Finnish companies are collecting more data than ever. The CRM fills up with customer information, the ERP runs operations, and financial management produces reports. Yet only 16% of companies are truly “data-driven” – at a level where information is integrated into decision-making at every level of the organisation (SD Times). The rest make decisions in a way that is hard to admit out loud: based on experience, gut feeling and whoever’s voice is loudest in the meeting. The amount of data isn’t really the problem — the problem is how the data is used.
As many as 61% of C-level executives admit that decision-making in their company is only weakly or rarely data-driven. Yet 90% of organisations say data is critical to success (Passive Secrets).
We know, but we don’t do… A classic Finnish problem – or actually a global one.
Internationally, the gap is clear. In the United States, 77% of companies report making data-driven decisions. In Europe, Germany and the UK follow at 69%, and Sweden at 48%. In Finland, according to Statistics Finland, 41% of companies performed data analytics in 2023 — but only 32% with their own staff. BI software, the tool that actually turns data into decisions, was used by only 39% of companies. Among the smallest companies, the figure drops to 26%.
Based on personal experience, I would add that even when BI tools are in use, management is still rarely data-driven. Far too little of the potential of BI tools is put to use. This is partly because the data is too fragmented, which makes it difficult to use. Almost everyone will surely recognise those dozens or hundreds of Excel files at their own workplace that can’t be used together in any meaningful way.
The foundation of data-driven management
So what is data-driven management in practice? Let’s dig into the basics for a moment.
Data-driven management is a concept that has been circulating in corporate culture for quite some time. However, it has usually been more talk or aspiration than an established management model.
Put simply, data-driven management means that a company knows how both to manage information (information management) and to lead with it (data-driven leadership). These are two different things, and this is exactly where most companies stumble. People talk about the same thing in different languages — or at worst, don’t talk about it at all.
Good data-driven management requires coordination between two worlds: management and IT. Management knows what information is needed to support decision-making — IT knows how to build it efficiently. When these two actively talk to each other, something useful and beautiful is created. When they operate in their own silos, the result is more Excel files and pointless dashboards. You end up paying an analyst for copy-paste work instead of analysis.
Information management — answers the question: what data do we have, where is it located and how is it managed?
This is the technical and operational foundation on which everything else is built. In other words, the cornerstone of data-driven management as a whole. The core of information management is simple: the right information, in the right place, at the right time — and reliable enough that you can actually depend on it.
Information management is built on three mutually supporting areas:
Data architecture creates the technical framework and structures. It defines how data is collected, where it is stored and how different systems communicate with each other. A well-built data architecture is like the frame of a house — you don’t see it, but without it everything stands on unstable ground.
Data governance ensures the quality, security, integrity and availability of data. It includes the rules, processes and responsibilities that guarantee data stays reliable throughout its entire lifecycle. Who owns which data? How are errors corrected? What is the single source of truth that everyone can rely on? These are the questions of data governance — and without answers to them, every department operates with its own version of the truth.
Data analytics turns raw data into understandable information. It identifies trends, spots anomalies and produces insights to support decision-making. Analytics is where data starts to speak — but only if the two previous areas are in order. The world’s finest analytics tool produces garbage if the data fed into it is unreliable or fragmented.
Unstructured Excel files are a good and common example. Everyone builds their own with their own logic, their own headings and their own formatting. No one agrees on common ground rules. A year later, the company has a jungle of dozens of files in which no one can find the truth anymore — let alone cross-compare the figures.
Try it in practice: export a report from your CRM and look at the format of the data — how dates are recorded, how customer names have been entered, how numbers are formatted. Then open the Excel file your sales team uses to track its own figures. Most likely the two can’t be compared without significant manual work. And this is exactly where one of the biggest pitfalls of data-driven management lies — when data isn’t collected with a consistent structure, combining and comparing it becomes nearly impossible.
Data-driven leadership — answers the question: how does information guide what we do?
If information management is the production of raw material, data-driven leadership is the moment that raw material is turned into something meaningful. It is a way of leading in which decisions are based on data — not on gut feeling, not on experience alone, and not on whoever’s voice is loudest in the meeting.
In practice, this means that when sales drop, you don’t guess the reason — you look at the data. When you launch a new product, you don’t rely on gut feeling alone — you study the customer data. When you budget for next year, you don’t extrapolate by hand from last year’s Excel — you analyse trends and scenarios.
Let’s say a company’s CEO notices that customer churn has increased. In the traditional model, the issue is discussed in the management team, each person presents their own view, and eventually something is decided — more or less on feel. In a data-driven company, you look at the data first: in which customer segment is churn growing, at what point in the customer journey do customers leave, is there a common denominator in industry, size or product? Only then is a decision made — and that decision is based on reality, not assumptions.
Data-driven leadership doesn’t mean experience and intuition get thrown out. On the contrary — the best decisions are made when years of experience and hard data are in dialogue with each other. Data tells you what is happening. Experience helps you understand why.
