How to measure your team’s data literacy before spending on training
Most data training programmes start with the course. The other way round works better: measure first where each team stands, then train only where there is a gap. Measuring doesn’t require a two-hour exam.
Why measure before training
A one-size-fits-all course bores those who already know and falls short for those who don’t. Measuring first tells you which teams need training, in what and at what level. It also gives you a baseline to check later whether the training worked.
What to measure: four capabilities
- Reading: understanding what a figure represents, where it comes from and what an indicator really measures.
- Working with data: finding, cleaning and preparing it independently.
- Analysing: comparing, segmenting and spotting patterns without always relying on an analyst.
- Arguing with data: backing a decision with data and explaining it precisely, without overstating what it shows.
These are the same four dimensions used by our free Data Literacy assessment. They fit the “information and data literacy” area of DigComp, the European digital competence framework.
How to ask so it isn’t an exam
Ask “how well do you read a chart, from 1 to 5?” and almost everyone answers 4. Pure self-assessment inflates results. A mix works better:
- Situation questions: “This indicator has gone up 40%. What would you check before presenting it to the committee?”
- A real chart with a common trick, such as an axis that doesn’t start at zero, to see who spots it.
- A few self-rating questions, only to see how people perceive themselves and compare it with the above.
Ten or twelve questions per role are enough. If the survey takes more than 15 minutes, people drop out or answer at random.
How to read the results
- By team, not by person: the goal is to decide where to train, not to grade people. If they fear it will be used against them, they won’t answer honestly.
- Against the level expected for the role: an executive doesn’t need to clean data, but does need to spot a poorly argued conclusion.
- Look for the most expensive gap: the team where a misreading has most impact, such as finance or risk, goes first.
What to do next
- Set the target level for each role with a levels framework.
- Prioritise two or three teams to start with.
- Train with their own data and real cases.
- Measure again after three to six months with equivalent questions to see progress.
Frequently asked questions
How often should we measure?
Once at the start and again after three to six months. After that, once a year is usually enough.
Can the results be used to assess individuals?
Better not. Use them by team to decide on training. If they are used to rate individuals, people answer defensively and the data stops being reliable.
Informational content.
What level of data literacy does your team have?
Free 5-minute assessment: your score on the 4 dimensions and what to work on first.