Directionally Correct, A People Intelligence Podcast

Episoade

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  The ROI of People Analytics from Aptitude Research - Madeline Laurano - #183 27.07.2026 1h 6min

  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 guest, Madeline Laurano, Founder and Chief Analyst at Aptitude Research! Host Cole Napper sits down with Madeline to unpack the real ROI of people analytics, drawing from Aptitude Research’s findings that only about 18 percent of HR leaders even track it while talent acquisition leaders lag further behind. They explore the critical gap between traditional HR metrics like time-to-fill that business executives largely ignore and the outcomes that actually matter at the C-suite level—retention, productivity, revenue impact, and cost. The conversation digs into how the pandemic-era technology buying spree left many organizations with underused systems whose data makes little sense, creating barriers that people analytics teams must now navigate by collaborating more closely with CFOs rather than operating in silos. Madeline and Cole contrast how HR leaders and analytics practitioners define ROI, emphasizing costs, benefits to the business and employees, and realistic payback periods that can shrink to months with AI rather than the multi-year horizons once common in HR tech. They discuss the need for ongoing measurement instead of once-a-year calculations, the value of distinguishing direct from indirect returns, and the simple power of “journaling” executive priorities to build credibility. Strategic workforce planning emerges as both a long-standing passion and source of frustration for Madeline—too often treated as a start-and-stop exercise triggered by layoffs or relocations—yet newly urgent amid AI-driven restructuring of how work and tasks get done. Cole outlines the extensive data required to assess AI’s true workforce impact: third-party skills and task information, actual usage from tools like Gemini or Claude, internal productivity metrics, non-employee labor contributions, and full cost comparisons including human labor versus AI tokens. Vendors claiming to have solved this, they agree, simply do not yet possess that complete picture. The pair also examine what it means to be an independent HR industry analyst: conducting quantitative surveys, qualitative interviews, and endless vendor demos to deliver market clarity and informed forecasts, while relying on hard-won judgment and discernment that years of experience—and even newly minted sharp analysts—can cultivate. Side conversations at small dinners and informal gatherings often reveal more about real buying decisions, organizational politics, and vendor positioning than formal research alone. Looking ahead, they explore the shift from people analytics toward people intelligence, where human judgment, context, and gut feel complement AI rather than being replaced by it, and why positioning AI as a tool serving people rather than an equal collaborator remains essential. Practical AI agent use cases that already work—highly focused, low-risk, end-to-end tasks such as candidate sourcing or frontline shift scheduling—demonstrate how technology can restore autonomy and meaningfully improve workers’ lives. Additional threads cover the declining relevance of college rankings beyond the top twenty for early-career hiring, the salary-equivalent value of well-designed jobs that offer variety, learning, and initiative, the underappreciated strategic role of organization design, and a proposed AI-era HR operating model built around workforce intelligence, capability architecture, and strategy. Throughout, Madeline shares insights from her role as MC and product judge at the HR Technology Conference and the messy current state of agentic AI that demands better governance and orchestration if the industry is to move beyond chaos. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  The State of Workforce Planning in 2026 - Nick Kennedy - #182 20.07.2026 1h 9min

  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 guest, Nick Kennedy, CEO of The Workforce Planning Institute! In this timely conversation, Cole Napper and Nick dive deep into the State of Workforce Planning Profession Report, revealing key insights on growth and challenges. The report shows massive variability in team sizes with no standard model—some 10,000-employee organizations run teams of six while smaller ones have just one or two. Job ads indicate strong expansion, post-COVID recovery, and 166% growth in APAC driven by aging workforce focus, local training, and Australian pioneers like Alicia Roach and Peter House. Nick explains why executive buy-in remains hard: SWP needs direct senior leader access, which layers dilute in massive firms. Midsize organizations around 50-100k employees often have larger median teams as they've matured the function longer, unlike giants still focused on operational planning. The episode explores centralized to federated models that build business accountability while keeping central guidance. It celebrates SWP Conference growth in Chicago, London, and Sydney, with anchored locations driving momentum and maturing content that closes practitioner gaps. Standout sessions from Target and McDonald's plus Five Eyes military collaboration highlight global relevance. Nick expanded the portfolio with interconnected events on people analytics, AI, talent, and capability under one ticket, embracing the golden triangle converging into workforce intelligence. Cole and Nick align on this convergence, discussing talent acquisition feeding market insights, analytics shifting to scenarios, and behavioral science for stakeholder influence. Regional differences reflect geopolitics and healthcare but common challenges like Workday foster global sharing via the Institute. Nick shares his entrepreneurial journey founding the Institute as a global body. From practitioner consulting, a botched tender prompted a pivot to community: collaborate over compete, democratize best practices, and support professionals thrust accidentally into roles. The Institute offers training, education, lifetime memberships, and a home for the profession without prescribing one right way. Personal touches include Nick's morning productivity, overcoming sleep paralysis by cutting alcohol, and Top Gear car passion. In Cole's Corner they discuss fears, rapid fire on careers and characters, plus BCG HR trends where SWP ranks high alongside rising talent and org design topics. AI workforce transformation gets optimistic treatment—break down roles, skill shifts, and buy/build plans. The Tampa Bay Rays Moneyball evolution sparks talk on variety, configuration, and AI-enabled experimentation for competitive chaos. This episode delivers practical wisdom for SWP maturity, convergence, and leading uncertainty. Nick's global trends and community insights offer a clear roadmap. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  Is People Analytics Having a Mid-Life Crisis? & Employee Listening at Netflix - Colby Nesbitt - #181 13.07.2026 1h 38min

