BDT T4

1
OM
IS

Organizational
WE ARE
BUSINESS
Decision Making
Decision Making, Problem Solving,
and Opportunity Capturing?
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The "Money" Ability?
What is the most important skill or abilitythat
separates successful and promotablebusiness
people from the crowd?
What skill or ability is both MOST prized (and
scrutinized) by top managers when determining the
organizational value of their core managers?
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Decision Making
? The business environment in which
organizations compete is high velocity, fast
paced, and dynamic.
? In order for organizations to be competitive in
this global business marketplace it is
ESSENTIAL that organizations continually
analyze and assess their specific competitive
environment and consciously implement
strategies to seize and capture new business
opportunities as they arise.
? While it is the responsibility of top
management to provide the strategic direction
of the firm it is really the innovative and
timely tactical decisions made by the lower
level managers that can have a profound affect
on the ultimate success of the organization.
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Keeping Count?
? The game is simple organizations highly
value business people who continually
demonstrate they can deliver when given the
organizations most challenging assignments
and tasks. Organizations keep an unwritten
count of who are the players and who are the
pretenders.
Players The Beatty Skill Set
1) Wants the organizations business challenges.
2) Ability to convert organizational problem
solving issues into win-win solutions.
3) Confidence to make the hard decisions based
on both past experience (hueristics) and
thorough analytical research.
4) Tireless commitment to the successful
completion of all tasks assigned on time
and in budget.
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Decision Making
Why is decision making so important?
What are the core components in a
typicalorganizational decision making process?
What are the four systems organizationscan use
to make decisions and gain acompetitive
advantage?
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Decision Making
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Decision Making
Characteristics
High Risk
Unstructured
Strategic
TOPMANAGEMENT
Op Risk
Unstructured
Tactical
MIDDLE MANAGEMENT
OPERATIONAL MANAGEMENT
Low Risk
Structured
Operational
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Decision Making
Intelligence
Problem discovery What is the problem?
Design
Solution discovery What are possible solutions?
Choice
Choosing Solutions What is the best solution?
Choosing Testing Did I make the best
decision?What can I learn from the decision I
made?
Implementation
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The Four Systems
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3
1
4
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Decision Support System
What is a Decision Support System (DSS)?
What are three quantitative models usedby a DSS?
What are the three common forms of datamining
analysis capabilities?
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Decision Support System
Definition
? any computer-based application systems designed
specifically to support managers and business
professionals during their decision-making
process.
Components
1) DSS Database a collection of stored
historical or current data obtained from
numerous sources (e.g., internal and external).
2) DSS Software the suite of software tools
used to complete data analysis using data
from the DSS database. Tools include a.
On-line Analytic Processing (OLAP) used to
analyze large amounts of data and quickly
obtain a specific result. b. Query used to
interrogate the database and obtain specific
data in a structured format c. Data
Mining used to analyze relationships between
specific data and provide new data
relationships and predictions
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Decision Support System
SUPPORTEDDECISION
DATACAPTURE
DATAANALYSIS
EXTERNALDATA
- OLAP- Queries- Models
DSSDATABASE
INTERNALDATA
UserInterface
DATAMINING
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Decision Support System
Three Quantitative Models Typically Used in DSSs
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 determines the inputs
necessary to achieve a desired level of
output.
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Data Mining
? may include AI capabilities to assist in data
analysis.? three common forms of data mining
analysis capabilities
1) 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 far away as possible. ? use gt CRM
system relies on cluster analysis to segment
customer information and identify behavioral
traits
2) Association Detection
? a technique that reveals the degree in which
variables are related and the nature and
frequency of there relationships in the
information.? use gt market basket analysis
analyses customer purchase information (e.g.,
web site or store) to detect customers buying
behavior and predict future behavior by
identifying affinities (similarities) among
customers choices of products or services.
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Data Mining
3) Statistical Analysis
? numerous statistical analysis performed on
data, such as information correlations,
distributions, and variance analysis.
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Executive Information Systems (EIS)
What is a Executive Information System?
What are typical characteristics of a EIS?
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Executive Information Systems (EIS)
Definition
? a specialized computer-based DSS application
system specifically designed to support the
strategic decision-making needs of an
organizational executive
System Characteristics
1) Ease of Use extremely user-friendly system in
which the interface (e.g., mouse, touch
screen) is user customized.
2) Consolidation involves the aggregation of
information and features simple roll-ups to
complex groupings of interrelated information.
3) Drill-Down enables users to click on
aggregate information to obtain additional
details on the information.
4) Slice-And-Dice allows user to view
information from different levels and
different perspectives.
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Executive Information Systems (EIS)
Digital Dashboard
? a quick view screen used by executives to
integrate core information from multiple
components and present it in a single unified
display.
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Artificial Intelligence (AI) Systems
What is Artificial Intelligence?
What are the three most commoncategories of AI
systems?
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Artificial Intelligence (AI) Systems
Definition
? a specialized computer-based application system
that attempts to emulate human behavior and
thought patterns. ? simulates human intelligence
such as the ability to reason and learn and
typically can
1) Learn or understand based on experience.
2) Make sense of ambiguous or contrary
information.
3) Use reasoning to solve problems and make
decisions.
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Artificial Intelligence (AI) Systems
? the three most common categories of AI include
1) Expert System
? computerized application that imitates the
reasoning processes of experts in solving
difficult problems.? used is a specific domain
where expertise is expensive or in short
supply ? examples gt granting a bank loan, or
problems with malfunctioning machine
2) Neural Networks
? computerized application used for solving
complex, poorly understood problems for which
large amounts of data has been collected.?
attempts to emulate how the brain reasons
(works) ? examples gt diagnosing illnesses, or
predict future financial performance based on
based information.
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Artificial Intelligence (AI) Systems
? the three most common categories of AI include
3) Intelligent Agents
? computerized applications that work in the
background without direct human intervention to
carry out specific, repetitive, and predictable
tasks for the user. short supply ? examples gt
determining what e-mails to accepts and delete,
and searching for the best air fare.
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Any Questions?