Directionally Correct, A People Analytics Podcast

Suzanne Bell, lead scientist at NASA’s Behavioral Health & Performance Lab who studies spaceflight behavioral health and team dynamics. She discusses preparing humans for Artemis and deep-space missions. Topics include selection and training, living in tiny spacecraft versus the ISS, managing team composition and disagreeable high-performers, sleep and cognitive readiness, and ethical AI use for long-duration missions.

Allan Church, Co-founder of Maestro Consulting and former PepsiCo talent leader, brings decades of practice in leadership models and potential assessment. He contrasts performance with potential and unpacks the limits of nine-box thinking. He outlines science-based predictors, practical assessment tools, AI limits, group dynamics, and how bespoke leadership models tie analytics to development.

John Barry, Co-CEO at HRBench, former HR tech founder focused on compensation analytics; Matt Maguire, CRO at HRBench, expert in product adoption and benchmarking; Brandon Collins, CTO at HRBench, engineering leader driving UX and AI workflows. They discuss consolidating HR data for strategic decisions. They debate commoditization of people analytics and shift from reports to action. They highlight org charts, scenario planning, and AI speeding engineering.

Jennifer Wilson, Partner and Global Co-Head of Heidrick & Struggles’ HR Officers practice, brings executive search and HR leadership know-how. She explores how CHRO responsibilities have expanded, the rise of AI-native HR leadership, why moving from number two to CHRO is hard, and whether people analytics can be a direct path to enterprise HR roles. Practical career moves and organizational design also come up.

Thanks to HRBench for powering this episode. To find out more about the company building the future of people intelligence, reach out to book a demo at hrbench.com/directionallycorrect Check out this episode of the #1 people analytics podcast special guest, Kinsey Li, Author of "People Analytics Explained" and Advisor at PwC! In this wide-ranging and deeply thoughtful conversation, host Cole Napper sits down with Kinsey to explore what it truly takes to succeed in people analytics beyond the technical skills that often dominate the narrative. Kinsey shares the inspiration behind her book, which emerged from her own early frustrations breaking into the field. Despite completing courses and gaining certifications, she found a major gap between technical training and the real-world capabilities required to be effective. Her core insight reframes the discipline: people analytics is not primarily about data, but about relationships. In her experience, success in the field is closer to 80% stakeholder management and 20% technical execution, a perspective that challenges how many professionals approach their development. The conversation dives into the consulting mindset that has shaped Kinsey’s career, highlighting two essential skills: scoping and listening. She explains that scoping is fundamentally about defining boundaries—understanding what problem you are solving, what success looks like, and just as importantly, what you will not address. In a field where organizational challenges are deeply interconnected, the ability to prioritize and maintain focus is critical. This requires not only analytical thinking but also confidence and judgment to push back when necessary. Kinsey also offers a fascinating look at how cultural context shapes people analytics work. Drawing on her experience across Australia, the UK, and now Jakarta, she contrasts Western and Eastern workplace dynamics. In more hierarchical environments, decisions can be executed بسرعة and scaled quickly, but often with less consultation. At the same time, she notes that some of the most advanced people analytics practices exist in small, less visible pockets across Asia, where innovation happens quietly without widespread sharing. The discussion expands into themes of career growth and learning, reinforcing the idea that breadth of experience often outweighs early specialization. Kinsey connects this to probabilistic thinking, emphasizing that careers are less like chess and more like poker, where exposure to diverse experiences increases the likelihood of long-term success. This aligns with Cole’s own reflections on building expertise through multidisciplinary exposure rather than narrow focus. They also explore evolving attitudes toward AI and data privacy, particularly among younger generations. Kinsey observes that digital natives are more willing to delegate thinking to AI and are often more comfortable sharing personal data, a shift that has significant implications for the future of people analytics. At the same time, both highlight the importance of maintaining ethical guardrails as capabilities expand. Throughout the episode, Kinsey brings a candid and personal perspective, discussing how her evolving mindset, including embracing a “default trust” approach and navigating neurodiversity, has shaped how she works and interacts with others. Her journey underscores that effectiveness in people analytics is as much about self-awareness and adaptability as it is about technical skill. This episode is a compelling reminder that the future of people analytics will be defined not just by better data, but by better thinking, stronger relationships, and a deeper understanding of how work actually gets done across different contexts and cultures. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.