But this is where you often run into the biggest obstacle — and it isn’t technology. It’s culture.
Data-driven leadership requires a change in mindset across the organisation. Decisions need to be justifiable, and that can feel uncomfortable, especially for leaders who are used to relying on their experience alone. Data challenges assumptions. It sometimes shows that what has been done for years hasn’t been as effective as people thought. This takes the courage to face the truth — and an organisational culture in which data is used for learning, not for blame.
Information management and data-driven leadership are not competing concepts — they are two sides of the same coin. One builds the foundation, the other puts it to use. Without high-quality data, you can’t lead with data. And without a culture of data-driven leadership, high-quality data just gathers dust on servers.
Put simply: if information management is in order but data-driven leadership is missing, the company has a great instrument panel — but no one looks at it while driving. If, on the other hand, the will to lead with data exists but information management is in a mess, decisions are made on the basis of unreliable data. Both are equally dangerous.
What do the numbers say?
Data-driven management isn’t built overnight. It requires patience, a systematic approach and, above all, commitment from the entire organisation. But once the groundwork is done properly, the results start to speak for themselves.
A good example can be found in the events sector. Levi’s Stadium, home arena of the NFL team San Francisco 49ers, built a so-called Executive Huddle command centre that collects real-time data from more than ten different sources: ticket sales, food and beverage outlets, merchandise stores and social media. Everything was visualised on the SAP HANA platform for the management team — in real time, during the game.
In practice, this meant that if a hot dog stand got congested, the system would raise an alert and staff would be reassigned immediately. If a particular piece of merchandise started running out in a specific section, restocking was ordered before any sales were lost. Decisions are no longer made at the next Monday meeting — they are made at the moment they matter.
The results were measurable: food and beverage sales per person grew by 35% and game-day customer satisfaction rose by 43%. Both correlate directly with revenue growth.
There’s also plenty of research on the subject. According to McKinsey, data-driven organisations are 23 times more likely to outperform competitors in customer acquisition, six times more likely to retain their customers and 19 times more likely to be profitable. In practice, the benefits show up concretely in everyday work — decisions get faster, problems are detected earlier and resources are allocated correctly. A BARC study showed that companies using data achieved on average an 8% increase in profits and a 10% reduction in costs (Keboola).
The journey isn’t a straight line. Data architecture has to be built, people have to be brought on board, and culture changes slowly. But every step in the right direction is a step towards an organisation where leadership is based on information — not on recollections of last quarter or last year.
Where to start?
Data-driven management can sound like a big project. And it can be — if you try to do everything at once. But you don’t have to.
The best starting point is surprisingly simple: take a moment to think about where in your company you’ve been missing information to support decision-making. What is the question your management team has never had a proper answer to? What is the report someone compiles by hand every week, taking hours of work? What is the metric people disagree on because everyone looks at a different source? That is your starting point.
There’s no point trying to solve everything at once. Data-driven management is built layer by layer — and that’s a good thing, because each layer delivers concrete benefits even before the whole is complete.
First, get the data in order: a consistent structure, reliable sources and systems that talk to each other. Then analytics — information in a visual format that shows what matters at a glance, without hours of wrangling Excel. And only on top of that, a culture of data-driven leadership — decisions based on reality, not on assumptions or on whoever’s voice is loudest.
And one important note: if Excel files are still part of everyday work — as they are in most companies — at least agree on common ground rules for using them. Create one structured template in which the format of name fields, the date format and the number structure are the same everywhere. It sounds small, but it’s a concrete first step towards data that can actually be compared and put to use.
Remember to keep data and visualisation separate. Raw data goes into Excel — row by row, in clean form, without colours, merged cells or formatting. Visualisations and summaries are built separately. That’s how your ERP and CRM handle data anyway.
The journey begins with a single question. What matters most is that it begins.
At Nordo, we help companies turn fragmented data into clear support for decision-making. We don’t sell technology for technology’s sake — we help you identify where data-driven leadership brings you the most value, and we build the solutions around that.
Complexity to Clarity. It’s not just a slogan — it’s how we approach every customer relationship.
Would you like to see how data-driven management could transform decision-making in your company? Get in touch.
Sources
SD Times. (2024). While most companies focus on data, only about 16% are ‘data-driven’. https://sdtimes.com/data/while-most-companies-focus-on-data-only-about-16-are-data-driven/
Passive Secrets. (2025). 55+ Data-Driven Decision-Making Statistics & New Trends 2025. https://passivesecrets.com/data-driven-decision-making-statistics/
Statistics Finland. (2023). Data analytics was performed by 41% of enterprises in 2023 (in Finnish). https://stat.fi/fi/julkaisu/cl8junjuw8i2g0cw15veu2sl2
Keboola. (2023). 5 Stats That Show How Data-Driven Organizations Outperform Their Competition. https://www.keboola.com/blog/5-stats-that-show-how-data-driven-organizations-outperform-their-competition