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Data-Driven Decisions vs Future-Focused Risk

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Data-Driven Decisions vs Future-Focused Risk

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You’re exactly right: risk is inherently about the uncertain future, and data is by definition about the known past. In saying that, there is a balance, data-driven risk management is important, but it must be complemented by forward-looking judgment and foresight to avoid becoming purely reactive or anchored in the past.

This creates tension, because:

Data helps with known–knowns (trends, patterns, forecasting).

Novel risks, emerging threats, or black swans are inherently non-data-driven, requiring judgment, imagination, and intuition.

Sensemaking, scenario planning, and horizon scanning are better suited to these contexts.

And we know…..

The role of expert intuition (à la Gary Klein’s recognition-primed decision model) is crucial in high-stakes, uncertain environments.

Neuroscience also tells us that emotion and gut feeling play a bigger role in risk perception and decision-making than most frameworks admit (cf. Slovic, Kahneman).

The most resilient organisations balance evidence with foresight. Data can guide, but it should not blind.

Some further reading that may help is:

Taleb’s “The Black Swan” and “Antifragile” argue forcefully against overreliance on data in risk. (https://www.penguin.co.uk/books/56380/the-black-swan-by-nassim-nicholas-taleb/9780141034591)

Gigerenzer’s “Risk Savvy” highlights the strengths of intuitive judgment over statistical analysis in complex environments. (https://www.penguin.co.uk/books/181878/risk-savvy-by-gigerenzer-gerd/9780241954614)

Fraser & Simkins (2016) discuss the limitations of purely quantitative ERM models and the need for qualitative overlay. (https://bcs.wiley.com/he-bcs/Books?action=index&bcsId=9202&itemId=1118691962)

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Risk management material does typically focus on risk transfer (e.g. through insurance or contracting out) and can sometimes underplay risk sharing, which is more complex, relational, and systemic. This matters in multi-party settings like:

International development programs (e.g., DFAT-funded consortia),

Public–Private Partnerships (PPPs),

Supply chains,

Strategic alliances or ecosystems (especially digital or climate-related).

It is a complex area, but an important one, because:

Interdependent risk: Many risks today are no longer confined to single actors (think cyber, ESG, geopolitical shocks) and so “your” risk is co-produced with others.

Relational governance: Contracts may allocate responsibility but don’t eliminate interdependence.

Risk perception asymmetry: Your partner may have a very different appetite, tolerance, or even definition of the same risk.

So, risk sharing can occur through (examples, not an exhaustive list):

Contractual mechanisms: indemnities, service-level agreements, performance bonds, etc.

Collaborative governance: joint risk registers, mutual contingency planning, transparent escalation protocols.

Co-investment in mitigation: e.g., funding joint resilience efforts or capacity-building.

There are some helpful frameworks and resources, these include:

ISO 31000 encourages contextualising risk, but doesn’t deeply engage with inter-organisational or systemic risk sharing.

Project finance and infrastructure risk management literature (e.g. Grimsey & Lewis, 2002) provide a practical view of contractual risk allocation and shared responsibility. (https://www.sciencedirect.com/science/article/abs/pii/S0263786300000405)

The OECD’s work on systemic risk and the International Risk Governance Council (IRGC) explore risk interdependencies. (https://www.oecd.org/en/publications/mapping-emerging-critical-risks_eb642ada-en.html)

For more relational models, look at “Risk in Inter-organizational Networks” (Van Wijk, 2010) and Partnership Risk Governance literature.( https://www.researchgate.net/publication/4771324_Inter-_and_Intra-Organizational_Knowledge_Transfer_A_Meta-Analytic_Review_and_Assessment_of_Its_Antecedents_and_Consequences)

In strategic settings, developing a risk alignment matrix - mapping your risk posture alongside counterparties - can be a powerful tool to surface blind spots and dependency risks.

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Couple thoughts, having read this.

Risk sharing and risk in relation to others.

We talk about risk transfer but I did not see too much about risk sharing, for example, through close attendance to the terms of contracts. In many circumstances especially where there is collaboration with others (funding contracts in international development and financing; PPP´s, for two), we are talking about risks in the presence of others, i.e., systemic risks. Arguably no risk exists in isolation of other actors, especially in a strategic context, so understanding how your risk profile fits with (your perception of) the profile of others is often going to be important? Any guidance you can give on that, or resources?

Data-driven decisions

Maybe a bit pedantic but risk is about the future so it can´t be driven by data which exists after the event. It can be informed, at best, by similar situations in the past. Risk management is at least as much about intuition, especially in novel situations where by definition there is no data? The idea that we manage by attending to what we can already evidence rather argues against the pro-active management of possible uncertain future events? Curious as to your view. Might just be a language question.

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Great High Level summary. Have you examples of decision tree and swot analysis that you could share. AM

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More info on how to tailor risk guidance based on an organisation’s level of maturity

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More info on how to tailor risk guidance based on an organisation’s level of maturity

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Am unsure whether I am posting this as a query or comment! But thinking about organisations that don't have this level of maturity. I have certainly seen organisations that wouldn't be ready to implement these tools, as well as some that don't have risk appetite statements. Am thinking about how to best guide those organisations at their level of maturity.