The profile this programme fits
This is not a programme for data scientists or statisticians. They already have the technical training to spot these errors at the methodological level. This programme is for the people who receive the output of that analysis and have to make decisions based on it.
It fits people in roles like marketing management, operations, commercial strategy, finance, product management, and general management. People who work with data regularly but whose primary expertise is not statistical. People who are confident with numbers but have not formally studied the cognitive traps that sit between data and interpretation.
Roles that tend to find this useful
Marketing & Growth
Attribution is one of the most correlation-heavy areas in any business. Marketing professionals regularly deal with data where causation is ambiguous and the temptation to draw strong conclusions is high.
Operations & Supply Chain
Efficiency metrics, throughput data, and supplier performance figures are all prone to the same thinking errors. Especially survivorship bias and misleading averages.
Finance & Commercial
Financial analysis often involves spotting trends in time-series data. That is exactly the context where spurious correlations and anchoring effects appear most frequently.
Senior Leadership
Leaders who receive synthesised data and make strategic decisions based on it are in a particularly important position to catch interpretation errors before they propagate into major commitments.
No prior statistical knowledge required
The programme assumes no background in statistics or data science. The concepts are explained through examples first, with any necessary technical vocabulary introduced only after the intuition is established. If you can read a bar chart and follow a line graph, you have all the technical foundation you need.
Some participants find that the programme changes how they think about data they have been working with for years. That is a common response. The errors are not obscure. They are hiding in plain sight.
Industries where this applies
The thinking errors covered in this programme appear across all sectors. The specific examples we use are drawn from retail, financial services, professional services, technology, and manufacturing. The principles transfer directly to any industry where decisions are made using data.
We have also structured the programme so that each module can be connected to your own industry context. The application exercises at the end of each module invite you to identify where the same error might appear in your specific work environment.
A quick self-check
This programme is likely a fit if any of the following describes your situation:
- You regularly receive reports or dashboards and need to make decisions based on them
- You have noticed that data sometimes seems to support whatever conclusion the presenter wanted to reach
- You want a structured way to question data claims without needing to become a statistician
- Your team makes decisions that involve interpreting trends, comparing metrics, or evaluating performance data
- You are responsible for training or developing colleagues who work with business data