Business risk and simulation modelling in practice : using excel, VBA and @RISK /: using excel, VBA and @RISK. (2015)

• Record Type: Book
• Further Information: Note: Michael Rees.
• Authors: Rees, Michael, 1964-
• Contents: Preface xvii About the Author xxiii About the Website xxv PART I An Introduction to Risk Assessment – Its Uses, Processes, Approaches, Benefits and Challenges CHAPTER 1 The Context and Uses of Risk Assessment 3 1.1 Risk Assessment Examples 3 1.1.1 Everyday Examples of Risk Management 4 1.1.2 Prominent Risk Management Failures 5 1.2 General Challenges in Decision-Making Processes 7 1.2.1 Balancing Intuition with Rationality 7 1.2.2 The Presence of Biases 9 1.3 Key Drivers of the Need for Formalised Risk Assessment in Business Contexts 14 1.3.1 Complexity 14 1.3.2 Scale 15 1.3.3 Authority and Responsibility to Identify and Execute Risk-Response Measures 16 1.3.4 Corporate Governance Guidelines 16 1.3.5 General Organisational Effectiveness and the Creation of Competitive Advantage 18 1.3.6 Quantification Requirements 18 1.3.7 Reflecting Risk Tolerances in Decisions and in Business Design 19 1.4 The Objectives and Uses of General Risk Assessment 19 1.4.1 Adapt and Improve the Design and Structure of Plans and Projects 20 1.4.2 Achieve Optimal Risk Mitigation within Revised Plans 20 1.4.3 Evaluate Projects, Set Targets and Reflect Risk Tolerances in Decision-Making 21 1.4.4 Manage Projects Effectively 21 1.4.5 Construct, Select and Optimise Business and Project Portfolios 22 1.4.6 Support the Creation of Strategic Options and Corporate Planning 25 CHAPTER 2 Key Stages of the General Risk Assessment Process 29 2.1 Overview of the Process Stages 29 2.2 Process Iterations 30 2.3 Risk Identification 32 2.3.1 The Importance of a Robust Risk Identification Step 32 2.3.2 Bringing Structure into the Process 32 2.3.3 Distinguishing Variability from Decision Risks 34 2.3.4 Distinguishing Business Issues from Risks 34 2.3.5 Risk Identification in Quantitative Approaches: Additional Considerations 35 2.4 Risk Mapping 35 2.4.1 Key Objectives 35 2.4.2 Challenges 35 2.5 Risk Prioritisation and Its Potential Criteria 36 2.5.1 Inclusion/Exclusion 36 2.5.2 Communications Focus 37 2.5.3 Commonality and Comparison 38 2.5.4 Modelling Reasons 39 2.5.5 General Size of Risks, Their Impact and Likelihood 39 2.5.6 Influence: Mitigation and Response Measures, and Management Actions 40 2.5.7 Optimising Resource Deployment and Implementation Constraints 41 2.6 Risk Response: Mitigation and Exploitation 42 2.6.1 Reduction 42 2.6.2 Exploitation 42 2.6.3 Transfer 42 2.6.4 Research and Information Gathering 43 2.6.5 Diversification 43 2.7 Project Management and Monitoring 44 CHAPTER 3 Approaches to Risk Assessment and Quantification 45 3.1 Informal or Intuitive Approaches 46 3.2 Risk Registers without Aggregation 46 3.2.1 Qualitative Approaches 46 3.2.2 Quantitative Approaches 48 3.3 Risk Register with Aggregation (Quantitative) 50 3.3.1 The Benefits of Aggregation 50 3.3.2 Aggregation of Static Values 51 3.3.3 Aggregation of Risk-Driven Occurrences and Their Impacts 52 3.3.4 Requirements and Differences to Non-Aggregation Approaches 54 3.4 Full Risk Modelling 56 3.4.1 Quantitative Aggregate Risk Registers as a First Step to Full Models 56 CHAPTER 4 Full Integrated Risk Modelling: Decision-Support Benefits 59 4.1 Key Characteristics of Full Models 59 4.2 Overview of the Benefits of Full Risk Modelling 61 4.3 Creating More Accurate and Realistic Models 62 4.3.1 Reality is Uncertain: Models Should Reflect This 62 4.3.2 Structured Process to Include All Relevant Factors 63 4.3.3 Unambiguous Approach to Capturing Event Risks 63 4.3.4 Inclusion of Risk Mitigation and Response Factors 66 4.3.5 Simultaneous Occurrence of Uncertainties