Digital maturity is not a level

Why companies need a digital maturity profile

Imagine your company has just completed a digital maturity assessment. There have been workshops, interviews, questionnaires, perhaps external consultants, and at the end, a slide in the presentation shows a figure such as ‘3.1 out of 5’. Perhaps the result is also described as ‘Emerging’, ‘Established’ or ‘Advanced’. At first glance, such categories seem helpful because they reduce complexity and give the impression that a company’s digital maturity can be grasped at a glance.

For me, however, this is precisely where the problem begins. Because immediately after the presentation, someone in the room quite rightly asks: “And what do we do with this now?”

By this point at the latest, it becomes clear whether the assessment actually helps the company to develop further or has merely produced an interesting status report. What, for example, does an average maturity score of 3.1 mean if analytics is already highly developed, but governance is barely functioning? What does ‘Advanced’ mean if an organisation uses modern cloud platforms, but customers still have to use different logins, enter information multiple times, or have completely different experiences across various digital channels?

This is precisely why I consider a single digital maturity level to be problematic. Whilst it provides a very simple statement, it can obscure or even eliminate precisely the information that would be crucial for the actual transformation.

Traditional maturity models are, and will remain, useful

I have no intention whatsoever of fundamentally questioning traditional maturity models. On the contrary: they are extremely helpful for clearly defined capabilities, as they can provide a clear description of how an organisation develops from simple to more complex capabilities.

This can be illustrated particularly well in the field of analytics. An organisation may well start by systematically collecting data for the first time and ask itself: What happened? This gives rise to reports and dashboards. As maturity increases, the question becomes: Why did it happen? Now, data sources are linked together, patterns are examined and causes are analysed. At a further stage of development, the focus shifts to using historical data to predict what is likely to happen, before analytics, machine learning or artificial intelligence are ultimately used to support decision-making or propose specific actions.

This progression from descriptive through diagnostic and predictive to prescriptive analytics is logical because it describes the maturity of a specific capability.

The problem arises only when we infer the digital maturity of an entire organisation from the maturity of this single capability.

A company may operate highly capable predictive analytics models whilst at the same time struggling to standardise basic digital processes. It may have a modern cloud architecture, whilst data remains organised in silos. It may employ highly trained customer experience specialists who, however, have neither sufficient decision-making authority nor the necessary resources at their disposal.

For me, therefore, one distinction is particularly important:

Capability Maturity describes how far a specific organisational capability has been developed. Enterprise Digital Maturity, on the other hand, describes how these different capabilities interact and collectively generate measurable value.

At first glance, this may sound like a semantic nuance, but it fundamentally changes the entire perspective.

Digital maturity is a profile, not a single figure

If we view digital maturity not as a single figure but as the interplay of various organisational capabilities, the result is a digital maturity profile rather than a single level.

In my experience, eight dimensions are particularly relevant here:

Strategy & Leadership

The first question is what role digital should actually play within the organisation. Is there a shared understanding of how digital capabilities contribute to corporate strategy, are priorities clearly defined, and are the necessary investments actually being made? Or does the digital strategy essentially consist of individual initiatives from different departments?

What matters is not that senior management regularly emphasises the importance of digitalisation, but whether digital decisions are consistently aligned with strategic objectives and whether priorities are subsequently implemented.

Organisation & Governance

Governance is less about the number of committees, guidelines or consultation processes than it is about clarity. Is it clear who is responsible for a digital capability, who is authorised to make decisions, and what standards apply to architecture, data, data protection, security or customer experience?

Good governance should make decision-making simpler, not more complicated: if responsibilities and guidelines are clear, teams do not have to clarify anew who is in charge and which rules apply every time a new issue arises.

People & Skills

No company will achieve digital maturity if the relevant capabilities lie exclusively with a handful of specialists or external service providers. Digital competence, data literacy and the necessary specialist knowledge must be present within the organisation to an appropriate extent and must evolve in line with business requirements. One point is particularly important to me here: an organisation does not automatically possess a capability simply because there is an employee somewhere who has mastered it. As long as knowledge is tied to individual people, the organisation remains vulnerable and can only scale that capability to a limited extent.

Processes & Ways of Working

Many companies have outstanding individual projects that are successfully implemented thanks to a great deal of personal commitment. However, this says little about how mature the organisation actually is. Maturity only arises when success becomes reproducible: processes must be understandable, repeatable and capable of being integrated across functional boundaries, whilst insights from data or customer feedback systematically lead to improvements. A successful project therefore does not in itself constitute an organisational capability; this only emerges when comparable results can be achieved repeatedly and under different conditions.

