Details

Project Risk Management

Essential Methods for Project Teams and Decision Makers
Wiley Corporate F&A 1. Aufl.

von: Yuri Raydugin
61,99 €
Verlag:	Wiley
Format:	EPUB
Veröffentl.:	15.08.2013
ISBN/EAN:	9781118746134
Sprache:	englisch
Anzahl Seiten:	400

In den Warenkorb

Als Gutschein

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

Titelbeschreibung

An easy to implement, practical, and proven risk management methodology for project managers and decision makers Drawing from the author's work with several major and mega capital projects for Royal Dutch Shell, TransCanada Pipelines, TransAlta, Access Pipeline, MEG Energy, and SNC-Lavalin, Project Risk Management: Essential Methods for Project Teams and Decision Makers reveals how to implement a consistent application of risk methods, including probabilistic methods. It is based on proven training materials, models, and tools developed by the author to make risk management plans accessible and easily implemented. <ul> <li>Written by an experienced risk management professional</li> <li>Reveals essential risk management methods for project teams and decision makers</li> <li>Packed with training materials, models, and tools for project management professionals</li> </ul> Risk Management has been identified as one of the nine content areas for Project Management Professional (PMP®) certification. Yet, it remains an area that can get bogged down in the real world of project management. Practical and clearly written, Project Risk Management: Essential Methods for Project Teams and Decision Makers equips project managers and decision makers with a practical understanding of the basics of risk management as they apply to project management. (PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.)

Inhaltsverzeichnis

Foreword xv Preface xix Acknowledgments xxix Part I: Fundamental Uncertainty of a Project Outcome Chapter 1: Nature of Project Uncertainties 3 Phases of Project Development and Project Objectives 4 Quest for Predictability of Project Outcome 5 Sources and Types of Deviations from Project Objectives 7 Key Objects of Risk (or Uncertainty) Management: Do We Really Know What We Try to Manage? 15 Uncertainty Exposure Changers 24 Conclusion 26 Notes 26 Chapter 2: Main Components of a Risk Management System 29 Risk Management Plan 30 Organizational Framework 32 Risk Management Process 39 Risk Management Tools 52 Conclusion 59 Notes 60 Chapter 3: Adequacy of Methods to Assess Project Uncertainties 61 Review of Deterministic Qualitative (Scoring) Methods 62 Review of Deterministic Quantitative Methods 68 Review of Probabilistic Qualitative Methods 76 Review of Probabilistic Quantitative Methods 80 Conclusion 87 Notes 88 Part II: Deterministic Methods Chapter 4: Uncertainty Identification 91 When Risk Management Becomes Boring 92 Three Dimensions of Risk Management and Uncertainty Identification 93 Risk Identification Workshops 95 Sources of Uncertainties and Risk Breakdown Structure 98 Bowtie Diagrams for Uncertainty Identification 101 Three-Part Uncertainty Naming 107 Role of Bias in Uncertainty Identification 110 Room for Unknown Unknowns 113 Conclusion 118 Notes 118 Chapter 5: Risk Assessment and Addressing 119 Developing a Risk Assessment Matrix 120 Using a Risk Assessment Matrix for Assessment As-Is 129 Five Addressing Strategies 136 Assessment after Addressing 141 Project Execution through Risk Addressing (PETRA) 145 Role of Bias in Uncertainty Assessment 147 Conclusion 149 Notes 150 Chapter 6: Response Implementation and Monitoring 151 Merging Risk Management with Team Work Plans 152 Monitor and Appraise 153 When Uncertainties Should Be Closed 154 When Should Residual Uncertainties Be Accepted? 155 Conclusion 155 Note 156 Chapter 7: Risk Management Governance and Organizational Context 157 Risk Management Deliverables for Decision Gates 158 Ownership of Uncertainties and Addressing Actions 160 Management of Supercritical Risks 162 Risk Reviews and Reporting 164 Bias and Organizational Context 168 Conclusion 175 Notes 175 Chapter 8: Risk Management Tools 177 Three Dimensions of Risk Management and Structure of the Uncertainty Repository 178 Risk Database Software Packages 181 Detailed Design of a Risk Register Template in MS Excel 184 Commercial Tools for Probabilistic Risk Analyses 185 Conclusion 191 Notes 192 Chapter 9: Risk-Based Selection of Engineering Design Options 193 Criteria for Engineering Design Option Selection 194 Scoring Risk Method for Engineering Design Option Selection 195 Decision Tree for Engineering Design Option Selection (Controlled Options) 199 Conclusion 202 Note 202 Chapter 10: Addressing Uncertainties through Procurement 203 Sources of Procurement Risks 204 Quantitative Bid Evaluation 207 Package Risk Management Post-Award 209 Conclusion 209 Notes 210 Chapter 11: Cost Escalation Modeling 211 Overview of the Cost Escalation Approach 211 Example of Cost Escalation Modeling 219 Selecting the Right Time to Purchase 223 Conclusion 224 Notes 224 Part III: Probabilistic Monte Carlo Methods Chapter 12: Applications of Monte Carlo Methods in Project Risk Management 227 Features, Value, and Power of Monte Carlo Methods 228 Integration of Deterministic and Probabilistic Assessment Methods 230 Uncertainty Objects Influencing Outcome of Probabilistic Analyses 231 Origin and Nature of Uncertainties 233 Role of Correlations in Cost and Schedule Risk Analyses 240 Project Cost Reserve 242 Project Schedule Reserve 244 Anatomy of Input Distributions 246 Probabilistic Branching 250 Merge Bias as an Additional Reason Why Projects Are Often Late 251 Integrated Cost and Schedule Risk Analysis 253 Including Unknown-Unknown Allowance in Probabilistic Models 256 Conclusion 259 Notes 260 Chapter 13: Preparations for Probabilistic Analysis 261 Typical Workflows of Probabilistic Cost and Schedule Analyses 262 Planning Monte Carlo Analysis 264 Baselines and Development of Proxies 267 Why Using Proxies is the Right Method 271 Mapping of Uncertain Events 272 Building and Running Monte Carlo Models 277 Conclusion 277 Notes 278 Chapter 14: Using Outputs of Monte Carlo Analyses in Decision Making 279 Anatomy of Output Distributions 280 Overall Project Uncertainty and Confidence Levels of Baselines 283 Project Reserve Criteria 287 Uncertainty of Cost Outcome and Classes of Base Estimates 291 Cost Reserve Drawdown 296 Sensitivity Analysis 298 Using What-if Scenarios for Advanced Sensitivity Analysis 304 Are We Ready for Construction, Logistics, or Turnaround Windows? 305 Validating Results and Closing Probabilistic Analysis 306 Conclusion 308 Notes 308 Part IV: Risk Management Case Study: Project Curiosity Chapter 15: Putting Together the Project Curiosity Case Study 311 Scope of the Case Study 312 Project Curiosity Baselines 313 Project Risk Management System Adopted by Project Curiosity 319 Overview of Project Uncertainty Exposure of Project Curiosity 326 Templates for Probabilistic Cost and Schedule Analyses 330 Building and Running Project Probabilistic Cost and Schedule Models 331 Three What-If Scenarios 333 Conclusion 334 Notes 335 Chapter 16: Decision Making 337 Key Points of the Probabilistic Analysis Report 338 Decision Gate Review Board Findings and Recommendations 350 Conclusion 352 Note 353 About the Author 355 Index 357

