<![CDATA[Data-driven innovation increasingly depends on controlled online experimentation to determine whether proposed changes improve organizational outcomes before broad deployment. However, the reliability of the measurement infrastructure that supports evidence-based experimentation remains insufficiently addressed. This article proposes the Trust-Aware Experiment Measurement Framework (TAEMF), a conceptual framework for governing measurement reliability in organizational experimentation. The framework integrates four measurement layers covering exposure capture, behavioral event integration, identity attribution, and curated metric modeling with a five-stage validation protocol and a formally defined trust-state model that determines whether experiment results are sufficiently reliable for promotion to decision systems. The framework is developed and evaluated using a Design Science Research methodology combined with discrete-event simulation. The simulation models 200 concurrent experiments over 60 days under five infrastructure degradation conditions and compares TAEMF with conventional and partial-validation baselines. Results show that TAEMF detects 81–97% of measurement failures across the tested conditions, compared with 5–88% for the conventional baseline and 31–91% for the partial-validation baseline. TAEMF also reduces the rate of invalid experiment results from 0.19–0.61 to 0.02–0.04. An ablation analysis demonstrates that each validation stage contributes to the framework's overall failure-detection capability, indicating that measurement reliability depends on coordinated validation rather than isolated controls. The findings establish the trustworthiness of measurement infrastructure as an important dimension of organizational experimentation capability. TAEMF provides a structured governance mechanism for assessing measurement reliability before experimental evidence is used to support organizational decisions and offers a systematic basis for strengthening the evidentiary foundation of data-driven innovation]]>
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