Risk = Probability * Impact
The resulting risk estimate represents a probable loss.Example
An ice cream cone costs $5 and a toddler has a 10% chance of dropping it without help. Risk = (10/100) * $5 = $0.50Probability Impact Matrix
When risk measures are based on rough estimates, as is often the case with project risk estimates, it is common to represent probability-impact as a matrix of discrete combinations. For example:| Probability-Impact Matrix: Toddler With Ice Cream | ||
Probability | Impact | Probable Loss |
90% | Small Ice Cream MessCost of clean up = $0.10 | $0.09 |
50% | Big Ice Cream MessCost of clean up = $0.50 | $0.25 |
10% | Total Loss of Ice CreamCost of replacement = $5 | $0.50 |
Probability Distributions
The relationship between probability and impact is better modeled with a probability distribution that provides all possible combinations of probability and impact. Sophisticated risk measurements, such as those used in to model investment risk, are typically based on probability distributions and other statistical techniques.Risk measures that rely on a single sample of probability-impact or several samples in a probability-impact matrix are less accurate than those that are properly modeled with a probability distribution. In the example above, there may be thousands of possibilities between a small mess and total loss of an ice cream cone that can be modeled with a smooth curve. Such a curve might have a long tail with remote probabilities such as an ice cream cone causing damage to your car upholstery. As such, the few samples represented in the probability-impact matrix are a rough estimate that wouldn't be used by a bank or insurance company to measure risk.| Overview: Probability Impact | ||
Type | ||
Probability-Impact Matrix Definition | A series of discrete risk estimates calculated as probability × impact represented in a matrix. | |
Related Concepts | ||
