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BS EN IEC 31010:2019

BS EN IEC 31010:2019

$215.11

Risk management. Risk assessment techniques

Published By Publication Date Number of Pages
BSI 2019 130
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This International Standard provides 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.

PDF Catalog

PDF Pages PDF Title
2 undefined
5 Annex ZA(normative)Normative references to international publicationswith their corresponding European publications
7 English
CONTENTS
11 FOREWORD
13 INTRODUCTION
14 1 Scope
2 Normative references
3 Terms and definitions
15 4 Core concepts
4.1 Uncertainty
16 4.2 Risk
5 Uses of risk assessment techniques
17 6 Implementing risk assessment
6.1 Plan the assessment
6.1.1 Define purpose and scope of the assessment
18 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
19 6.1.6 Review criteria for decisions
21 6.2 Manage information and develop models
6.2.1 General
6.2.2 Collecting information
6.2.3 Analysing data
22 6.2.4 Developing and applying models
23 6.3 Apply risk assessment techniques
6.3.1 Overview
24 6.3.2 Identifying risk
6.3.3 Determining sources, causes and drivers of risk
25 6.3.4 Investigating the effectiveness of existing controls
6.3.5 Understanding consequences, and likelihood
27 6.3.6 Analysing interactions and dependencies
6.3.7 Understanding measures of risk
30 6.4 Review the analysis
6.4.1 Verifying and validating results
6.4.2 Uncertainty and sensitivity analysis
31 6.4.3 Monitoring and review
6.5 Apply results to support decisions
6.5.1 Overview
32 6.5.2 Decisions about the significance of risk
6.5.3 Decisions that involve selecting between options
33 6.6 Record and report risk assessment process and outcomes
7 Selecting risk assessment techniques
7.1 General
34 7.2 Selecting techniques
36 Annex A (informative)Categorization of techniques
A.1 Introduction to categorization of techniques
A.2 Application of categorization of techniques
Tables
Table A.1 – Characteristics of techniques
37 Table A.2 – Techniques and indicative characteristics
42 A.3 Use of techniques during the ISO 31000 process
Figures
Figure A.1 – Application of techniques in the ISO 31000 risk management process [3]
43 Table A.3 – Applicability of techniques to the ISO 31000 process
45 Annex B (informative)Description of techniques
B.1 Techniques for eliciting views from stakeholders and experts
B.1.1 General
B.1.2 Brainstorming
47 B.1.3 Delphi technique
48 B.1.4 Nominal group technique
49 B.1.5 Structured or semi-structured interviews
50 B.1.6 Surveys
51 B.2 Techniques for identifying risk
B.2.1 General
52 B.2.2 Checklists, classifications and taxonomies
54 B.2.3 Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA)
55 B.2.4 Hazard and operability (HAZOP) studies
56 Table B.1 – Examples of basic guidewords and their generic meanings
57 B.2.5 Scenario analysis
59 B.2.6 Structured what if technique (SWIFT)
60 B.3 Techniques for determining sources, causes and drivers of risk
B.3.1 General
61 B.3.2 Cindynic approach
62 Table B.2 – Table of deficits for each stakeholder
Table B.3 – Table of dissonances between stakeholders
63 B.3.3 Ishikawa analysis (fishbone) method
64 Figure B.1 – Example Ishikawa (fishbone) diagram
65 B.4 Techniques for analysing controls
B.4.1 General
B.4.2 Bow tie analysis
66 Figure B.2 – Example of Bowtie
67 B.4.3 Hazard analysis and critical control points (HACCP)
69 B.4.4 Layers of protection analysis (LOPA)
71 B.5 Techniques for understanding consequences and likelihood
B.5.1 General
B.5.2 Bayesian analysis
73 B.5.3 Bayesian networks and influence diagrams
74 Figure B.3 – A Bayesian network showing a simplified version of a realecological problem: modelling native fish populations in Victoria, Australia
75 B.5.4 Business impact analysis (BIA)
77 B.5.5 Cause-consequence analysis (CCA)
78 Figure B.4 – Example of cause-consequence diagram
79 B.5.6 Event tree analysis (ETA)
80 Figure B.5 – Example of event tree analysis
81 B.5.7 Fault tree analysis (FTA)
82 Figure B.6 – Example of fault tree
83 B.5.8 Human reliability analysis (HRA)
84 B.5.9 Markov analysis
85 Figure B.7 – Example of Markov diagram
Table B.4 – Example of Markov matrix
86 B.5.10 Monte Carlo simulation
Table B.5 – Examples of systems to which Markov analysis can be applied
90 B.6 Techniques for analysing dependencies and interactions
B.6.1 Causal mapping
92 B.6.2 Cross impact analysis
94 B.7 Techniques that provide a measure of risk
B.7.1 Toxicological risk assessment
Figure B.8 – Example of dose response curve
96 B.7.2 Value at risk (VaR)
Figure B.9 – Distribution of value
Figure B.10 – Detail of loss region VaR values
98 B.7.3 Conditional value at risk (CVaR) or expected shortfall (ES)
Figure B.11 – VaR and CVaR for possible loss portfolio
99 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)
100 Figure B.12 – ALARP diagram
101 B.8.3 Frequency-number (F-N) diagrams
102 Figure B.13 – Sample F-N diagram
103 B.8.4 Pareto charts
Figure B.14 – Example of a Pareto chart
105 B.8.5 Reliability centred maintenance (RCM)
106 Table B.6 – An example of RCM task selection
107 B.8.6 Risk indices
108 B.9 Techniques for selecting between options
B.9.1 General
109 B.9.2 Cost/benefit analysis (CBA)
111 B.9.3 Decision tree analysis
112 B.9.4 Game theory
113 Table B.7 – Example of a game matrix
114 B.9.5 Multi-criteria analysis (MCA)
116 B.10 Techniques for recording and reporting
B.10.1 General
117 B.10.2 Risk registers
118 B.10.3 Consequence/likelihood matrix (risk matrix or heat map)
119 Figure B.15 – Part example of table defining consequence scales
Figure B.16 – Part example of a likelihood scale
120 Figure B.17 – Example of consequence/likelihood matrix
122 B.10.4 S-curves
Figure B.18 – Probability distribution function and cumulative distribution function
124 Bibliography

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BS EN IEC 31010:2019
$215.11