In this post, I will summarise the lectures of the RIS525 course. Each lecture is divided into a set of questions. The group work questions are answered in this post. First, the question is presented with a concise answer in cursive. After this, a more elaborate answer is given. I will turn the questions and their concise answers into flashcards at the end of the course and post them here. Combining this summary and the answers to the group work questions should form a good base for the exam.

Flashcards

Week 2: Introduction and Definitions

Question 1: What is risk management?

• Balancing conflicts between exploring opportunities and avoiding losses or disasters.

Question 2: What is a cost-benefit analysis?

• E[NPV] = EX – EC.

Cost-benefit analysis (CBA) is an economic evaluation technique that compares the expected benefits (EX) with the expected costs (EC) of a decision, project, or investment. To calculate the outcome, every variable needs to be transformed into a monetary value.

Question 3: What is a cost-effectiveness analysis?

EC/EZ.

Cost-Effectiveness Analysis (CEA) is an economic evaluation method that compares the costs (EC) of achieving a specific outcome (EZ). The outcome of the analysis is the cost-effectiveness index. It provides insights into the most efficient way to achieve a desired result, especially when multiple alternatives are available. For example; expected cost per expected number of lives saved.

Question 4: What is multi-attribute analysis?

Question 5: What is expected utility theory, and how to use it?

• Expected Utility Theory is a foundational concept in economic decision-making. It suggests that individuals make choices based on maximizing their expected utility (EU), where utility represents the satisfaction or value derived from an outcome. The theory forms the basis for various economic analyses.

Example: Alt. 1: 0 NOK (50%) 1,000,000 NOK (50%) vs. Alt. 2: 500,000 NOK (100%).

This scenario presents two alternatives with different probabilities and outcomes. The calculation involves determining the expected value (EX) and expected utility (EU) for each alternative, aiding in decision-making under uncertainty.
The EX for alt1 = 0*0.5 + 1000,000*0.5 = 500,000
The EX for alt2 = 500,000.
The EU for alternative 1 = u(0)*0.5 + u(1000,000)*0.5= 0*0.5+1*0.5=0.5
The EU for alternative 2 = u(500.000)*1.0 = 0.95*1.0=0.95

How do we determine the utility value? It is common to put the best utility to 1. And the utility value for the worst outcome to 0. The utility value between the best and worst will be based on preferences. Which will be covered in one of the next lectures.

Question 6: What is risk?

• Many definitions among which:
• C * P
• C, U

Risk is often quantified as the product of consequence (C) and probability (P). The consequence refers to the impact or severity of an event, while probability represents the likelihood of its occurrence. Another definition of risk is the product of Consequences and associated Uncertainties C, U.

Question 7: What is a risk analysis?

Question 9: What are some ways of visualizing risk?

Risk Matrix:

• Description: A risk matrix is a two-dimensional grid that maps the likelihood of risks against their impact. It typically uses color coding to indicate the severity of risks, with green representing low risk, yellow for medium risk, and red for high risk.
• Application: This tool is useful for providing a quick overview of risk levels, helping stakeholders prioritize which risks need immediate attention.

Bubble Diagram:

• Description: A bubble diagram is similar to a risk matrix but includes an additional dimension to represent uncertainties. The x-axis and y-axis still map the likelihood and impact of risks, respectively, while the size of the bubbles represents the level of uncertainty associated with each risk.
• Application: This method provides a more comprehensive view by incorporating the uncertainty aspect, making it easier to understand which risks are well understood and which ones require more information.

Risk Plots:

• Description: Risk plots are graphical representations that incorporate the probability of an event, the magnitude of consequences, and the strength of knowledge. These plots use a 90% confidence interval to display the severity of the consequences. Typically, the x-axis represents the consequences, while the y-axis shows the likelihood of these consequences occurring. A third dimension indicates the strength of knowledge or uncertainty associated with the risk.
• Application: Risk plots are beneficial for providing a nuanced understanding of risks, but can be hard to understand.

Week 3 & Week 5 Safety Risk Management: Integrating economic and safety perspectives

Question 1: What does ALARP mean?

• As Low As Reasonably Practicable Means that a risk-reducing measure should be implemented provided it cannot be demonstrated that the costs are grossly disproportionate to the benefits obtained

Question 3: Is it appropriate to use the ALARP principle in safety management?

Question 4: How does ALARP compare to an (extreme) economic/development perspective and a Safety/protection perspective?

Question 5: What does the formula ”EC>EX * grossly disproportionate factor” mean and how should it be used?

• If the expected costs (EC) exceed the expected benefits (EX) by a grossly disproportionate factor (DPF), it suggests that the costs outweigh the benefits significantly. A correct way of using this formula would be by using a variable DPF depending on the context. The shortcoming of this approach is that decisions are still based on Expected Values, which means that uncertainties are not completely taken into account.

Question 6: Explain the layered approach in Risk Management.

The first step is to conduct a crude analysis. This step is very basic, simply answering the question, “Are the costs low, and the benefits high?” If the answer is yes, then the risk-reducing measure is implemented. If the answer is no, we move on to step two.

