Grounding decisions in data you collect and analyze rather than intuition, from metrics to data strategy.
Data-driven decision-making is the practice of basing choices on verified data and rigorous analysis. It spans from reading basic metrics to designing organizational data strategies, integrating data literacy, analytical reasoning, and judgment to reduce uncertainty across all contexts.
5-level data literacy model (Unaware to Driven) used to define maturity boundaries for data utilization and derive behavioral criteria per level.
Defines progressive analytics capability path through 4 maturity stages (Descriptive→Prescriptive), used to design stage-specific behavioral criteria in checklists.
International assessment measuring adult literacy, numeracy, and problem-solving proficiency across 6 levels, providing governmental/international authority for data-driven decision competency.
Extends classical decision theory to the big data and analytics era through the DECAS framework. The concept of collaborative rationality between human judgment and machine analysis provides academic grounding for L4-L7 data-judgment integration competency checklists.
