Advertise on podcast: Directionally Correct, A People Analytics 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, ⁠Ann-Marie Clayton Johnson⁠, Senior Director, Human Resource Business Partner at Microsoft & Former Salesforce People Analytics Leader! Cole has known Ann-Marie since she was a Salesforce people analytics leader he looked up to. Then she became an HR business partner at Microsoft, and this episode asks why. Analytics was the highlight of her last decade: curiosity, access, and a team that shaped strategy by defining the metrics, work she credits in part to Ernestine. She left before seniority locked the door. Companies hesitate to trust a senior analytics person in a role they have never held, even though she would take that risk herself. Cole ties the move to advice from the CHRO practice at Heidrick & Struggles: business partner experience is often the barrier between people analytics and the top job. What an HRBP does depends on the company. Smaller firms fold in operations. At Salesforce, partners did communications and employee experience. At Microsoft, Ann-Marie supports senior leaders in SMB and channel, a high-growth business whose sellers carry hundreds of accounts rather than enterprise’s one-to-one model. Her weeks are leadership development, off-sites, talent walks, succession, and org design, including SMB-specific roles inside functions built for enterprise. The sharper turn is producer to consumer. Any partner worth their salt should use analytics. Her background helps her see the system of data. On a low-performance steerco she pushed upstream: what predicts low performance, where the hot spots are, which managers deserve a double click, before a case opens. Connect the points so the story is visible. An agent or a dashboard does not change the world. She has been at Microsoft only since February. People analytics had gone tools-forward and help-yourself. It did not work, and consulting is coming back. Nate Schultz joined from Salesforce, aligned to her skip level, with a team supporting sales. She wants those consultants senior enough to know statistics and the business. A leader who wanted people back in the office became the test. About 19 people were going in, not enough to know whether attendance helped. The answer came back as not statistically significant. She needed practical significance, and a partner who will say the variables are wrong. Embedding fails unless people are held accountable in writing. If data use is not in Connects goals, it will not show up. She wants a culture that still asks how do you know. People analytics is not dead, but the hypothesis work she loved is fading, while the technical layer stays because AI needs people who can structure and choose data. Anyone too far from the business will not last. Cole’s inquisitor and change agent frame matches: ask, analyze, act. The field over-indexed on the automatable middle, and people intelligence flattens the rest into a data layer and an intelligence layer. I-O training let her skip years across centers of excellence. She shares the resume-bullet framework and the S-curve: leave while the work is energizing and build breadth instead of waiting on a pyramid of junior analysts. She is a military spouse. Ryan went to West Point and deploys often. She helps transitioning service members and is PTA president for a year. Cole’s Corner covers teaching, a Texas shore, and Harry Potter. As a future CHRO she would not lose the employee experience that pulled her in after Cisco. They take on Andreessen on talent and workplace b******t versus lying. Change comes from winning companies. Find her on LinkedIn as Ann Marie Clayton Johnson. 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, ⁠Kelly Monahan⁠, Future of Work & AI Advisor and recent Author of “Reclaim the Plot”! Cole Napper sits down with Kelly for a wide-ranging conversation that moves from the uncanny to the practical and back again. Kelly recounts spending six hours in a recording studio so an AI digital avatar could learn her likeness, then months training it, only to watch that digital twin land in the Wall Street Journal. Her first reaction was that it was creepy: a likeness that was her and yet not her. Over time she began using it to open keynotes and to show that the AI conversation is larger than large language models, though she is candid that it is still more novelty than something she would send into a meeting the way Reed Hoffman does. That experiment sits inside a larger argument. After years in tech, Kelly concluded we have lost the plot on the pursuit of AI. The technology has existed since the 1950s; the current wave is real and transformative, especially agentic systems, but treating early ChatGPT as an excuse to hollow out knowledge work without redesigning the work itself is a mistake. Productivity gains show up, she says, citing McKinsey and BCG, only when work redesign accompanies the tools. Only about 21 percent of companies have done that redesign. Without it, people simply send more email and sit in more meetings. AI becomes an expensive way to illuminate how poorly designed the work was in the first place. Kelly walks through a simulation she built in hours for her forthcoming book’s fictional company, Driftwell—work that would once have taken a team ninety days and tens of thousands of dollars. A parent agent spun up specialists, connected to HubSpot, and orchestrated the whole thing. She defines an agent as a system that takes action toward a goal rather than merely chatting. The same pattern appeared in her four years at Upwork around the November 2022 “D-Day” of ChatGPT: the freelancer market entered an existential crisis, disruption arrived slowly rather than overnight, early AI users earned more and bid on larger projects, and inequity widened along a power-law distribution. The lasting finding was that this is a massive skilling moment, especially for transactional content work. The conversation turns to leadership. Most senior leaders mandate AI without using it themselves, either because they believe strategy is too elevated for tools or because they fear