The illusion of insight: When poor data drives security strategy

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22 September 2025

Cargo crime remains a persistent but often underreported threat, with fragmented data obscuring its real impact on supply chain operations. Misleading statistics and inconsistent reporting may create a distorted view of risk, resulting in misaligned policies and misplaced resources. This piece argues that the solution is not simply to gather more data at any cost, but to focus on obtaining better data: grounded, contextual, and fit to support meaningful decisions.

By Jeanne Albin - LandRisk Manager

In the age of information overload, where sensational articles and being first to release or comment on incidents, reports, figures, or statistics is increasingly often paramount, fake or fabricated data is no longer just a nuisance: it is a strategic risk.

Nowhere is it more dangerous, perhaps, than in the domain of crime analysis, where even well-intentioned stakeholders often rely on incomplete, inflated, irrelevant, or even entirely synthetic data to understand threats. The results? At best, a fake sense of clarity and awareness, born from misplaced trust; at worst, the adoption of irrelevant or outright inappropriate preventive measures and strategies.

In the field of supply chain security, unreliable data often arrives wearing the clothes of legitimacy: shiny charts (but without sources or scale), incident maps (but based on unverifiable or unstandardised reporting), or seemingly elaborate trend analysis (but extrapolated from narrow datasets and/or without nuance), for example, which create confident-sounding yet, in some cases, technically baseless claims. Purely quantitative comparisons between the number of incidents recorded in different countries over a specific period or a claim of a ‘13% increase in incidents in 2024 over the previous year’ (to quote our own numbers), for example, may be presenting a distorted threat picture if they do not address limitations such as the differences in national reporting procedures or variations in data collection, and are not supplemented by more detailed and nuanced (e.g., country-specific, exposure, impact, etc.) information. Such misrepresentations risk redirecting attention and resources away from areas of genuinely elevated threat to those that merely appear riskier due to more complete or visible reporting.

At the same time, with pressure mounting to produce timely and actionable insights and as the appetite for data-driven decisions continues to grow, the use of new technologies, and, in particular, AI tools appears particularly appealing. On the surface, these systems offer objectivity and efficiency. However, between made-up incident examples presented as real cases and a reliance on static (and, in cases, unverified) datasets, the risk of amplifying the aforementioned problems should not be neglected, particularly when discussing subjects where incident reporting is patchy.

And here, in fact, lies the true problem: quasi-systemic gaps in reliable data. In Europe, incidents impacting supply chain operations (and, at the forefront, cargo crime) continue to be underreported, and, in still too many cases, inaccessible, misclassified, lost in bureaucratic aggregation, or buried behind perceived-higher-impact events in public conversations. This is problematic for many reasons, not the least of which is that this distorts the impact of criminality on logistics operations: when a theft from a truck is recorded as a ‘property crime’ or ‘vehicle crime’, for example, the supply chain element is erased—and so is the opportunity for an educated, intelligence-led response. In this vacuum, it is easier for filler or lesser-quality data to seal the gap.

This is precisely the kind of issue addressed in the upcoming Risk Intelligence webinar: “Data Deficit in Cargo Crime Reporting: How Gaps Undermine Security, Policy, and Prevention Efforts.” While the cargo crime threat itself is real and remains significant throughout Europe, gaps and difficulties in accessing structured, reliable, and precise incident-level reporting allow speculative discourses to set the agenda, with consequences ranging from misaligned priorities, misinformed or imprecise risk maps, and policies that treat symptoms rather than causes.

For supply chain operators, security professionals, planners, and regulators alike, the answer is thus not to rely on data at any cost, but to demand verified and nuanced statistics and analysis—the only kind that can truly be used to design intelligence-led policies. Fake certainty is worse than acknowledged uncertainty, and in the world of supply chain security, it can be the difference between preventing an incident and reacting too late.

For more on why context and verification matter, read our briefing: “Why is ChatGPT not an intelligence analyst.”

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