Solving data quality challenges: Key takeaways from the Data Gurus podcast

On Sima Vasa’s Data Gurus podcast, Bob Fawson, co-founder and CEO of Data Quality Co-op, joined a panel of experts including Dyna Boen (Escalent), John Kay (Intuit), and Steve Snell (Rep Data). The discussion featured perspectives from the brand, agency, and supplier sides. During the discussion, Bob zoomed out to the bigger picture about how the research industry doesn’t have a tools problem, it has a coordination problem when it comes to improving data quality.

Core industry challenges

Bob framed today’s challenges as a systems issue rather than a single-survey issue. “I also think we have a coordination problem, and that’s what we’re trying to solve.” Programmatic sampling brought scale and speed, but it also “fueled the growth” of complexity. Looking ahead, “AI and synthetic audiences are going to increase that complexity.”

The result is an ecosystem where every stakeholder runs their own isolated defenses, while bad actors and disengaged participants slip through the seams. Conversations about quality skew negative, and evidence of what works is fragmented. “There’s lots of data about how quality goes wrong, and lots of cheap talk about how quality goes right,” Bob said.

A credit-score mindset for trust

Bob’s remedy is to change the unit of analysis from the individual project to the ecosystem. He described DQC’s vision as “something conceptually like a credit score that follows respondents and suppliers around.” The goal isn’t to replace anyone’s proprietary checks, it’s to give every study a head start by carrying forward validated signals that already exist elsewhere.

That approach depends on suppliers and buyers sharing standardized, privacy-safe quality signals so the next project is smarter than the last. “When any one of us walked into a bank, they don’t know us perfectly,” Bob explained. “But they have an initial, evidence-based view of risk. Research needs the same shared context.”

Stop solving quality one survey at a time

Per-survey controls still matter, but Bob argued they can’t be the only line of defense. “We have to stop trying to solve quality on every survey exclusively. We have to keep trying to solve it in every survey, but also have more transparency across companies, across surveys.” This shift reduces duplication and hidden costs while creating a common language brands, agencies, and sample providers can use to align expectations from the start. The takeaway is balance in order to keep passive, behind-the-scenes detection strong while avoiding redundant hurdles that punish honest participants for showing up.

Communicate quality like an outcome, not a mystery

Bob also wants the industry to communicate quality more clearly to brands. “How can we, who are downstream of the clients, better communicate about data quality in a way that’s proactive and helpful?” He advocates for straightforward, comparable reporting that surfaces what matters without forcing clients to decode complex quality mechanics.

What’s next

“Programmatic sampling is not going away. Synthetic audiences are not going away,” Bob said on the Data Gurus podcast. The path forward is to adapt governance to the world we have—through shared signals, cross-vendor transparency, and incentives that reward good actors on both sides of the exchange. He encourages moving from a patchwork of point solutions to an industry-level coordination challenge. Carry forward trusted signals across studies. Balance detection with experience. Report quality in ways decision-makers can act on quickly. Do these things, and the system becomes smarter, faster, and fairer for everyone involved.

Hear DQC’s Bob Fawson in conversation with industry leaders Steve Snell (Rep Data), Dyna Boen (Escalent), and John Kay (Intuit) on Sima Vasa’s Data Gurus podcast here: https://www.infinity-2.com/podcasts/solving-data-quality-challenges-with-dyna-boen-of-escalent-jon-kay-of-intuit-bob-fawson-of-data-quality-co-op-and-steven-snell-of-rep-data/