A finance team that explains the figures
Correct reports nobody understands, comparisons without context and spreadsheet models only one person can touch. What each finance profile should know about data, the most common mistakes and a 30-day training plan.
The 5 most common mistakes
Finance calculates well; what fails most often is explaining what the figures mean for whoever has to decide.
Reports only their author understands
Tables full of figures with no clear conclusion: leadership does not know what to decide.
How to avoid itStart every report with the main message and show only the figures that support it.
Percentages without the base
One cost rises 200%, but it was €300; another rises 5% and it is €200,000.
How to avoid itAlways show the absolute change next to the percentage.
Mistaking correlation for cause
Two indicators rise together and the conclusion is that one causes the other.
How to avoid itLook for the business explanation and test it before deciding.
Spreadsheet models nobody else understands
Chained formulas that depend on one person; if they leave, nobody knows how they work.
How to avoid itDocument assumptions and sources, and separate data, calculations and results.
Forecasts presented as certainties
A budget or forecast is presented as a single figure, with no range or assumptions.
How to avoid itGive scenarios (cautious, base and optimistic) and explain which assumptions change them.
Sound familiar?
Measure your team’s level with the free self-assessment: 20 statements scored by dimension.
Download the self-assessment →What each profile should know
The levels come from the data literacy framework: basic, use, analysis and management. Not everyone needs to reach the same one.
| Profile | What they should be able to do | Level |
|---|---|---|
| Accounting | Record with judgement, spot errors and understand how their data is used in reports | Basic / Use |
| Controller / financial analyst | Analyse variances, build clear models and explain the figures to the business | Analysis |
| Finance director | Tell what the numbers say and decide with scenarios | Use / Management |
| Managers in other areas | Read their P&L and understand their budget | Basic |
Your data training, in three steps
Short training using the team’s real data. Each step links to the guide and the template.
Measure the level
Give each profile the free self-assessment and pick the two or three gaps that most affect the area’s work.
Train with real cases
Short sessions: reading variances, combining absolute and percentage change, building scenarios and presenting a conclusion.
Make it stick
A common report format with the message at the top, documented assumptions in models and a go-to person.
Frequently asked questions
Why does a team that already works with numbers need data training?
Working with numbers is not the same as communicating them or questioning where they come from. What fails most often is explaining what the figures mean for whoever has to decide.
What should other areas know about finance?
How to read their P&L and budget, the difference between revenue and cash received or between cost and payment, and whom to ask.
Do they need to learn BI tools?
It helps the analyst. For the rest of the team, reading dashboards well and knowing where their data comes from is enough.
What does it have to do with the AI Act?
Article 4 deals with AI literacy for people who use AI systems in the company. If the team uses AI assistants to analyse or draft reports, it is worth including in their training.
What level of data literacy does your team have?
Free five-minute assessment: your score in the four dimensions and what to work on first.