Plan-vs-Actual Learning Loop.

VYAN compares plan to actual at every cycle, attributes variance to specific drivers and decisions, and feeds the attribution into the next planning cycle. Significant drift surfaces as a quality alert. The system learns from its own errors at the cycle frequency, not the review frequency.

Planning quality improves quarter over quarter without intervention. Drift caught when it starts. The engine becomes a learning asset rather than a frozen artifact.