E-Book, Englisch, 352 Seiten
Koller Risk Assessment and Decision Making in Business and Industry
2. Auflage 2005
ISBN: 978-1-4200-3505-6
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
A Practical Guide, Second Edition
E-Book, Englisch, 352 Seiten
ISBN: 978-1-4200-3505-6
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Building upon the technical and organizational groundwork presented in the first edition, Risk Assessment and Decision Making in Business and Industry: A Practical Guide, Second Edition addresses the many aspects of risk/uncertainty (R/U) process implementation.
This comprehensive volume covers four broad aspects of R/U: general concepts, implementation processes, technical aspects, and examples of application. Each section provides practical guidance, combining technical information with advice on how to implement R/U techniques and processes in real-world corporate environments. Following an examination of general principles involved in quantitatively assessing risks and their impact on value, the book describes the two main probabilistic measures of project value - Expected Value of Success (EVS) and the Expected Value for the Portfolio (EVP). The text clearly demonstrates how these metrics are used in individual-project and portfolio management.
By presenting concepts in layman's terms and fully integrating advice related to technical and human characteristics of R/U-related corporate life, this book serves as a complete primer for professionals in any business environment.
What's New in the Second Edition:
- Provides guidance for implementation of R/U processes in modern corporations
- Offers a crucial breakthrough by defining the terms "risk" and "uncertainty" in ways that can be applied in all aspects of science and business
- Explores real-world impediments to process change and implementation
- Addresses R/U from a corporate decision-maker's perspective, detailing how to employ R/U to set budgets, manage portfolios, value investments, and execute other critical tasks
Zielgruppe
Statisticians, business, finance, and economic professionals, and engineers
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
INTRODUCTION
What Companies Really Want to Do
Practical Risk Assessment
You Can Do It
ABOUT RISK AND UNCERTAINTY
Various Views on the Subject - Einstein Was Never Going to Get
There
Definitions of Risk and Uncertainty
Two Values - The Expected Value of Success (EVS) and the Expected
Value for the Portfolio (EVP)
Risk Assessment and Risk Management
What Questions Do I Ask and How Do I Integrate the Information?
RISK ASSESSMENT: GENERAL CHARACTERISTICS AND
BENEFITS
Why Risk Assessment?
Common Language
Holistic Thinking
Awareness
Consider Range of Possibilities
Establish Probabilities
Communication with Customers and the Public
Probabilistic Branching
Relationships between Variables
Linking of Disciplines
Checklist - Do Not Take It for Granted
Updating Estimates
To What Types of Problems Can Risk Assessment Be Applied?
RISK ASSESSMENT - A PROCESS
Risk Assessment - The Process
The Time It Takes to Do It Right, and When to Get Started
What Is Typically Done
What Is Not Typically Done
What to Provide
Size Does Not Matter (Not That I Was Worried about That)
Stakeholders
THE PERCEPTION FROM WITHIN - WHY THIS CAN BE
SO DARN HARD TO IMPLEMENT
Simple Resistance to Change and Momentum of Old Ways
Learning How the Organization Really Works
Practitioners Who Have Been Doing It for Years Are Difficult to
Change - Newcomers Are Easier to Deal With
Not Invented Here
Instant Access to Executives - If You Are from Outside, You Are
Smarter/Better
Turf Wars
Experts Who Are Not
Management That Has Limited Appreciation and the Deterministic
Mindset
Coming from the Right Place
Establishing Credibility So You Are Not Just Another Voice in the
Wilderness
Time for Preparation of the Organization - Who Benefits?
Ramifications of Implementing a Probabilistic Risk System
For This to Be Effective, Every Part of the Company Must Participate
Not Just One Time - This Must Be Done Over and Over, Like a Diet
CONSISTENCY - THE KEY TO A RISK PROCESS
Biggest Bang from Assessing Multiple Opportunities
Type Consensus Models
Common Measure
Risk Assessment Vision
Sometimes Better to Be Consistent Than to Be Right
Locking the Model
Users Will Game the System - The Risk Police
Databasing Inputs and Outputs
Numbers That Reach Decision Makers
Forums
Language
Risk as a Corporate Function
COMMUNICATION
Communication - Just One Shot
Communication - Why Bother?
