ISO 31010:2019 - 30+ Risk Assessment Techniques Explained

Explore techniques to elicit stakeholder and expert views for better decision making and risk assessment. Learn methods like brainstorming, Delphi, nominal group technique, interviews, and surveys to gather diverse insights.

Facilitate brainstorming to identify risks for the Med Datapro healthcare software launch, categorize by impact and likelihood, and prioritize data security and regulatory compliance.

Use the Delphi technique, a structured communication method, to gather anonymous expert opinions through iterative rounds of open-ended questions, converging toward consensus for decisions in complex issues like healthcare software.

Apply the Nominal Group Technique to structured brainstorming, ensure equal participation, generate diverse ideas, rank them anonymously, and reach a consensus for informed decisions.

Explain how structured and semi-structured interviews collect stakeholder input for risk assessment, combining predefined questions with flexible probing to balance data consistency and depth.

Surveys provide a systematic method to collect data from many respondents via online, paper, telephone, or in-person formats, with objectives and questions including pre-testing, and analyze quantitative and qualitative responses.

Explore techniques for identifying risks, including checklists, classifications and taxonomies, Fmea, Hazop, scenario analysis, and Swift, to categorize, assess, and mitigate potential failures and hazards early in the project lifecycle.

Leverage checklists, classifications, and taxonomies to identify and manage risks. Organize risks into categories like technical, operational, financial, and external for structured analysis and better decision making.

Apply FMEA for proactive error prevention by identifying failure modes, causes, and effects across requirements gathering, coding, testing, deployment, security management, and maintenance; calculate risk priority numbers and guide mitigations.

Hazop for operational safety identifies deviations and their consequences using guide words, applying a structured, multidisciplinary approach to risks across the software development life cycle.

Explore scenario analysis as a strategic risk assessment tool to identify key drivers, develop plausible future narratives, assess impacts, and craft resilient action plans to mitigate risks and seize opportunities.

What-if analysis drives scenario planning by brainstorming hypothetical scenarios, analyzing outcomes, prioritizing risks by likelihood and impact, and developing contingency plans to mitigate risks and stay prepared.

Explore the swift structured what-if technique for systematic risk identification and analysis, guided by prompts and a facilitator to uncover causes, consequences, likelihood, and prioritized mitigation strategies.

Apply the syndetic approach to map system interconnections and identify risk sources and drivers. Use Ishikawa analysis to uncover root causes across categories like people, processes, materials, and equipment.

The syndetic approach maps interactions within a system to reveal root causes and interdependencies, enabling holistic risk assessment, scenario planning, and resilient contingency planning.

Apply the Ishikawa fishbone diagram to identify root causes. Define the problem and categorize causes into environment, machine equipment, manpower, human investment, financial method, process, and material.

Explore bowtie analysis, hazard analysis and critical control points (HACCP), and layers of protection analysis (LOPA) to map risks, identify barriers, and assess preventive, mitigative, and recovery measures.

Visualize risk with bow-tie analysis, merging fault tree and event tree to map threats, top event, barriers, escalation factors, consequences, and unauthorized access to patient data.

Use layers of protection analysis (LOPA), a semi-quantitative risk assessment, to identify initiating events and protective layers, assess their failure on demand probabilities, and determine if additional measures are needed.

Apply hazard analysis and critical control points to identify, evaluate, and control biological, chemical, and physical hazards across the production process to prevent foodborne illnesses.

Explore techniques to assess consequences and likelihood of risks, including Bayesian analysis, Bayesian networks, influence diagrams, BIA, CCA, ETA, FTA, HRA, Markov analysis, Monte Carlo simulation, and privacy impact analysis.

Bayesian analysis updates prior and posterior probabilities with new evidence using Bayes theorem, refining risk assessments in real time for events like server crashes, data breaches, and software development deadline.

Model dependencies and probabilistic relationships with Bayesian networks and influence diagrams, update outcomes with new evidence, and guide resource allocation for server crashes, load, vulnerabilities, and delays in tech solutions.

