The ECHO Index: A KS&R Technical Whitepaper
Synthetic data has exploded in market research, and so has the marketing around it. Vendors show marginal distributions that look close enough, plausible respondents generated in seconds, all wrapped in a polished dashboard. None of it proves the data can support a real decision.
KS&R’s ECHO Index is a rigorous, transparent framework that scores synthetic data against a baseline built from real human responses, combining statistical and machine-learning evidence into a single interpretable number. It doesn’t just tell you whether synthetic data is fit for purpose, it tells you exactly where it breaks.
What’s inside this whitepaper?
- Four classes of evidence used to evaluate synthetic data, and the criteria that scale today.
- How the ECHO Index turns two critical scoring mechanisms, statistical and machine learning, into a single, interpretable metric for any audience.
- The baseline method that makes scoring meaningful for almost any dataset.
- A practical roadmap for anyone building, buying, or stress-testing synthetic data.
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About the Author
Ben Cortese leads KS&R Decision Sciences & Innovation team, where he focuses on AI strategy and governance, advanced quantitative methodologies, synthetic data evaluation, and model validation. With more than a decade of experience applying statistical and analytical techniques to complex research challenges, Ben helps organizations assess emerging methods with rigor, transparency, and confidence.
Ben is leading KS&R’s work on the ECHO Index, a framework designed to evaluate the quality, reliability, and trustworthiness of synthetic data by benchmarking it against human response. He holds a PhD in statistics from Syracuse University and brings a practical, evidence-based perspective to how synthetic data can be tested, understood, and responsibly applied in research.
