Excel or Power BI: when it's worth moving to automated reports
Excel isn’t a bad tool. It’s excellent for calculations, modelling and one-off analysis. The problem starts when Excel becomes a reporting system, because that’s not what it was built for.
Where Excel reaches its limits
When a report has to be repeated. A one-off analysis in Excel takes an hour. The same analysis every month for a year takes twelve hours, with a risk of error every single time.
When data comes from several sources. Combining accounting, till and CRM data in Excel is possible, but every update means several exports and manual reconciliation.
When file versions start multiplying. “Report_2026_final_v3_CORRECTED.xlsx” is a familiar sight. Half the meeting is spent working out whose numbers are right.
When the volume of data grows. At a few hundred thousand rows, Excel starts to grind to a halt.
What Power BI does differently
The key difference is that the connection to the data stays in place. A Power BI report isn’t a file of copied figures; it’s a live connection to the data source that refreshes itself.
Everything else follows from that: there’s no monthly report preparation, everyone looks at the same figures, and historical data builds up on its own, so comparisons with the previous year appear without any extra work.
Three signs it’s time to change
- Preparing reports takes more than a day a month. That’s part of someone’s salary being paid for copying and pasting.
- The figures differ depending on who prepared them. A sign that there’s no single source of truth.
- Decisions are made too late. If you learn about a problem from a report prepared three weeks after the fact, it’s often too late to react.
Do you have to give up Excel?
No. In practice, Excel stays where it’s strong: modelling, budgeting and ad hoc calculations. Power BI takes over the repetitive work: the regular reports that need to refresh without anyone touching them.
Incidentally, Power BI reads Excel files perfectly well, so your existing budget or plan files can become one of its data sources.
How they differ in practice
| Excel | Power BI | |
|---|---|---|
| Data refresh | manual export | automatic, on a schedule |
| Combining several sources | by copying and reconciling | a single data model |
| Who sees the report | whoever the file was sent to | everyone who has been given access |
| History for comparisons | built up by hand | builds up automatically |
| Versions | lots of files | a single source |
| Viewing on a phone | awkward | standard |
The table also explains the difference in cost: Excel is “free” until you count the staff time it demands every month. We set out what that figure looks like in practice in the article how much Power BI costs.
What to do with your existing Excel files
A common fear is having to start everything from scratch. You won’t.
Existing files usually remain useful in three ways: the budget becomes a data source for comparisons, the metric definitions developed over the years are carried over into the reports, and historical data is loaded in one go so that year-on-year comparisons work from day one.
In practice the move is gradual: first a handful of the most frequently repeated reports are moved across, and Excel stays for everything else. We describe the four-step process separately.
When Excel is perfectly adequate
It’s only fair to say this too. If your company is small, you prepare a report once a month in half an hour, the data comes from a single system and one person reads the report, Excel is perfectly fine and there’s no need to change anything.
The switch pays off once at least two of the three apply: repetition, multiple sources or multiple readers.
Where to start
If you use Rivilė or Finvalda, the quickest route is a ready-built report package that replaces most monthly Excel summaries: you’ll find the Rivilė and Finvalda versions on their own pages, and prices on the pricing page.
If you’re still weighing up what the platform actually is, start with the article what is Power BI.