  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 guest, Colby Nesbitt, Senior Manager of Employee Listening at Netflix! In this wide-ranging conversation, Cole Napper and Colby dive deep into whether People Analytics is having a full-blown midlife crisis. They explore how the field was built on the assumption that more headcount equals more productivity, an idea that's decoupling in the age of AI and shifting economics. Colby and Yuyan Sun's recent work argues we should move beyond headcount metrics to measuring productive capacity—the tasks, value, costs, and risks executed by humans and AI alike. Revenue per employee benchmarks are climbing, and companies are now rewarded for leaner operations, forcing People Analytics to reinvent itself or risk irrelevance. The discussion gets spicy on the future of HR operating models. Colby envisions intelligence layers collapsing across functions, with HRBPs empowered by data while shared services get automated and centers of excellence hollowed out by AI. They debate how People Analytics, L&D, recruiting, and talent management might evolve into a more unified, boundary-spanning intelligence function. Colby shares insights from her unique journey as an IO psychologist at a performance management company, highlighting the science-practitioner gap and the humility required when moving from academia to startups and now Netflix. A highlight is the backstory of Colby's wildly popular SIOP session inspired by Hot Ones—complete with panelists eating increasingly spicy wings while delivering unfiltered takes on embedding with IT/data science, revisiting psychological contracts, and the value of failed experiments and humanizing conferences. Colby recounts changing flights for sessions and the genuine wisdom mixed with hilarity, like JP Elliott sharing Taco Bell taco-making hacks. They tackle Netflix's iconic culture memo, emphasizing that culture must be deliberately cultivated as a product, not owned solely by HR, and why portability across companies is tricky. Colby reflects on her NYT-profiled high school years, intrinsic motivation drawn from running as a metaphor for life, and the joy of big questions in her Substack Variance Explained. Sports analogies abound: why professional sports serve as a proxy for war and data-rich playground for studying leadership, teamwork, and performance—but why they're imperfect metaphors for work due to radical transparency in pay and metrics. Performance distributions spark debate—is it a power law for outputs or normal for behaviors? They unpack compensation tensions between equity, proportionality, procedural vs. distributive justice, and whether high performers are underpaid relative to their value. Colby challenges the field on relevance, questioning why IO psychology settles for modest predictive validities and comfortable topics instead of tackling zeitgeist issues. Cole shares lessons from implementing 360 feedback that failed in reality, underscoring first-principles thinking. Additional gems include listening for capability beyond sentiment, non-response bias in surveys, disembodiment of knowledge work, off-duty deviance in the WFH era, and Price's Law on outputs driving disproportionate impact. Colby stresses writing for intrinsic reasons—what only you can contribute—while navigating power laws in content creation. This episode is a masterclass in big ideas, self-reflection, and forward momentum for the field. From AI's impact on work systems to chaos as a ladder for builders who entered People Analytics early, Colby and Cole emphasize curiosity, first-principles, and using this transformative moment to take big swings. Whether you're rethinking metrics, HR structure, employee listening, or your own career, this conversation delivers fresh perspectives grounded in real experience at Netflix and beyond. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  What Analytics Do Startups & PE-Backed Firms Need? - Andrew Bartlow - #180 06.07.2026 1h 26min

  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 guest, Andrew Bartlow, Operating Partner & Senior Advisor at Altamont Capital Partners; Co-Founder, People Leader Accelerator! In this episode, Cole Napper sits down with Andrew Bartlow for a wide-ranging conversation on what HR and people analytics leaders can learn from the world of venture-backed startups, private equity, and high-growth technology companies. Drawing on decades of experience spanning engineering, HR leadership, venture-backed software companies, private equity portfolio operations, and executive coaching, Andrew explains why context—not best practices—should drive every people decision. Together, they unpack how venture capital, private equity, and public companies operate under fundamentally different business models, why HR leaders must understand investor expectations, and how those realities should shape workforce strategy, talent priorities, and the metrics that matter. Andrew demystifies concepts like bootstrapping, exits, venture funding, private equity ownership, and startup ecosystems while explaining how those forces influence executive decision-making and the role HR plays in creating business value. The discussion explores why business acumen is the defining capability for modern HR leaders and why people analytics should always begin with understanding how the company creates value. Rather than chasing universal scorecards or generic best practices, Andrew argues that every metric should align with the organization's current business context. They debate which workforce measures truly matter—including headcount versus plan, critical hiring progress, labor cost as a percentage of revenue, productivity, profitability, and growth—and why commonly reported metrics like eNPS often receive far more attention than they deserve. Cole and Andrew also explore how startup environments create entirely different talent dynamics than mature enterprises, why employee turnover is often driven more by external alternatives than internal dissatisfaction, and how labor markets, organizational stage, investor pressure, and company culture influence retention. They discuss talent density, organizational design, multi-incumbent roles, workforce planning, performance management, and why many HR teams mistakenly optimize for activities that executives value least. The conversation also covers Andrew's entrepreneurial journey building an HR technology startup, lessons learned from failure, the realities of software entrepreneurship, and why founder experience fundamentally changes how leaders think about business. They discuss AI's growing impact on HR, how automation will reshape business partner roles, why judgment remains uniquely human, and what tomorrow's HR leaders must do to remain indispensable as AI increasingly handles transactional work. Andrew also shares the philosophy behind People Leader Accelerator, how the program develops high-impact HR executives, why contextual thinking separates exceptional leaders from average ones, and what future HR professionals should prioritize if they want lasting influence inside their organizations. Whether you work in people analytics, HR business partnering, organizational effectiveness, workforce planning, talent strategy, executive leadership, or simply want to better understand how high-growth companies think about people and performance, this episode offers a practical masterclass in aligning HR with business outcomes in the AI era. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  Is People Intelligence the Future? Unpacking a Manifesto - Cole Napper & Alexis Fink - #179 29.06.2026 57min

