Directionally Correct, A People Intelligence Podcast

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.

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.

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.

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.

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.