The ECHO Index: A KS&R Technical Whitepaper
Ben Cortese, PhD our VP of Decision Sciences and Innovation, brings more than a decade of experience in advanced quantitative methodologies and a passion for uncovering hidden insights through data to KS&R. Ben leads a close-knit team of expert data scientists and analysts that are the backbone of quantitative research for the organization, providing full-service consultation and analytics to our clients. But what truly sets him apart is his quantitative thought leadership, tackling challenging problems such as pricing research, feature prioritization, and predictive analytics through novel and innovative techniques. While his Ph.D. in statistics from Syracuse University is a testament to his dedication to the craft, Ben is about more than just numbers. A proud father and husband, he cherishes time outdoors with his family, spending time in the garden, and playing golf during Syracuse's fleeting sunny spells. For Ben, it's not just about data – it's about balance and the joy of life's simple pleasures.
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.
Download the Whitepaper
Complete the following form:
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.
