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BS EN IEC 31010:2019 – TC

BS EN IEC 31010:2019 – TC

$280.87

Tracked Changes. Risk management. Risk assessment techniques

Published By Publication Date Number of Pages
BSI 2019 334
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PDF Catalog

PDF Pages PDF Title
1 compares BS EN IEC 31010:2019
2 TRACKED CHANGES
Text example 1 — indicates added text (in green)
206 undefined
209 Annex ZA(normative)Normative references to international publicationswith their corresponding European publications
211 English
CONTENTS
215 FOREWORD
217 INTRODUCTION
218 1 Scope
2 Normative references
3 Terms and definitions
219 4 Core concepts
4.1 Uncertainty
220 4.2 Risk
5 Uses of risk assessment techniques
221 6 Implementing risk assessment
6.1 Plan the assessment
6.1.1 Define purpose and scope of the assessment
222 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
223 6.1.6 Review criteria for decisions
225 6.2 Manage information and develop models
6.2.1 General
6.2.2 Collecting information
6.2.3 Analysing data
226 6.2.4 Developing and applying models
227 6.3 Apply risk assessment techniques
6.3.1 Overview
228 6.3.2 Identifying risk
6.3.3 Determining sources, causes and drivers of risk
229 6.3.4 Investigating the effectiveness of existing controls
6.3.5 Understanding consequences, and likelihood
231 6.3.6 Analysing interactions and dependencies
6.3.7 Understanding measures of risk
234 6.4 Review the analysis
6.4.1 Verifying and validating results
6.4.2 Uncertainty and sensitivity analysis
235 6.4.3 Monitoring and review
6.5 Apply results to support decisions
6.5.1 Overview
236 6.5.2 Decisions about the significance of risk
6.5.3 Decisions that involve selecting between options
237 6.6 Record and report risk assessment process and outcomes
7 Selecting risk assessment techniques
7.1 General
238 7.2 Selecting techniques
240 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
241 Table A.2 – Techniques and indicative characteristics
246 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]
247 Table A.3 – Applicability of techniques to the ISO 31000 process
249 Annex B (informative)Description of techniques
B.1 Techniques for eliciting views from stakeholders and experts
B.1.1 General
B.1.2 Brainstorming
251 B.1.3 Delphi technique
252 B.1.4 Nominal group technique
253 B.1.5 Structured or semi-structured interviews
254 B.1.6 Surveys
255 B.2 Techniques for identifying risk
B.2.1 General
256 B.2.2 Checklists, classifications and taxonomies
258 B.2.3 Failure modes and effects analysis (FMEA) and failure modes, effects and criticality analysis (FMECA)
259 B.2.4 Hazard and operability (HAZOP) studies
260 Table B.1 – Examples of basic guidewords and their generic meanings
261 B.2.5 Scenario analysis
263 B.2.6 Structured what if technique (SWIFT)
264 B.3 Techniques for determining sources, causes and drivers of risk
B.3.1 General
265 B.3.2 Cindynic approach
266 Table B.2 – Table of deficits for each stakeholder
Table B.3 – Table of dissonances between stakeholders
267 B.3.3 Ishikawa analysis (fishbone) method
268 Figure B.1 – Example Ishikawa (fishbone) diagram
269 B.4 Techniques for analysing controls
B.4.1 General
B.4.2 Bow tie analysis
270 Figure B.2 – Example of Bowtie
271 B.4.3 Hazard analysis and critical control points (HACCP)
273 B.4.4 Layers of protection analysis (LOPA)
275 B.5 Techniques for understanding consequences and likelihood
B.5.1 General
B.5.2 Bayesian analysis
277 B.5.3 Bayesian networks and influence diagrams
278 Figure B.3 – A Bayesian network showing a simplified version of a realecological problem: modelling native fish populations in Victoria, Australia
279 B.5.4 Business impact analysis (BIA)
281 B.5.5 Cause-consequence analysis (CCA)
282 Figure B.4 – Example of cause-consequence diagram
283 B.5.6 Event tree analysis (ETA)
284 Figure B.5 – Example of event tree analysis
285 B.5.7 Fault tree analysis (FTA)
286 Figure B.6 – Example of fault tree
287 B.5.8 Human reliability analysis (HRA)
288 B.5.9 Markov analysis
289 Figure B.7 – Example of Markov diagram
Table B.4 – Example of Markov matrix
290 B.5.10 Monte Carlo simulation
Table B.5 – Examples of systems to which Markov analysis can be applied
294 B.6 Techniques for analysing dependencies and interactions
B.6.1 Causal mapping
296 B.6.2 Cross impact analysis
298 B.7 Techniques that provide a measure of risk
B.7.1 Toxicological risk assessment
Figure B.8 – Example of dose response curve
300 B.7.2 Value at risk (VaR)
Figure B.9 – Distribution of value
Figure B.10 – Detail of loss region VaR values
302 B.7.3 Conditional value at risk (CVaR) or expected shortfall (ES)
Figure B.11 – VaR and CVaR for possible loss portfolio
303 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)
304 Figure B.12 – ALARP diagram
305 B.8.3 Frequency-number (F-N) diagrams
306 Figure B.13 – Sample F-N diagram
307 B.8.4 Pareto charts
Figure B.14 – Example of a Pareto chart
309 B.8.5 Reliability centred maintenance (RCM)
310 Table B.6 – An example of RCM task selection
311 B.8.6 Risk indices
312 B.9 Techniques for selecting between options
B.9.1 General
313 B.9.2 Cost/benefit analysis (CBA)
315 B.9.3 Decision tree analysis
316 B.9.4 Game theory
317 Table B.7 – Example of a game matrix
318 B.9.5 Multi-criteria analysis (MCA)
320 B.10 Techniques for recording and reporting
B.10.1 General
321 B.10.2 Risk registers
322 B.10.3 Consequence/likelihood matrix (risk matrix or heat map)
323 Figure B.15 – Part example of table defining consequence scales
Figure B.16 – Part example of a likelihood scale
324 Figure B.17 – Example of consequence/likelihood matrix
326 B.10.4 S-curves
Figure B.18 – Probability distribution function and cumulative distribution function
328 Bibliography

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BS EN IEC 31010:2019 - TC
$280.87