AS/NZS IEC 31010:2020
Risk management - Risk assessment techniques
Objective of this Standard is to provide guidance on the selection and application of techniques for assessing risk in a wide range of situations. The techniques are used to assist in making decisions where there is uncertainty, to provide information about particular risks and as part of a process for managing risk. The document provides summaries of a range of techniques, with references to other documents where the techniques are described in more detail. This Standard is identical with, and has been reproduced from, IEC 31010:2019 Risk management - Risk assessment techniques.
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AS/NZS IEC 31010:2020 Risk assessment techniques
English
CONTENTS
FOREWORD
INTRODUCTION
1 Scope
2 Normative references
3 Terms and definitions
4 Core concepts
4.1 Uncertainty
4.2 Risk
5 Uses of risk assessment techniques
6 Implementing risk assessment
6.1 Plan the assessment
6.1.1 Define purpose and scope of the assessment
6.1.2 Understand the context
6.1.3 Engage with stakeholders
6.1.4 Define objectives
6.1.5 Consider human, organizational and social factors
6.1.6 Review criteria for decisions
6.2 Manage information and develop models
6.2.1 General
6.2.2 Collecting information
6.2.3 Analysing data
6.2.4 Developing and applying models
6.3 Apply risk assessment techniques
6.3.1 Overview
6.3.2 Identifying risk
6.3.3 Determining sources, causes and drivers of risk
6.3.4 Investigating the effectiveness of existing controls
6.3.5 Understanding consequences, and likelihood
6.3.6 Analysing interactions and dependencies
6.3.7 Understanding measures of risk
6.4 Review the analysis
6.4.1 Verifying and validating results
6.4.2 Uncertainty and sensitivity analysis
6.4.3 Monitoring and review
6.5 Apply results to support decisions
6.5.1 Overview
6.5.2 Decisions about the significance of risk
6.5.3 Decisions that involve selecting between options
6.6 Record and report risk assessment process and outcomes
7 Selecting risk assessment techniques
7.1 General
7.2 Selecting techniques
Annex€A (informative)Categorization of techniques
A.1 Introduction to categorization of techniques
A.2 Application of categorization of techniques
A.3 Use of techniques during the ISO€31000 process
Annex€B (informative)Description of techniques
B.1 Techniques for eliciting views from stakeholders and experts
B.1.1 General
B.1.2 Brainstorming
B.1.3 Delphi technique
B.1.4 Nominal group technique
B.1.5 Structured or semi-structured interviews
B.1.6 Surveys
B.2 Techniques for identifying risk
B.2.1 General
B.2.2 Checklists, classifications and taxonomies
B.2.3 Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA)
B.2.4 Hazard and operability (HAZOP) studies
B.2.5 Scenario analysis
B.2.6 Structured what if technique (SWIFT)
B.3 Techniques for determining sources, causes and drivers of risk
B.3.1 General
B.3.2 Cindynic approach
B.3.3 Ishikawa analysis (fishbone) method
B.4 Techniques for analysing controls
B.4.1 General
B.4.2 Bow tie analysis
B.4.3 Hazard analysis and critical control points (HACCP)
B.4.4 Layers of protection analysis (LOPA)
B.5 Techniques for understanding consequences and likelihood
B.5.1 General
B.5.2 Bayesian analysis
B.5.3 Bayesian networks and influence diagrams
B.5.4 Business impact analysis (BIA)
B.5.5 Cause-consequence analysis (CCA)
B.5.6 Event tree analysis (ETA)
B.5.7 Fault tree analysis (FTA)
B.5.8 Human reliability analysis (HRA)
B.5.9 Markov analysis
B.5.10 Monte Carlo simulation
B.6 Techniques for analysing dependencies and interactions
B.6.1 Causal mapping
B.6.2 Cross impact analysis
B.7 Techniques that provide a measure of risk
B.7.1 Toxicological risk assessment
B.7.2 Value at risk (VaR)
B.7.3 Conditional value at risk (CVaR) or expected shortfall (ES)
B.8 Techniques for evaluating the significance of risk
B.8.1 General
B.8.2 As low as reasonably practicable (ALARP) and so far as is reasonably practicable (SFAIRP)
B.8.3 Frequency-number (F-N) diagrams