Know Your Clients
Focus on Impact and Mitigation
Mitigation Is Not Enough
Killing Projects
Diplomatically Handle Winners and Losers
Communicating the Value of Risk Assessment
It Starts at the Top
Create Success Story Presentation
Web Stuff
BUILDING A CONSENSUS MODEL
What Is the Question? - Most of the Time and Effort
Consensus Model
Group Dynamics
Write It Down
Sort It Out
Group Dynamics Again
Units
Overarching Categories
No Such Thing as a Universal Model
Difficult to Get People's Time to Go Through All This
BUILD A CONTRIBUTING FACTOR DIAGRAM
The Contributing Factor Diagram - Getting Started
Identify and Define Variables
Ask the Right Question
Double-Dipping
Double-Dipping and Counting the Chickens
Fixing the Double-Dipping and Counting the Chickens Problems
CFD-Building Example
Short List of Hints for Building a CFD
EDUCATION - CRITICAL AT THREE LEVELS
Education for Management
Introductory Class for Risk-Model Builders
Advanced Training for Risk-Model Builders
Organizational Attitude and Training Centers
Time Demands and Organization of the Education Effort
Difference between Education and Training
RISK ASSESSMENT TECHNOLOGIES
Different Approaches
Discriminant Function Analysis
Bayesian Analysis
Decision Trees
Factor Analysis
Neural Nets
The Risk Matrix
Risk Registers
MONTE CARLO ANALYSIS
A Bit of History
What Is It Good For?
Simple Monte Carlo Example
Buckets
How Many Random Comparisons Are Enough?
Output from Monte Carlo Analysis - The Frequency and Cumulative
Frequency Plots
Interpreting Cumulative Frequency Plots
Combining Monte Carlo Output Curves
DECISIONS AND DISTRIBUTIONS
Decisions
Just What Is a Distribution?
Distributions - How to Approach Them
Symmetrical Distributions
Skewed Distributions
Spiked Distributions
Flat Distributions
Truncated Distributions
Discrete Distributions
Bimodal Distributions
Reading Data from a File
Peakedness
Triangular Distributions
Specific Distribution Types
Speaking Distributions
Flexibility in the Decision-Making Process
CHANCE OF FAILURE
Chance of Failure - What Is It?
Failure of a Risk Component
Chance of Failure that Does Not Affect an Input Distribution
Incorporating Chance of Failure in a Plot of Cumulative Frequency
Another Reason for Chance of Failure
The Inserting Zeroes Work-Around
Chance of Failure and Multiple Output Variables
A Clear Example of the Impact of Chance of Failure
TIME-SERIES ANALYSIS AND DEPENDENCE
Introduction to Time-Series Analysis and Dependence
Time-Series Analysis - Why?
Time-Series Analysis - How?
Time-Series Analysis - Results
Time-Series Analysis That Is Not
Some Things to Consider
Dependence - What Is It?
Independent and Dependent Variables
Degree of Dependence
Multiple Dependencies and Circular Dependence
Effect of Dependence on Monte Carlo Output
Dependence - It Is Ubiquitous
RISK-WEIGHTED VALUES AND SENSITIVITY ANALYSIS
Introduction to Risk-Weighted Values and Sensitivity Analysis
Risk-Weighted Values - Why?
Risk-Weighted Values - How?
The Net Risk-Weighted Value
The Economic Risk-Weighted Resource (ERWR) Value
The Expected Value of Success (EVS) and the Expected Value for the
Portfolio (EVP)
Risk-Weighted Values - The Answer
Sensitivity Analysis - Why?
Sensitivity Analysis - How?
Sensitivity Analysis - Results
WHAT COMPANIES REALLY WANT TO DO
The Portfolio Effect - Sometimes You Just Do Not Get It
Estimate Budgets
Estimate Project Value - Two Types: The Expected Value of Success
(EVS) and the Expected Value for the Portfolio (EVP)
Ask the Right Questions to Determine the Quality of the Information
Being Conveyed
RISK ASSESSMENT EXAMPLES
Introduction
Qualitative Model
Semi-Quantitative Model
Mini Time-Series Model
Fate-Transport (Process/Health) Model
Decision-Tree Conversion
Legal Model
Comprehensive Risk Assessment Example
EVS/EVP Example