  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 our latest HR Tech Voices episode of 2026! In a special twist, host, Cole Napper, steps into the guest seat as he’s interviewed by special guest host, Alexis Fink, Founder of Propeller Insights and Co-Founder of the Data Driven HR Academy! We explore what "people intelligence" really means, Cole's People Intelligence Manifesto, and why people analytics isn't dead but instead is evolving into its next chapter. At the center of the conversation is Cole's People Intelligence Manifesto and the ideas that inspired it. Rather than arguing that people analytics is dead, Cole explains why the discipline is entering a new era where AI fundamentally changes how organizations collect, analyze, and act on workforce data. He introduces his vision for people intelligence as the convergence of people analytics, talent intelligence, workforce planning, and behavioral science into a unified function capable of driving faster, smarter business decisions. Alexis challenges many of the manifesto's boldest claims, leading to a thoughtful discussion about why organizations should stop treating dashboards as the ultimate deliverable and instead focus on creating business impact through decision support, organizational change, and intelligence. They explore why AI will increasingly automate descriptive reporting while elevating the importance of asking better questions, influencing leaders, and translating data into action. The discussion also examines why industrial-organizational psychology is becoming more important—not less—in the AI era. As work itself is redesigned around skills, tasks, jobs, and intelligent systems, they explain why expertise in job analysis, organizational design, behavioral science, and workforce strategy will become even more valuable than traditional reporting capabilities. Throughout the episode, Cole and Alexis debate whether people analytics professionals should remain scorekeepers or become active players helping organizations shape strategy and transformation. They discuss the responsibility of analytics leaders to create shared meaning from data, challenge executive assumptions when necessary, and guide organizations through one of the largest technological shifts in the history of work. The conversation also explores the growing gap between research and practice, why collaboration between academics and practitioners remains difficult, and how organizations can better bridge evidence-based science with real-world business decisions. They discuss the future of people analytics teams, the changing skills professionals should develop, the role of AI-native technology platforms, and why today's disruption creates enormous opportunity for those willing to evolve. Whether you're a people analytics leader, HR executive, workforce planner, organizational effectiveness professional, IO psychologist, HR technologist, or simply curious about how AI is reshaping the future of work, this episode offers an honest and thought-provoking look at where the profession is headed and why its next chapter may be even more exciting than its first. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  Is a Digital Twin Coming for You & Your Job? - Allen Kamin - #178 22.06.2026 1h 12min

  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 guest, Allen Kamin, Practice Leader, Organizational Effectiveness at Oracle! In this wide-ranging and thought-provoking conversation, Cole Napper sits down with Allen Kamin to explore some of the biggest questions facing people analytics, organizational effectiveness, workforce strategy, and the future of work in the age of AI. Drawing on a career that spans Oracle, Google, GE, consulting, and decades of involvement in industrial-organizational psychology, Allen shares lessons from the front lines of organizational transformation and explains why many companies may be focusing on the wrong problems as AI rapidly reshapes how work gets done. The discussion begins with one of Allen’s most influential ideas: the concept of the digital twin. Long before generative AI, large language models, and AI agents entered the mainstream, Allen was exploring how organizations could create digital representations of workers based on the behavioral data and “digital exhaust” employees generate every day. Together, Cole and Allen unpack what digital twins actually mean, how employee monitoring technologies have evolved, where organizations may be overreaching, and whether AI systems will ever be capable of fully replacing knowledge workers. Allen reflects on how his original predictions have aged over the past decade, what he got right, what surprised him, and why the emergence of agentic AI may fundamentally alter how organizations make decisions, collaborate, and distribute work between humans and machines. The conversation then shifts into several of Allen’s recent articles and thought leadership pieces. He explains his concept of the “day after problem” in people analytics and argues that the field has become overly focused on building dashboards and delivering data while often neglecting the harder challenge of influencing decisions and changing organizational outcomes. As AI makes reporting easier than ever, Allen argues that the future of people analytics will be determined not by better dashboards but by better decisions. Cole and Allen also discuss why many HR systems are optimized for approval rather than actual use, why organizations often design solutions from the inside out instead of the outside in, and how excessive complexity can undermine even the most technically sound programs. They explore the importance of user-centered design, manager adoption, and balancing scientific rigor with practical utility. The discussion expands into systems thinking and organizational effectiveness as Allen shares his perspective that every function within HR can be doing its job perfectly while the organization as a whole still fails. Using examples from sports, large global enterprises, and executive leadership teams, he explains why organizations need better mechanisms for prioritization, governance, and cross-functional alignment. Along the way, Allen reflects on his career journey, his involvement in the industrial-organizational psychology community, the value of professional relationships, lessons learned from consulting and corporate leadership roles, and his perspective on what separates meaningful work from merely productive work. The episode concludes with a lively discussion on AI, workforce planning, employee experience, organizational culture, executive leadership, employee listening, engagement research, career development, and the future role of people analytics in an increasingly complex business environment. Whether you're a people analytics leader, HR executive, workforce planner, organizational psychologist, consultant, manager, or simply someone fascinated by how AI is changing work, this episode offers a thoughtful and practical look at where organizations are headed next. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  The Skills vs Tasks Debate We Need - Angela Le Mathon & Sandra Loughlin - #177 15.06.2026 1h 6min

