Burke Introduces a New Framework for Assessing Synthetic Data Quality
As synthetic data options become more widely available, the key question is whether they can inform real-world decisions with confidence. Burke's research compared multiple synthetic methodologies and tested whether LLM-based synthetic panels can replace human respondents, how generative data models perform relative to synthetic panels, and whether the quality of the underlying human data remains critical in a synthetic-data world.
The study finds that while LLM-based synthetic panels can be valuable for early exploration, they are not yet reliable for decision-grade applications that rely on quantitative insight: at the commonly cited 80% accuracy level, LLM-based synthetic data produced false conclusions in roughly 60% of tested business scenarios. By contrast, methods grounded in validated respondent-level human data, known as generative data models, performed substantially better, suggesting greater potential for decision-support applications.
At the center of the study is Burke's FAR Framework, which evaluates synthetic data quality across three dimensions:
- Fidelity - Whether synthetic data aligns with the underlying source of truth.
- Authenticity - Whether synthetic responses reflect realistic variation rather than simply reproducing existing data.
- Resolution - Whether relationships between variables, segments, and business conclusions are preserved.
The study also identified a clear threshold for decision reliability at which synthetic approaches were far more likely to preserve research conclusions, offering an important signal for organizations trying to separate promising applications from the less reliable.
"Organizations are hearing increasingly strong claims about synthetic data," said
"AI is impacting how organizations generate insight and make decisions," said
"Our goal is always to help our clients make the best decisions for their business," said
The findings are a result of the work of Burke Labs™, the organization's area dedicated to testing and accelerating new AI and technology solutions that transform respondent experiences, analytics, and reporting.
Burke, Inc. is a leading decision intelligence consultancy helping organizations accelerate growth through insights, strategy, innovation, and training powered by high-quality research, advanced analytics, and expert guidance. Founded in 1931, Burke combines rigorous measurement with human-centered consulting to help clients better understand people, markets, and opportunities.
For more information, please contact: info@burke.com
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SOURCE Burke, Inc.
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