Thanks to HRBench for powering this episode. To find out more about the company building the future of people intelligence, reach out to book a demo at hrbench.com/directionallycorrect Check out this episode of the #1 people analytics podcast with special guests, Stacia Garr & Dani Johnson, both are Co-Founders and Principal Analysts at RedThread Research! In this wide-ranging and intellectually rich conversation, Cole Napper sits down with two of the most influential thinkers in the people analytics and HR research space to explore how AI, data, and evolving workforce dynamics are reshaping how organizations operate and make decisions. The discussion dives into RedThread’s latest research, including the evolution of mega trends shaping the future of work. Stacia and Dani reflect on themes like geopolitical disruption, the continued shift toward growth over people, and the accelerating integration of AI into enterprise workflows. Rather than viewing AI as a standalone concept, they emphasize it as an enabler becoming embedded into how organizations function—so much so that it may soon become “the air we breathe.” A major focus is the rise of multi-source analysis platforms (MSAPs), which aggregate and harmonize data across HR systems to drive better decisions. The trio explores how organizations are moving beyond siloed data toward integrated ecosystems combining employee experience, workforce planning, skills data, and operational insights. This shift represents a broader transformation in how companies understand work, breaking it down into tasks, outcomes, and dynamic systems involving both humans and AI. Dani brings a strong perspective on skills, tasks, and talent mobility, arguing that tasks may serve as the bridge between skills and work in an AI-driven world. However, both she and Stacia challenge the idea that mapping tasks alone is enough, suggesting organizations may need to rethink work from the outcome level entirely. This raises questions about whether current workforce design approaches are too rooted in legacy systems already being disrupted by AI. The episode also tackles a central question: will AI replace jobs or augment them? Stacia and Dani are clear—AI will replace some jobs, and already is. The challenge lies in how organizations respond, particularly in redeploying talent, maintaining learning pathways, and ensuring employees build the judgment needed to work effectively alongside AI. Another thread explores the “hollowed-out expert,” where individuals appear knowledgeable due to AI but lack true expertise. This raises concerns about authenticity and performance assessment, especially as research shows AI effectiveness depends heavily on user knowledge and cognitive ability. Throughout, the conversation challenges rigid HR operating models and one-size-fits-all transformation frameworks, emphasizing that success depends on asking better questions, understanding context, and adapting continuously. The episode closes with reflections on career success, the importance of social capital, and a core truth: despite rapid technological change, organizations exist because people prefer to work together. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.

Scott Hines, former co-host and people analytics practitioner who writes 'The Disconnect' on network analysis, returns for a reunion chat. They cover stepping back after loss, the hidden cost of content creation, AI reshaping knowledge work, automation tradeoffs, and building a digital command center. Conversation also touches on network silos, assessment design, and shifting workplace dynamics.

Check out this episode of the #1 people analytics podcast with special guest, Neil Morelli, Senior Director, Human+AI Collaboration and Workforce Transformation at Salesforce! If you like this episode, go ahead and sign up for Neil’s newsletter People-first AI! In this wide-ranging and deeply engaging conversation, Cole Napper sits down with Neil to unpack one of the most important shifts happening in the workplace today: AI workforce transformation. Rather than treating AI as just another tool, Neil explains how organizations are now rethinking the very nature of work itself. At the center of this shift is a move away from focusing purely on “jobs” or “tasks” and toward understanding work as dynamic units of value creation, where humans and AI systems collaborate in increasingly complex ways. Neil shares how AI introduces what feels like a new category of “digital talent,” fundamentally changing how organizations think about workforce composition, productivity, and value delivery. This shift requires leaders to rethink not just roles, but how work is structured, measured, and optimized. The conversation explores how organizations are beginning to adopt more economic-style thinking—focusing on value-added work versus overhead—and how new forms of observability are making it easier to measure contributions from both humans and AI systems. A major theme throughout the episode is the importance of mental models and frameworks for working effectively with AI. Neil emphasizes that success with AI isn’t about mastering prompt engineering tricks, but about breaking down problems, structuring work intelligently, and even using AI to help design better workflows. This “use AI to use AI” mindset becomes a powerful way to scale both individual and organizational capability. The discussion also dives into the evolving role of people analytics and workforce planning. Neil and Cole highlight how traditional analytics must now integrate more deeply with workforce planning, economics, and business strategy. The future belongs to practitioners who can bridge quantitative rigor with qualitative understanding of skills, motivation, and human behavior. Importantly, the episode doesn’t shy away from the human side of transformation. Neil discusses the psychological barriers to AI adoption, including fear, reduced psychological safety, and misconceptions about value and performance. He underscores that leadership behavior is critical—when managers model AI usage and create supportive environments, adoption accelerates. Without that, even the best tools and mandates fall flat. The conversation also touches on experimentation, collaboration, and the evolving nature of expertise. While AI democratizes access to capabilities, Neil argues that domain expertise remains essential for judgment, validation, and accountability. As organizations navigate uncertainty, the ability to be “directionally correct” becomes more valuable than ever. Blending practical insights with forward-looking perspective, this episode offers a thoughtful exploration of how AI is reshaping work, organizations, and the role of human talent in 2026 and beyond. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.

Meet Paola Alfaro, founder of HumanWorks who builds people analytics foundations across LATAM, and Maria Nolazco Masson, Ipsy analytics leader and writer who turns HR data into stories. They discuss building analytics from scratch in Latin America. They talk about data governance, training leaders, AI speeding workflows, community growth, and how storytelling and influence beat raw technical skills.

Dr. Paula Caliguiri, distinguished professor and global talent expert who co-founded Skillify. She explores cultural agility versus adaptability. She traces expatriate research to modern novelty at work. She discusses why soft skills like curiosity and humility matter as AI reshapes jobs. She describes Skillify’s approach to building durable people skills at scale.