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 intelligence podcast with special guest, Jack Buckley, Chief People and Systems Officer at Roblox!

In this wide-ranging conversation, host Cole Napper sits down with Jack to explore his unconventional journey from Navy nuclear engineer and tenured statistics professor to running a federal agency and now leading both the people and systems teams at the gaming platform company. They dig into what it really means to hold a dual CHRO and CIO role, with Jack arguing that success depends more on the right organization than a uniquely special person. At a mid-size, engineering-heavy firm like Roblox with around 3,500 employees, combining people processes with internal tools and enterprise systems creates powerful synergies that might not work elsewhere, especially where the systems side focuses less on pure technical leadership and more on how work actually gets done day to day. Jack shares how he arrived at Roblox through the rapid acquisition of his game-based assessment startup during the pandemic, just weeks before a planned sale to McKinsey, bringing deep expertise from redesigning the SAT at the College Board, leading research and psychometrics at the National Center for Education Statistics, and pioneering innovative measurement approaches at places like the American Institutes for Research. Listeners will hear about the frontier of game-based assessment for hiring early-career software engineers, product managers, and data scientists, including why explainable scoring rooted in evidence-centered design and item response theory still matters even as AI reshapes technical evaluations, and how the team moved existing technology onto the Roblox platform itself while maintaining rigorous, non-black-box methods. The discussion turns to AI enablement across the business, from safe agentic coding tools embedded in engineering workflows to thoughtful automation that avoids black-box risks in HR, legal, and finance, plus practical lessons on verifying outputs, building deterministic harnesses, and focusing on real workplace problems rather than hype or vendor pitches. Jack also reflects on building people analytics and employee listening from scratch when the company was far smaller, the value of succession planning that exposed him gradually to every part of the function, the necessity of humility when moving from specialized analytics into broader service leadership, and even using Roblox itself for multi-day new-hire orientation, game jams that teach both play and Studio creation, and cooperative team-building experiences. Along the way the conversation wanders into favorite pizza styles from New York to thin-crust Chicago tavern style, the sudden midlife appeal of birdwatching with AI feeders, cooperative games like Helldivers 2 that reward communication over competition, and the midlife questions facing people analytics as a field, including whether it is experiencing a true crisis of trailblazers versus button-pushers or simply needing new S-curves of applied problem-solving drawn from neighboring domains like labor economics and operations research. Packed with insight on measurement, talent strategy, technology enablement, and leadership that blends rigorous science with practical problem-solving, this episode captures the spirit that defines directionally correct people intelligence while showing how one career can connect nuclear engineering, educational testing, serious games, and the dual people-and-systems mandate at a major platform company. 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 intelligence podcast with special guest, Hadeel Al-Tashi, Head of SHRM Labs and Future of Work Investor!

In this rich conversation host Cole Napper and Hadeel unpack exactly what SHRM Labs is and how it operates as SHRM’s innovation and venture arm. Established five years ago, the Labs exists to scan emerging technologies shaping the future of work, educate SHRM’s more than 340,000 members, and create a bridge between builders and the practitioners who will actually use the tools. Hadeel shares why she left the private-sector and venture-capital world for this role inside a massive membership organization: the unmatched scale of insight SHRM provides into real workplace priorities, adoption barriers, and pain points that pure market investors rarely see with the same clarity.

They dig into what truly excites her right now—solutions that solve today’s critical HR and business problems rather than speculative futures ten years out. Impact, proven usage, and alignment with member data are the filters she uses to separate signal from noise. On AI she is candid: HR still lags the broader organization (36 percent adoption versus 52 percent), the gap is expected to widen, and uptake is heavily skewed toward large enterprises and toward lower-risk recruiting tasks. High-stakes decisions around compliance or terminations rightly keep a stronger human in the loop. Last year’s agent hype has cooled because organizations simply are not ready; the real hunger is for tools that deliver immediate workforce insights so leaders can make rapid, data-backed decisions amid ongoing layoffs and uncertainty.