  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, Angela Le Mathon, VP, Workforce Intelligence & Insights at Walmart & Sandra Loughlin, Chief Learning Scientist at EPAM! In this wide-ranging and highly thought-provoking conversation, Cole Napper sits down with two of the most influential voices shaping the future of workforce intelligence, skills strategy, organizational design, and AI-enabled work. Together, they tackle one of the biggest debates currently unfolding across HR, people analytics, workforce planning, and business leadership: What is the true unit of work in the AI era? Is the future built around skills, tasks, jobs, agents, or something entirely different? Sandra explains why skills remain one of the most important—and misunderstood—constructs in organizational science. She explores why skills are measurable despite being latent constructs, why organizations must improve how they identify and validate skills, and why skills data may become foundational to workforce decision-making in the years ahead. Angela brings a complementary perspective focused on tasks, work decomposition, and business impact, explaining why tasks have become central to many AI transformation conversations and how organizations can think more systematically about measuring and redesigning work. The discussion expands into the rapidly evolving relationship between humans and AI. Cole, Angela, and Sandra examine whether AI agents should be treated as workers or technology, the psychological implications of anthropomorphizing AI, and why organizations must be careful not to lose the uniquely human elements of collaboration, judgment, learning, creativity, and meaning-making. The conversation also explores how AI may fundamentally reshape HR itself. The group discusses whether traditional HR operating models remain fit for purpose, how AI could force organizations to rethink decades-old assumptions about work and workforce management, and why understanding work at a far more granular level may become a strategic necessity. Along the way, they debate organizational incentives, AI adoption realities, employee concerns, workforce transformation maturity, and the gap between vendor promises and practical implementation. Angela shares insights from Walmart’s perspective on human-centered AI adoption, highlighting why technology should ultimately serve employees rather than replace them. Sandra introduces emerging ideas around AI-native organizations, workforce intelligence, and the concept of a “Knowledge Office”—a future organizational capability designed to sense, interpret, activate, and sustain value from enterprise knowledge and data. The discussion also dives into skills architectures, capability orchestration, adaptive labor models, organizational learning, employee surveillance concerns, workforce data infrastructure, talent mobility, knowledge management, and the growing importance of understanding how work actually gets done rather than relying on outdated job descriptions and static organizational structures. Whether you're a people analytics leader, CHRO, workforce planner, learning leader, HR executive, organizational scientist, consultant, or business executive trying to navigate AI transformation, this episode offers a nuanced and refreshingly honest conversation about what is changing, what is not changing, and what organizations must understand if they hope to successfully redesign work for the future. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  People Insights at HP & The Value of Data Security - Amy Stevenson - #176 08.06.2026 1h 5min

  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 guest, Amy Stevenson, Senior Director People Insights at HP! In this wide-ranging and highly practical conversation, Cole Napper welcomes back Amy Stevenson for a discussion that spans the evolution of people analytics, the realities of building enterprise-scale analytics capabilities, the future of AI in HR, and the leadership lessons that come from spending years turning strategy into execution. Amy reflects on her journey building and scaling HP’s People Insights function over more than five years, sharing what it takes to create a sustainable analytics organization capable of delivering value in a rapidly changing business environment. Drawing on experience across multiple industries and leadership roles, she explains why successful people analytics teams must think beyond dashboards and reporting and instead focus on long-term capability building, organizational influence, and business impact. A major theme throughout the discussion is the challenge of balancing innovation with governance. Amy provides a thoughtful perspective on the realities of working with sensitive workforce data, discussing the distinctions between privacy and security, the complexities of role-based access, and why HR data presents unique challenges compared with other enterprise data domains. She also explains why partnerships with legal, privacy, cybersecurity, IT, finance, and enterprise technology teams are becoming increasingly important as organizations develop broader AI and data strategies. The conversation explores one of the most debated questions facing analytics leaders today: build versus buy. Amy shares how HP approached developing internal capabilities, the role of proprietary intellectual property, and how leaders can evaluate whether internally developed tools and methodologies truly create strategic advantage. She also discusses the importance of peer networks, professional communities, and trusted relationships in helping analytics leaders validate ideas, exchange knowledge, and avoid common pitfalls. Cole and Amy spend significant time examining the impact of generative AI on people analytics. They discuss governance models, emerging organizational structures for AI oversight, the challenges of integrating HR data into enterprise AI ecosystems, and how leaders can responsibly explore new use cases while maintaining ethical standards and stakeholder trust. Amy argues that while AI will undoubtedly transform work, its greatest value may come from freeing professionals to spend more time on deeper thinking, creativity, and problem solving. Beyond technology, the discussion repeatedly returns to leadership. Amy emphasizes the importance of relationships, credibility, and organizational trust as the foundations of successful analytics programs. She shares insights on gaining recognition for analytics work, influencing stakeholders, navigating enterprise transformation efforts, and ensuring that people analytics functions become trusted strategic partners rather than simply technical support teams. The episode also ventures into talent, learning, and career development. Amy and Cole debate hiring for potential versus hiring for immediate qualifications, discuss what distinguishes exceptional performers, and explore how broad experiences often create stronger leaders than narrow specialization. They also examine the future career paths available to analytics professionals and why developing business breadth may be just as important as deep technical expertise. As always, the conversation blends practical advice, intellectual curiosity, humor, and reflection, offering valuable lessons for analytics practitioners, HR leaders, and anyone interested in how organizations can better use data, technology, and human insight to make better decisions. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  The Power of Us & Social Identity at Work - Jay Van Bavel - #175 01.06.2026 58min

  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 guest, Jay Van Bavel, Professor of Psychology & Neural Science at NYU and Author of “The Power of Us”! In this wide-ranging and deeply thought-provoking conversation, Cole Napper sits down with Jay Van Bavel to unpack one of the most important—and often misunderstood—forces shaping organizations, workplaces, and society today: identity. Drawing from decades of research in psychology, neuroscience, group behavior, and conflict, Jay explains why identity is far more than an academic concept—it shapes how we think, what we value, who we trust, and how organizations succeed or fail. At the center of the discussion is a powerful idea: we are shaped by the groups we join. Jay explains how identities act like lenses through which we interpret the world, influencing behavior, priorities, and even morality. Whether in workplaces, families, professional communities, or social groups, the identities we adopt quietly shape our decisions and relationships in ways most people underestimate. Cole and Jay explore one of the defining workplace challenges of the modern era: rising polarization, incivility, and declining trust. Jay shares research on why remote work, shrinking social circles, and fragmented organizational identities may be contributing to lower cooperation and weaker connections at work. The discussion reframes psychological safety—not as avoiding conflict, but as creating environments where people can challenge ideas, disagree productively, and take interpersonal risks without fear. The episode also dives into inclusion, bias, and organizational performance. Jay explains why diverse teams only outperform when paired with shared identity, inclusive norms, and psychological safety. He offers a nuanced perspective on why some approaches to DEI created backlash, what organizations misunderstood, and how leaders can foster inclusion in ways grounded in science rather than ideology. Cole and Jay examine the hidden power of dissent, asking why organizations often punish the very people who care most about the group. Jay shares practical strategies for avoiding groupthink, encouraging constructive disagreement, and building cultures where dissent strengthens decision-making rather than undermining cohesion. The conversation also explores why social skills may matter more than technical skills in the future of work, how Gen Z’s changing relationship with in-person interaction is affecting workplaces, and why relationship-building may become one of the most valuable capabilities in an AI-driven world. Along the way, they discuss conformity, culture fit, social media, moralization, and even the surprising story behind the rivalry that created Adidas and Puma as a lesson in identity and belonging. If you work in HR, people analytics, organizational psychology, talent management, or simply want to better understand why people behave the way they do inside groups, this conversation offers practical, research-backed insights for building healthier and higher-performing organizations. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  The Strategic Workforce Planning Handbook - David Edwards - #174 25.05.2026 1h 6min

