Decision Support and Business Intelligence Systems Chapter 2: Decision Making, Systems, Modeling, and Support
Decision Support Systems (DSS) Dissecting DSS into its main concepts Building successful DSS requires a through understanding of these concepts
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
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
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%)
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
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
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
Decision-Making: Intelligence Phase Scan the environment Identify problem situations Monitor the results of the implementation
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)
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
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!
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)
Decision-Making: The Implementation Phase Solution to a problem = Change Implementation: putting a recommended solution to work
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
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
System Environment Output(s) Input(s) Processes Feedback Boundary
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
Closed and Open Systems A Closed System is totally independent of other systems and subsystems An Open System is very dependent on its environment
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
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
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
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)
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!
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.
How Decisions Are Supported Support for the Implementation Phase Enabling implementation of the selected solution to the system
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
End of the Chapter Questions / Comments…