We have this conversation with clients on a regular basis. The conclusion is always the same: the questions asked of BI change faster than the answers. And there is little your team can do about that.
Three forces overtaking your reports
Three developments are making it clear, all at once, that reports alone no longer cut it.
External parties want the data, not the report. Investors, auditors and chain partners no longer settle for a PDF or an Excel file. They want a dataset they can run their own analyses on. Drillable, reproducible, on their schedule.
Regulation enforces data discipline. CSRD, EU Taxonomy, energy reporting: everything must be auditable per entity, per country, per period. That is a data design question, not a reporting question.
And then there is AI. We will keep this short: AI mainly exposes, painfully, what was already broken. Point a Copilot or agent at your data model and within a day you will see where it creaks. Anyone with business logic buried in hardcoded filters gets nonsense back.
Grown around yesterday's questions
So why do so many BI environments grind to a halt? History. A question came in, the team built something, and the next question stacked on top. Nobody had time to zoom out.
We recognise the pattern at almost every organisation we speak to:
- Pipelines run on legacy technology drifting towards end-of-life
- Business logic lives in report filters instead of in the data model. Ten filters switched on to produce one calculation
- External data lands manually on a SharePoint, in varying formats, at varying moments
- The data model grew out of reports instead of business questions
- The team works reactively and never gets round to thinking ahead
That last one is a consequence. Treading water all day leaves no room for looking ahead.
Data is bigger than BI
The solution starts with how you see BI: as one of the consumers of a broader data platform.
The principle: one source, many consumers. "One version of the truth" is a nice ambition. In practice every consumer needs their own truth. An investor looks at things differently than a controller. What you do manage centrally: the source, the definitions, the logic. You write every calculation out once, in the model. Everyone who uses it looks at the same facts.
The same goes for Excel. The problem sits in the export: from that moment on, nobody knows what happens to the data. Turn it around: connect Excel to the platform. The end user keeps their freedom and you keep governance, security and traceability.
That way you separate producing data (central, controlled) from consuming it (free, with the end user). Whether that happens through a dashboard, an API, an investor portal or an AI agent.
Technology is 20%, design is 80%
AI now does most of the coding work on a platform like this. The centre of gravity has shifted to the front: the design of your golden model.
That means sitting down with the business to define the 10 to 20 core questions per domain. Which problems do we solve daily? What do we want to steer on? From those you derive your facts, dimensions and KPIs. Once that model stands, more than half the work is done.
And yes, that brings you to dull words like data governance and data dictionary. Dull, but this is exactly what makes your numbers traceable. We saw a rounding difference of hundreds of millions at a client that nobody could reproduce, because the calculation was buried under a pile of filters. Record your calculations centrally, with version control, and you answer that question in minutes.
AI-ready without a separate AI programme
Do this well and your data is AI-ready without setting up a separate programme for it. Your model is documented and your logic is recorded centrally. An agent you ask "how many deals did this team close last month?" gives a sensible answer, because the context is simply there.
Better still: you flip the questions. You get a notification when a booking has failed, instead of checking the system yourself to see if everything went right. That is the difference between viewing reports and data products that work for you.
Start small, but start with design
Chances are you already own the technology. Many organisations have their Microsoft stack in place, often including licences they barely use. The gains are in designing differently.
That is why we start by looking. What is actually there, what is its quality, where do you want to go and what is the gap? The result is a roadmap with an explicit go/no-go moment. First a clear view of reality, then the building.
Not sure whether your current BI still delivers what it should? Request a BI Quick Check. We take an honest, independent look and tell you where you stand. Even if the answer is that everything is in good shape.
Already know things need to change? Then start with a Discovery. In six weeks we map where you stand, what you need and what it costs. You get a concrete plan, not a report for the drawer.
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