  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 guest, David Edwards, Chief Workforce Strategist at Dark Artistry, Author of "The Strategic Workforce Planning Handbook"! In this wide-ranging and deeply practical conversation, Cole Napper sits down with David Edwards to unpack one of the most important—and often misunderstood—disciplines shaping the future of work: strategic workforce planning. Drawing from decades of experience across HR, workforce strategy, and organizational transformation, David explains why workforce planning is far more than forecasting headcount. Instead, it is about ensuring organizations have a workforce fit for future business purpose—and understanding the risks that emerge when they do not. David reflects on publishing The Strategic Workforce Planning Handbook and the challenge of writing in a field evolving at breakneck speed. He candidly shares how rapidly advancing AI capabilities made parts of the book feel outdated almost immediately, highlighting just how quickly workforce realities are shifting and why practitioners must constantly adapt. A major theme of the conversation is the relationship between business strategy, workforce demand, and workforce risk. David explains why organizations often misunderstand “strategy,” arguing that workforce planning only becomes meaningful when deeply connected to business objectives. Through practical examples, he demonstrates how hidden vulnerabilities—aging talent populations, concentrated expertise, succession gaps, and critical capability shortages—can quietly threaten organizational performance if left unaddressed. The discussion also explores the increasingly inseparable relationship between people analytics and workforce planning. David argues that workforce planning cannot exist without evidence, while analytics alone often lacks the context necessary to influence business decisions. Together, the two disciplines help leaders identify which parts of the workforce are truly strategic, where risks exist, and how talent decisions shape long-term business outcomes. Cole and David spend significant time discussing AI’s accelerating impact on workforce planning itself. Rather than viewing planning as a static annual process, David envisions a future where AI enables more dynamic analysis of workforce risk, capability gaps, and changing work structures. The conversation moves beyond simple headcount questions to larger issues: How will AI reshape work? Which capabilities will become more valuable? And how should organizations prepare for a future changing faster than traditional planning cycles can handle? Beyond strategy and frameworks, the episode takes a surprisingly personal turn as David reflects on his career journey—from volunteering as a teacher in Kenya at age eighteen to singing in a seventeen-piece soul band and helping redeploy employees at risk of losing their jobs. Those experiences shaped a deeply people-centered philosophy rooted not just in business outcomes, but in helping people navigate transitions and continue meaningful careers. Cole’s Corner brings provocative debates on management quality, aging workforces, mentorship, knowledge transfer, and what organizations should do with long-tenured employees whose performance no longer matches evolving business needs. The episode closes with a thoughtful reflection on technological disruption, history, and human resilience as Cole and David consider whether today’s AI-driven transformation mirrors other moments of dramatic societal change. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  Human Centered Design, Coca-Cola, & People Insights - Sue Lam - #173 18.05.2026 1h 14min

  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 guest, Sue Lam, VP of Global People Insights, Culture, Strategy & Planning at The Coca-Cola Company! In this wide-ranging and highly practical conversation, Cole Napper sits down with Sue Lam, VP of Global People Insights, Culture, Strategy & Planning at The Coca-Cola Company, to explore what it actually takes to turn people analytics into meaningful organizational change. Returning to the podcast after her original episode was lost during a platform migration, Sue reflects on how the field has evolved and why analytics teams must move beyond dashboards and reporting to influence real-world behavior. Sue shares how her role at Coca-Cola blends people insights, culture, and strategy to help leaders make better decisions through data—but with an important distinction: her team focuses on behavioral change, not just surfacing insights. She walks through a compelling example of Coca-Cola’s culture transformation, where analysis revealed employees were still being rewarded for behaviors tied to an outdated operating model. Rather than stopping at the findings, her team partnered across leadership development, rewards, talent, and local culture teams to redesign manager conversations, interventions, and training to reinforce desired behaviors. A major theme throughout the episode is human-centered design and why HR must shift from building programs to designing experiences. Instead of asking what training managers need, Sue argues organizations should ask what it feels like to become a manager, where friction exists, and what unseen pressures employees face. By focusing on the employee experience rather than the HR process, organizations can create systems that improve both performance and wellbeing. Cole and Sue also discuss the overlap between social psychology, industrial-organizational psychology, and behavioral science, exploring why ideas from adjacent disciplines like marketing and design thinking may be essential to HR’s future. Sue reflects on her unconventional path as a social quantitative psychologist and how it unexpectedly prepared her for culture and organizational work. The conversation expands into larger workplace debates, including whether industrial-organizational psychology is doing enough to influence real business decisions. Together, they discuss why evidence-based research often struggles to shape practice in elite organizations, where hiring decisions may rely more on credentials, networks, and backchannel references than formal science. They also explore how stronger partnerships between researchers and practitioners could accelerate more applied insights. AI’s growing impact on hiring becomes another key focus. Cole and Sue debate whether resumes and traditional credentials are becoming less meaningful signals of competence in a world where AI can generate polished applications and work samples. While public proof of work and personal brands may surface talent, both question how organizations will distinguish genuine expertise from polished outputs and whether recruiting may ultimately shift back toward trust, relationships, and human networks. Alongside the serious topics, the episode balances humor and storytelling as Cole and Sue unpack shows like Industry and Silicon Valley, reflecting on what they reveal about workplace incentives, analytics, and organizational behavior. The discussion also touches on workplace jargon, organizational “BS,” high performers, academic publishing, and the future of people intelligence. Throughout the conversation, Sue brings intellectual rigor, practical wisdom, and humor, offering listeners a thoughtful look at how organizations can create better employee experiences while driving stronger business outcomes. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  What We Know About Astronauts, Artemis 2, & NASA - Suzanne Bell - #172 11.05.2026 1h 1min

