The document discusses Decision Support Systems (DSS), which help senior executives manage vast amounts of disparate data to improve decision-making across various sectors. It outlines the components, processes, and types of DSS, emphasizing the importance of technology and data analysis in complex decision-making scenarios. Additionally, it details various types of decision-making challenges and the advantages of modern DSS, including enhanced decision quality, cost reduction, and improved productivity.

1. Information Systems 371
March 14, 2019
Topic: Decision Support Systems
Lecturer: Nicholas Davis

2. Decision Support Systems
Overview
• Senior level executives live in
fast paced environments that
highly competitive, fast-paced,
with near real-time demands
made upon them.
• They are overloaded with
information, disparate data
distributed throughout the
enterprise, and a global scope of
responsibility
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3. DSS History Graphic
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4. Decision Support Systems
Overview
The combination of high speed networks, in
combination with “Big Data” and the imminent rise
of Artificial Intelligence, has led to the creation of
information systems which can assist with the
assembling, evaluation and presentation of this
wealth of information
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5. Decision Support Systems
Overview
• These systems have the potential to improve
decision making by suggesting solutions that are
better than those made by humans alone.
• They are used in all areas, from dog food
production to healthcare, to garbage collection, to
the stock market
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6. Decision Support Systems
Overview
• Collect data
• Process data
• Evaluate Data
• Present Data
• This is a Decision Support System
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7. Components of a Decision
Support System
A DSS is made up of:
1. A source of data
2. A method or model to analyze the data
3. A user interface
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8. 3 Steps in the DSS Process
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9. Let’s Look at an Example
Step 1 – Describe the Big Picture
A developing country is going to build a railway system to
connect a potential inland industrial area and a good
agricultural area with a port. An international development
agency recommended that iron already present in the area,
should be mined and refined locally, using an infrastructure
that still needs to be established The refined iron could
possibly be exported to Germany and Japan for use in the
automobile industry. A core component of success of the
project depends upon the supply of skilled labor. To
overcome this problem an education and training center has
to be established to get worker prepared by the time the
iron processing plant is ready to open The development
agency also recommends the fertile farm land in the area
should be prepared for intensive farming to provide food for
consumption by the people working at the iron processing
plant The railway should link the industrial area to local
farms and the sea port.
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10. Proceed?
Yes or No
• Does the high level plan seem
plausible and reasonable?
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11. Step 2 - List All Questions
That Must be Answered
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•Is the route optimal? Are all likely users connected? What are other possible routes?
•Growth of traffic: To what extent does development of a railway system depend on
development of port, new town, airport, industrial area and agricultural area in order to
make the railway sustainable in terms of revenue?
•Competition: To what extent would development of an improved road system eliminate
the need for a new railway to be constructed?
•Engineering problems: How much electricity is needed for electric train? Would it be
better to use a diesel train? Where would the fuel or electricity come from, to power the
train?
•Supply problem: Where will the supply of construction equipment and workers come
from?
•Operational problem: With inadequate supply of local skilled workers where will
operating team be sourced from? Will contractors need to be brought in from foreign
countries? If so, what are the added complexities?
•Time Scale: When is the start date, the completion date and milestones along the entire
timeline?
•Cost: What will the total cost of the project be?
•Infrastructure: Will available supporting services include: telephone, fire, water, radio
communication, hospitals, hotels and housing?

