『Directionally Correct, A People Intelligence Podcast』のカバーアート

Directionally Correct, A People Intelligence Podcast

Directionally Correct, A People Intelligence Podcast

著者： WRKdefined Podcast Network
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Directionally Correct is the #1 people intelligence podcast in the world. Hosted by Cole Napper, the podcast dives into people intelligence, workforce planning, behavioral science, and talent analytics, helping leaders navigate the future of AI in the workplace with insight and a dash of fun. To find out more, check out colenapper.comAll rights reserved by WRKdefined マネジメント マネジメント・リーダーシップ 科学 経済学
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  • Does Revenue-Per-Employee Matter? & Random Stuff - William Tincup - #185

    Does Revenue-Per-Employee Matter? & Random Stuff - William Tincup - #185
    2026/08/10
    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.
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    1 時間 53 分
  • Is the IQ Debate in I-O Psychology Really Over? - Dr. Deniz Ones - #184

    Is the IQ Debate in I-O Psychology Really Over? - Dr. Deniz Ones - #184
    2026/08/03
    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.
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    1 時間 19 分
  • The ROI of People Analytics from Aptitude Research - Madeline Laurano - #183

    The ROI of People Analytics from Aptitude Research - Madeline Laurano - #183
    2026/07/27
    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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    1 時間 7 分
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