Data-Driven Decision Making
Use data and analytics to inform strategic and operational decisions.
Data-driven organizations make decisions based on evidence rather than intuition or tradition. This requires data literacy—understanding how to collect, analyze, and interpret data—and analytical tools ranging from spreadsheets to machine learning. Common approaches include descriptive analytics (what happened), diagnostic analytics (why it happened), predictive analytics (what might happen), and prescriptive analytics (what should we do). However, data has limitations: correlation doesn't imply causation, selection bias skews results, and models can embed historical discrimination. Effective data-driven decision-making combines quantitative evidence with qualitative insights (customer interviews, expert judgment) and ethical considerations. Organizations need data governance—standards for quality, security, and access—and a culture…
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