Risk Mitigation Over Time

Explanation

The chart demonstrates two distinct “wedge trends” plotted over the course of a project. You’ll notice there are control limits set on the graph; these are calculated in advance, in alignment with stages of project maturity. For example, week “0” may represent a conceptual design phase, and week “6” may represent final design. More risk is allowed at the beginning, and less risk is allowed at the end. In the first wedge, indicated by “Wedge 1”, we see that negative risk approached zero more quickly. A steeper slope of negative risk indicates that the overall risk distribution was negative at the start of the project. Due to negative risk being reduced, “Wedge 2” represents net positive risk. The data in this chart is normalized around the average overall risk for the project.

Negative Risk Defined

Negative risk is represented by failure modes and escapes inherent to existing design. As negative risk deviation approaches zero, the probability and severity of unplanned failure decreases. Negative risk is always represented as less than zero, but negative risk decreasing indicates less risk of failure.

High Negative Risk Examples:

The failure will stop an entire system – e.g. a critical component out of spec shuts down a circuit
The failure mode is virtually undetectable – e.g. requires extensive testing to detect after a software or product is nearly ready to ship
The failure is highly probable, e.g. 1 in 3 odds to 1 in 100
Major safety concerns, e.g. insufficient chemical tracking system for ingredients in food manufacturing, which are hazardous if expired

Low Negative Risk Examples

A failure mode exists, but is barely noticeable to the customer, if at all. No impact to function
Failure mode is easily detectable and reparable
Failure mode is highly unlikely, e.g. 1 in 500,000 or greater
No safety concerns inherent to the process, or safeguards are effective at preventing injury

Positive Risk Defined

Positive risk is represented by the difficulty and likelihood of success when action is taken with the intent of a positive outcome. As positive risk approaches zero, the likelihood of success increases. Positive risk is always represented as greater than zero, and positive risk decreasing indicates higher odds of success.

High Positive Risk Examples:

Low levels of design or process validation – e.g. conceptual design phase, preliminary design of experiments, no training conducted for procedure
High iterations of change – e.g. complex system or product design
Criticality to quality – e.g. risk is higher if there is less apparent benefit to the customer

Low Positive Risk Examples

A design has been validated through extensive testing and demonstrated reproducibility
Low iterations of change remaining, or the change is on a simple system
Customers want the change and will willingly pay a higher price for the performance improvement