Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty

• Autore: Raydugin Yuri G
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (399 pages)
• Disciplina: 658.155
• Nota di contenuto: Intro -- Preface -- References -- Contents -- Abbreviations -- Chapter 1: Introduction: Why and How This Book Has Been Written? -- References -- Chapter 2: Cornerstone Ideas, Concepts and Paradigms -- 2.1 Traditional Project Risk Management Paradigm: Standalone Risks and Predict-Then-Act Decision-Making Pattern -- 2.1.1 Predict-Then-Act Decision-Making Pattern -- 2.1.2 Traditional Definition of Risk -- 2.1.3 Additional Inconsistencies of the Traditional PRM and Departure from It -- 2.2 Nonlinear Project Risk Management Paradigm: Interacting Risks -- 2.2.1 Inconsistency of the Traditional PRM Paradigm in Complex Projects -- 2.2.2 A Project as a System -- 2.2.3 Risk Interactions in Complex Project Systems -- 2.2.4 Risk Definition for Complex Projects -- 2.2.5 Emergence of Non-linear Monte Carlo Methodology -- 2.2.6 Dynamics of Complex Projects as Complex Systems -- 2.3 When Predict-Then-Act Decision-Making Does Not Work? -- 2.3.1 Limits and Shortcomings of Predict-Then-Act Decision-Making Pattern -- 2.3.2 Essay on Economy and Structural Imbalances: Micro-Economy Vs. Macro-Economy Mindsets -- 2.3.3 What's in It for a Project Specialist?: Emergence of Monitor-and-Adapt Decision-Making Pattern -- 2.3.4 Assay on Systems Thinking -- 2.3.5 Some Previous Practical Examples -- 2.4 Shaping Monitor-and-Adapt Decision-Making -- 2.4.1 Essay on Mathematical Theory of Games -- 2.4.2 Decision Making Under Deep Uncertainty (DMDU) -- 2.4.3 Definition of Risk for the Monitor-and-Adapt Decision-Making Pattern -- 2.4.4 Model-Centric Concept of Future -- 2.4.5 Future-Based Project Uncertainty Taxonomy and Its Relevance to PRM -- 2.4.6 Overview of Deep Uncertainty Handling Methods -- 2.4.7 A Way Forward -- 2.5 Merging Traditional, Complexity and Deep Uncertainty Paradigms with Project Work Process -- 2.5.1 Limitations of the Traditional Project Work Process. ; 2.5.2 Dynamic Adaptive Project Work Process -- 2.6 Intent of this Book -- References -- Part I: Traditional PRM and Vicinities -- Chapter 3: Scoring Method -- 3.1 Basic Concepts Behind the Traditional PRM -- 3.1.1 Project Value Concept -- 3.1.2 Project Objectives -- 3.1.2.1 Quantifiable Project Objectives -- 3.1.2.2 Qualitative Project Objectives -- 3.1.2.3 Hard Vs. Soft Objectives Vs. Modelling -- 3.1.2.4 Reasonable Number of Project Objectives -- 3.1.3 Traditional Risk Definition -- 3.1.4 Project Uncertainty Parameters -- 3.1.4.1 Uncertainty of Impact -- 3.1.4.2 Uncertainty of Occurrence -- 3.1.4.3 Four Primary Risk Objects of the Traditional PRM -- 3.1.4.4 Uncertainty of Favourability -- 3.1.4.5 Uncertainty of Manageability -- 3.1.4.6 Uncertainty of Identification -- 3.1.4.7 Additional Terminology: (Un)Known-(Un)Knowns -- 3.1.4.8 PRM System to Handle Uncertainty Parameters -- 3.1.5 Role of Bias -- 3.1.5.1 Definitions and Types of Bias -- 3.1.5.2 Psychological Bias -- 3.1.5.3 Organizational Bias -- 3.1.5.4 Role of Bias in Selecting Wrong PRM Tools -- 3.1.5.5 Bias and Stretched Targets -- 3.1.6 PRM Fallacies -- 3.2 Traditional PRM Framework: Context and Requirements -- 3.2.1 Understanding PRM