Your data is telling you
a story. It might be lying.
A structured training programme that teaches business professionals to catch the thinking errors hiding inside their own reports, dashboards, and decisions.
The gap between data and good decisions
Most businesses have more data than ever. Fewer have the thinking skills to interpret it without falling into well-documented cognitive traps. This programme focuses on exactly that gap.
We work through real business scenarios rather than textbook theory. The kind of situations that actually appear in board reports, marketing dashboards, and quarterly reviews.
Correlation is not causation
Probably the most misunderstood concept in business analysis. We break it down through examples your team will recognise immediately.
How the programme works
Three structured phases that move you from recognising errors to building a lasting habit of sharper data thinking.
Recognise the patterns
Before you can catch a thinking error, you need to know what it looks like. The first phase introduces each major cognitive trap through a real business example pulled from sectors like retail, finance, and operations. No abstract theory. Just situations that feel uncomfortably familiar.
Covers correlation errors, base rate neglect, and anchoring bias in reporting contexts.
Dissect real decisions
The second phase goes deeper. We take documented business decisions where data was misread and walk through the exact point where the thinking went wrong. These are not cautionary tales. They are structured case studies with clear takeaways you can apply to your own work.
Includes analysis of survivorship bias in strategy, misleading averages in performance reviews, and spurious dashboard trends.
Build your mental checklist
The final phase is about habit formation. You leave with a practical set of questions to apply every time you encounter a data claim, a chart, or a recommendation backed by numbers. Not a rigid framework. A flexible way of thinking that gets faster with use.
Includes a reference card with the twelve questions to ask before acting on any data-backed recommendation.
What learning looks like
Thinking errors we cover
Each module is built around a specific, named error. You will know what to call it, where it appears, and how to catch it before it shapes a decision.
Good data, wrong conclusions
The problem is rarely the data itself. Most organisations have access to reasonably good information. The problem is the thinking applied to it.
When two metrics happen to move together, it is natural to assume one is driving the other. When a strategy works for a handful of visible companies, it is natural to copy it. These are not failures of intelligence. They are predictable features of how human reasoning works under pressure and time constraints.
This programme makes those patterns visible. Once you can see them, they become much harder to ignore.
About the ProgrammeReady to sharpen your data thinking?
Individual access and team packages available. Start by finding out if this programme fits your role and your organisation.