How do you decide if you should put the money from your community into your swimming pool or into your roads? Into motors or pumps? All assets have one thing in common: they are there to provide a service. All assets also have a chance of failing to provide that service. That chance of failure (probability) and the impact from that loss of service—how critical it is to the stakeholder—(consequence) combine to make risk. In other words, Risk = Probability x Consequence. Risk can be used universally between all asset types – social, economic, health, education, etc. This allows communities or companies to carefully compare which assets should have priority, and when combined with powerful decision making tools like Decision Quality & Decision Analysis, it allows careful assessment and weighing of decisions that are defensible.
This is easier said than done. The best way to do this is to build a matrix that combines your levels of service with your assets. You can qualitatively or quantitatively rate how much impact there would be on your stakeholders should those assets to fail to provide their service. When you sum up how each asset impacts your levels of service, you now have a consequence. This consequence can also inform your criticality, if that’s something you track already. To determine probability of failure you need some different factors; these are generally factors concerning asset condition. They may be results from quantitative tests or qualitative observations. There is some nuance to turning asset condition factors into probabilities, but for qualitative ratings, you can derive total probability of asset failure by summing the individual probability of each factor. The multiplication of the total asset probability and total asset consequence gives you risk for that asset. Below is a sample matrix, because a picture is worth 1000 words:
The most powerful part of calculating asset risk is that it can be used to normalize different projects by their risk to level of service. Now that you know the risks to your levels of service, you can start to compare how your spending programs most effectively reduce those risks.
Consider a municipal water treatment example. You have two potential ways to spend funds: a project to replace your raw water pumping, and another to add ultraviolet disinfection. Which project should you do? You can examine the reduction of risk to level of service by estimating each project’s effects on the risk matrix. Moreover, once the risk reduction from each project is known, you can divide by cost, showing you the risk reduction per dollar spent. Sorting these projects (and others in the queue) by their risk reduction per dollar spent gives you the most efficient risk-reduction strategy.
A risk matrix can also be used as a gut-check: if you know which assets you are comfortable with—and which you are not—you know (qualitatively) where you feel the organization should be. This is likely validated by your matrix. Your approach can then be to define an acceptable threshold of risk for your organization, perform a gap analysis, and start reducing the risk in your organization to an acceptable level.
When you increase your efficiency, everyone prospers.