Yuri Raydugin

Project Risk Management

• Gebundenes Buch

Produktbeschreibung

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.
Written by an experienced risk management professional
Reveals essential risk management methods for project teams and decision makers
Packed with training materials, models, and tools for project management professionals

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.

Produktdetails

• Wiley Corporate F&A
• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 400
• Erscheinungstermin: 10. September 2013
• Englisch
• Abmessung: 235mm x 157mm x 26mm
• Gewicht: 722g
• ISBN-13: 9781118482438
• ISBN-10: 1118482433
• Artikelnr.: 37328827

Autorenporträt

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.

Inhaltsangabe

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