Hadeel offers straight talk for anyone dreaming of launching an HR-tech startup. Start with a must-have problem you are passionate about, validate demand cheaply—even as a service—before pouring money into engineering, focus on a narrow ideal customer profile, and learn the language of lean startups, TAM, and product-market fit. Funding can begin with angels, friends, family, or accelerators; institutional capital usually waits for paying customers. Domain expertise and data-driven founders are far more attractive than pure technologists who have never lived the problem. She notes the talent-acquisition space is currently over-funded and sees bigger opportunity in skills validation and combating the rising wave of candidate fraud. The conversation also touches the small, collaborative nature of the HR-tech community, Hadeel’s own path (she once planned to be a doctor until she discovered she cannot stand blood), her dream of visiting Yemen’s otherworldly Socotra island, and why she would choose Mulan as her fictional counterpart.

Throughout, the episode balances practical advice, SHRM research highlights, and honest reflection on what it takes to build technology that actually moves the profession forward. 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, Sasha Arjannikova, Director of Analytics Business Partnering at Adobe!

In this rich conversation with host Cole Napper on Directionally Correct, Sasha shares how to build a people analytics function that genuinely partners with the business, bringing insights back to leaders in ways that drive real decisions while earning trust as a data subject matter expert. She unpacks the delicate balance of deep analytical sophistication with business fluency, audience analysis, empathy, and change management so that complex findings land and spark action rather than gathering dust. Listeners hear how Sasha navigates living in both worlds—translating the unspoken needs and hypotheses of HR business partners and executives into clear asks for data science and research teams, then distilling rigorous outputs into the language the business already uses. The discussion explores her role at Adobe after the team restructured around domains of expertise, the energy of operating at the speed of the business, co-creating with savvy HR partners, and ensuring employee survey insights move from understanding to visible action in a data-focused, people-centered culture. Sasha reflects on her unconventional path from childhood cow herding (paid in the best fresh milk) and modeling that taught confidence yet revealed the gap between glamorous exteriors and daily reality, to studying communication as the flip side of I-O psychology and now writing a practical book that equips leaders with research-backed principles for evaluating and partnering with AI. She and Cole dig into the HR Strategy Forum’s AI collaboratory work with practitioners and academics like Alexis Fink and Alec Levenson, the urgent need for people-centered AI implementation so HR leads rather than lags, and the risks of over-automating junior roles that erode internal pipelines, institutional knowledge, and long-term organizational health. They examine the pendulum swings between pyramidal and diamond-shaped organizations, the existential challenge of data quality and ground truth across every field, evolving mental models for performance cycles and hierarchies in agile work, and the identity shifts facing the people analytics profession itself. Looking three years ahead, Sasha anticipates roles merging, faster answers through AI-native tools, and the critical importance of automating tasks that drain joy rather than those that energize, preserving human judgment, connection, and satisfaction. The episode also covers three thought-provoking articles: the surprising tolerance of attractiveness bias because people fail to notice it (with stark implications for AI image generation and coding of confidence or success), research showing a spouse’s conscientiousness predicts a partner’s job satisfaction, income, and promotions via practical support and reduced cognitive load, and provocative ideas from the Work Design Lab on how finance teams at Anthropic already use AI skills for forward-looking work while HR still largely remains stuck in backward-looking analysis—complete with caveats around data quality, testing, deterministic versus probabilistic outcomes, and architectural readiness. Throughout, the pair emphasize communication as a two-way street, slowing down with intention amid rapid change, measuring the real impact of analytics, and building credibility before offering predictions. Sasha invites practitioners to join upcoming HR Strategy Forum sessions and connects on LinkedIn under her distinctive name. This episode delivers practical wisdom for anyone seeking to make people analytics truly influence strategy, culture, and the future of work while staying grounded in the human element that technology amplifies but never replaces.

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, William Tincup, Editor, Analyst, Advisor, Host at Wrkdefined!

