Dataondersteunde

Dataondersteunde is a Dutch term used to describe processes, decisions, or systems that are supported by data and analytics. The phrase combines 'data' with 'ondersteunen' (to support) and is often used in discussions of data governance, digital transformation, and evidence-based decision making in organizations and public institutions. In practice, dataondersteunde approaches rely on data collection, cleaning, integration, and analysis to inform choices, while still recognizing the role of human judgment.

Core elements include data availability and quality, data governance, data lineage, analytics capabilities, and transparency about methods and assumptions. Implementations require governance frameworks, data architecture, data privacy and security, and data literacy among stakeholders to interpret results. Applications span corporate decision-making, policy design, healthcare, education, and research. For example, a procurement decision might be guided by supplier performance data and risk analytics. Benefits include improved accuracy, traceability, accountability, and efficiency. Challenges include data quality issues, biases in data, overreliance on quantitative indicators, privacy concerns, and the need for interpretable results.

Dataondersteunde differs from a purely data-driven approach by emphasizing that data informs decisions while human expertise and context remain essential. See also: data-driven, evidence-based policy, data governance, data literacy.