Context -- 3.2.2 Shaping PRM Requirements -- 3.2.2.1 Project Categories -- 3.2.2.2 Line-of-Sight Concept and Three PRM Integration Dimensions -- 3.2.2.3 Project Phase -- 3.2.2.4 PRM Deliverables -- 3.3 Traditional PRM Process -- 3.4 Traditional PRM Tools -- 3.4.1 Risk Breakdown Structure (RBS) -- 3.4.2 A Bowtie Diagram -- 3.4.2.1 Using the Traditional Bowtie Diagram for Risk Identification -- 3.4.2.2 Using Bowtie Diagram for Risk Addressing -- 3.4.2.3 Using Bowtie Diagram for Probability Assessments -- 3.4.3 Risk Assessment Matrix (RAM) -- 3.4.3.1 RAM for Scoring Risk Assessments -- 3.4.3.2 RAM for Risk Addressing -- 3.4.3.3 RAM for Risk Reporting. ; 3.4.4 Risk Register -- 3.4.5 PRM Plan -- 3.4.6 PRM Questionnaire -- 3.5 Business Case: Traditional PRM Application -- References -- Chapter 4: Linear Monte Carlo Methodology -- 4.1 Traditional Monte Carlo Framework: Context and Requirements -- 4.1.1 Two Traditional PRM Risk Assessment Methodologies: Scoring Vs. Monte Carlo -- 4.1.2 Versions of Sampling Methodology -- 4.1.3 History of Monte Carlo Methodology -- 4.1.4 Comparison of Monte Carlo Methodology Versions -- 4.1.5 Organizational Context of SCRA Implementation -- 4.1.6 Confidence Levels and Decision-Making Criteria -- 4.1.6.1 Pre-determined Confidence Levels -- 4.1.6.2 Stretches Targets -- 4.1.6.3 Project and Corporate Reserves -- 4.1.6.4 Joint Confidence Levels (JCL) -- 4.1.6.5 Unknown-Unknown Allowances -- 4.1.6.6 Contingency Drawdown -- 4.2 Traditional Monte Carlo Process -- 4.2.1 Plan -- 4.2.2 Prepare -- 4.2.2.1 Freezing Project Scope -- 4.2.2.2 Development of a Proxy Schedule -- 4.2.2.3 Developing of a Cost Estimate -- 4.2.2.4 Converting Existing Scoring Risk Register to Probabilistic (Monte Carlo) Risk Register -- 4.2.2.5 Templates for Weather Events and Environmental Protection Restrictions -- 4.2.3 Risk Mapping of Schedule Risks -- 4.2.4 Assess Before Addressing (As-Is) (Monte Carlo) -- 4.2.5 Factor in Addressing -- 4.2.6 Assess After Addressing (To-Be) (Monte Carlo) -- 4.2.7 Factor in General Uncertainties -- 4.2.8 Correlations -- 4.2.9 Validate Inputs -- 4.2.10 Build and Run Monte Carlo Model -- 4.2.11 Review Results -- 4.2.12 What-If Scenarios? -- 4.2.13 Develop and Run What-If Scenarios -- 4.2.14 Report -- 4.3 Traditional Monte Carlo Tools -- 4.3.1 L-SCRA Input Data Collection Templates -- 4.3.1.1 General Duration Uncertainties (Template T1) -- 4.3.1.2 General Cost Uncertainties (Template T2) -- 4.3.1.3 Schedule and Cost Uncertain Events (Template T3): Probabilistic Risk Register. ; 4.3.1.4 Weather Modelling (Template T4) -- 4.3.1.5 Environment-Protection Closure Windows (Template T5) -- 4.3.1.6 Resources (Template T6) -- 4.3.2 Monte Carlo Software Packages for L-SCRA Modelling -- 4.4 Business Case: Traditional Monte Carlo (L-SCRA) Modelling -- References -- Chapter 5: Phenomenological Methods -- 5.1 General Overview of Phenomenological Methods -- 5.2 Schedule Benchmarking -- 5.2.1 Organizational Framework of Benchmarking -- 5.2.2 Benchmarking Process -- 5.2.2.1 Plan -- 5.2.2.2 Establishing Discipline Duration Dictionaries (DDD) -- 5.2.2.3 Establishing Rate Tables -- 5.2.2.4 Merging DDD and RT with a Project WBS -- 5.2.2.5 Running Benchmarking Metrics -- 5.2.2.6 Benchmarking Result's Validation -- 