of thousands on
potential solutions and evolves the population
toward better solutions


Fuzzy logic


a way to get computers to come
closer to the ability to see fine distinctions, not
just ones and zeros

A Neural Network