How mature is your company when it comes to data?

Yes, you can roll out an exciting new AI tool… but if your data is scattered across different systems, no one knows where anything lives, and Excel is still the solution to every problem, then it’s no surprise the tool doesn’t deliver what you expected. But how do you know if your data foundations are solid enough to get AI going? Easy: by looking at your data maturity.

Why data maturity makes all the difference

The data maturity model shows how ‘grown-up’ your organization is in handling data and places you in one of five levels. If you’re at level 1, your data maturity is still in its infancy and at level 5, you’re truly next-level. Your level is determined by how you store your data, how you analyze it and how you use the results that come out of it.

The 5 levels: from baby steps to full-blown unicorn

Level 1 - Held together with duct tape

→ Files are everywhere and you spend fifteen minutes searching for “that one Excel file” before a meeting starts.

→ Colleagues argue about numbers because everyone has their own manually compiled version.

→ You make important business decisions based on assumptions and gut feeling, because hard facts are missing.

Level 2 - Operational insight

→ You have dashboards that show what’s happening in your business, but you’re always responding after things happened.

→ Decision-making is finally based on facts from dashboards instead of “I think so.”

→ Monthly reports give you overview, but you still miss real-time insight to shift to another approach immediately when needed.

Level 3 - Smarter steering

→ Your system alerts you when key numbers shift, so you can act before issues escalate.

→ Teams no longer need to hunt for patterns themselves - alerts point them in the right direction.

→ KPIs and thresholds steer your operations, reducing waste structurally.

Level 4 - Predictive power

→ Your data predicts what customers need and when, even before they call to place a new order.

→ Inventory replenishes automatically before shortages happen.

→ Planning and margins improve because you anticipate rather than react.

Level 5 - Data powered

→ AI agents autonomously handle routine tasks, while your people focus on strategy and meaningful work.

→ The organization scales effortlessly, without needing a proportional increase in staff.

→ Your processes run 24/7; your team monitors where the risks actually are.

Which level are you at?

So how do you know which level your company belongs in? Your answers to the questions below will give you a pretty good idea.

Where does your data live?

A) Data? I throw everything into Excel and email files all day long

B) In a dashboard like Power BI, but I only see things in hindsight when we make reports

C) We have a central data platform with alerts when something unusual happens

D) We run predictive models on our data across the business

E) Our AI agents operate autonomously and keep everything running smoothly

How do you make decisions?

A) Based on gut feeling and scattered numbers - guesswork is my middle name

B) Based on handmade monthly reports, which is lots of work, though

C) Based on real-time KPIs with alerts

D) Based on forecasts and trends from my platforms

E) My systems decide on their own and I just check in every now and then

What’s your biggest data challenge?

A) Finding that one Excel file…

B) Getting insights faster, so I’m not always behind

C) Acting proactively based on data - not reactively

D) Keeping up with growth without adding more people

E) Challenge? Let me ask my AI agent…

If you mostly answered E, you’re a rare exception: I’ve got nothing left to teach you about data maturity 😉.

Did you select mostly A, B, or C? Then there’s still a long way to go before you can call yourself data mature. But don’t worry, with a few focused tweaks, the next level is within reach.

Full throttle to the next level

Now that you know your likely level, how do you move up? With a few concrete actions, you can often make big strides and see instant improvements.

On to level 2: Map your sources and define one single source of truth per domain. Sales from the CRM, stock from the ERP. Set clear ownership rules.

On to level 3: Build alerts into your dashboards that are not just showing what happened, but build alerts that go off when action is needed. If waste goes above 3%, for instance, the team gets notified.

On to level 4: Add predictive models for demand, purchasing timing, and maintenance. You’ll start anticipating instead of reacting.

On to level 5: Identify processes with low risk, high frequency, and clear rules. Let AI agents run those processes, with human approval where needed.

Start with structure, not tools

My biggest piece of advice on data maturity? Start by structuring your data, not by buying expensive tools. Create clarity first: where does your data live? What do you use? What’s missing? Once you have that foundation, real progress follows and then you can start thinking about a data platform. Otherwise, you’ll keep investing in tools that solve nothing because the basics are a mess.

Curious where your biggest opportunities lie? Download our orangepaper on AI readiness for the full picture, or book an AI Discovery Track right away. Within 4–6 weeks, you’ll know exactly where you stand - and which steps deliver the most impact.