Risk assessment comparison on a system including 5 macro-elements
Sep 21st, 2016
A client considering a full scale ORE deployment asked for a risk assessment comparison on a system including 5 macro-elements in one of his processes.
A risk assessment comparison on a system including 5 macro-elements
The client wanted to compare a quantitative:
- common practice risk assessment result with
- risk assessment with ranges expressing probabilities and finally
- risk assessment where we would consider interdependencies between macro-elements.
We estimated quantitative probabilities of failure of each macro-elements based on case histories and by encoding experts’ opinions into ranges.
We also estimated Consequences of failure of each macro-element using the following components:
- Health and Safety
- Business Interruption
- Environmental and finally
- Crisis and Reputational
For each component, and for the sake of this very simple example, we used average consensus values.
Due to the extremely simple case we tackled in this example we used a compact version of ORE, which works on a worksheet.
The risks evaluated following common practices (i.e. selecting the higher consequence component as the consequence value) are generally significantly smaller than both the risks evaluated considering:
a) complex consequences AND interdependencies and even
b) only complex consequences.
- Figure: A risk assessment comparison on a system including 5 macro-elements (numbered 1 to 5, horizontal axis, risks in the vertical axis) under three evaluation modes: common practice, b) including complex consequences and a) complex consequences AND interdependencies.
Significance of the results
- Figure: Pie diagrams showing the risk prioritization following common practice risks and complex consequences AND interdependencies risks.
Notice how significantly different is the risk prioritization between the two cases of the figure above.
If 1M$ was available for mitigations then only 27+22=49% would be allotted to elements 1 & 2 following the common practice risk prioritization, whereas 37+31=68% of risks lie within those two elements when considering more realistic complex consequences AND interdependencies.
This highlights a clear case where mitigative funds would be misplaced and unwanted exposures would remain unmitigated. In other words, following this example a used of common practices would squander 14+20+16= 51% of funds on mitigating elements 3,4,5 whereas only 7+18+7= 32% of the risks lie within those three elements.
It is of paramount importance to include complex consequences AND interdependencies in the risk estimates even when dealing with simple systems.
Riskope’s ORE allows to perform these analyses in simple and complex systems, and constitutes an invaluable platform to deliver integrated and convergent risk assessments.
Come to our next courses in (A path to zero failures in tailings facility) Keystone (Colorado) Oct 2nd, 2016 and (Risk Assessment, Decision Making and Management of Mine Waste Facilities) Vancouver Nov 13th, 2016 (B.C.) to work on a full example explained A to Z.
Tagged with: assessment, Comparative, decision, decision making, education, management, Optimum Risk Estimates, ORE, Probability Impact Graphs
Category: Consequences, Optimum Risk Estimates, Probability Impact Graphs, Risk analysis, Risk management