People make the difference: Why organisation and culture determine the success of data-driven companies

Many data transformations do not fail because of the technology. They fail because of the people. New platforms are introduced, AI pilots launched, dashboards built – and yet the hoped-for impact fails to materialise. The reason usually lies not in the tech stack, but in the organisation: in the mindset, in the roles, in the empowerment.

This is not a new insight – but one that is still far too often underestimated in practice. Peter Drucker once said, “Culture eats strategy for breakfast”, and that is exactly how it is.

What the market is currently showing

96 per cent of companies are already investing in data & AI or have launched relevant initiatives. Nevertheless, many complain about a lack of results.

The reason: only 62 per cent of companies have a unified data management system, and only 77 per cent have established a company-wide data strategy at all. Technology is purchased before the organisational foundations are in place.

Accordingly, the need is clear: 90 per cent of the client companies surveyed explicitly expect data and AI service providers to offer training programmes to foster a data-driven corporate culture – not just technical implementation.

The real problem: culture cannot be deployed

In my consulting practice, I repeatedly encounter the same pattern: a company invests heavily in modern data infrastructure. The tools are good. The architecture is solid. But the business units continue to use their Excel spreadsheets. Analyses end up in inboxes and are rarely actually used. AI recommendations are viewed with scepticism because nobody understands how they were generated.

When I speak to Data & AI executives across different industries, a similar picture often emerges: there are difficulties in changing organisational behaviours. Specifically: there is no data-driven culture. These are not technical problems.

Data literacy and data culture: two sides of the same coin

It is worth distinguishing between the terms:

• Data literacy refers to individual skills – the ability to read, interpret and use data for decision-making.
• Data culture describes the collective mindset of an organisation – whether data is actually used when it matters.

Put simply: literacy is the individual mindset, culture is the organisational one. Both must grow together. One without the other won’t get you very far. What

I’ve learnt from some training courses is that we forget 70 to 80 per cent of what is taught within a month – unless the person applies what they’ve learnt immediately in their daily work. In the age of agentic AI and given how AI currently shapes my own daily life, I apply this principle myself quite successfully. So I also recommend it to my clients when we start designing the roadmap. Successful data literacy programmes should follow the 70:20:10 model: 70 per cent learning through practical application, 20 per cent through social learning and coaching, 10 per cent through formal training.

In practice, this means: if you want to build a genuine data culture, you mustn’t stop at training sessions. They must integrate learning opportunities directly into day-to-day work and create communities where a culture of learning from mistakes is practised and it is acceptable to ask colleagues for help without ‘making a fool of oneself’. This often requires support over a suitable period of time.

By 2030, data literacy will be one of the most in-demand skills – comparable to basic digital skills today. Forecasts show that by 2027, more than half of Chief Data Officers are expected to secure dedicated budgets for data literacy programmes.

Three building blocks of a data-driven organisation

In my work with companies, a framework has proven effective that addresses three interlinked components:

Values and standards

How do employees handle data? Are decisions justified and made transparent? Is uncertainty communicated or concealed? A data-driven culture requires lived-out standards and a culture of learning from mistakes – not just lip service in PowerPoint presentations.

Data governance as a basis of trust

Data is only used if people trust it. Governance – that is, clear structures for responsibility, quality and access – is therefore not just a compliance issue, but a cultural factor. Anyone who does not know where a figure comes from or who is responsible for it will, when in doubt, ignore it. I will explore this strategic dimension of the processes in my next blog post

Data literacy as a strategic competence

By 2030, data literacy will be one of the most sought-after skills – comparable to basic digital skills today. Organisations with structured data literacy programmes significantly outperform those without such programmes in terms of competitiveness. Accordingly, by 2027, more than half of Chief Data Officers are expected to secure dedicated budgets for such programmes or to focus on forming their own communities that exemplify precisely these topics within the organisation (ambassadors, guides, key users, etc.)

The skills shortage is intensifying the pressure

Over 90 per cent of companies report a shortage of data and AI specialists. This means that those who fail to empower their existing staff to work with data lose out twice over – they can neither recruit externally nor scale up internally.

Data literacy is therefore no longer just a ‘nice-to-have’ training initiative. It is a strategic lever for building up organisational capabilities despite the skills shortage.

Key roles for a data-driven workplace

The transformation requires not only new skills but also new organisational structures. Three roles are particularly crucial here:

• Data Stewards act as a bridge between IT and business. They ensure that data within their department is accurate, up-to-date and usable – and translate technical requirements into business reality.
• Analytics Translators (Business Analysts) translate business requirements into technical specifications – and vice versa. They are the missing link between what the business needs and what the data teams can deliver.
• Chief Data Officers (CDOs) continue to establish data literacy as a strategic priority at management level and ensure that data competence does not remain a ‘nice-to-have’ but is understood as a core competence.

What this means in practice – using an industrial company as an example

At a leading medical technology manufacturer, which we supported on its journey to becoming a data-driven organisation, this very cultural aspect was a key success factor: Even the best data platform would have been ineffective if the sales team had not learnt to work with customer segments – or if the back-office staff had been unable to draw insights from the data to actively address cross-selling opportunities.

Here, systematic investment in data literacy took place from the outset – from key account managers to product specialists in the field. New roles such as data stewards were created within the departments, and tasks were deliberately embedded in job profiles. The result: service revenue rose by 12%, and the cross-selling rate by 15%. Not because the platform was special – but because the organisation actually made use of it.

How adesso supports you: From training to a lived culture

In my projects, I guide companies along precisely this path. Typical building blocks:

• Data Culture Assessment: Where does the organisation stand today? What barriers exist – in mindsets, in processes, in structures?
• Role design: What new roles does the organisation need? How will data stewards, analytics translators and CDOs be integrated?
• Tailor-made data literacy programmes based on the 70:20:10 model – with a direct link to participants’ day-to-day work.
• Executive coaching: Data-driven decision-making starts at the top. If executives prioritise gut feeling over data, the rest of the organisation will follow suit.
• Change management support: Cultural change takes time and consistency. We support organisations in gradually embedding new norms – not as a one-off project, but as an ongoing process.

If you feel that your organisation isn’t yet making full use of the data available – or if data literacy programmes haven’t had the desired effect so far – I’d be delighted to have a chat. Just send me a quick email or get in touch using the keyword “Organisation & Culture”.