What you'll take from this
Most SMEs sit between stage 1 (Data Aware) and stage 2 (Data Proficient). That's not a problem — it's a starting position. The problem arises when the organisation doesn't know where it stands and has no plan for the next step.
Data maturity isn't just about technology. The Coleman Data Maturity Model measures progress across seven dimensions: from business strategy and data quality to organisational culture and governance. Buying software without addressing the other dimensions is spending money without results.
The goal isn't stage 5 — the goal is the logical next step. For a company at stage 1, AI solutions from stage 5 aren't relevant. The priority is structure, data quality and a single source of truth.
The three biggest obstacles for SMEs are predictable: the resource paradox ("no budget"), the talent shortage ("data scientists are unaffordable") and the culture barrier ("we've always done it this way"). Each has a proven solution.
What is data maturity for SMEs?
Data maturity is the degree to which an organisation structurally uses data for decision-making — from ad-hoc Excel reports to predictive analytics that autonomously adjust processes. The Coleman Data Maturity Model, designed specifically for SMEs, measures this maturity across seven dimensions and five stages. Den Otter Solutions uses this model as the basis for the Data Maturity Scan, which gives SME businesses a clear position in 28 questions and a concrete growth path.
The director knows data matters. There's been investment in software, there are dashboards, there's someone who "does something with Power BI." But the question that's rarely asked: where does the organisation actually stand? And what's the logical next step? Without that position check, every data initiative becomes a gamble — and most SMEs invest in stage-3 solutions while they have stage-1 problems.
The Coleman Data Maturity Model distinguishes five stages of data maturity, from Pre-data (stage 0, fully analogue) through Data Aware and Data Proficient to Data Savvy (stage 3, the optimal level for many SMEs) and ultimately Data Driven and Data Optimised. Den Otter Solutions uses this model as the basis for the Data Maturity Scan, which maps an SME's position across seven dimensions: business strategy, data management, human capital, technological infrastructure, analysis application, governance and organisational culture.
How do you measure data maturity?
Before the stages make sense, it needs to be clear what's being measured. Data maturity is assessed across seven dimensions that together determine whether an organisation genuinely operates in a data-driven way. The Coleman Data Maturity Model, which Den Otter Solutions uses as the basis for the Data Maturity Scan, scores each dimension from stage 0 to stage 5.
Business Strategy & Data Integration
Does data function as an afterthought or as the driving force behind strategy?
Data Management & Quality
Does the organisation work from a single truth or from fragmented spreadsheets?
Human Capital & Skills
Does the team have the data literacy to interpret numbers correctly?
Technological Infrastructure
Is the infrastructure scalable and are systems interconnected?
Analysis Application & Insight
Does the organisation look back (what happened?) or forward (what will happen?)?
Governance & Security
Is data security guaranteed and is there GDPR compliance?
Organisational Culture
Are decisions made based on facts or on intuition?
An organisation can be at stage 3 on one dimension and stage 1 on another. That's normal. The model reveals where the weakest link sits — and that's where investment delivers the greatest return. Can you identify the weakest dimension in your organisation? That's where the biggest gains are.
Which stage of data maturity is your organisation at?
In practice, most SMEs sit between stage 1 and 2. The goal of this model isn't a jump to stage 5 — it's identifying and taking the logical next step.
The organisation operates fundamentally analogue. Data is a by-product, not a tool. The priority is digitisation — eliminating paper processes and structurally capturing data.
Recognisable by
There's an awareness that data matters. People collect data, but it ends up in isolated silos and endless spreadsheets — "Excel hell." Reports are manual, error-prone and dependent on specific individuals.
The risk
The Collector Trap — the focus is on owning data, not using it. Systems become contaminated quickly due to a lack of standards.
The next step
Define data standards. Start by cleaning up the three most important data sources. Read how
data governance without bureaucracy structures this process.
Recognisable by
Basic processes are defined. Data quality is being actively pursued and the first dashboards are emerging. Successes are no longer flukes, but still require significant manual effort.
The risk
Stagnation. The organisation gets stuck producing "nice reports" that never lead to action.
The next step
Connect systems and create a
Single Source of Truth. Shift from standalone dashboards to a central data model. This is the moment when the Data Maturity Scan by Den Otter Solutions delivers the most value — it reveals which dimensions are blocking growth to stage 3.
Recognisable by
Standardisation across the entire company. Data is no longer purely for accountability but forms the basis for strategic decisions. Cross-functional teams share insights — Marketing and Sales look at the same definitions.