Data & Analytics

The development is particularly evident in the area of data and analytics. It makes a significant difference whether a company merely collects data and produces historical reports, analyses causes, forecasts future developments, or already uses prescriptive analytics and machine learning to support decision-making. However, it is not just the technology used that is decisive: a data lake does not automatically make a company data-driven, just as a dashboard does not guarantee that decisions are actually based on data. Data initially merely creates the opportunity for better decisions; digital maturity is demonstrated by whether the organisation reliably makes use of this opportunity.

Technology & Architecture

In the technological sphere, the key question is whether the digital landscape consists merely of an ever-increasing number of applications, or whether this gives rise to an integrated and scalable architecture. The decisive factor is whether systems communicate via standardised interfaces, utilise shared data and identity mechanisms, and whether new capabilities can be added without having to develop bespoke integrations each time. A modern technology landscape therefore does not automatically digitise a company. In the worst-case scenario, it merely digitises existing organisational silos and, in the long term, actually makes them even more difficult to break down.

Customer Experience & Value

For me, customer experience is a particularly interesting dimension because this is where internal digital maturity becomes immediately visible to outsiders. A customer is not interested in how your organisation is structured internally, which department operates which platform, or who is responsible for which data. What they experience is whether digital touchpoints function consistently, whether information is available, whether interactions build on one another in a meaningful way, and whether their needs are understood. Different logins, contradictory information, the need to enter data multiple times, or completely different user interfaces are therefore often not isolated UX problems, but visible symptoms of a lack of integration, governance or ownership.

Customers do not experience your digital strategy. They experience the consequences of your digital maturity.

Measurement, Learning & Optimisation

Finally, the question arises as to whether an organisation merely measures or actually learns. Dashboards, KPIs and reports are important monitoring tools, but they do not in themselves create maturity. This arises when analytics, the Voice of the Customer, user tests, A/B tests, and usage and adoption metrics form a closed learning cycle, and insights are systematically incorporated into decisions and changes.

A dashboard shows you what is happening. A learning organisation uses this information to make targeted changes to what happens next.

Why an average score can create a false sense of security

Let’s take a simple example. An organisation rates Strategy & Leadership as 3, Organisation & Governance as 2, People & Skills also as 2, Processes & Ways of Working as 2, Data & Analytics, on the other hand, as 4, Technology & Architecture also as 4, Customer Experience & Value as 2, and Measurement, Learning & Optimisation as 3.

The mathematical average is 2.75. One could easily interpret this as ‘Digital Maturity Level 3’, which would make for a very catchy management statement.

At the same time, however, this would have largely obscured the assessment’s most important finding, as the company clearly does not have a primary technology problem. Its analytics capabilities are also comparatively well developed. Introducing even more platforms or additional analytics technology would therefore probably not generate a commensurate added value. The real bottlenecks lie rather in governance, skills, processes and customer experience.

Figure: Digital maturity profile – illustration and model development by Holger Tempel

This is precisely the information a Digital Maturity Assessment should provide.

In my view, its purpose is not to give a company as precise a school-style mark as possible. Its purpose is to identify which capabilities are currently preventing the next meaningful stage of development.

Digital capabilities do not develop in isolation

There is also another point which, in my view, is not given sufficient consideration in many maturity models: an organisation’s various capabilities are interdependent.

Predictive analytics, for example, requires reliable data, suitable data models, the relevant expertise and governance. Personalisation can only work sustainably if customer data, consent management, content, technology and operational processes work together. And artificial intelligence only reliably generates value if the organisation is not only able to run models, but also understands what data is being used, how results are evaluated and who ultimately bears responsibility for decisions.

A highly mature capability can therefore be significantly held back by a less mature, dependent capability.

An excellent analytics platform built on unreliable data remains limited. A modern cloud architecture without governance can lead to new technical debt simply accumulating more quickly. And whilst a Voice-of-Customer platform generates interesting insights, if no one is responsible for deriving changes from them, its actual value remains limited.

That is why the question “How mature is this capability?” alone is not enough. We must also ask: “On which other capabilities does its actual benefit depend?”

