Dr. Poornima Luthra, Author, Educator and Keynote Speaker, joins Sima Vasa to make the evidence-based case that DEI backlash is rooted in fear, not fact, and that most organizations have never done the systemic work required to make inclusion stick. Poornima draws on two years of primary research — interviews, discourse analysis and emotion coding — to identify five core fears driving resistance and explains why reframing DEI as uniqueness, fairness and belonging changes the entire conversation. She also covers what active allyship actually requires and why homogeneous organizations can’t generate the innovation that today’s business environment demands.

Key Takeaways:

00:00 Introduction.

10:15 DEI resistance exists on a spectrum, from hesitation to overt backlash, and is always rooted in fear.

12:24 Five fears drive the backlash: change, getting it wrong, discomfort, taking action and lack of positive impact.

16:00 Short-term metrics obsession is the structural reason organizations fail to sustain inclusion work.

19:09 Diverse hiring in a regulated pharma AI team succeeded when leadership committed to a longer onboarding runway.

21:00 Most data still shows that majority dominant groups hold the vast majority of top roles and wealth.

23:47 Reframing DEI as uniqueness, fairness and belonging neutralizes the opposition because everyone wants those things.

29:22 Active allyship requires self-work first: curiosity, honest introspection on privilege and bias buddies for ongoing accountability.

Resources Mentioned:

“The Art of Active Allyship” by Dr. Poornima Luthra — https://www.amazon.com/Art-Active-Allyship-Behaviours-Inclusion/dp/8797290327

Dr. Poornima Luthra TED Talk (2019) — “Why GQ is the kind of intelligence we all need” — https://www.ted.com/talks/poornima_luthra_why_gq_is_the_kind_of_intelligence_we_all_need

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#Analytics #Data #Strategy

Thor Olof Philogène, Founder and CEO of Stravito, joins Sima Vasa to discuss knowledge discovery at scale and how AI-powered insights intelligence can turn fragmented enterprise research into a competitive asset.

Thor also covers Stravito’s AI + human expertise model, the launch of AI personas that simulate consumer perspectives from real segmentation data, and why insights professionals are uniquely positioned for the current AI moment.

Key Takeaways:

00:00 Introduction.
04:15 The right team outranks capital and strategy every time.
05:00 Psychological safety eliminates political overhead and unlocks organizational capacity.
08:14 Getting people to use data is harder than acquiring it.
08:49 Large enterprises commission enormous research but rarely know where it lives.
11:13 A neutral, agnostic layer surfaces trusted answers from one place.
16:24 Purpose-built AI informed by human expertise outperforms general-purpose tools.
27:19 AI personas simulate consumer perspectives from real segmentation data in real time.
31:45 Insights professionals have spent their careers training for the AI moment.

Resources Mentioned:

Stravito | Website
Lavazza x Stravito AI Personas — Ad Age
Euromonitor
Mintel

Thanks for listening to the Data Gurus podcast, brought to you by Infinity Squared. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show, and be sure to subscribe so you never miss another insightful conversation.

#Analytics #MA #Data #Strategy #Innovation #Acquisitions #MRX #Restech

On this episode, host Sima Vasa talks to Jason Cohen, Founder and CEO of Simulacra Synthetic Data Studio, about the limits of traditional research, the evolution of synthetic data, and why causal modeling matters more than larger sample sizes. Drawing on his experience building and exiting Gastrograph AI, Jason explains how real-world data gaps undermine decision-making and how synthetic data can support scenario-based predictions when applied responsibly.

Key Takeaways:

00:00 Introduction.
05:24 Most brands can’t know in advance if research data is “correct.”​
09:44 Generic LLM personas rarely represent any real population.​
13:08 Cross‑coverage lets AI infer missing audience segments.​
16:04 Synthetic data is real when it’s actually used.​
19:36 Diversity in base samples drives credible synthetic expansion.​
23:28 Sample boosting alone doesn’t fix bad research outcomes.​
25:08 Synthetic data scales insights for hard‑to‑reach cohorts.​
26:08 Misused synthetic personas can drive completely wrong decisions.​

Resources Mentioned:

Simulacra Synthetic Data Studio | Website

Thanks for listening to the Data Gurus podcast, brought to you by Infinity Squared. If you enjoyed this episode, please leave a 5-star review to help get the word out about the show, and be sure to subscribe so you never miss another insightful conversation.

#Analytics #MA #Data #Strategy #Innovation #Acquisitions #MRX #Restech