The SME advantage
The organisation is agile enough to act directly on insights, without the bureaucracy of a large corporation. This is the optimal level for many SMEs.
The next step
Shift from descriptive ("what happened?") to diagnostic ("why did it happen?"). Invest in analytical skills within the existing team.
Recognisable by
Data is woven into the organisation's DNA. Processes are adjusted based on real-time insight. Predictive analytics support decision-making — the organisation anticipates rather than reacts.
The shift
Employees are no longer data processors but analysts supported by technology. The dashboard is no longer the end product — it's the starting point of a conversation.
The next step
Automation of routine decisions. Implement alerting and exception-based reporting.
Recognisable by
Predictive and prescriptive analytics are integrated into daily operations. Data is treated as a product in itself. Continuous improvement is the norm — not the project.
The reality
Few SMEs reach stage 5 fully, and they don't need to. The value is in the journey, not the destination. A company operating solidly at stage 3 outperforms one that sprints to stage 5 without having the foundations in order.
Why do SMEs get stuck at stage 1 or 2?
The three biggest obstacles to data maturity in SMEs are the resource paradox, the talent shortage and the culture barrier. Den Otter Solutions sees these barriers recur at virtually every SME that wants to make the transition to data-driven working.
The resource paradox. "We don't have the budget for a data platform." Many entrepreneurs associate data analytics with heavy investments. This is the Resource Constraint Paradox: insights are needed to save costs, but the resources to generate those insights are lacking. The solution: cloud technology breaks this cycle. With Power BI and Microsoft Azure, you pay per use — no heavy upfront investments. Access to enterprise infrastructure at a fraction of the cost.
The talent shortage. "Data Scientists are unaffordable." Experienced data professionals are scarce and expensive. The solution: democratisation. Through intuitive tools and temporary external expertise for setup, existing employees can be trained as "Citizen Data Scientists." Rob den Otter fulfils the role of Analytics Translator — the bridge between the business question and the technical solution, so the SME doesn't need to hire a full-time data specialist.
The culture barrier. "We trust our gut feeling." In many SMEs, the founder's intuition is the primary strategy. The transition to data-driven working feels like a loss of control. The solution: data doesn't replace intuition — it reinforces it. Data serves as evidence to validate gut feelings. A mature data culture doesn't mean the computer is in charge, but that decisions are made based on facts rather than assumptions.
ConclusionClimbing the maturity ladder isn't a sprint — it's a strategic journey. For an organisation at stage 1, complex AI solutions from stage 5 aren't relevant. The priority is structure, data quality and ownership.
It starts with a position check. Not a vague feeling of "we should do something with data," but a clear picture across the seven dimensions: where does the organisation score well, where is the weakest link, and what is the logical first investment?
The Data Maturity Scan by Den Otter Solutions provides that position check. In 28 questions based on the Coleman Data Maturity Model, it becomes clear which stage the organisation is at — and what the concrete next step is. Not a hundred-page report, but a clear profile with an action list.
Frequently asked questions
How long does it take to grow from stage 1 to stage 3?+
For a typical SME with 50-200 employees, a realistic timeline is twelve to eighteen months — provided there is focus on the right dimensions. The Data Maturity Scan by Den Otter Solutions identifies which dimensions deserve priority.
Can I skip stages in the data maturity model?+
No. Each stage builds on the previous one. Without the data standards from stage 1, the central data model from stage 2 is unreliable. Without that data model, the cross-functional insights from stage 3 are impossible. Skipping stages leads to technical debt that is more expensive to fix later.
Is the Coleman Data Maturity Model suitable for every type of SME?+
Yes. The model is specifically designed for SMEs and is sector-independent. The seven dimensions apply to a logistics company, a hospitality chain or a healthcare organisation. The application per dimension differs — the framework is universal.
What if my organisation is at stage 3 on one dimension and stage 1 on another?+
That is normal and occurs at most companies. The model makes precisely this inequality visible. The dimension with the lowest score is the bottleneck — that's where the biggest gains are. An organisation with a strong data model but without governance risks the pitfalls described in the article on
Power BI implementations.
What does the Data Maturity Scan by Den Otter Solutions cost?+
The online scan is free and delivers an indicative maturity profile in 28 questions. For organisations wanting a more in-depth analysis, Den Otter Solutions offers the Data Start Scan as a paid service — a more comprehensive assessment including stakeholder interviews and a concrete advisory report.
