Ep 86: Architecting the Future of Workforce Intelligence with Ben Zweig

Bob Pulver welcomes Ben Zweig, CEO of Revelio Labs and labor economist, for a deep dive into the evolving world of workforce analytics. Drawing from their overlapping experiences at IBM, Bob and Ben explore how the early days of cognitive computing sparked a journey toward greater transparency in labor market data. Ben explains how Revelio Labs is building a “Bloomberg Terminal” for workforce insights—grounded in publicly available data and powered by sophisticated taxonomies of occupations, tasks, and skills. Together, they examine the importance of job architecture, the promise and pitfalls of AI in workforce analytics, and the complexities of measuring contingent and freelance labor. Ben also shares a preview of his upcoming book, Job Architecture, and how LLMs are being used to redefine how organizations model and respond to changes in work itself.



Keywords



Revelio Labs, Ben Zweig, labor market data, job architecture, workforce analytics, strategic workforce planning, AI in HR, cognitive computing, IBM, labor economics, generative AI, skills-based hiring, public labor statistics, contingent workforce, gig economy, talent intelligence



Takeaways




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Revelio Labs aims to recreate company-level workforce insights using publicly available employment data, similar to how Bloomberg transformed financial markets.




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Job architecture is built on three distinct but interrelated taxonomies: occupations, tasks, and skills.




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Many orgs think of skills as the building blocks of jobs, rather than attributes of people—a conceptual misstep that limits strategic planning.




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Gen AI is being used to score the automation vulnerability of tasks, enabling better insights into how work is changing.




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Strategic workforce planning is often misnamed—what most companies do is operational, not truly strategic.




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Contingent and freelance labor remains a blind spot in many traditional labor statistics and HR systems.




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The ability to adjust for data bias, reporting lags, and incomplete workforce signals is critical for creating trustworthy insights.




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Revelio’s Public Labor Statistics offers an independent source of macro labor data, complementing BLS and ADP methodologies.






Quotes




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“Skills are attributes of people. Tasks are the building blocks of jobs.”




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“What’s exciting is that these are hard problems with big upside—unlike finance, where most of the low-hanging fruit is gone.”




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“We’re asking LLMs to tell us what they’re good at—and how confident they are in that judgment.”




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“Most organizations don’t need to pay $1M to build a taxonomy anymore. They just need the right approach and the right data.”




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“There’s no reason we shouldn’t be repurposing labor market insights to help individuals, not just institutions.”






Chapters



00:00 — Intro and HR Tech reflections



02:08 — Ben’s background in economics and IBM analytics



06:43 — Why labor market data lags behind capital markets



09:22 — Building a flexible, bias-adjusted analytics stack



14:19 — Empathy for job seekers and candidate friction



16:10 — Why job discovery is fundamentally an information problem



19:53 — Unpacking job architecture: occupations, tasks, and skills



24:28 — Scoring AI’s impact on tasks, not skills



28:39 — Summarization vs. hallucination in generative AI



38:45 — Introducing RPLS: Revelio Public Labor Statistics



45:40 — The challenge of tracking freelance and contingent work



51:58 — Dealing with ghost data and workforce ambiguity



53:35 — Real-life uses of AI and Ben’s curiosity mindset



54:42 — Closing thoughts








Ben Zweig:   / ben-zweig  



Revelio Labs: https://reveliolabs.com



Job Architecture (pre-order): https://www.amazon.com/Job-Architectu...








For advisory work and marketing inquiries:



Bob Pulver:⁠⁠ ⁠  / bobpulver⁠⁠⁠  



Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠



Substack: ⁠https://elevateyouraiq.substack.com⁠