5.2.2.7 Reporting -- 5.2.3 Benchmarking Tools -- 5.3 Parametric Cost Estimating -- 5.3.1 Organizational Framework of Parametric Cost Estimating -- 5.3.2 Parametric Cost Estimating Process -- 5.3.2.1 Plan -- 5.3.2.2 Model Definition -- 5.3.2.3 Data Collection -- 5.3.2.4 Data Normalization and Model Development -- 5.3.2.5 Model Testing -- 5.3.2.6 Cost Forecasting -- 5.3.2.7 Reporting -- 5.3.3 Parametric Cost Estimating Tools -- 5.3.4 Main Deliverables -- References -- Chapter 6: Risk-Based and Economic-Based Alternative's Selection (RBEBAS) -- 6.1 RBEBAS Framework: Context and Requirements -- 6.1.1 A Project as an Idea in FEL0 and FEL1 -- 6.1.2 RBEBAS Context in FEL2A -- 6.1.3 Risk Definition for Alternative's Selection -- 6.1.4 RBEBAS Organizational Requirements -- 6.1.5 Alternative's Selection beyond FEL2A -- 6.1.6 Role of Bias in RBEBAS -- 6.2 RBEBAS Process -- 6.2.1 Plan -- 6.2.2 Generate Alternatives -- 6.2.3 Formulate Alternatives -- 6.2.4 Identify, Relevant?, Reject -- 6.2.5 Assess As-Is, Plan Response, Assess To-Be -- 6.2.6 Risk Level Acceptable? and Reject -- 6.2.7 Develop NPV CF -- 6.2.8 Select Alternative with a Best NPV CF. ; 6.2.9 Reporting -- 6.3 RBEBAS Tools -- 6.3.1 Risk Breakdown Structure (RBS) for RBEBAS -- 6.3.2 Bowtie Diagram for RBEBAS -- 6.3.3 Risk Assessment Matrix (RAM) for RBEBAS -- 6.3.4 Risk Register for RBEBAS -- 6.4 Business Case: Using RBEBAS -- References -- Chapter 7: Cost-Escalation and Exchange-Rate Volatility Modelling -- 7.1 Cost-Escalation and Exchange-Rate Volatility Framework: Context and Requirements -- 7.1.1 Two Additional Cost Risk Contingencies -- 7.1.2 Three Cost-Escalation Modelling Methods -- 7.1.2.1 General-Inflation (GI) Modelling -- 7.1.2.2 Project-Cost-Structure (PCS) Modelling -- 7.1.2.3 Project-Cash-Flow (PCF) Modelling -- 7.1.3 Foundations of the PCF Method for Cost Escalation Modelling -- 7.1.4 Foundations of the PCF Method for Exchange-Rate Volatility Modelling -- 7.1.5 Upgrade of the PCF Method to Its Probabilistic (Monte Carlo) Version -- 7.1.6 Cash Flow Optimization to Reduce Cost Escalation and Exchange-Rate Volatility Contingencies -- 7.1.7 PCF Method Implementation Requirements -- 7.2 Cost-Escalation and Exchange-Rate Volatility Modelling Process -- 7.2.1 Plan -- 7.2.2 Probabilistic? -- 7.2.3 Cash Flow Statement -- 7.2.4 Marco-Economic Indices Selection -- 7.2.5 Contract Markups -- 7.2.6 Uncertainty Ranges -- 7.2.7 PCF Model Development -- 7.2.8 PCF Model Run -- 7.2.9 PCF Result's Review -- 7.2.10 What-If Scenarios? -- 7.2.11 What-If Scenario's Development -- 7.2.12 What-If Scenario's Runs -- 7.2.13 RBEBAS Implications -- 7.2.14 Reporting -- 7.3 Cost-Escalation and Exchange-Rate Volatility Modelling Tools -- 7.4 Business Case: Cost Escalation Modelling -- References -- Part II: Project System Complexity, Nonlinear PRM and Systems Dynamics -- Chapter 8: Projects as Systems -- 8.1 A Generic Structure of Projects as Systems: Three Interacting Subsystems -- 8.1.1 Four Project System Complexity Types. ; 8.1.2 Three Types of Part's Interactions.
• Titolo autorizzato: Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty
• ISBN: 9783031569883; 9783031569876
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910865280803321
• Lo trovi qui: Univ. Federico II