Not every dimension needs to reach Level 5

Another mistake can easily arise from the very logic of a five-level model. If Level 1 is low and Level 5 is high, Level 5 automatically appears to be the goal.

I believe this is wrong.

Not every company needs to automate every decision. Not every process requires predictive analytics. Not every customer journey needs real-time personalisation. And not every organisation needs a highly complex cloud or data architecture.

Higher maturity costs money, can increase organisational complexity in some cases, and must therefore serve an economic or strategic purpose.

For this reason, in my view, a Digital Maturity Profile should always consider at least two metrics: Current Maturity – that is, the capabilities that are reliably in place today – and Required Maturity – that is, the capabilities that are actually necessary to achieve the organisation’s strategic goals.

It is the difference between the two that is truly interesting.

The relevant question is therefore not: “How do we reach Level 5 across the board?” It is: “What level of digital maturity do we need to reliably achieve our business and customer objectives?”

How can you tell that digital maturity has actually increased?

This brings us to a point that I personally consider particularly important. An organisation has not automatically become more digitally mature simply because the next assessment yields a higher score.

Rather, maturity should be demonstrated through observable capabilities.

For example, an organisation is not more mature simply because it has adopted a digital strategy. It is more mature when digital investments are prioritised based on shared criteria and decisions are made in a transparent manner. It is not more mature simply because a governance board has been set up. It is more mature when teams know who has decision-making authority and relevant decisions do not regularly get stuck between departments.

Even 500 completed data literacy training courses are, at first, merely an activity metric. It only becomes interesting when employees subsequently use data more independently and can demonstrably make better decisions based on it. The same applies to technology. A data lake is, initially, merely infrastructure. Maturity is demonstrated by whether relevant business questions can be answered more reliably and quickly.

Nor is a redesigned website in itself proof of greater maturity in the customer experience. What matters far more is whether customers can carry out their tasks more easily, experience less friction and receive a more consistent experience across various touchpoints.

Digital maturity should therefore, where possible, be assessed on the basis of observable capabilities and robust evidence, rather than solely on the basis of an organisation’s self-assessment. In my view, a good digital maturity assessment should therefore not end with a score, but with a better basis for decision-making.

It should highlight which capabilities are actually in place today, which of these are required for the strategy, where relevant gaps exist, which dependencies are hindering progress, and how the organisation can later recognise that a capability has actually improved.

This significantly changes the function of a maturity model. A benchmark becomes a diagnosis, a score becomes a prioritisation, and an audit can give rise to a development roadmap.

Conclusion: Digital maturity must enable action

In my view, digital maturity should never be regarded as an end in itself. It is not about deploying as many technologies as possible, achieving the highest possible levels of maturity, or being able to present the most impressive score at the end of an assessment. What matters far more is whether an organisation develops the capabilities it needs to achieve its strategic goals better, faster and more reliably.

This is precisely why I believe a Digital Maturity Profile is more helpful than a single maturity rating. It highlights where an organisation is already strong, where dependencies exist, and where additional investment can actually make a difference. Above all, it prevents companies from reflexively introducing more technology, even though the real bottleneck may lie in governance, processes, capabilities or a fragmented customer experience.

A good assessment should therefore not answer the question of how ‘digital’ a company is on a scale of one to five. It should provide clarity on which capabilities are in place, which are still missing, and which of these need to be developed next in order to generate measurable benefits.

Perhaps that is why the most important question following a Digital Maturity Assessment is not ‘What level have we reached?’, but ‘What can our organisation reliably do better tomorrow than it can today?’

An organisation does not become more digitally mature simply because its assessment score changes; it becomes more digitally mature when it can reliably do things it could not do before.

Notes:

The Digital Maturity Profile described in this article and the accompanying figure were developed by Holger Tempel as an independent synthesis and further development of existing maturity approaches. If you would like to discuss digital maturity with Mr Tempel, it is worth taking a look at his website or connecting with him on LinkedIn.

The following sources, amongst others, are suitable as technical starting points and for further reading:

Greg Dowling / Glassbox (2021): 5 elements of digital experience analytics maturity
AltexSoft (2020): Analytics Maturity Model: Levels, Technologies, and Applications
Boston Consulting Group / Google (2019): The Dividends of Digital Marketing Maturity
Boston Consulting Group (2024): Accelerating AI-Driven Marketing Maturity

Would you like to support Holger Tempel and discuss digital maturity or the Digital Maturity Profile? Then please share this post within your network or within your organisation.