B.8.4 Pareto charts
B.8.5 Reliability centred maintenance (RCM)
B.8.6 Risk indices
B.9 Techniques for selecting between options
B.9.1 General
B.9.2 Cost/benefit analysis (CBA)
B.9.3 Decision tree analysis
B.9.4 Game theory
B.9.5 Multi-criteria analysis (MCA)
B.10 Techniques for recording and reporting
B.10.1 General
B.10.2 Risk registers
B.10.3 Consequence/likelihood matrix (risk matrix or heat map)
B.10.4 S-curves
Bibliography
Figures
Figure A.1 – Application of techniques in the ISO€31000 risk management process [3]
Figure B.1 – Example Ishikawa (fishbone) diagram
Figure B.2 – Example of Bowtie
Figure B.3 – A Bayesian network showing a simplified version of a realecological problem: modelling native fish populations in Victoria, Australia
Figure B.4 – Example of cause-consequence diagram
Figure B.5 – Example of event tree analysis
Figure B.6 – Example of fault tree
Figure B.7 – Example of Markov diagram
Figure B.8 – Example of dose response curve
Figure B.9 – Distribution of value
Figure B.10 – Detail of loss region VaR values
Figure B.11 – VaR and CVaR for possible loss portfolio
Figure B.12 – ALARP diagram
Figure B.13 – Sample F-N diagram
Figure B.14 – Example of a Pareto chart
Figure B.15 – Part example of table defining consequence scales
Figure B.16 – Part example of a likelihood scale
Figure B.17 – Example of consequence/likelihood matrix
Figure B.18 – Probability distribution function and cumulative distribution function
Tables
Table A.1 – Characteristics of techniques
Table A.2 – Techniques and indicative characteristics
Table A.3 – Applicability of techniques to the ISO€31000 process
Table B.1 – Examples of basic guidewords and their generic meanings
Table B.2 – Table of deficits for each stakeholder
Table B.3 – Table of dissonances between stakeholders
Table B.4 – Example of Markov matrix
Table B.5 – Examples of systems to which Markov analysis can be applied
Table B.6 – An example of RCM task selection
Table B.7 – Example of a game matrix
Previous versions
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AS/NZS IEC 31010:2020 Risk assessment techniques
English
CONTENTS
FOREWORD
INTRODUCTION
1 Scope
2 Normative references
3 Terms and definitions
4 Core concepts
4.1 Uncertainty
4.2 Risk
5 Uses of risk assessment techniques
6 Implementing risk assessment
6.1 Plan the assessment
6.1.1 Define purpose and scope of the assessment
6.1.2 Understand the context
6.1.3 Engage with stakeholders
6.1.4 Define objectives
6.1.5 Consider human, organizational and social factors
6.1.6 Review criteria for decisions
6.2 Manage information and develop models
6.2.1 General
6.2.2 Collecting information
6.2.3 Analysing data
6.2.4 Developing and applying models
6.3 Apply risk assessment techniques
6.3.1 Overview
6.3.2 Identifying risk
6.3.3 Determining sources, causes and drivers of risk
6.3.4 Investigating the effectiveness of existing controls
6.3.5 Understanding consequences, and likelihood
6.3.6 Analysing interactions and dependencies
6.3.7 Understanding measures of risk
6.4 Review the analysis
6.4.1 Verifying and validating results
6.4.2 Uncertainty and sensitivity analysis
6.4.3 Monitoring and review
6.5 Apply results to support decisions
6.5.1 Overview
6.5.2 Decisions about the significance of risk
6.5.3 Decisions that involve selecting between options
6.6 Record and report risk assessment process and outcomes
7 Selecting risk assessment techniques
7.1 General
7.2 Selecting techniques
Annex€A (informative)Categorization of techniques
A.1 Introduction to categorization of techniques
A.2 Application of categorization of techniques
A.3 Use of techniques during the ISO€31000 process
Annex€B (informative)Description of techniques
B.1 Techniques for eliciting views from stakeholders and experts
B.1.1 General
B.1.2 Brainstorming
B.1.3 Delphi technique
B.1.4 Nominal group technique
B.1.5 Structured or semi-structured interviews
B.1.6 Surveys
B.2 Techniques for identifying risk
B.2.1 General