Autorenportrait

DR. YURI RAYDUGIN is an experienced risk management professional who has developed and implemented successful risk systems for several major energy companies, including Royal Dutch Shell, SNC-Lavalin, and TransCanada Pipelines. He provides risk management coaching and training as well as risk assessment services and has published white papers and articles for a number of journals, including the International Journal of Risk and Contingency Management.

Back cover copy

Risk management has been identified as one of the nine content areas for Project Management Professional (PMP) certification. Yet, project risk management remains an area that is often bogged down by inconsistent methods and a sense of general confusion as to what methods should be applied, where, and how. Written to provide a practical understanding of the basics of risk management, Project Risk Management presents an easy-to-implement, practical, and proven risk management methodology for today's project managers and decision makers. Drawing on author Yuri Raydugin's risk management experience in almost two dozen major and mega capital projects, Project Risk Management shows you how to employ a consistent application of risk methods, including probabilistic methods. Dr. Raydugin illustrates existing training materials, models, and tools he has developed over the years to make risk management accessible and easy to execute. Written at an advanced level that doesn't get bogged down by mathematics, Project Risk Management balances technical information with accessible language to simplify the assessment of the uncertainties in a project. Conveniently laid out in four accessible parts, Project Risk Management examines: <ul> <li>The Nature of Project Uncertainties</li> <li>The Three Dimensions of Risk Management</li> <li>The Risk Management Organizational Framework and Process</li> <li>Tools to Support the Organizational Framework and Process</li> <li>Risk Workshops, Reviews, and Reporting</li> <li>The Structure of a Project Risk Management Plan</li> <li>Project Execution through Risk Addressing (PETRA Technique)</li> <li>The Role of "Broiler Black Swans" and Unknown Unknowns</li> <li>The Role of Psychological and Organizational Bias</li> <li>The Selection of Engineering Design Options Using Risk Management</li> <li>Addressing Project Uncertainties through Procurement</li> <li>Cost Escalation Modeling</li> <li>Integrated Cost and Schedule Risk Analysis (CSRA)</li> <li>Building and Running Monte Carlo Models</li> <li>Criteria for Cost and Schedule Project Reserves</li> <li>Key Points of a Probabilistic CSRA Report</li> <li>Project Cost Uncertainty and AACE Classes</li> <li>Cost Reserve Drawdown</li> <li>Risk-Based Informed Decision Making</li> </ul> Project Risk Management empowers you with the knowledge and skills to conduct effective risk management processes while avoiding the many pitfalls inherent in project management.