What is meant by the term “data-driven decision making”?

Data-driven decision making is fundamentally about utilizing data analysis to inform and guide decisions, rather than relying solely on intuition, anecdotal evidence, or past experiences. In this approach, data is collected, analyzed, and interpreted to provide insights that can lead to better outcomes. This process involves using quantitative and qualitative data to identify trends, patterns, and correlations that might not be apparent without rigorous analysis.

By basing decisions on solid data, organizations can minimize biases, enhance accountability, and make more accurate predictions about future events. This method helps ensure decisions are objective, aligned with reality, and therefore more likely to lead to successful results.

The other options describe approaches that do not embody the essence of data-driven decision making. Relying only on past experiences dismisses the insights gained from current data, while avoiding the use of data altogether contradicts the fundamental principle of being data-driven. Additionally, prioritizing intuition over analysis overlooks the benefits that can be derived from using empirical evidence to inform choices.