262
15 Risk-Informed Decision Making
of failure will have to go down, especially considering that tailings dams have a
long life span during service and post-service, and, again, the FoS cannot help
measure the changes.
15.11.2 Risk Communication Using Comparisons
Most tables of risk comparisons in the literature contain a mix of risks characterized
by different levels of uncertainty. In addition, most risk comparison tables offer only
single-digit risk estimates, with no range or error term. For risks such as driving,
where fatalities can be counted, the number is likely to be reliable, at least in some
countries. However, even if the risk comparison data are carefully and accurately
reported, they can be misleading. For example, the risk statistics for driving includes
many different driving situations. Yet speeding home after a long party in the early
morning is two orders of magnitude more dangerous than driving slowly to work
during the day. This type of reasoning may explain why in our experience people
have trouble relating such “general” risks to the specific risks posed by a project of,
say, a tailings dam.
As a result, risks such as those generated by major tailings dam failures, occurring
at a rate of 10
−3 –10
−4 (Oboni and Oboni 2013; see Chap. 4) estimated on the basis
of incomplete statistics and flawed by under-reporting and other biases, or necessarily simplified models and evaluation approaches, require great care in presentation
and comparison. As already pointed out, consistent relative risk and benchmarking are of paramount importance, as are complete analyses of consequences and
well-developed dam break studies.
Useful risk comparison should be accurate and pertinent. For example, comparing
the risks of a chemical processing plant to voluntary actions such as smoking or
driving without a seat-belt is neither accurate nor pertinent.
15.11.3 Anticipating Objections
A risk assessment (RA) should be performed by an independent entity (Brehaut
2017; Roche et al. 2017). Nevertheless, the proponent of a project and the public
might have objections to the RA. In this section we discuss how to help remove
objections in order to bring credibility and ultimately SLO and CSR by applying a
mix of technical and soft concepts and skills.
Explicitly considering and explaining data uncertainties helps to explain how risk
estimates are obtained and appease the objections summarized above. Enhancing
the transparency of risk assessments is of course extremely important in this line of
thought. This goal cannot be reached if, for example, arbitrary limits are selected
for boiler-plate risk matrices where the coloring scheme does not bear any relation
to public (or corporate) risk tolerance (Chapman and Ward 2011; Cox et al. 2005;
15 Risk-Informed Decision Making
of failure will have to go down, especially considering that tailings dams have a
long life span during service and post-service, and, again, the FoS cannot help
measure the changes.
15.11.2 Risk Communication Using Comparisons
Most tables of risk comparisons in the literature contain a mix of risks characterized
by different levels of uncertainty. In addition, most risk comparison tables offer only
single-digit risk estimates, with no range or error term. For risks such as driving,
where fatalities can be counted, the number is likely to be reliable, at least in some
countries. However, even if the risk comparison data are carefully and accurately
reported, they can be misleading. For example, the risk statistics for driving includes
many different driving situations. Yet speeding home after a long party in the early
morning is two orders of magnitude more dangerous than driving slowly to work
during the day. This type of reasoning may explain why in our experience people
have trouble relating such “general” risks to the specific risks posed by a project of,
say, a tailings dam.
As a result, risks such as those generated by major tailings dam failures, occurring
at a rate of 10
−3 –10
−4 (Oboni and Oboni 2013; see Chap. 4) estimated on the basis
of incomplete statistics and flawed by under-reporting and other biases, or necessarily simplified models and evaluation approaches, require great care in presentation
and comparison. As already pointed out, consistent relative risk and benchmarking are of paramount importance, as are complete analyses of consequences and
well-developed dam break studies.
Useful risk comparison should be accurate and pertinent. For example, comparing
the risks of a chemical processing plant to voluntary actions such as smoking or
driving without a seat-belt is neither accurate nor pertinent.
15.11.3 Anticipating Objections
A risk assessment (RA) should be performed by an independent entity (Brehaut
2017; Roche et al. 2017). Nevertheless, the proponent of a project and the public
might have objections to the RA. In this section we discuss how to help remove
objections in order to bring credibility and ultimately SLO and CSR by applying a
mix of technical and soft concepts and skills.
Explicitly considering and explaining data uncertainties helps to explain how risk
estimates are obtained and appease the objections summarized above. Enhancing
the transparency of risk assessments is of course extremely important in this line of
thought. This goal cannot be reached if, for example, arbitrary limits are selected
for boiler-plate risk matrices where the coloring scheme does not bear any relation
to public (or corporate) risk tolerance (Chapman and Ward 2011; Cox et al. 2005;