In Step 2, a more detailed analysis is conducted. If appropriate, an economic assessment is made. The Expected Net Present Value (ENPV) of implementing the risk-reducing measure is calculated by subtracting the expected costs (E C) from the expected benefits (EX). Another calculation made is the Initial Cost of Averting a Fatality (ICAF). The ICAF is calculated by dividing the costs of implementing the safety measures by the expected number of lives saved. The outcome of this calculation is then compared to a Value of a Statistical Life (VSL). If the ICAF value is lower than the VSL value and/or if the ENPV provides a positive value, the risk-reducing measure should be implemented. If this analysis indicates high costs or uncertainties, we move on to step three.

In Step 3, a more qualitative analysis is conducted. First, uncertainties are analyzed. This involves describing all relevant uncertainty factors, estimating their impact on profitability through sensitivity analysis, and considering how to manage these uncertainties. Methods include point estimates, high and low estimates, and probability distributions of costs and benefits. Secondly, a Checklist for Robustness is used to evaluate whether the measure increases manageability, provides a more robust solution, applies best available technology (BAT), addresses personnel safety, or has strategic considerations. If this last step also indicates that implementing the risk-reducing measure is not beneficial, the measure should not be implemented.

Question 7: What is the Expected utility theory and its axiomatic bases?

Axiomatic basis

§Axiom 1: Weak order

§Axiom 2: Continuity

§Axiom 3: Preference increasing with probability     

§Axiom 4: Compound probabilities

§Axiom 5: Independence
Implies that if we have two lotteries with a common outcome and one of the lotteries is preferred to the other, then preferences will not be affected if a common outcome is replaced by another common outcome.
The comonotonic independence axiom
This implies that if we have two lotteries with a common outcome and one of the lotteries is preferred to the other, then preferences may be affected if a common outcome is replaced by another common outcome as long as the ranking of the common outcome changes.

Question 8: What is an indifference curve?

An indifference curve in risk management shows combinations of risk and return that yield the same level of satisfaction or utility to decision-makers. It helps illustrate the trade-offs between risk and return preferences in decision-making processes.

Question 9: Should the Risk Acceptance Criteria (RAC) be set by the authorities or by the companies themselves?

Authorities, with their broader societal viewpoint, may consider factors that companies might overlook, such as the potential impact on public safety, environmental concerns, or long-term social costs (externality costs). RACs should therefore be set by the authorities.

Week 7 Contributions to improved risk assessments

Question 1: What improvements can be made to the HFMEA model and why?

1. Integrating Uncertainty in Risk Evaluation

Traditional HFMEA primarily focuses on the severity and probability of potential failures. However, this approach can overlook the uncertainties that might affect these probabilities and severities. Abrahamsen et al. suggest incorporating a broader evaluation that includes uncertainties. This means acknowledging that our understanding of risks is often imperfect and considering the variability in data and potential for unexpected outcomes.

Why it Matters: By considering uncertainties, healthcare providers can better prepare for and mitigate risks that might otherwise be underestimated. This leads to more robust and reliable risk assessments.

2. Broader Evaluation of Control Measures

In traditional HFMEA, if an effective control measure exists, no further action is deemed necessary. However, Abrahamsen et al. argue that this approach is too simplistic. They recommend a more comprehensive evaluation of control measures, including their reliability and the uncertainties associated with them.

Why it Matters: Even effective control measures can fail under certain conditions. By assessing the reliability and uncertainties of these measures, healthcare providers can ensure that they have multiple layers of protection and are not overly reliant on a single control that might fail.

Practical Implications of These Improvements

Enhanced Risk Categorization: The improved HFMEA model uses a two-step risk classification procedure. First, it categorizes combinations of probability and severity into high, medium, or low risk. Then, it adjusts these categories based on the level of uncertainty involved. This ensures that even risks deemed low or medium can be reevaluated if significant uncertainties are present.

Thorough Control Measure Assessment: The new approach involves a detailed assessment of each control measure’s effectiveness, reliability, and associated uncertainties. This leads to a more nuanced understanding of the overall performance of these measures, ensuring that potential failures are comprehensively managed.

Question 2: How can an integrated framework for Safety- and Uncertainty management in petroleum operations be implemented?

What is the Integrated Framework?

The integrated framework aims to bring together safety management and uncertainty management into a cohesive process. Traditionally, these have been handled separately, with safety management focusing on identifying and mitigating risks, while uncertainty management deals with the variability and unpredictability of risk factors.

Steps to Implement the Integrated Framework

1. Two-Dimensional Risk Concept

This concept forms the foundation of the framework, emphasizing both the events (A) and consequences (C) as well as the associated uncertainties (U). This approach goes beyond merely calculating probabilities and expected values, acknowledging that uncertainties play a critical role in risk assessment.

2. Conducting Hazard Identification (HAZID) Early

Early in the project stages, conduct a thorough HAZID analysis. This involves identifying potential hazards and uncertainties in the current operations. Engaging personnel from various operational roles ensures a comprehensive understanding of the risks and uncertainties involved.

