Quantum computing, particularly superconducting quantum computing, is rapidly advancing toward medium- and large-scale qubit configurations, yet this scaling has introduced critical challenges in quantum measurement and control (M&C) efficiency. A primary barrier to practical M&C deployment lies in the excessive duration of core tasks—a limitation that traditional optimization strategies have failed to address universally. Methods relying on Reset gates demand specialized quantum chip architectures (e.g., dedicated Reset resonators), while Restless measurement-based approaches require high-speed real-time response from M&C equipment; both are incompatible with the diverse hardware setups common in academic and industrial research. To address this gap, this study first establishes a comprehensive time-domain model of M&C task execution, quantifying the contribution of each phase (e.g., signal playback, data acquisition, idle waiting) to total latency. Through experimental validation across 8 representative M&C tasks on real quantum processors, two key insights emerge: (1) trigger time—previously set arbitrarily to 3–10 × the qubit energy relaxation time (T₁)—dominates total task duration, accounting for ~ 90% of execution time; (2) M&C experiments maintain stable accuracy even when trigger time is reduced, as residual quantum state interference from shortened waiting periods has negligible impact on measurement results. Leveraging these insights, a universal variable trigger scheme (VTS) is proposed, which abandons the one-size-fits-all trigger time paradigm. Instead, VTS dynamically assigns trigger durations based on qubit T₁ and experiment type. Simulation tests across diverse T₁ scenarios confirm VTS’s efficacy, outperforming existing methods in both efficiency and hardware compatibility.