(81bi) The Value of Subjective Vs. Objective Risk Analysis to Expedite Ranking of Functional Systems and Assets

Introduction

In Risk Management there is a need to identify the most critical assets and systems to the overall functional objectives of any unit process to focus on risk mitigation. While many risk management guidelines recommend using a objective risk criteria to identify the criticality of the assets or systems, this study will identify how subjective risk criteria combined with a focus on functional system failure scenarios yields a very valuable relative criticality ranking that quickly allows the Risk Management team prioritize maintenance work, capital investment, critical spare parts, and emergency work planning necessary to mitigate the risk of failure.

Methods

There are three key points to this method. 1.) Break the treatment process into functional systems of assets, 2.) Identify the failure scenarios that are known by the subject matter experts, 3.) Then subjectively rank each of these failure scenarios.

Functional Systems. As Dunn (1972) noted subjective assessment of risk can be faulty for any individual or small group because they tend to focus on a limited data set to draw their conclusions. To improve the accuracy, it is important to identify the functions or systems of assets, (Moubray (1997), IIMM (2002) and how those function may fail. This exercise breaks down the assessment into small sets of assets with limited functions that the subject matter experts are familiar with so that they can improve their subjective assessment of the consequences and the probability of the failure occurring to support a risk rating.

Identify a Failure Scenario. A second feature of the technique is to envision specific failure scenarios, particularly ones that have occurred and are familiar to the subject matter experts. While this approach may not necessarily identify all of the failure scenarios, it will likely identify the most frequently occurring. Again, the idea is to focus the process to work within the experience of the subject matter experts to improve their subjective risk assessment capabilities, Carlstrom (2000) and Weber (1997)

Subjective Ranking of Risk. Risk is a combination of consequence and likelihood of a failure. By separating out the consequence and likelihood in the analysis, steps are further taken to improve the subjective risk assessment capacity of the subject matter experts, improving the results. In addition, the consequences can further be categorized by a level of service expectation, for example, ask the question of how the consequence of failure will effect the Environment or the Quality of the product allows the subject matter experts to further evaluate and categorize their responses the the evaluations of the failure scenarios.

Results and Conclusions

Veolia Water North America has been implementing the key elements of breaking down the risk analysis process for six years. The results, while based on subjective data have been very impressive yielding identification of several high risk systems that had never been identified by either the engineers or operators. An example of a typical identification of an unknown potential system failure was in Gresham Oregon, Yarlott (2007) Rush (2009). An electrical substation, that had operated for thirty plus years with no maintenance was identified through the process of breaking down functional systems, identifying failure scenarios, and then subjectively ranking was quickly identified as one of the most critical systems at the wastewater treatment plant. A failure of this substation transformer, would cut power to a lower treatment plant and would have resulted in a 5 MGD stream of untreated wastewater going directly to the Columbia River.

While objective risk criteria is the most conclusive, it is clear (Dunn 1972, Carlstrom (2000), Weber (1997)) there is value in collecting and evaluating subjective risk rankings of subject matter experts. In fact, modelling of subjective risk assessment (Carlstrom (2000)) is becoming an excepted method of evaluating risk when there is no objective data or the relationships between the objectives data is very complex. For the Risk Manager, the method offers a way to collect subjective information from existing data or subject matter experts available at the time, to document the reasoning and conclusions, and then to use that data to make decisions to reduce the risk exposure of the facility he is managing.

References

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