the C-suite itself will shrink. Intelligence and expertise are being commoditized; what remains is change management and the messy human middle that agents cannot yet own. Accountability becomes the billion-dollar question: if two hundred agents gather the inputs, can an executive still be accountable for a decision they cannot fully verify? Span of control, entry-level learning-by-doing pathways in consulting, and the dignity of physical work all get examined. Kelly worries we told a generation to abandon the physical world even though those jobs often carry meaning, community, and contribution that leisure-only futures may not replace. In Cole’s Corner they cover growth mindset (Kelly argues the label matters less than accompanying behavioral interventions and human relating), the 1975 “folly of rewarding A while hoping for B,” broken performance management, and eye-watering revenue-per-employee figures that raise questions about reinvestment, customers, and long-term social consequences. Kelly points listeners to LinkedIn and reclaimtheplotbook.com. 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, Kevin Trowbridge, Director of Compensation and HRIS at Kimray! In this conversation Cole Napper sits down with Kevin to unpack what it means to lead compensation and HRIS as one combined function at a 78-year-old Oklahoma manufacturer that had no dedicated role for either until 2024. Kevin landed in the work almost by accident: a math degree, a banking career that burned him out, and a friend who spotted a utility job that wanted someone who could handle numbers. That first administrator seat taught the unglamorous truth. You run the reports, match the jobs, build the structures, and learn that compensation is finance with a human being on the other side of every figure. The work still looks more like an apprenticeship than something you can absorb from a book. WorldatWork’s CCP typically takes three to five years because the classroom only sticks if you are already living the messy decisions. Comp ratios, percentiles, internal equity, and survey matching all sound like people-analytics language, so Cole asks why compensation and people analytics so rarely sit in the same room. Kevin’s answer is blunt. Pay makes people nervous. Companies that lag the market do not want that exposed. Culture can offset dollars, and at Kimray it often does. Tenure of 40-plus years is still common. Leaders teach culture to other businesses through a foundation. Frontline supervisors get executive-level leadership training. People stay because the values match, not because every offer sits at the 75th percentile. Kimray manufactures pressure regulators, valves, sensors, and level controllers for oil and gas, made in the USA. Until May 1 of this year it was family owned. It is now an ESOP, so employees become beneficial owners through a company-funded retirement plan that sits on top of the 401(k). That ownership story collides with another unusual design choice: the CEO refuses traditional sales commissions. He does not want credit-stealing or split-store fights. Sales grew from roughly 100 million to the 230–250 million range with a company-wide EBITDA bonus instead. The team is now testing a group accelerator so everyone rows toward the same outcome. AI is the thread that keeps Kevin up at night. Tools like Claude already save his analyst hours and even teach him Python. HRBench turned a ten-minute request for three years of departmental turnover into a clean, trusted slide. Workforce planning lets finance and leaders add, subtract, and cost positions in the same conversation. Kevin still asks the moral question: if AI swallows the entry-level report running and employee-relations grunt work, who develops the next generation of compensation and HRIS professionals? In ten years the seniors will retire unless companies keep the apprenticeship intact. The episode also lands in a 60–65 percent blue-collar workforce. Extreme heat changes time spent at work not working. Air conditioning in a machine shop is a retention variable, not a perk. Kevin lives that contrast personally: diesel truck, red Oklahoma dirt, 11 acres, pond, chickens, a log-cabin house next to the in-laws, and a history nerd’s dream of Trowbridge, England. Rapid-fire Cole’s Corner covers banking as the road not taken, Neo from The Matrix, and a three-year forecast in which agentic tools run basic analysis in the background while compensation, analytics, and core HR finally stop living in separate Excel dumps. Attract, reward, and retain only work if the numbers, the culture, the systems, and the next generation of talent are treated as one problem. This episode is the field notes. 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, Denise Teo, Former Head of Analytics & People Science at Grab! Denise spent nearly a decade at Grab, the Southeast Asia super app that began in 2012 to make rides safer where that was not a given. Today it is a hyper-local platform for rides, food, financial services, and B2B work. She joined in 2016 when Grab was still small, first in operations analytics, then commercial and product, before switching into people. She is not from HR or I-O psychology. She came from tech analytics and found the place where quantitative rigor meets the messy applied world of people. She built the function from zero to one, then rebranded it as People Science: stop stopping at insights and get better at effecting change through real partnerships. Denise is self-critical about the traps people analytics teams fall into. First, caring more about methods than outcomes. Complexity becomes a proxy for skill even when the business is not ready. Firms advertise the coolest methods, then drop people into sanitized work that never uses them. Cole argues there is little correlation between method sophistication and business value. Second, not knowing who the users are: employees, leadership, and the people team. User research should be easier because users sit in the same office, yet teams still skip discovery. Many analytics products exist only to paper over bad HCM interfaces. Third, failing to bring