We do modern frequentist statistics: Using fake-data simulation

The article argues that fake-data simulation is a practical way for organizations to test statistical claims before acting on them, revealing how seemingly significant results can emerge from noise, weak design, or flawed analysis. For CIOs and technology leaders, the strategic takeaway is that simulation-based validation can reduce decision risk, improve trust in analytics, and force teams to make their assumptions, data-generating logic, and analysis pipelines explicit before insights are operationalized.