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, 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.