B.2.2 Checklists, classifications and taxonomies
B.2.3 Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA)
B.2.4 Hazard and operability (HAZOP) studies
B.2.5 Scenario analysis
B.2.6 Structured what if technique (SWIFT)
B.3 Techniques for determining sources, causes and drivers of risk
B.3.1 General
B.3.2 Cindynic approach
B.3.3 Ishikawa analysis (fishbone) method
B.4 Techniques for analysing controls
B.4.1 General
B.4.2 Bow tie analysis
B.4.3 Hazard analysis and critical control points (HACCP)
B.4.4 Layers of protection analysis (LOPA)
B.5 Techniques for understanding consequences and likelihood
B.5.1 General
B.5.2 Bayesian analysis
B.5.3 Bayesian networks and influence diagrams
B.5.4 Business impact analysis (BIA)
B.5.5 Cause-consequence analysis (CCA)
B.5.6 Event tree analysis (ETA)
B.5.7 Fault tree analysis (FTA)
B.5.8 Human reliability analysis (HRA)
B.5.9 Markov analysis
B.5.10 Monte Carlo simulation
B.6 Techniques for analysing dependencies and interactions
B.6.1 Causal mapping
B.6.2 Cross impact analysis
B.7 Techniques that provide a measure of risk
B.7.1 Toxicological risk assessment
B.7.2 Value at risk (VaR)
B.7.3 Conditional value at risk (CVaR) or expected shortfall (ES)
B.8 Techniques for evaluating the significance of risk
B.8.1 General
B.8.2 As low as reasonably practicable (ALARP) and so far as is reasonably practicable (SFAIRP)
B.8.3 Frequency-number (F-N) diagrams
B.8.4 Pareto charts
B.8.5 Reliability centred maintenance (RCM)
B.8.6 Risk indices
B.9 Techniques for selecting between options
B.9.1 General
B.9.2 Cost/benefit analysis (CBA)
B.9.3 Decision tree analysis
B.9.4 Game theory
B.9.5 Multi-criteria analysis (MCA)
B.10 Techniques for recording and reporting
B.10.1 General
B.10.2 Risk registers
B.10.3 Consequence/likelihood matrix (risk matrix or heat map)
B.10.4 S-curves
Bibliography
Figures
Figure A.1 – Application of techniques in the ISO€31000 risk management process [3]
Figure B.1 – Example Ishikawa (fishbone) diagram
Figure B.2 – Example of Bowtie
Figure B.3 – A Bayesian network showing a simplified version of a realecological problem: modelling native fish populations in Victoria, Australia
Figure B.4 – Example of cause-consequence diagram
Figure B.5 – Example of event tree analysis
Figure B.6 – Example of fault tree
Figure B.7 – Example of Markov diagram
Figure B.8 – Example of dose response curve
Figure B.9 – Distribution of value
Figure B.10 – Detail of loss region VaR values
Figure B.11 – VaR and CVaR for possible loss portfolio
Figure B.12 – ALARP diagram
Figure B.13 – Sample F-N diagram
Figure B.14 – Example of a Pareto chart
Figure B.15 – Part example of table defining consequence scales
Figure B.16 – Part example of a likelihood scale
Figure B.17 – Example of consequence/likelihood matrix
Figure B.18 – Probability distribution function and cumulative distribution function
Tables
Table A.1 – Characteristics of techniques
Table A.2 – Techniques and indicative characteristics
Table A.3 – Applicability of techniques to the ISO€31000 process
Table B.1 – Examples of basic guidewords and their generic meanings
Table B.2 – Table of deficits for each stakeholder
Table B.3 – Table of dissonances between stakeholders
Table B.4 – Example of Markov matrix
Table B.5 – Examples of systems to which Markov analysis can be applied
Table B.6 – An example of RCM task selection
Table B.7 – Example of a game matrix
Previous versions
AS/NZS IEC 31010:2020
Online Library subscription information
Online library subscriptions provide a cost-effective solution for organisations of any size to access the latest standards, offering 24/7 access to a personalised catalogue. The service ensures subscribers have have the most up-to-date version of selected standards, incluing automatic updates for any amendments or versions. Pricing is dependent on the chosen standards and the number of concurrent users, with discounts applied from the standards PDF price. For customised subscriptions or further inquiries, contact the Online Library team.