Appendix A
Making Sense of Probabilities
and Frequencies
Making sense of probabilities and frequencies (in a quantitative way) is necessary
to benefit from better risk assessment. Oftentimes users feel compelled to use
qualitative approaches to risk assessments. Their justification includes that probability evaluations are complicated, they require “statistics”. As a result, users
embrace index-approaches (probabilities are given (absurd) values like 1, 2, 3… n),
qualitative approaches (small, medium, large… fast food style) while believing they
will get a good understanding of their risks out of this.
This Appendix allows to simply define ranges of probabilities and frequencies
based on analogies and tables, no “statistical” calculations required. By doing so,
the user is forced to acknowledge uncertainties (resulting in expanding the estimate
range) strongly reducing the “garbage-in-garbage-out” syndrome. Furthermore, if a
consistent approach is used, then the relative estimates of probabilities will be
consistent among each other.
A further benefit of using quantitative estimates is the ability to update those
estimates as new data become available. Suppose you have selected ranges of
min-max probabilities for all events. Those ranges of probabilities offer a way to
use future observations to “correct” a priori estimates and thus build a dynamic risk
register.
This makes sense, especially as we live in dynamic climate change,
socio-economic, and political environments, and many companies use Internet of
Things (IoT) or big data. Beware of the temptation to use a single number for
estimates. Use ranges, as this is the way to acknowledge inevitable uncertainties.
© Springer Nature Switzerland AG 2020
F. Oboni and C. Oboni, Tailings Dam Management for the Twenty-First Century,
https://doi.org/10.1007/978-3-030-19447-5
273
Making Sense of Probabilities
and Frequencies
Making sense of probabilities and frequencies (in a quantitative way) is necessary
to benefit from better risk assessment. Oftentimes users feel compelled to use
qualitative approaches to risk assessments. Their justification includes that probability evaluations are complicated, they require “statistics”. As a result, users
embrace index-approaches (probabilities are given (absurd) values like 1, 2, 3… n),
qualitative approaches (small, medium, large… fast food style) while believing they
will get a good understanding of their risks out of this.
This Appendix allows to simply define ranges of probabilities and frequencies
based on analogies and tables, no “statistical” calculations required. By doing so,
the user is forced to acknowledge uncertainties (resulting in expanding the estimate
range) strongly reducing the “garbage-in-garbage-out” syndrome. Furthermore, if a
consistent approach is used, then the relative estimates of probabilities will be
consistent among each other.
A further benefit of using quantitative estimates is the ability to update those
estimates as new data become available. Suppose you have selected ranges of
min-max probabilities for all events. Those ranges of probabilities offer a way to
use future observations to “correct” a priori estimates and thus build a dynamic risk
register.
This makes sense, especially as we live in dynamic climate change,
socio-economic, and political environments, and many companies use Internet of
Things (IoT) or big data. Beware of the temptation to use a single number for
estimates. Use ranges, as this is the way to acknowledge inevitable uncertainties.
© Springer Nature Switzerland AG 2020
F. Oboni and C. Oboni, Tailings Dam Management for the Twenty-First Century,
https://doi.org/10.1007/978-3-030-19447-5
273