"Data literacy" is often used to mean something close to junior analyst competence, which sets the bar so high that most people conclude it is not for them. The useful definition is much narrower.
What baseline literacy actually means
- Knowing what a number is measuring, and what it is not.
- Recognising when a sample cannot support the claim being made from it.
- Asking where a figure came from before repeating it in a decision.
- Understanding that a confident chart and a reliable chart look identical.
None of that requires statistics training. It requires the habit of asking one more question, which is a professional disposition rather than a technical skill.
Most bad decisions we reviewed did not come from bad analysis. They came from good analysis being quoted by someone who did not know what it excluded.
Where it sits in the framework
This is why baseline data literacy appears inside several standards rather than only in Data & Analytics. A project lead who cannot interrogate a delivery metric is exposed in exactly the same way as an analyst who cannot build one.