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Decision Support Systems
Yong Choi
School of Business
CSU, Bakersfield
Type of Decision-makings
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Structured (Programmed)
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Unstructured (Nonprogrammed)
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routine & repetitive, predictable problems
standard solutions exist
non-routine, unpredictable, “fuzzy” complex problems
no cut-and-dried solutions
Semistructured (Programmed + Nonprogrammed)
 non-routine, predictable,
 Require a combination of standard solution procedures and
individual judgement
Stages of Decision Making
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Stage 1: Intelligence
identify the problems/opportunities and then, collect data or
information
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Stage 2: Design
analyze/develop the possible solutions for the feasibility
GO back to stage 1 if there is insufficient data.
Stages of Decision Making
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Stage 3: Choice
Choose one alternative
Go back to stage 1 or 2 if there are no satisfactory solutions.
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Stage 4: Implementation
Implement the selected alternative
Failure of implementation  go back to stage 1 or 2 or 3
Ex) Buying a new car
Transaction Processing Systems (TPS)
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Developed in the early1960s
Serve the operational management level
Performing and recording daily routine and repetitive
transactions
Primary focus: structured decision-makings
Transaction Processing Systems
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Lifeblood of an organization
Provide summarized and organized data in the
accounting and finance areas
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Account receivable and payable
Sales transactions
Payroll
Management Information Systems
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Developed in the 1960s
Intended to serve the operational or middle
management level
Summary and exception reports
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monthly production reports
Quarterly travel expense reports
Difference between expected sales and actual sales of a
particular product
Primary focus: fairly structured decision-makings
Decision Support System (DSS)
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An interactive computer-based system that helps
decision makers in the solution of semi-structured
and unstructured problems.
Developed in the early 1970s
Originally, designed to serve the middle
management
Primary focus: semi-structured and unstructured
decision-makings
Decision Support System
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What is a DSS?
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DSS Examples
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A highly flexible and interactive IT system that is
designed to support decision making when the problem is
not structured. Provide alternative-analysis report
investment portfolios
Plant expansion
See text book for detail examples
Three Fundamental Components of a DSS
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Model management component – consists of both
the DSS models and the model management system
Data management component – stores and
maintains the information that you want your DSS to
use
User interface management component – allows
you to communicate with the DSS
Three Fundamental Components
Three Fundamental Components of DSS
3.
Model management component
Data management component
User interface management component
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See the online lecture or the textbook for details
1.
2.
Model driven DSS
Primarily stand alone systems
isolated from major organization's information systems
Use models (LP, Simulation)
Sensitivity analysis as a main technique
What-If analysis
Goal Seek Analysis
What-if analysis vs. Goal-seek analysis
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Attempt to check the impact of a change in the
assumptions (input data) on the proposed solution
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What will happen to the market share if the advertising
budget increases by 5 % or 10%?
Attempt to find the value of the inputs necessary to
achieve a desired level of output
Use “backward” solution approach
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A DSS solution yielded a profit of $2M
What will be the necessary sales volume to generate a profit
of $2.2M?
Tools for Model Driven DSS
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Linear Programming
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Lindo
Gindo
Spreadsheet Software
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Excel
Lotus 1-2-3
Quattro Pro
Data Driven DSS
Many current and the newest DSS
Data-driven DSS with On-line Analytical Processing
(OLAP) provide the highest level of functionality and
decision support that is linked to analysis of large
collections of historical data.
Discover previously unknown patterns by analyzing large pools
of data from data warehouse
Data mining as main technique
Data Mining
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Help managers to find hidden patterns and
relationships in large databases to predict future
behavior
–
“If a house is purchased, then new refrigerator will be
purchased within two weeks 65% of the time.”
Model Driven DSS vs. Data Driven DSS
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A Model Driven DSS uses various models such as
statistical model, simulation model or financial model
for decision makings. So, decisions are based on
models.
A Data Driven DSS emphasizes access to and
manipulation of a time-series of internal company
data and sometimes external data to aid decision
makings. So, decisions are based on analyzed data.
Web-based DSS for customers
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Evaluate and compare real estate prices
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Evaluate alternative investment in mortgage
portfolios
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fidelity.com (on-line investor center)
Evaluate and compare air fares
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Zillow.com: 10402 Loughton Ave. 93311
travelocity.com
Evaluate and compare various automobile prices
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aotubytel.com
Executive Information Systems OR
Executive Support Systems
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Developed in the late 1980s
Serve the senior management level
Designed mainly to monitor organization’s performance
and address decision makings quickly and accurately
Very user-friendly, supported by graphics
Drill-down capability
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EIS drill-down interface design
The Need of EIS
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Need for more timely and accurate information for
better decision makings
Need to access internal/external databases to detect
environmental changes
Need to be more proactive due to intensive
competition
Gain computer literacy