Decision Support and Business Intelligence Systems

Slides:



Advertisements
Similar presentations
Chapter 2: Decision Making, Systems, Modeling, and Support
Advertisements

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-1 Chapter 2 Decision-Making Systems,
SPK : MODEL DAN PENDUKUNG
Operations Research Session Objectives:  To describe the need and importance of Operations Research for rationale decision making in health care delivery.
DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT
Decision making, systems, modeling and support
Decision Making, Systems, Modeling, and Support
Chapter 2: Decision Making, Systems, Modeling, and Support
Introduction to Modeling
Chapter 2: Decision Making, Systems, Modeling, and Support
Copyright 2007 John Wiley & Sons, Inc. Chapter 91 Managerial Support Systems.
DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT
DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT
MANAGEMENT USES OF INFORMATION Pertemuan 02 Matakuliah: F0204 / SISTEM AKUNTANSI Tahun: 2007.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-1 Chapter 4 Modeling and Analysis Turban,
Data Analysis Modeling, and Decision Making
Chapter 2: Decision Making, Systems, Modeling, and Support
Modeling.
Chapter 2 Decision-Making Systems, Models, and Support
Decision-Making Processes
Decision Support Systems
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 2: Decision Making, Systems, Modeling, and Support.
Decision-Making: Introduction and Definitions The opening vignette demonstrated some aspects of a typical business decision: The decision is often made.
Chapter 7 alternatives and Models in Decision Making
Decision Making, Systems, Modeling, and Support
Chapter 4 MODELING AND ANALYSIS. Model component Data component provides input data User interface displays solution It is the model component of a DSS.
Chapter 4 Dr. Fadi Fayez Updated by: Ola A.Younis.
1 Chapter 5 Modeling and Analysis. 2 Modeling and Analysis n Major component n the model base and its management n Caution –Familiarity with major ideas.
Analyzing Business Decision Processes
Mata Kuliah: CSM 211, Management Support System Tahun Akademik: 2012/2013 DECISION MAKING SYSTEM, MODELLING AND SUPPORT Pertemuan-3 Hasil Pembelajaran.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 2-1 Chapter 2 Decision-Making Systems,
1 CHAPTER 2 Decision Making, Systems, Modeling, and Support.
1 (CHAPTER 5 Con’t) Modeling and Analysis. 2 Heuristic Programming Cuts the search Gets satisfactory solutions more quickly and less expensively Finds.
Software Development Life Cycle by A.Surasit Samaisut Copyrights : All Rights Reserved.
1 CHAPTER 2: DECISION MAKING, SYSTEMS, MODELING, AND SUPPORT Decision Support Systems and Intelligent Systems, 7th.
© 2005 Prentice Hall1-1 Stumpf and Teague Object-Oriented Systems Analysis and Design with UML.
Decision Support and Business Intelligence Systems (9 th Ed., Prentice Hall) Chapter 2: Decision Making, Systems, Modeling, and Support.
1 1 Slide © 2004 Thomson/South-Western Body of Knowledge n The body of knowledge involving quantitative approaches to decision making is referred to as.
CHAPTER 3 Managers and Decision Making 1. Decision Making, Systems, Modeling, and Support 2  Conceptual Foundations of Decision Making  The Systems.
Simon Model of Decision Making
1 CHAPTER 2 Decision Making, Systems, Modeling, and Support.
Modern Systems Analysis and Design Third Edition Chapter 2 Succeeding as a Systems Analyst 2.1.
1-1 © Prentice Hall, 2004 Chapter 1: The Object-Oriented Systems Development Environment Object-Oriented Systems Analysis and Design Joey F. George, Dinesh.
1 CHAPTER 4 Complexity of Decision Making. 2 The Principle of Choice What criteria to use? Best solution? Good enough solution? Decision Support Systems.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang1-1 Turban, Aronson, and Liang Decision.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 6-1 Chapter 6 Decision Support System Development.
© 2008 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.
Chapter 2: Foundations and Technologies for Decision Making
Decision Support System by Simulation Model (Ajarn Chat Chuchuen)1 CHAPTER 1 Introduction to Decision Support System.
SPK : MODEL DAN PENDUKUNG
Chapter 4 Modeling and Analysis
Intelligent Systems Development
Decision Making, Systems, Modeling, and Support
Decision Support Systems Course
MANAGEMENT RICHARD L. DAFT.
Chapter 2 Succeeding as a Systems Analyst
Chapter 2: Decision Making, Systems, Modeling, and Support
Chapter 2 Decision-Making Systems, Models, and Support
Implementing and Integrating Management Support Systems
SPK : MODEL DAN PENDUKUNG
B. Information Technology (IS) CISB434: Decision Support Systems
Chapter 2 Decision-Making Systems, Models, and Support
Decision Support Systems: An Overview
CHAPTER 9 (part a) BASIC INFORMATION SYSTEMS CONCEPTS
Foundations and technologies for decision making
Stumpf and Teague Object-Oriented Systems Analysis and Design with UML
Modeling and Analysis Tutorial
Chapter 12 Analyzing Semistructured Decision Support Systems
Chapter 1.
Stumpf and Teague Object-Oriented Systems Analysis and Design with UML
Presentation transcript:

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…