  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 guest, Suzanne Bell, Lead Scientist, NASA’s Behavioral Health & Performance Lab! In this wide-ranging and deeply fascinating conversation, Cole Napper sits down with Suzanne Bell to explore one of the most unique and high-stakes applications of industrial-organizational psychology in the world: preparing human beings to live, work, and thrive in space. As a lead scientist at NASA, Suzanne shares how her team supports astronaut selection, behavioral health, team dynamics, cognitive readiness, sleep science, and mission performance as humanity prepares for a sustained return to deep space through the Artemis missions and eventually journeys to Mars. The conversation dives into the enormous psychological and operational challenges associated with long-duration spaceflight. Suzanne explains how life aboard spacecraft like Orion differs dramatically from even the International Space Station, where astronauts already operate under isolation and confinement. Living in an extremely small shared environment with little privacy introduces new complexities around teamwork, adaptability, emotional regulation, and interpersonal dynamics. She discusses how NASA studies these conditions through both real missions and Earth-based analog environments, allowing researchers to better understand what makes teams resilient under prolonged stress. Cole and Suzanne also unpack the science behind astronaut selection and what constitutes “fit to mission.” Suzanne explains that while technical expertise matters, behavioral competencies such as adaptability, teamwork, emotional stability, and the ability to both lead and follow become increasingly critical as missions grow longer and more isolated. She emphasizes that NASA applies rigorous scientist-practitioner principles, including competency modeling, multimethod assessment, and evidence-based selection systems, to identify individuals capable of succeeding in some of the harshest environments humans have ever encountered. One of the most compelling sections of the discussion focuses on how humans adapt under stress. Suzanne shares insights from NASA’s growing database of individuals who have lived in isolated and confined environments, highlighting research showing that humans are remarkably adaptable but that transitions themselves often create the greatest challenges. Whether adjusting to microgravity, returning to Earth, or preparing for life on another planet, the process of adaptation places enormous demands on cognition, emotion, and physical functioning. She also reveals emerging findings showing that declines in positive affect during long-duration isolation can reduce task speed even when accuracy remains high, reinforcing the importance of emotional well-being for mission success. The conversation also explores Bayesian statistics, small-sample research, and how NASA approaches evidence generation in situations where only a handful of astronauts may ever participate in a mission. Suzanne explains how her lab transformed its data infrastructure to aggregate findings across missions and simulations, enabling faster learning cycles and more effective decision-making for future Artemis missions. The discussion becomes a masterclass in applied research design, demonstrating how rigorous analytics can still thrive in environments with limited data but extraordinarily high consequences. Cole and Suzanne also spend significant time discussing AI, ethics, and the future of scientist-practitioner work. Suzanne shares how NASA is thinking about AI-assisted monitoring and Earth-independent operations for future Mars missions where communication delays make real-time support from Earth impossible. Together they explore the ethical responsibilities researchers have to engage with emerging technologies proactively, ensuring science helps shape responsible adoption rather than reacting after the fact. Beyond the science, the episode offers a deeply human look into Suzanne herself, including her routines, leadership philosophy, curiosity about the world, and perspective on balancing an incredibly demanding career with family life. The result is an inspiring conversation about psychology, leadership, teamwork, innovation, resilience, and the future of human exploration. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  What is Potential & How Do You Assess for It? - Allan Church - #171 04.05.2026 1h 15min

  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 guest, Allan Church, Co-Founder and Managing Partner at Maestro Consulting! In this wide-ranging and deeply insightful conversation, Cole Napper sits down with Allan Church to unpack one of the most debated and often misunderstood topics in the field of talent management: the distinction between performance and potential. Drawing on decades of experience at PepsiCo and beyond, Allan challenges the simplistic assumptions that many organizations still rely on—particularly the idea that high performance automatically equates to high potential. Instead, he emphasizes that success in a current role predicts performance at a similar level of complexity, not necessarily at the next level, a nuance that is frequently overlooked in practice. The discussion explores how organizations continue to rely on reductionist frameworks like the nine-box grid, often without the rigor or clarity needed to differentiate performance from potential effectively. Allan explains that most leaders struggle to make this distinction, especially when assessments are conducted simultaneously, leading to flawed talent decisions and reinforcing biases. He introduces a more structured and science-based perspective on potential, outlining key components such as cognitive ability, personality, motivation, learning agility, and leadership capability—many of which can be measured through validated tools rather than intuition alone. A key theme throughout the conversation is the tension between simplicity and accuracy. Organizations often seek clean, easy answers, but Allan argues that meaningful talent evaluation requires embracing complexity and using multiple data sources. He also highlights the importance of customized leadership models that reflect an organization’s strategy and future direction, rather than relying on generic frameworks. These models not only guide assessment but also align development, feedback, and succession planning in a cohesive way. The conversation also dives into the evolving role of AI in talent assessment. While AI can aggregate and analyze large amounts of data, Allan cautions that it is only as good as the inputs and outcomes it is trained on. Without a clear definition of potential and robust underlying data, AI risks reinforcing existing misconceptions rather than improving decision-making. He also raises important ethical considerations around monitoring and data collection, noting the potential trade-offs between insight and trust. Beyond assessment, Allan addresses broader challenges in talent management systems, including the persistent dissatisfaction with performance management. He describes it as a “no-win” system—necessary for differentiation and feedback, yet universally disliked. Rather than seeking a perfect solution, he suggests organizations focus on execution, consistency, and alignment with business needs. Similarly, he argues that many failures in succession planning stem not from flawed design, but from poor follow-through. Throughout the episode, Allan brings a systems-thinking perspective, emphasizing that talent management must balance investment in high potentials with development opportunities for the broader workforce. He challenges the false dichotomy between elite talent focus and inclusive development, advocating for a more integrated approach that supports both organizational performance and employee growth. This episode is packed with practical wisdom, candid reflections, and thought-provoking perspectives on how organizations can move beyond outdated assumptions and build more effective, evidence-based approaches to people analytics and talent strategy. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  People Analytics is a commodity & HRBench will save it - John Barry, Matt Maguire, & Brandon Collins - #170 27.04.2026 1h 7min