and Risks 66 4.3.6 Assessing Outcomes in Non-Linear Situations 67 4.3.7 Reflecting Operational Flexibility and Real Options 67 4.3.8 Assessing Outcomes with Other Complex Dependencies 71 4.3.9 Capturing Correlations, Partial Dependencies and Common Causalities 73 4.4 Using the Range of Possible Outcomes to Enhance Decision-Making 74 4.4.1 Avoiding “The Trap of the Most Likely” or Structural Biases 76 4.4.2 Finding the Likelihood of Achieving a Base Case 78 4.4.3 Economic Evaluation and Reflecting Risk Tolerances 82 4.4.4 Setting Contingencies, Targets and Objectives 83 4.5 Supporting Transparent Assumptions and Reducing Biases 84 4.5.1 Using Base Cases that are Separate to Risk Distributions 85 4.5.2 General Reduction in Biases 85 4.5.3 Reinforcing Shared Accountability 85 4.6 Facilitating Group Work and Communication 86 4.6.1 A Framework for Rigorous and Precise Work 86 4.6.2 Reconcile Some Conflicting Views 86 CHAPTER 5 Organisational Challenges Relating to Risk Modelling 87 5.1 “We Are Doing It Already” 87 5.1.1 “Our ERM Department Deals with Those Issues” 88 5.1.2 “Everybody Should Just Do Their Job Anyway!” 88 5.1.3 “We Have Risk Registers for All Major Projects” 89 5.1.4 “We Run Sensitivities and Scenarios: Why Do More?” 89 5.2 “We Already Tried It, and It Showed Unrealistic Results” 89 5.2.1 “All Cases Were Profitable” 90 5.2.2 “The Range of Outcomes Was Too Narrow” 90 5.3 “The Models Will Not Be Useful!” 91 5.3.1 “We Should Avoid Complicated Black Boxes!” 91 5.3.2 “All Models Are Wrong, Especially Risk Models!” 91 5.3.3 “Can You Prove that It Even Works?” 92 5.3.4 “Why Bother to Plan Things that Might Not Even Happen?” 93 5.4 Working Effectively with Enhanced Processes and Procedures 93 5.4.1 Selecting the Right Projects, Approach and Decision Stage 93 5.4.2 Managing Participant Expectations 95 5.4.3 Standardisation of Processes and Models 95 5.5 Management Processes, Culture and Change Management 96 5.5.1 Integration with Decision Processes 96 5.5.2 Ensuring Alignment of Risk Assessment and Modelling Processes 97 5.5.3 Implement from the Bottom Up or the Top Down? 98 5.5.4 Encouraging Issues to Be Escalated: Don’t Shoot the Messenger! 99 5.5.5 Sharing Accountability for Poor Decisions 99 5.5.6 Ensuring Alignment with Incentives and Incentive Systems 100 5.5.7 Allocation and Ownership of Contingency Budgets 101 5.5.8 Developing Risk Cultures and Other Change Management Challenges 102 PART II The Design of Risk Models – Principles, Processes and Methodology CHAPTER 6 Principles of Simulation Methods 107 6.1 Core Aspects of Simulation: A Descriptive Example 107 6.1.1 The Combinatorial Effects of Multiple Inputs and Distribution of Outputs 107 6.1.2 Using Simulation to Sample Many Diverse Scenarios 110 6.2 Simulation as a Risk Modelling Tool 112 6.2.1 Distributions of Input Values and Their Role 113 6.2.2 The Effect of Dependencies between Inputs 114 6.2.3 Key Questions Addressable using Risk-Based Simulation 114 6.2.4 Random Numbers and the Required Number of Recalculations or Iterations 115 6.3 Sensitivity and Scenario Analysis: Relationship to Simulation 116 6.3.1 Sensitivity Analysis 116 6.3.2 Scenario Analysis 119 6.3.3 Simulation using DataTables 121 6.3.4 GoalSeek 121 6.4 Optimisation Analysis and Modelling: Relationship to Simulation 122 6.4.1 Uncertainty versus Choice 122 6.4.2 Optimisation in the Presence of Risk and Uncertainty 129 <p&g
• Edition: 1st
• Publisher Details: Hoboken, New Jersey : John Wiley & Sons, Inc
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 658.1550285554; Risk management -- Computer simulation; Risk management -- Data processing
• Languages: English
• ISBNs: 9781118904046
• Related ISBNs: 9781118904039
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.