Quantitative & Qualitative Risk Analysis: Practicalities, Rationalisations and Convergence of Practice(s)
Quantitative & Qualitative Risk Analysis: Practicalities, Rationalisations and Convergence of Practice(s). Tony Ridley, MSc CSyP MSyI M.ISRM

Quantitative & Qualitative Risk Analysis: Practicalities, Rationalisations and Convergence of Practice(s)

Threats, hazards, danger, perils and risk(s) do not materialise or present with numerical values or self-authoring, objective units of measure. Humans conduct varying degrees of analysis, which result in numbers assigned to these risk factors or categories.

Therefore, both qualitative and quantitive methods are required and practices in real world risk environments. The question is, how are quantitative and qualitative risk(s) analysis converged, rationalised or integrated from various sources, literature or disciplines?

In other words, try as we may, risk(s) aren't spawned with prescribed, objective numbers such as numbers extracted in a lottery or other games of chance.

Statistics, economics, mathematics and various other forms of calculations prescribe numbers to natural occurrences, phenomena, events and happenings, which means there are both qualitative and human judgement factors present in even the most seemingly objective of quantitative risk analysis. Therefore, practitioners, consumers and professionals need to understand how these numbers are derived and what process or positivist measures were taken to refine or improve the process of integration.

Mixed and multi-method analysis combines both qualitative and qualitative risk analysis practices. As the name(s) suggest.

Extracting some form of observed, recorded or defined process, numbers supplant people, processes and experiences at some point.

The process is both iterative and reflexive. Sometimes, the process and practice is documented in full. Many times, it is not and numbers, models, graphs and calculations dominate the conversation.

Rare, passionate and purist quantitative risk analyst assert that number are neutral and there is no hint of qualitative risk analysis attached to their work product or communications. Not only is this unlikely, it is also impractical to defend such a position in all instances, across all risk environments and contexts. Moreover, risk quantification and calculation is not dominated by or remains the sole bastion of econometrics or financial/accounting practices. Ironically, scientometrics has been analysing and critiquing this notion for some time now. However, all disciplines and practices benefit from elegant calculations and visceral graphics, but come laden with bias, assumptions and variable conventions of their own. Not to be taken at face value.

Three prominent approaches emerge in the convergence of quantitative and qualitative risk analysis, where the requirement is needed or greater knowledge and understanding will be derived from the process.

Segregated, sequential and convergent synthesis represent the three key approaches. Each with their own step process, nuanced approach and documented procedures. In short, traceability, origins, alternatives and truncations are all declared and mapped in full, as part of the empirical rigour and scientific method.

With the objective of capturing a richer, fuller, more informed understanding of the subject, including risk(s)
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Therefore, researchers, practitioners, scholars, academics and consumers of quantitative and qualitative risk analysis (especially where they are converged or curated) should look for these signposted stages, phases and practices.

While reliability, repeatability and validity may still vary, the output is likely far more objective and rigorous than hasty or abbreviated convergence of numbers and experiences, presented under the banner of quantitative risk analysis.

Especially where the risk analysis seeks to inform action, investment, priorities or decision(s).

It is important to remember that despite the seemingly unassailable reliability, objective and clarity of numbers, they are invariable assigned numerical values created by humans. Humans are flawed, inconsistent, influence by emotion, limited in their physical and conceptual views and dependent upon a constant stream of new and updated information.

In short, no one is perfect, nor are their calculations infallible in describing natural phenomena, complex problems or the real world, including risk(s). Especially where disparate concepts, literature, disciplines and thoughts converge.

Seems axiomatic, but requires reiteration and reminding, nonetheless.

In sum, real world and applied quantitative risk analysis is typically derived from some form of qualitative analysis. Therefore, structure methods, documented processes and reliable practices are required when utilising mixed, multi or hybrid methods.

Especially when it comes to the calculation, quantification or rating of threat, harms, perils, hazards or danger.

The number 5, 21 or 30 may seem real and more reliable than words and descriptions, but it remains the product of complex curation, consideration, analysis and processes, indicative of qualitative analysis.

Even in risk discourse or analysis.

In short, have a repeatable, transparent process, look for a process, ask for a process and use a process when evaluation, rationalising, converging or presenting either quantitive risk analysis, qualitative risk analysis... or both simultaneously.

Tony Ridley, MSc CSyP FSyI SRMCP

Risk, Security, Safety, Resilience & Management Sciences

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