  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, John Barry, Co-CEO at HRBench, Matt Maguire, CRO at HRBench and Brandon Collins, CTO at HRBench! In this wide-ranging and highly practical conversation, host Cole Napper sits down with the leadership team behind HRBench to explore how decades of shared experience in HR tech have shaped their vision for the future of people intelligence. What stands out immediately is the deep working history among the trio—relationships built over years at companies like Salary.com and PayFactors—which has translated into a strong foundation of trust, alignment, and execution speed as they build HRBench. At the core of the discussion is a simple but powerful idea: data should be the foundation of every HR decision. The team reflects on how their early work in compensation analytics revealed a broader gap across HR—organizations lacked a unified way to bring together workforce data, understand it, and act on it strategically. HRBench was built to solve exactly that, consolidating disparate HR data into a single system that enables faster insights, benchmarking, and decision-making without months of manual reporting work. A recurring theme throughout the episode is the rapid commoditization of traditional people analytics capabilities. Dashboards, reporting, and even predictive analytics are becoming easier and cheaper to build, largely due to advances in AI. But rather than diminishing the field, the guests argue this shift raises the bar. The real value is no longer in producing reports—it’s in driving action, enabling better decisions, and embedding intelligence directly into business workflows. The conversation also dives into how AI is transforming both product development and organizational productivity. Brandon shares how engineering workflows have fundamentally changed, with AI agents now writing and reviewing code, dramatically compressing development timelines. At the same time, Matt highlights how customers are using tools like HRBench alongside AI to achieve output levels that previously required much larger teams, signaling a major shift in how HR functions scale. Despite the excitement around AI, the group is clear-eyed about its limitations. Data quality, security, and business context remain critical challenges. “Garbage in, garbage out” still applies, and organizations must be thoughtful about how they manage sensitive employee data. Trust—both in the data and in the people interpreting it—continues to be essential, especially when insights inform high-stakes decisions. Looking ahead, the discussion turns to the future of people analytics as part of a broader intelligence layer within organizations. Rather than siloed functions like workforce planning, talent analytics, and behavioral science, the field is converging into a unified capability focused on generating and applying insight. The team envisions a future where organizations can model themselves as digital twins, simulating workforce decisions and understanding their impact across the business in real time. They also touch on emerging areas like qualitative data analysis, workforce transformation, and the evolving definition of work in an AI-driven world. Across all of it, one idea remains consistent: organizations that can combine high-quality data with actionable intelligence—quickly and affordably—will have a significant competitive advantage. Blending strategic insight with candid moments and humor, this episode offers a clear window into how experienced builders in HR tech are thinking about the next chapter of the industry and why the shift from people analytics to people intelligence is already underway. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  Is People Analytics Ready to be CHRO & Executive Search - Jennifer Wilson - #169 20.04.2026 50min

  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 guest, Jennifer Wilson, Partner and Global Co-Head, HR Officers Practice at Heidrick & Struggles! In this wide-ranging and deeply practical conversation, Cole Napper sits down with Jennifer Wilson to unpack how the role of the Chief Human Resources Officer is evolving in real time—and why the expectations for HR leadership have never been higher. Jennifer shares her unconventional path into executive search, describing how her early career in consulting and global work across Hong Kong and the US shaped her perspective on leadership, organizational design, and the human side of business transformation. What emerges is a clear view of executive search not just as recruiting, but as a front-row seat to how leadership itself is changing. A major theme throughout the discussion is the rapid expansion of the CHRO role. Drawing on research from Heidrick & Struggles, Jennifer explains how the number of required capabilities for CHROs has nearly doubled over the past decade, reflecting the growing complexity of the job. Today’s CHRO is no longer an administrative leader but a strategic enterprise partner expected to connect business strategy with people strategy, advise CEOs directly, and lead through ambiguity. The conversation highlights how skills like AI enablement, workforce planning, succession strategy, and organizational design are becoming essential, alongside enduring traits like empathy, judgment, and high emotional intelligence. The discussion goes deep on AI’s impact, particularly the idea of an “AI-native CHRO.” Jennifer is candid that such profiles are still rare, with most leaders only having partial exposure to AI-driven transformation. Rather than searching for perfect technical expertise, organizations are prioritizing curiosity, adaptability, and the ability to lead change. This reflects a broader shift: the future of HR leadership is less about mastering every domain and more about integrating across them. Cole and Jennifer also explore career pathways into the CHRO role, including the limitations of traditional HR development models. They discuss why many leaders lack the breadth of experience required and why moving from a number two role into the top job is such a significant leap. People analytics emerges as a particularly interesting lens—while it offers a unique enterprise-wide perspective, Jennifer notes that it cannot be the sole foundation for a future CHRO. Exposure to business leadership, operational accountability, and direct advisory experience remains critical. The conversation also demystifies executive search, clarifying a common misconception: search firms work for companies, not candidates. While building relationships can help, relying solely on headhunters is not a viable career strategy. This insight grounds the discussion in reality, emphasizing the importance of proactive career management. In the latter part of the episode, the conversation broadens to hiring practices, assessment tools, and the growing intersection between HR and technology. Jennifer pushes back on the idea of merging CHRO and CTO roles, arguing instead for stronger collaboration rather than unrealistic “unicorn” expectations. The future, she suggests, will depend on how effectively leaders integrate human and technical systems to drive organizational success. Throughout, Jennifer paints a compelling picture of the ideal HR leader for the future: engaging, empathetic, data-driven, agile, and capable of navigating constant change. It’s a vision that challenges both current leaders and aspiring ones to rethink how they build skills, gain experience, and lead in an increasingly complex world. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  People Analytics Explained, Consulting Skills & Pivot to Asia - Kinsey Li - #168 13.04.2026 1h 4min

