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Three control levels for effective data transformation

Digitalization Services
  • Data Transformation
Susanne Wolf

September 17, 2024

Three people discuss the control levels of a successful data strategy.

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Efficient data management is crucial to an organization’s success, as data initiatives serve as the driving force behind successful implementation. However, efforts often fail due to a lack of business relevance, operational challenges, and technical limitations.

The valantic data-to-value framework offers a structured approach to help businesses transition from data novices to data masters. It emphasizes three core areas of control: data strategy, information governance, and system architecture.

Three control levels for data transformation
Data transformation succeeds when business, operational and technical control work hand in hand.

The data-to-value framework by valantic

Without a doubt, successful data transformation is attainable when business, operational, and technical control work hand in hand. That’s why our team at valantic places particular emphasis on the three key control levels: data strategy, information governance, and system architecture.

Data strategy: business control

Establishing a clear data strategy on a business control level is the first step toward successful data transformation. It ensures that the benefits of data are recognized and systematically pursued, making data utilization an integral part of the business model. Additionally, defining the desired level of data utilization is crucial before embarking on the data transformation journey.

Key questions when defining the data strategy:

  • How can you leverage data to enhance your business?
  • What realistic target can you establish for data utilization?
  • How can your data contribute to achieving future business objectives?
  • Which data use cases are relevant to you, and how can you implement them?

Information governance: operational control

Well-thought-out information governance enables the accurate, reliable, and transparent digital mapping of the physical world. Metadata management plays a crucial role on the operational control level, serving as a key instrument in this process.

These measures create transparency across the entire data repository, facilitating seamless data management and the automation of data processes.

Clearly defining roles, responsibilities, and processes is equally important. The result is a systematic implementation of data- and information-specific tasks, covering areas such as quality, security, risk and compliance management.

Key questions when establishing information governance:

  • How can you ensure transparency and high quality in managing your data?
  • What are the required roles, responsibilities, processes, and tools?

System architecture: technical control

A robust system architecture, embodied in a company-wide IT roadmap, enables flexible and efficient data utilization. Establishing and adhering to IT standards and guidelines provides vital support for your enterprise’s data transformation efforts. These measures play a crucial role in facilitating the agile use of data, from rapid provisioning to exploratory applications.

The IT roadmap serves as your digital blueprint, detailing the current state of the business, application, infrastructure, interface and security architecture. It provides an ideal framework for creating a focused, harmonized, and sustainable IT landscape across the entire organization, ensuring that IT standards are implemented with maximum synergy and longevity.

Key questions for a successful system architecture:

  • What technical systems and architectures can assist in managing your data?
  • How can these systems be developed and operated efficiently?

Three control levels in perfect unison

For a successful data transformation, the three control levels – data strategy, information governance, and system architecture – must work in unison. When these elements are integrated, they ensure effective data utilization and deliver quantifiable business value.

Want to talk about data thinking with us?

As the creators of the data-to-value framework, our team at valantic are experts in the field of data thinking. We are always happy to answer any questions and are here to offer our support.

Laurenz Kirchner, valantic

Laurenz Kirchner

Partner & Managing Director

valantic

Sebastian Reiss Principal at mm1

Sebastian Reiss

Principal

valantic

 

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