users along. Nascent functions outpace readiness; partners who are not data-native retreat to Excel when the model arrives. Southeast Asia makes the work harder and richer. Cultures and languages differ sharply. Qualitative text was nearly inaccessible before large language models unlocked an asset that used to sit unused. Denise sees the field growing fast in Asia. She simplifies the practice into thinking, doing, and communicating. The doing layer is what most people enjoy and what AI is hollowing out fastest. What remains is judgment about the right problems, design of guardrails, and translating insights for brains that do not think like yours. You move from the factory floor to the control tower. Cole maps this to his inquisitor-and-change-agent framing and adds orchestration of agents. Both worry that a thousand flowers blooming can scale noise as fast as signal. That shift hits identity. Denise is leaving full-time work at Grab to try fractional practice across more organizations. She describes the hollow feeling many analysts report: routines vanish, mastery of SQL or Python feels threatened, and purpose thins when the tasks that defined the job are no longer yours. Cognitive surrender is uncritical acceptance of AI outputs in place of your own reasoning. Cole contrasts people intelligence with workforce intelligence. The first treats AI as a tool that serves humans. The second risks putting people in service to the machine. Ethics and privacy have cooled even as data use expanded. Denise’s heuristics are symmetry, transparency matched by action, and consent plus agency. Value has to flow back to employees or the exchange stays extractive. Cole tests the principle at the limit with genetic data; Denise holds to those heuristics rather than a yes or no. In Cole’s Corner she would have been a fusion chef, most wants to see Iceland, and picks the zebra from Racing Stripes who believes he can race with thoroughbreds. On fractional leadership she says budget constraints already push organizations toward smaller units of exchange. They close on Andrew Merritt’s output-gap piece and John Sullivan on brilliant jerks. Denise is on LinkedIn. Hire her. 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, Roxanne Bisby Davis, Head of People Intelligence at Cisco! Cole Napper talks with Roxanne about a title they almost share, how people intelligence gets built inside a large technology company, and why trust has to sit at the center of listening and analytics. Roxanne has been at Cisco more than twenty-six years. She arrived in 2000 as a contingent worker, converted to full time later that year, and did not set out to run this function. She started in recruiting, was pulled into HR marketing because she knew PowerPoint, learned to simplify executive messages so people across the company could understand the intent, covered a leave and inherited early meeting surveys, and stayed as Cisco invested in listening, research, data science, and storytelling. People intelligence stuck as the name because the work outgrew an annual census or a narrow analytics shop. Her team now includes researchers, data scientists, and storytellers looking at the full depth of humans at work, not just the average. She keeps coming back to Todd Rose’s point that nobody is an average. Leaders need the range if decisions are going to serve more than the middle. Storytelling starts with listening more than speaking, asking questions that pull color and context, reading the room, and answering the “what’s in it for me” so people feel seen. Trust has followed her for years because it is so individualized and so fragile when teams and leaders keep moving. Psychological safety was a major finding in Cisco’s 2016 best-team research. Reciprocal trust matters: employees trusting the institution, and the institution extending trust back instead of treating listening as one-way extraction. She welcomes skeptics because skepticism sharpens transparency. Cisco tested survey load before a full census in 2006, ran annual surveys into the mid-2010s, then moved to quarterly plus continuous listening so they would not have to ask every day. Daily thumbs-up surveys can work in cultures that close the loop fast. In a company of Cisco’s size, the cost of attention can make daily asks feel like asking for asking’s sake. Cole compares that to Buffett’s weighing machine versus voting machine: a snapshot is not the same as a relationship that changes behavior. Roxanne also traces ITSG, the IT Survey Group that spun from the old Mayflower consortium so tech companies could share norms and get practical help without cold-calling peers. She still values consortiums that pull you out of your own echo chamber. She has always tried to make order out of chaos and treat messy organizational problems as pattern puzzles. If she were not doing this work she would be a professional organizer. She most wants to visit New Zealand and she would be Mary Poppins, walking around with a bag of tricks to connect people and make things better. Looking ahead, she argues the field only grows where capability is paired with radical transparency. New tools make surveillance cheap. That is why informed consent, employee choice, and the human premium matter more, not less. Psychology in the loop is not the same as a vague human-in-the-loop slogan. AI slop flattens people toward the average. Automation works when you design human-automation-human chains instead of sprinkling potential onto isolated tasks. Skills inference only works if employees keep voice and agency, because a skill you can do but hate will not produce engagement. People intelligence is synthesis across individual motivation, team conditions, process, and business outcomes, not a single data layer pretending to be the whole story. 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, 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.

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.

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.

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.

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.