12. Proceed?
Yes or No
• Is it technically possible to accomplish
the required tasks?
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13. Step 3 – Spec Out
the Details of All Tasks
• Steps in each task
• Cost of each task
• Time for each task
• Based upon these realities, can you
still justify the project and make it
real? If so, based upon everything you
no know, do you start the project or
not?
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14. Decision Support Systems
• DSS tries to address the complexity of
these type of situations by automating as
much as possible
• Ideally, decision makers are presented
with fewer choices, based upon more
complex automated collection and
analysis of data by DSS systems
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15. DSS
Decision Making Characteristics
• Decision is made based only on the
information available, no
speculation
• The process is iterative, data and
decisions based upon that data may
change over time
• All decisions must be pragmatic:
For example, if there is not funding,
the project won’t move forward, no
matter how practical the path for the
project is.
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16. Everyone Who is Responsible
For Making Decisions is in Effect a
Manager
• Organizations are filled with decision
makers at all levels.
• Managing these decisions is an art, but
one which involves more and more
quantitative science, every day
• Technology permits new types of
evaluation
• Organizations are becoming more
complex
• The marketplace is changing more
rapidly
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17. DSS Evaluates 3 Core Elements
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18. All DSS Have Three
Core Elements to Evaluate
1. Objectives
What do we want to accomplish?
Example: Maximize profit
Example: Be the first to market
Example: Produce a superior and differentiated
product
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19. All DSS Have Three
Core Elements to Evaluate
2. Decision Variables
What questions do we need to answer, in
order to accomplish our goal?
Example: Determine how to appropriately
price a product for sale
Example: Determine length of time tests
should be run on a new product/service to
verify that it functions as intended
Example: Determine the responsibilities to
assign to each worker
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20. All DSS Have Three
Core Elements to Evaluate
3. Constraints
What limitations are we facing?
Example: We can’t charge less than our cost
Example: We must test enough to meet minimum
safety regulations
Example: We must ensure that employees have enough
training, or they won’t be able to produce the product
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21. DSS Must Be Able to Address
3 Types of Problems
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22. DSS Must Be Able to Address
Three Types of Problems
1. Structured
Situations in which the procedures to follow when
a decision is needed can be specified in advance
• Repetitive
• Standard solution methods exist
• Complete automation may be feasible
• Example: Does the production line accept or
reject a burnt peanut?
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23. DSS Must Be Able to Address
Three Types of Problems
2. Unstructured
Decision situations where it is not possible to specify
in advance most of the decision procedures to follow
• One-time
• No standard solutions
• Rely on judgment
• Automation is usually infeasible
Example: Do you go to Jim’s party on Friday night,
or stay home, “watch Netflix and chill”?
Better Example: Should we source ball bearings from
China instead of Mexico?
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24. DSS Must Be Able to Address
Three Types of Problems
3. Semi-structured
Decision procedures that can be pre specified, but
not enough to lead to a definite recommended
decision
Some elements and/or phases of decision making
process have repetitive elements.
Example: if the ball bearings we source are not
round enough, we need to evaluate other
alternatives
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25. Technology Based DSS
• Gathers data
• Evaluates it using models and
algorithms
• Displays metrics in a user friendly
format, for use in
executive/managerial decision
making
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26. Why Do We Need DSS
Anyway?
Increasing Complexity in Decision
Making Process
• Technology
• Information
• Pace of change
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27. Why Do We Need DSS
Anyway?
Increasing availability of
computerized support
• Inexpensive high-powered
computing
• Better software
• More efficient software development
process
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28. Benefits of New Generation
DSS
• Decision quality
• Improved communication
• Cost reduction
• Increased productivity
• Time savings
• Improved customer and employee
satisfaction
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29. 7 Types of DSS Systems
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30. The Seven Types of DSS
File Drawer Systems, that provide
access to the data items.
Examples: A massive CSV file
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31. The Seven Types of DSS
Data Analysis systems, that support
manipulation of data by computerized tools
for a specific task.
Example: Spreadsheet sorting by field name
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32. The Seven Types of DSS
Analysis Information systems, that
provide access to a series of decision
oriented databases and small models.
Example: An online troubleshooting
system
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33. The Seven Types of DSS
Accounting and financial models, that
calculates the consequences of possible
actions.
Example: Using an ERP to calculate how
much revenue the university will take in if
they increase tuition by 1% annually
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34. The Seven Types of DSS
Representational model, that estimates the
consequences of actions based on simulation
models.
Example: Using engineering design software to
see what will happen to a bridge when 50% of
the support structure is removed.
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35. The Seven Types of DSS
Optimization models, that
provide guidelines for action
by generating an optimal
solution
Example: The minimum
amount mechanical engineers
are necessary to have on-site,
to ensure that the assembly
line keeps moving with 99.5%
uptime?
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36. The Seven Types of DSS
Suggestion models, that perform
the logical processing to a specific
suggested decision for a task.
Example: What are the ideal time
periods to offer an “early bird
special” price at a restaurant?
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37. New Generation DSS
Requires Many Different Systems
• Database research
• Artificial intelligence
• Human-computer interaction
• Simulation methods
• Software engineering
• Telecommunications
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38. In Class Exercise
Clinical decision support system for
medical diagnosis.
1. Objectives
2. Decision making variables
3. Constraints
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39. In Class Exercise
A bank loan officer verifying the credit
of a loan applicant
1. Objectives
2. Decision making variables
3. Constraints
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40. In Class Exercise
An engineering firm that has bids on
several projects and wants to know if
they can be competitive with their
costs.
1. Objectives
2. Decision making variables
3. Constraints
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41. In Class Exercise
Apple iPhone X production quantity for coming
quarter example
DSS is extensively used in business and management.
Executive dashboards and other business
performance software allow faster decision making,
identification of negative trends, and better allocation
of business resources.
1. Objectives
2. Decision making variables
3. Constraints
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42. In Class Exercise
A railway system, which tests its equipment
on a regular basis using a decision support
system.
1. Objectives
2. Decision making variables
3. Constraints
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43. In Class Exercise
Make decisions in the stock market. Which
stocks and sectors to buy and sell today, and
what the triggers will be
1. Objectives
2. Decision making variables
3. Constraints
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44. How DSS Results are Delivered
Periodic Scheduled Reports:
Prespecified format on a regular basis,
available but not pushed to specific
people
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45. How DSS Results are Delivered
Exception Reports: Reports about
exceptional conditions. These may be
triggered by an event, or produced
regularly (How many times did the
production line go down unexpectedly
last qtr)
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46. How DSS Results are Delivered
Demand Reports and Responses,
Information available when
requested
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47. How DSS Results are Delivered
Push Reporting, Information
pushed to manager
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48. DSS Analysis Types
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49. Common DSS
Usage Techniques
What-if Analysis
• End user makes changes to variables,
or relationships among variables, and
observes the resulting changes in the
values of other variables
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50. Common DSS
Usage Techniques
Sensitivity Analysis
Value of only one variable is changed
repeatedly and the resulting changes in
other variables are observed
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51. Common DSS
Usage Techniques
Goal-Seeking
Set a target value for a variable and
then repeatedly change other
variables until the target value is
achieved
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52. Common DSS
Usage Techniques
Optimization
Goal is to find the optimum value for one or more
target variables given certain constraints
One or more other variables are changed
repeatedly until the best values for the target
variables are discovered
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