Creating Consequence of Failure Ratings

As with the probability of failure of an asset, the consequence of failure of that asset also needs to be quantified. Systems can quantify the consequence of failure by creating a rating structure that includes a numeric rating and a degree of impact description for each rating. From an implementation perspective, it may be easiest to use the same scale for both consequence and probability of failure. If a 1 to 5 scale was used for probability of failure, systems may want to use a 1 to 5 scale for the consequence of failure. If a system wishes to weigh one of the factors more heavily than the other, it is possible to have a 1 to 5 rating for probability of failure and 1 to 10 rating for consequence of failure or vice versa. If the scale is 1 to 5 for both probability and consequence, the overall risk will be between 1 and 25. A rating of “0” is never used because it would result in an overall risk of 0 and no asset is completely without any risk of failure or consequence of failure. 

One of the best ways to develop standardized criteria is to engage a cross-section of utility staff who have different perspectives and different experiences with the assets. Staff should choose a rating scale, such as 1 to 5 or 1 to 10, and keep the descriptions broad enough so the ratings can apply to any assets (gray and green) in the utility. Creating these ratings does not have to be a long, time-intensive activity. A small system should be able to complete the process of developing the rating structure by meeting a few times for a few hours each. A larger system may take longer and may wish to have a more extensive rating system. 

Once developed, staff will use the structure to assign a rating to each asset based on the type and level of consequences a utility may experience if an asset fails. See the following examples of possible rating structures below. In these examples, 1 is the lowest probability of failure. 

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Table 5: In-depth consequence of failure ratings with descriptions

This is a more detailed rating structure. This structure is often suited to utilities who are further along in their asset management journey. A more descriptive rating structure helps to ensure that ratings are as objective as possible. 

Finding a balance between general and specific descriptions can be challenging. Each consequence descriptor should be generic enough to describe the impact from a green or gray asset failure and specific enough to be as objective as possible.  

• • Generic descriptions allow systems to assess whether the impact from a specific degraded green asset renders the same degree of impact to the system as a specific degraded gray asset. See the tables above for generic, qualitative examples. 
  • Specific descriptions often apply to measurable consequences, such as dollar amounts, number of homes impacted, number of road closures, number of buildings affected, etc. See the tables above for examples of specific, quantitative examples. 

There are no industry standards for the consequence of failure for given assets, so they are best defined by utility staff. Consider how many levels of ratings will work best for your utility.  

• • An even number of ratings can deter staff from the natural temptation to pick a middle value (e.g., 3 on a scale of 1-5).  
  • Avoid too many levels in a rating structure. The difference between levels could be so minute that it is challenging to determine what its probability of failure is. A 1-4, 1-5, or 1-6 scale are often the highest recommended. 

Utility staff will assign a consequence of failure to an asset rating based on the rating structure they create. Staff must consider all three consequence categories when assigning a rating to make informed judgements about the consequences of failure across all types of assets. If the system can collect and store information, it is also valuable to identify which types of consequences (financial, environmental, social) are likely to dominate the analysis. For example, Asset A has the potential for serious social consequences, and the likelihood is rated a 4. Asset B has minor financial consequences, and the consequence is rated 2. There are no industry standards for consequence of failure of given assets, so they are best defined by system personnel as described previously. However, the more applicable empirical data that is collected on an asset, the more accurate and objective the consequence of failure estimate will be and the more consistent they will be with industry best practice. 

Collecting data to help determine the consequence of failure for green assets may be more challenging initially because their inclusion in this type of analysis is a relatively new practice compared to gray assets. Additionally, collecting the appropriate data may require expertise that is outside the typical knowledge of a water or wastewater system (e.g., fire, forestry, geomorphology). 

It is not advisable to compare consequence of failure rating from unrelated facilities. Different geographies, types of treatment provided, size of community, age of system, etc. would prohibit a direct comparison. Consequence of failure ratings must be aligned with individual treatment plants and the communities in which they operate. It may make sense to have the same rating structure across all systems within one community. If a community operates two drinking water treatment plants and two wastewater treatment plants, it can and should use the same rating system across all facilities. 

The goal is to determine which of your assets have more consequence if they fail than other assets in your system. View the examples below to see how different failures can have different consequences and different consequence ratings. 

Consequence of failure ratings – Stacy Gallick, Asset Management Director, Johnson County Wastewater, Olathe, KS