How do you ensure that a data strategy doesn't just remain on paper, but actually leads to better working practices? On February 10,TaraKikken, change expert, and Joost Wijdeven, business intelligence consultant, explored this question in depth during a webinar.

Only when strategy, governance, and adoption come together can lasting value be created for the organization. This was also underscored by concrete examples from the sector. Successful data transformation goes beyond tooling and dashboards.

Start with insight and direction

An effective approach starts with understanding the current situation. Many organizations struggle with fragmented figures, unclear responsibilities, and the feeling that data-driven working is just an "add-on." A data maturity scan is a central part of From Data to Action and helps to objectively determine where an organization stands and where there is potential for improvement. Based on this, you can formulate a data strategy that offers a concrete perspective for action and forms the basis for a roadmap.

Set up data governance step by step

For the successful implementation of the data strategy, it is important that data governance and data organization are consciously and gradually established. This should lead to concrete agreements about roles, responsibilities, and cooperation in daily practice.

Governance affects the entire organization. By taking an integrated view of processes, ownership, and decision-making, cohesion is created and initiatives do not exist in isolation from one another. The introduction of data governance can start small, for example within a single data domain, and then be implemented across the entire organization.

The Valid 3V model—prepare, change, and embed—serves as a guideline in this process. People are central to each phase, with targeted communication, active employee involvement, and structural attention to adoption. Only in this way can data governance become an integral part of the organization.

Work with clear goals and roles

Clear goals at the organizational, project, and adoption levels ensure focus. Make these as concrete and measurable as possible.  A carefully assembled project team is indispensable in this regard. Roles such as the sponsor from senior management, project manager, change manager, data experts, and key users together provide direction and support. Gaining insight into the impact and risks in advance helps to plan realistically and determine the pace of change.