Explore business impact analysis (BIA) to identify critical functions, assess disruption impacts, determine maximum tolerable downtime, and prioritize recovery strategies with financial and non-financial implications.

Explore cause and consequence analysis (CCA) to uncover root causes and potential consequences of events, map interdependencies with diagrams, and design preventive measures and contingency plans.

Explore forward-looking event tree analysis (eta) to map initiating events to outcomes, assess branch probabilities, and prioritize safeguards and resources for risk mitigation.

Apply fault tree analysis (FTA), a top-down deductive method, to identify root causes by mapping pathways to a top event using a tree diagram and logic gates.

Identify, evaluate, and mitigate human error in complex systems through task analysis, recognizing slips, lapses, and mistakes, and applying fault or event tree analysis.

Model Markov analysis to describe system transitions using a transition matrix and predict steady state behavior and reliability, as shown with Tech Solutions' operational, maintenance, and failed states.

Explore Monte Carlo simulation, a random sampling method that builds a probability distribution from thousands of iterations to quantify risk and uncertainty in project timelines and guide decision making.

Explore privacy impact analysis and data protection impact assessment, mapping data flows, identifying privacy risks, and applying mitigation strategies like encryption and access controls to comply with GDPR.

Explore causal mapping and cross-impact analysis to map dependencies and interactions within complex systems, revealing key drivers, feedback loops, and cascading effects for risk management and decision making.

Visualize and analyze relationships within a system by mapping factors, drawing connections, and using causal maps or influence diagrams to reveal key drivers, outcomes, and feedback loops.

Map interdependencies within a system to foresee ripple effects and guide decision making, planning, and risk mitigation across supply chain, production, and delivery.

Explore techniques that provide quantitative risk measures, including toxicological risk assessment and VAR with its confidence level. Examine CVaR and tail risk analysis for extreme loss scenarios.

Identify hazards, assess dose-response and exposure assessment, and perform risk characterization to quantify health risks from toxic substances and guide mitigation for public health and the environment.

Calculate value at risk, a statistical metric that estimates the maximum expected loss over a defined horizon at a given confidence level under normal market conditions.

Explore CVaR, or expected shortfall, as an advanced risk metric that averages losses beyond the VAR threshold to reveal tail risks and guide robust risk management.

Analyze techniques for evaluating risk significance to prioritize mitigation, including alarp and as low as reasonably practicable principles, frequency diagrams, Pareto charts, reliability centered maintenance, and risk indices.

Apply alarp and so far as is reasonably practicable to evaluate and manage risk, balancing mitigation costs against benefits to reach acceptable levels.

Explore frequency-number diagrams that visualize the link between event frequency and casualties, plot data points from incidents, and enable data-driven risk prioritization, scenario comparison, and cumulative risk assessment.

Apply Pareto charts to rank risk causes by frequency or impact in descending order, visualize the cumulative line, and prioritize top factors to focus resources on the most significant issues.

Learn how reliability centered maintenance (RCM) identifies failure modes and consequences to tailor preventive and corrective tasks, prioritize risks, and continuously improve maintenance for critical assets.

Calculate risk indices by multiplying likelihood and impact scores (1–5) to quantify and rank risks, enabling prioritized mitigation and clear risk communication.

Examine techniques for selecting between options by weighing costs, benefits, and multiple criteria using CBA, decision trees, game theory, and MCA to enable transparent, justifiable decisions.

Assess cost benefit analysis to evaluate economic feasibility by comparing costs and benefits. Quantify direct, indirect, and intangible costs in monetary terms and compute the net benefits for decision making.

Use decision tree analysis to map decision paths, assign probabilities and payoffs, and calculate expected value under uncertainty; perform sensitivity analysis to test robustness and communicate results to stakeholders.

Game theory analyzes interdependent decisions of rational players, from prisoner's dilemma to Nash equilibrium, to predict outcomes and guide pricing, competition, and negotiation strategies.

Apply multi-criteria analysis to weigh and score multiple criteria: cost, time, quality, and security features, balancing tradeoffs to select the best option.