Data Mindedness

The intelligence in the analytics

If everything here is full of data anyway…

...then the least we can do is use it

Data can become a competitive advantage that turns entire industries upside down. From a business perspective, optimised data flow should determine the structure of the organisation and how internal processes are defined. The CIO is responsible for proper data handling, from data gathering to data assessment and utilisation. The CIO has all of the tools necessary to approach business divisions with new business ideas or opportunities for optimisation.

Data mindedness broadens horizons


From data warehouses to big data to machine learnable data lakes

Data procurement

From own data collection to case-by-case data exchange to control centres in data ecosystems

AI processes

From the application of AI to in-house AI IT developments to AI-driven business model change processes

The task of an IT organisation is to develop legacy data warehouse and big data systems into machine learnable data lakes. This data knowledge, combined with AI expertise, forms the basis for integrating the CIO organisation into product and software development.

Data mindedness includes the following elements:

  • Developing data strategies for various scenarios (from growth through own data to outsourcing to external data operators)
  • Developing an AI strategy
  • Creating a product/service roadmap focused on data and AI

The growing importance of AI to the success of a business is also increasing demands in terms of employee competencies. Methodological expertise – the ability to handle a variety of tools and programme libraries – is becoming a key success factor.

The benefits to IT: the CIO increases their share of the business’ value chain on the basis of data and AI expertise.

Recommendations for action for a new role of IT in the company

  • Roadmap new business ideas and potential cost savings facilitated through data and actively address the topic of AI from an IT perspective.
  • Address the data strategy, for example via a scenario analysis concerning a data vision
  • Find answers to key questions, such as: What data do we already possess and how can it be used? What are our data analysis and data engineering capabilities?

Do you have any questions about the New School of IT?

What the New School of IT is also changing: no technology can replace face-to-face dialogue. Let's talk about your vision.


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