3. Categorizing Uncertainty Factors

Uncertainty factors are categorized as high, medium, or low based on their conditions and potential influence on risk indices. This helps in understanding the impact of uncertainties on the overall risk assessment.

Why it Matters: Categorizing uncertainties provides a structured way to assess and manage them, ensuring that even low-probability but high-impact events are adequately considered.

4. Broader Evaluation of Control Measures

Instead of only identifying control measures, this step involves a detailed assessment of their effectiveness, reliability, and associated uncertainties. This includes:

• Identifying existing control measures.
• Assessing their effects and reliability.
• Evaluating the uncertainties associated with these measures.
• Determining the overall performance of the control measures.

Question 3: Why and how do should we determine the value of information in risk analysis?

Why Determine the Value of Information?

1. Improves Decision Quality: By quantifying the potential benefits of additional information, VOI helps in making better-informed decisions.
2. Cost Justification: VOI helps in assessing whether the cost of obtaining additional information is justified by the benefits it provides.
3. Risk Reduction: Additional information can reduce uncertainties, leading to more accurate risk assessments and better risk management strategies.
4. Resource Allocation: Helps in prioritizing where to invest in additional data collection and analysis efforts.

How to Determine VOI

1. Framing the Problem: Define the decision problem and the decision alternatives, including the type of additional information that could be considered.
2. State of Nature: Collect information about risks, including probabilities and outcomes, and design a model to calculate expected benefits.
3. Assessment of Information Quality: Evaluate the probability that the additional information provides correct or incorrect answers.
4. Evaluation Without Additional Information: Calculate the expected benefits without the additional information.
5. Evaluation With Additional Information: Calculate the expected benefits assuming perfect information.
6. Evaluation With Imperfect Information: When relevant, evaluate the situation with imperfect information, considering the quality and reliability of the information.
7. Sensitivity Analysis: Assess how the results change depending on different parameter values used in the calculations and the importance of these parameters.
8. Handling of Uncertainty: Describe the uncertainties and their influence on the conclusions achieved.

Example: Investment in a Mine

A practical example given in the document illustrates the VOI process through a decision on whether to invest in a mine. Here’s a simplified outline:

1. Framing the Problem: The decision is whether to start mining operations, which depends on whether the mine is profitable.
2. State of Nature: Assess the probability of high mineral concentration in the mine based on previous data from other mines.
3. Assessment of Information Quality: Assume geological exploration provides perfect information about the mineral concentration.
4. Evaluation Without Additional Information: Calculate expected benefits based on existing data, leading to an expected value.
5. Evaluation With Additional Information: Calculate the expected benefits with the perfect geological exploration data, yielding a higher expected value if the information supports mining.
6. Sensitivity Analysis: Show how changing the parameters, such as the cost of mining operations, affects the VOI.
7. Handling of Uncertainty: Address uncertainties related to the assumptions, such as the reliability of geological data.

Conclusion

VOI is a tool for making informed risk decisions. It ensures that the expected improvements in decision quality justify the costs of obtaining additional information. The process involves evaluating the benefits of additional information, assessing the quality and reliability of this information, and performing sensitivity and uncertainty analyses to ensure robust decision-making.

References

• Selvik, J.T., Lohne, H.P., & Aven, T. (2011). On the use of value of information measure in decision making – a drilling jar case. Proceedings of the European Safety and Reliability Conference 2011 (ESREL 2011).
• Abrahamsen, E.B., Aven, T., & Iversen, R.S. (2009). An integrated framework for safety management and uncertainty management in petroleum operations.
• Week 7 e-learning module on Value of Information (VOI).

Question 4: What is a ‘vision zero’ strategy’ and why should or shouldn’t it be implemented?

Week 9 Visualisation and communication of risk

Question 1: What are the up- and downsides of risk matrices?

A risk matrix is easy to understand and allows for easy comparison between risks. The simplification is also the downside of the matrice. The main downside is the insufficient representation of uncertainties. This is because the risk matrix uses expected values as a starting point for defining risk.

Question 2: Bubble diagrams v.s. Risk plots, which one to use as an alternative to risk matrices?

Each graph has its strengths and weaknesses and the appropriate graph depends on the decision-making context. Bubble diagrams make it easier to compare risks. Whilst risk plots provide more information on the possible consequences, by providing the severity of the consequences in a confidence interval.

Week 10 On the importance of adopting a system approach as a basis for risk-informed decisions

Question 10-1 What is a ‘systems approach’ and why should we use it as a basis for risk-informed decisions?

The implementation of new safety measures can undermine the overall safety of the system. for instance by diminishing the amount of resources that can be attributed to current or other safety measures. An example of a current development is the use of virtual reality in safety management. Virtual Reality can be beneficial but in its current state, it is likely to be costly. Many working hours have to be spent on learning, working with and updating the systems. This might diminish the amount of time that is spent on regular safety training and therefore undermine the overall quality of the safety training.

Week 12 Repetition