How can you use probabilities to analyze system risk?

1 Define the system

The first step is to define the system you want to analyze, including its boundaries, components, functions, inputs, outputs, and interactions. You also need to define the system performance criteria, such as reliability, availability, safety, or quality. These criteria will help you measure the impact of system risk on the system goals and objectives. You can use various methods to define the system, such as functional analysis, system architecture, or system modeling.

2 Identify the sources of uncertainty and variability

The second step is to identify the sources of uncertainty and variability that affect the system performance. Uncertainty is defined as a lack of knowledge or information about the system or its environment, while variability refers to changes or fluctuations in the system or its environment. Examples of sources of uncertainty and variability include random failures or errors in the system components or functions, environmental factors such as weather, temperature, or noise, human factors such as user behavior, preferences, or errors, and requirements changes, design changes, or implementation changes. To identify these sources, you can use risk identification techniques, failure modes and effects analysis (FMEA), or fault tree analysis (FTA).

3 Assign probabilities to the events and outcomes

The third step is to assign probabilities to the events and outcomes that affect the system performance. Probability is a measure of how likely an event or outcome is to occur, based on the available evidence or data. You can use different types of probabilities, such as objective probabilities based on empirical data or statistical analysis, subjective probabilities based on expert judgment or intuition, and Bayesian probabilities which are updated based on new evidence or data. Various methods can be used to assign probabilities to the events and outcomes, such as probability distributions, probability trees, or Bayesian networks.

4 Calculate the expected value and variance of the system performance

The fourth step is to calculate the expected value and variance of the system performance, based on the probabilities of the events and outcomes. The expected value is the average or most likely value of the system performance, while the variance is a measure of how much it deviates from the expected. To calculate these values, you can use expected value analysis, which involves summing up the products of probabilities and values; Monte Carlo simulation, which generates random samples of outcomes and calculates statistics; or sensitivity analysis, which evaluates how performance changes with different values of uncertain or variable factors. By using probabilities to analyze system risk, you can gain a better understanding of uncertainty and variability in your system and how they affect performance. You can also use them to compare alternatives, prioritize risks, and design risk mitigation strategies.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?