In this wide-ranging, unfiltered, and often provocative conversation, host Cole Napper sits down with one of the most recognizable and influential voices in the HR technology community for a discussion that refuses to stay inside the usual polite boundaries. William lays out why he believes a genuine car crash is approaching as Silicon Valley and Wall Street fall deeply in love with the revenue-per-employee ratio, celebrating companies that deliver growth with dramatically fewer human heads even while the true cost of the AI tools powering that efficiency remains largely invisible on the balance sheet. They examine how the actual work being performed, the humans performing it, and the rapidly emerging class of AI agents and agentic systems all reshape that metric and force a fundamental reset in people analytics, workforce planning, talent intelligence, and behavioral science. The pair dig into the practical consequences: who gets promoted and paid more when one analyst finishes the same deliverable in five hours with Claude and ChatGPT while another still needs the full forty, how pay equity conversations must evolve, and why location-based compensation is inherently biased. Recruiters come under sharp scrutiny next. William is characteristically blunt that most still do not trust their own data or analytics because, at core, they are salespeople who would rather post a new requisition on LinkedIn or Indeed than mine the three million candidates already living inside the ATS. He explains why generative AI has not magically repaired that distrust and what real incentive redesign would look like if organizations actually wanted recruiters living inside the systems they already own rather than treating the ATS as pure compliance theater. Vendors receive equally direct counsel: stop selling AI into HR by endlessly explaining the how, the tokens, and the architecture; start selling clear outcomes to IT and the buyers who care about results rather than propeller-hat technical details. The conversation ranges further into the leadership void created by vanishing entry-level jobs, the competitive advantage that silent high-performing recruiting teams refuse to discuss publicly, the dangers of political and cultural homogeneity killing innovation inside companies, the quiet normalization of workplace surveillance, the measurable drop in spoken words per day, and the only realistic path most people will ever have to a billion-dollar outcome—creating rather than climbing the corporate ladder. Along the way William shares the raw personal story of a 2015 psychotic break that nearly ended his life, the carefully tuned medication regimen that keeps him level, the floor-to-ceiling paintings that pour out of mania, the long career arc from youngest assistant manager in Walmart history to advisor of more than fifty technology exits, and the deliberate filters he uses in conversation and relationships. The result is an episode that is equal parts strategic warning about the coming AI-native economic model, practical counsel for practitioners and vendors, and unapologetic life lesson for anyone trying to stay directionally correct when the old models of work, measurement, and career no longer hold. 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, Dr. Deniz Ones, Hellervik Professor of Industrial Psychology & Distinguished McKnight University Professor, University of Minnesota!

In this rich conversation on Directionally Correct, host Cole Napper and Deniz Ones dive deep into one of the most consequential debates in industrial-organizational psychology: the predictive power of cognitive ability tests for job performance, the role of range restriction, and whether classic findings from Schmidt and Hunter still hold. Ones, who never took a formal I-O psychology course yet trained under legends including Frank Schmidt and Jack Hunter, brings a unique perspective shaped by three decades at the University of Minnesota and close professional proximity to Paul Sackett. She recounts the origins of meta-analysis in the field, how sampling error, reliability differences, and range restriction were systematically addressed, and why the 1998 Schmidt-Hunter validity matrix remains foundational even as newer work questions the magnitude of corrections applied to concurrent validation studies. Listeners hear a careful unpacking of the “for whom, when, and where” of validity: operational validities must be interpreted against the variability of actual applicant pools, which have grown more restricted over time in the United States, while scientific estimates should reflect unrestricted population parameters so they can be tailored to different labor markets worldwide. Ones emphasizes that cognitive ability continues to predict the acquisition of job knowledge and task performance, that experience does not erase ability differences, and that dismissing general mental ability while simultaneously pursuing artificial general intelligence risks a contradictory “botification” of human talent. The discussion expands into individual differences research, including cybernetic trait complexes, meta-analytic profiles of life success, and the mapping of maladaptive trait combinations that drive counterproductive work behavior. Ones also reflects on her path as an eighth-generation scholar who emigrated from Turkey, the gateway role of cognitive ability for those without privileged lineage, and the broader societal levers needed to address adverse impact beyond selection systems alone. In Cole’s Corner the pair explore rapid-fire personal questions, the limits of off-the-shelf assessments for extreme performers under power-law distributions, why predictor-criterion correlations have remained modest given the multiply determined nature of performance, the political economy of academic publishing, and the accelerating challenges of integrating machine learning into legally and professionally defensible selection while the technology itself keeps moving. Throughout, Ones advocates letting the literature breathe across hundreds of studies, keeping the big picture in view, and recognizing that practice often leads science in I-O psychology. The episode offers both technical nuance and a humanistic reminder of why rigorous measurement of human potential ultimately serves organizations and individuals alike.

If you like this episode, you’d also love exploring prior episodes—visit colenapper.com for the full archive and show links.