  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.
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  What RedThread Research Says About AI & Everything Else - Stacia Garr & Dani Johnson - #167 06.04.2026 1h 12min

  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.
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  Scott RETURNS for a Co-Host Reunion - Scott Hines - #166 30.03.2026 1h 10min

  Check out this episode of the #1 people analytics podcast with special guest, Scott Hines, Previous Co-Host of Directionally Correct! In this long-awaited reunion episode, Cole and Scott reconnect after Scott's time away from the mic, diving into a candid, wide-ranging conversation that blends humor, reflection, and sharp insight on the evolving world of work, technology, and people analytics. The discussion opens with Scott’s decision to step away from the podcast, driven in part by personal reflection following the loss of his mother and a reassessment of how he spends his time. What follows is an honest look at the hidden effort behind content creation, the opportunity cost of side projects, and the reality that even passion projects can become demanding commitments. As the conversation unfolds, the two explore how advances in AI are reshaping not just workflows, but the very nature of knowledge work itself. From fully automated academic research to AI-powered coding and reporting tools, they reflect on the accelerating pace of change and the tradeoffs that come with it, including the subtle erosion of foundational skills. At the same time, they wrestle with the paradox of wanting to stay current in a rapidly evolving tech landscape while avoiding the noise, hype, and constant distractions that come with it. This tension shows up in their discussion of digital minimalism, notification fatigue, and the idea of building a “command center” for life and work. The episode also revisits core people analytics topics, including the relationship between cognitive ability and personality, the nuances of assessment design, and the ongoing debate around prediction, fairness, and subgroup differences. Scott brings his signature analytical lens, while Cole connects these ideas back to real-world applications and the future of workforce strategy. They also touch on broader societal themes, from generational shifts in workplace behavior to the potential long-term impacts of pandemic-era disruptions on social and cognitive development. True to form, the episode mixes depth with levity. The duo riff on everything from the “Gen Z stare” to the absurdity of hyper-competitive pickleball, while also tackling more serious ideas like workplace surveillance, the changing nature of organizations in an AI-driven world, and whether academia should still be viewed as a calling or simply another job under pressure. Throughout, there’s a consistent thread: questioning assumptions, challenging norms, and trying to make sense of a world where the boundaries between human and machine capabilities are increasingly blurred. The episode closes on a high note with updates on Scott’s new role at HRBench and Cole’s continued growth of the podcast and broader ecosystem, signaling that while things evolve, the core mission of exploring people analytics and the future of work remains as strong as ever. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.
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  AI Workforce Transformation at Salesforce & Work Intelligence - Neil Morelli - #165 23.03.2026 1h 6min

  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.
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  The REAL Conversation about People Analytics in LATAM - Maria Nolazco Masson and Paola Alfaro- #164 16.03.2026 1h 9min

  Check out this episode of the #1 people analytics podcast with special guests, Maria Nolazco Masson, People Operations, Analytics & Systems Senior Manager at IPSY & Paola Alfaro, Founder at HumanWorks! In this wide-ranging and deeply honest conversation, host Cole Napper explores what is really happening in the people analytics space across Latin America, the challenges professionals in the region face as the discipline matures, and why the future may be far brighter than many expect. Maria and Paola share firsthand perspectives from inside the rapidly evolving LATAM people analytics community. Rather than inheriting mature analytics infrastructures like many organizations in North America or Europe, many companies across Latin America are building the plane while flying it—creating people analytics capabilities from scratch while simultaneously educating leaders on the value of workforce data. The conversation highlights how professionals in the region are navigating limited resources, fragmented systems, and a lack of established data teams while still pushing the field forward. Maria reflects on her unconventional path into analytics, beginning with operational HR reporting and gradually evolving into deeper data work across systems, dashboards, and storytelling. She shares how her early career focused heavily on technical execution—pulling data, building charts, and automating reports—before she realized the real impact comes from translating numbers into narratives that influence decisions. Today, her focus is on helping organizations move beyond descriptive dashboards toward meaningful insights that actually shape business outcomes. Paola complements this perspective by discussing the realities of consulting with organizations that often lack the foundational data infrastructure required for analytics. Her work frequently begins not with optimization, but with education—helping leaders understand what data governance, data culture, and analytical thinking even look like in practice. She also discusses her early “aha moment” discovering people analytics as a discipline and how that experience shaped her mission to bring more structured analytics methodologies into HR across Latin America. Throughout the discussion, the group explores several themes shaping the future of the field: the growing influence of AI on analytics workflows, the importance of data governance as organizations scale their analytics capabilities, and the rising need for professionals who can translate insights into action. Maria and Paola both emphasize that while tools and automation are accelerating rapidly, human context, interpretation, and influence remain essential to turning data into impact. The episode also highlights the growing momentum of the LATAM people analytics community itself. Paola shares how regional leaders are building stronger networks, launching conferences, and creating communities where practitioners can collaborate, learn, and accelerate the adoption of workforce analytics practices across countries. This spirit of collaboration, adaptability, and curiosity may ultimately become Latin America’s greatest advantage as the field evolves globally. Along the way, the conversation touches on personal career growth, navigating impostor syndrome, building confidence with data, mentoring the next generation of professionals, and balancing technical expertise with the communication skills required to influence executives. Both guests bring thoughtful, candid perspectives on what it really takes to grow in a field that continues to reinvent itself. If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.