What the market is currently showing
96 percent of companies are already investing in data & AI or have launched corresponding initiatives. Despite this, many complain about the lack of results
The reason: only 62 percent of companies have a standardized data management system, and only 77 percent have even established a company-wide data strategy. Technology is purchased before the organizational foundations are in place.
As a result, the need is clear: 90 percent of the client companies surveyed explicitly expect data &AI service providers to offer training to promote a data-driven corporate culture – not just technical implementation.
The real problem: culture cannot be deployed
In consulting practice, I encounter the same pattern time and again: a company invests heavily in modern data infrastructure. The tools are good. The architecture is solid. But the specialist departments continue to use their Excel spreadsheets. Analyses end up in the inbox and are rarely actually used. AI recommendations are viewed with scepticism because no one understands how they came about.
When I talk to data & AI executives in different industries, a similar picture often emerges: there are difficulties in changing organizational behaviour. 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 keeping the terms apart:
- Data literacy refers to individual skills – the ability to read and interpret data and use it to make decisions.
- Data culture describes the collective mindset of an organization – whether data is actually used when it matters.
Simply put: Literacy is the individual mindset, culture is the organizational one. The two must grow together. One without the other won’t get you far.
In some training courses, I once learned that we forget 70 to 80 percent of what is taught in training courses within a month – unless the person applies what they have learned directly in their daily work. In times of agentic AI and how AI is currently shaping my own everyday life, I use the principle quite successfully myself. So I also recommend it to my clients when we start designing the roadmap. Successful data literacy programs should follow the 70:20:10 model: 70 percent learning through practical application, 20 percent through social learning and coaching, 10 percent through formal training.
In practice, this means that if you want to build a real data culture, you can’t stop at training. You need to integrate learning opportunities directly into your daily work and create communities in which a culture of error is practiced and it is okay to ask your colleagues for help without “embarrassing yourself”. This often requires support over an appropriate period of time.
By 2030, data literacy will be one of the most sought-after skills – comparable to basic digital skills today. Forecasts show: 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 organization
In my work with companies, a framework that addresses three interlinked components has proven successful:
Values and standards
How do employees handle data? Are decisions justified and made transparent? Is uncertainty communicated or hidden? A data-driven culture needs practised standards and a culture of error – not lip service in PowerPoint presentations.
Data governance as a basis for trust
Data is only used if people trust it. Governance – i.e. clear structures for responsibility, quality and access – is therefore not just a compliance issue, but a cultural factor. If you don’t know where a figure comes from or who is responsible for it, you are likely to ignore it. I will shed light on this strategic dimension of 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. Organizations with structured data literacy programs will significantly outperform those without such programs in terms of competitiveness. Accordingly, by 2027, more than half of Chief Data Officers are expected to secure dedicated budgets for corresponding programmes or focus on forming their own communities that exemplify precisely these topics in the organization (ambassadors, pilots, key users, …)
The skills shortage is intensifying the pressure
Over 90 percent of companies report a lack of data & amp; AI specialists. This means that if you don’t empower your existing employees to handle data, you lose out twice over – you can neither recruit externally nor scale internally
Data literacy is therefore no longer a nice-to-have training measure. It is a strategic lever for expanding corporate capabilities despite a shortage of skilled workers.
Relevant roles for a data-driven working world
The transformation requires not only new skills, but also new organizational structures. Three roles are particularly crucial:
- Data stewards act as a bridge between IT and business. They ensure that data in their specialist area is correct, 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 anchor 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 – the example of an industrial company
A key success factor for a leading medical technology manufacturer, which we accompanied on its way to becoming a data-driven organization, was precisely this cultural aspect: the best data platform would have remained ineffective if the sales team had not learned to work with customer segments – or if the back office had not been able to draw insights from the data in order to actively address cross-selling potential.
Systematic investment was made in data literacy right from the start – from key account managers to product specialists in the field. New roles such as data stewards were created in the divisions and tasks were deliberately anchored in job profiles. The result: service sales increased by 12% and the cross-selling rate by 15%. Not because the platform was special – but because the organization actually used it.
How adesso supports: From training to living culture
In my projects, I accompany companies on exactly this path. Typical building blocks:
- Data Culture Assessment: Where does the organization stand today? What barriers are there – in people’s minds, in processes, in structures?
- Role design: What new roles does the organization need? How are data stewards, analytics translators and CDOs embedded?
- Customized data literacy programs based on the 70:20:10 model – with direct reference to the participants’ daily work.
- Executive coaching: Data-driven decision-making starts at the top. When managers put gut feeling above data, the rest of the organization does too.
- Change support: Cultural change takes time and consistency. We support organizations in gradually anchoring new norms – not as a one-off project, but as a continuous process.
If you have the feeling that your organization is not yet really using the available data – or if data literacy programs have not yet had the desired effect – I look forward to talking to you. Just drop me a line or get in touch with the keyword “Organization & Culture”.
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Further links
👉 www.adesso.de
Photo: pixabay
