1. Decision Support and Business Intelligence Systems
Chapter 2:
Decision Making, Systems, Modeling, and Support

2. Decision Support Systems (DSS)
Dissecting DSS into its main concepts
Building successful DSS requires a through understanding of these concepts

3. Decision Making
Decision Making: a process of choosing among alternative courses of action for the purpose of attaining a goal or goals
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

4. Characteristics of Decision Making
Groupthink
Evaluating what-if scenarios
Experimentation with a real system!
Changes in the decision-making environment may occur continuously
Time pressure on the decision maker
Analyzing a problem takes time/money
Less or too much information

5. Characteristics of Decision Making
Better decisions
Tradeoff: accuracy versus speed
Fast decision may be danger
Areas suffering most from fast decisions
personnel/human resources (27%)
finance (24%)
organizational structuring (22%)
quality/productivity (20%)
IT selection and installation (17%)
process improvement (17%)

6. Decision Making versus Problem Solving
Simon’s 4 Phases of Decision Making
1. Intelligence 2. Design 3. Choice 4. Implementation
Decision making and problem solving are interchangeable
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

7. Decision Making and Problem Solving
A problem occurs when a system
does not meet its established goals
does not yield the predicted results, or
does not work as planned
Problem is the difference between the desired and actual outcome

8. The Decision-Making Process
Systematic Decision-Making Process
Intelligence
Design
Choice
Implementation
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

9. Decision-Making: Intelligence Phase
Scan the environment
Identify problem situations
Monitor the results of the implementation

10. Decision-Making: Intelligence Phase
Potential issues in data/information collection and estimation
Lack of data
Cost of data collection
Inaccurate and/or imprecise data
Data estimation is often subjective
Data may be insecure
Data change over time (time-dependence)

11. Decision-Making: The Design Phase
Finding/developing and analyzing possible courses of actions
A model of the decision-making problem is constructed, tested, and validated

12. Decision-Making: The Choice Phase
Includes the search, evaluation, and recommendation of an appropriate solution to the model
Solving the model versus solving the problem!

13. Decision-Making: The Choice Phase
Search approaches
Analytic techniques (solving with a formula)
Algorithms (step-by-step procedures)
Heuristics (rule of thumb)
Blind search (truly random search)

14. Decision-Making: The Implementation Phase
Solution to a problem = Change
Implementation: putting a recommended solution to work

15. Systems
A SYSTEM is a collection of objects such as people, resources, concepts, and procedures intended to perform an identifiable function or to serve a goal
System Levels (Hierarchy): All systems are subsystems interconnected through interfaces
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

16. The Structure of a System
Three Distinct Parts of Systems
Input
Processes
Outputs Systems
Are surrounded by an environment
Frequently include a feedback mechanism A human, the decision maker, is usually considered part of the system
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

17. System
Environment
Output(s)
Input(s)
Processes
Feedback
Boundary

18. Inputs are elements that enter the system
Processes convert or transform the inputs into outputs
Outputs describe the finished products
Feedback is the flow of information from the output to the decision maker, who may modify the inputs or the processes (closed loop)
The Environment contains the elements that lie outside but impact the system's performance
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

19. Closed and Open Systems
A Closed System is totally independent of other systems and subsystems
An Open System is very dependent on its environment

20. Models Major Component of DSS
Use Models instead of experimenting on the real system
A model is a simplified representation or abstraction of reality.
Reality is too complex
Much of the complexity is actually irrelevant in problem solving
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson
Copyright 1998, Prentice Hall, Upper Saddle River, NJ

21. Types of Models
Models can be classified based on their degree of abstraction
Iconic models (Physical replica of a system)
Analog models
Mathematical (quantitative) models
Less
Degree of abstraction
use mathematical relationships to represent complexity Used in most DSS analyses
More

22. The Benefits of Models Compression of time
Lower cost of analysis on models
Cost of making mistakes on experiments
Evaluation of many alternatives
Reinforce learning and training

23. How Decisions Are Supported
Support for the Intelligence Phase
Enabling continuous scanning of external and internal information sources to identify problems .
Business activity monitoring (BAM)
Business process management (BPM)
Product life-cycle management (PLM)

24. How Decisions Are Supported
Support for the Design Phase
Enabling generating alternative courses of action, determining the criteria for choice
Generating alternatives
Structured/simple problems: standard and/or special models
Unstructured/complex problems: human experts,
A good “criteria for choice” is critical!

25. How Decisions Are Supported
Support for the Choice Phase
Enabling selection of the best alternative given a complex constraint structure
Use sensitivity analyses, what-if analyses.

26. How Decisions Are Supported
Support for the Implementation Phase
Enabling implementation of the selected solution to the system

27. New Technologies to Support Decision Making
Web-based systems
Cell phones, Tablet PCs
other wireless technologies
Faster computers, better algorithms, to process “huge” amounts of heterogeneous/distributed data

28. End of the Chapter
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